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Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using <t>Microsoft</t> Excel and the red boxes are households actually visited during the survey.
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1) Product Images from "Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti"

Article Title: Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

Journal: International Journal of Health Geographics

doi: 10.1186/1476-072X-12-3

Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using Microsoft Excel and the red boxes are households actually visited during the survey.
Figure Legend Snippet: Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using Microsoft Excel and the red boxes are households actually visited during the survey.

Techniques Used:

2) Product Images from "The Deuterator: software for the determination of backbone amide deuterium levels from H/D exchange MS data"

Article Title: The Deuterator: software for the determination of backbone amide deuterium levels from H/D exchange MS data

Journal: BMC Bioinformatics

doi: 10.1186/1471-2105-8-156

Data Workflow . A . The protein of interest is digested with an enzyme and the resulting peptides are analyzed by LC MS. B . Peptide identity is then established with database search tools such as Sequest. C . The protein is incubated with D 2 O at multiple time points, digested with an enzyme and the resulting peptides are analyzed by LC MS. D . Resulting raw files are converted to mzXML. E . Search results are converted into PepXML. F . User selects the peptides of interest from the search results to create the peptide set. G . Core Deuterator processing and interactive tools for H/D/exchange data curation. H . Data visualization components such as graphs in Microsoft Excel and 3D structure overlays in PyMol.
Figure Legend Snippet: Data Workflow . A . The protein of interest is digested with an enzyme and the resulting peptides are analyzed by LC MS. B . Peptide identity is then established with database search tools such as Sequest. C . The protein is incubated with D 2 O at multiple time points, digested with an enzyme and the resulting peptides are analyzed by LC MS. D . Resulting raw files are converted to mzXML. E . Search results are converted into PepXML. F . User selects the peptides of interest from the search results to create the peptide set. G . Core Deuterator processing and interactive tools for H/D/exchange data curation. H . Data visualization components such as graphs in Microsoft Excel and 3D structure overlays in PyMol.

Techniques Used: Liquid Chromatography with Mass Spectroscopy, Incubation

3) Product Images from "PubChemSR: A search and retrieval tool for PubChem"

Article Title: PubChemSR: A search and retrieval tool for PubChem

Journal: Chemistry Central Journal

doi: 10.1186/1752-153X-2-11

Property data exported into Microsoft Excel . Selected property-related fields of the 25 'acetaminophen' related compounds were exported into an Excel file. The filtering, sorting and graphing features of Excel can then be used to examine this data.
Figure Legend Snippet: Property data exported into Microsoft Excel . Selected property-related fields of the 25 'acetaminophen' related compounds were exported into an Excel file. The filtering, sorting and graphing features of Excel can then be used to examine this data.

Techniques Used:

4) Product Images from "A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division"

Article Title: A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division

Journal: PLoS Genetics

doi: 10.1371/journal.pgen.1002590

Phenotypes of ribosomal proteins. We grouped strains (n = 53) that lack ribosomal proteins of the 60S subunit (RPL), against strains (n = 43) that lack ribosomal proteins of the 40S subunit (RPS). We then compared the two groups based on the %G1 DNA content (this study; A), fitness (data from Giaever et al [33] ; B), or haploid median cell size (data from Jorgensen et al [23] ; C). The box plots were generated with Microsoft Excel. The box represents the middle 50% of the data range (from the 25th percentile to the 75th percentile). The band within the box is the median, while the cross shows the mean. The ends of the whiskers represent the lowest datum still within 1.5 of the interquartile range (IQR) of the lower quartile, and the highest datum still within 1.5 IQR of the upper quartile. Any data points not included within the whiskers are shown as outliers, displayed as filled circles. For the fitness data in B, the lower quartiles are not visible, because they are equal to 1 (i.e., most strains have fitness values similar to WT). The P values were calculated from t tests.
Figure Legend Snippet: Phenotypes of ribosomal proteins. We grouped strains (n = 53) that lack ribosomal proteins of the 60S subunit (RPL), against strains (n = 43) that lack ribosomal proteins of the 40S subunit (RPS). We then compared the two groups based on the %G1 DNA content (this study; A), fitness (data from Giaever et al [33] ; B), or haploid median cell size (data from Jorgensen et al [23] ; C). The box plots were generated with Microsoft Excel. The box represents the middle 50% of the data range (from the 25th percentile to the 75th percentile). The band within the box is the median, while the cross shows the mean. The ends of the whiskers represent the lowest datum still within 1.5 of the interquartile range (IQR) of the lower quartile, and the highest datum still within 1.5 IQR of the upper quartile. Any data points not included within the whiskers are shown as outliers, displayed as filled circles. For the fitness data in B, the lower quartiles are not visible, because they are equal to 1 (i.e., most strains have fitness values similar to WT). The P values were calculated from t tests.

Techniques Used: Generated

5) Product Images from "Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000"

Article Title: Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000

Journal: Scientific Data

doi: 10.1038/sdata.2016.34

Sample Modelski Data Table. Sample table received directly from Modelski in Microsoft Word format. Cities are listed in bold type and are grouped by region (here, South and Southeast Asia). Population values are indicated in thousands. These tables were then transcribed into the Excel format highlighted in Supplementary Fig. 1 for further analysis.
Figure Legend Snippet: Sample Modelski Data Table. Sample table received directly from Modelski in Microsoft Word format. Cities are listed in bold type and are grouped by region (here, South and Southeast Asia). Population values are indicated in thousands. These tables were then transcribed into the Excel format highlighted in Supplementary Fig. 1 for further analysis.

Techniques Used:

6) Product Images from "Reducing number entry errors: solving a widespread, serious problem"

Article Title: Reducing number entry errors: solving a widespread, serious problem

Journal: Journal of the Royal Society Interface

doi: 10.1098/rsif.2010.0112

Errors in adding numbers in Microsoft Excel. Excel's SUM() function, which is used to total all columns in this figure, ignores values that are not numbers. No errors are reported in any of the examples. ( a ) Two apparently identical sums giving different results. The erroneous sum in the right-hand column is caused by 3.1. having a final decimal point/full stop, and hence being treated as text, and thus processed as zero by SUM . The difference between the column sums may not be noticed by a user, particularly since in normal use they are unlikely to double-check the ‘same’ columns, as used here for illustrative purposes. ( b ) The ‘show precedents’ feature is one way to help check calculations. It highlights the operands of a cell, but here the precedents for the incorrect total are shown as including the value that has been ignored. Evidently, Excel's notion of ‘precedents’ is the range of possible operands, rather than the actual operands, and therefore the feature is misleading. ( c ) Through innocent error or intentional mischief, even more unusual column sums can be produced. In the left column, the cell ‘3.1’ is generated by the formula ='3.1' , which turns the apparently correct number 3.1 into a string, with value zero as before. In the right column, the cell ‘23’ is actually the number 995, but formatted as ‘23’ using a custom format.
Figure Legend Snippet: Errors in adding numbers in Microsoft Excel. Excel's SUM() function, which is used to total all columns in this figure, ignores values that are not numbers. No errors are reported in any of the examples. ( a ) Two apparently identical sums giving different results. The erroneous sum in the right-hand column is caused by 3.1. having a final decimal point/full stop, and hence being treated as text, and thus processed as zero by SUM . The difference between the column sums may not be noticed by a user, particularly since in normal use they are unlikely to double-check the ‘same’ columns, as used here for illustrative purposes. ( b ) The ‘show precedents’ feature is one way to help check calculations. It highlights the operands of a cell, but here the precedents for the incorrect total are shown as including the value that has been ignored. Evidently, Excel's notion of ‘precedents’ is the range of possible operands, rather than the actual operands, and therefore the feature is misleading. ( c ) Through innocent error or intentional mischief, even more unusual column sums can be produced. In the left column, the cell ‘3.1’ is generated by the formula ='3.1' , which turns the apparently correct number 3.1 into a string, with value zero as before. In the right column, the cell ‘23’ is actually the number 995, but formatted as ‘23’ using a custom format.

Techniques Used: Produced, Generated

7) Product Images from "Loss of the mitochondrial protein-only ribonuclease P complex causes aberrant tRNA processing and lethality in Drosophila"

Article Title: Loss of the mitochondrial protein-only ribonuclease P complex causes aberrant tRNA processing and lethality in Drosophila

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkw338

Loss of mt:RNase P complex proteins causes decreases in ATP in vivo . ( A ) Larvae mutant for mldr and scu have greatly reduced levels of ATP compared to wild-type ( y w ). ( B ) Larvae ubiquitously expressing RNAi for rswl, scu and mldr using tubGAL4 also have reduced levels of ATP. scu A mutant larvae are included as a control. ( C, E ) mldr and scu mutant larvae (C) and larvae ubiquitously expressing rswl-RNAi (E) do not have decreased mitochondrial aconitase activity relative to cytoplasmic aconitase activity. ( D, F ) Representative cellulose acetate membranes for C and E, respectively, showing cytoplasmic (cyto) and mitochondrial (mito) aconitase activity. ‘+’ and ‘−’ indicate the electrophoretic migration. Error bars represent s.e.m.. P - values were calculated using a two-tailed Student's t -test in Microsoft Excel. Information on replicates can be found in the Materials and Methods.
Figure Legend Snippet: Loss of mt:RNase P complex proteins causes decreases in ATP in vivo . ( A ) Larvae mutant for mldr and scu have greatly reduced levels of ATP compared to wild-type ( y w ). ( B ) Larvae ubiquitously expressing RNAi for rswl, scu and mldr using tubGAL4 also have reduced levels of ATP. scu A mutant larvae are included as a control. ( C, E ) mldr and scu mutant larvae (C) and larvae ubiquitously expressing rswl-RNAi (E) do not have decreased mitochondrial aconitase activity relative to cytoplasmic aconitase activity. ( D, F ) Representative cellulose acetate membranes for C and E, respectively, showing cytoplasmic (cyto) and mitochondrial (mito) aconitase activity. ‘+’ and ‘−’ indicate the electrophoretic migration. Error bars represent s.e.m.. P - values were calculated using a two-tailed Student's t -test in Microsoft Excel. Information on replicates can be found in the Materials and Methods.

Techniques Used: In Vivo, Mutagenesis, Expressing, Activity Assay, Migration, Two Tailed Test

Loss of mldr and scu results in lethality in Drosophila. (A–C) Predicted structure of Mulder based on the Arabidopsis thaliana PRORP1, PRORP2 and the human PRORP available structures ( A ) and Scully ( B and C ) based on the available human MRPP2 structures. The modeled MRPP2 monomer is shown in blue in B whereas the expected tetrameric assembly is shown in C. The point mutations used in this study are indicated with yellow (A) and red (B, C) circles. The scu alleles Q159Stop and E205X result in truncations. The E205X and Q159Stop mutations result in a 19-residue truncation in yellow and an additional 87-residue truncation in green, respectively shown in B. The position of W465, Y121 in Mulder and S163, Q159 and E205 are all shown as ball and sticks. ( D ) Table summarizing percent pupation and eclosion for mldr and scu alleles. ( E ) Western blot indicating larvae mutant for mldr B and mldr C have greatly reduced protein levels. ( F–H ) Pupation rates. Both mldr B and mldr C mutant larvae have delayed pupation with 40% of mldr C mutant larvae failing to pupate (F). Larvae mutant for scu have delayed pupation as well. The scu 4058 allele also fails to pupate 40% of the time (G). (H) Expressing UAS-rswl-RNAi using ActGAL4 shows a modest but reproducible pupation delay. Note the different scale in the X-axis. The controls (black lines) for F–H are a representative sibling control for one of the genotypes. The lines stop because the adults eclose. ( I ) Negative geotaxis assay. Expressing scu or rswl RNAi in dopaminergic neurons using Ple-GAL4 has no effect on adult fly locomotion, whereas expressing mldr-RNAi causes an age-dependent decrease in locomotion. AE = After Eclosion. Error bars = s.e.m. for F, G and s.d. for H. * P = 0.02, determined using a two-tailed Student's t -test in Microsoft Excel.
Figure Legend Snippet: Loss of mldr and scu results in lethality in Drosophila. (A–C) Predicted structure of Mulder based on the Arabidopsis thaliana PRORP1, PRORP2 and the human PRORP available structures ( A ) and Scully ( B and C ) based on the available human MRPP2 structures. The modeled MRPP2 monomer is shown in blue in B whereas the expected tetrameric assembly is shown in C. The point mutations used in this study are indicated with yellow (A) and red (B, C) circles. The scu alleles Q159Stop and E205X result in truncations. The E205X and Q159Stop mutations result in a 19-residue truncation in yellow and an additional 87-residue truncation in green, respectively shown in B. The position of W465, Y121 in Mulder and S163, Q159 and E205 are all shown as ball and sticks. ( D ) Table summarizing percent pupation and eclosion for mldr and scu alleles. ( E ) Western blot indicating larvae mutant for mldr B and mldr C have greatly reduced protein levels. ( F–H ) Pupation rates. Both mldr B and mldr C mutant larvae have delayed pupation with 40% of mldr C mutant larvae failing to pupate (F). Larvae mutant for scu have delayed pupation as well. The scu 4058 allele also fails to pupate 40% of the time (G). (H) Expressing UAS-rswl-RNAi using ActGAL4 shows a modest but reproducible pupation delay. Note the different scale in the X-axis. The controls (black lines) for F–H are a representative sibling control for one of the genotypes. The lines stop because the adults eclose. ( I ) Negative geotaxis assay. Expressing scu or rswl RNAi in dopaminergic neurons using Ple-GAL4 has no effect on adult fly locomotion, whereas expressing mldr-RNAi causes an age-dependent decrease in locomotion. AE = After Eclosion. Error bars = s.e.m. for F, G and s.d. for H. * P = 0.02, determined using a two-tailed Student's t -test in Microsoft Excel.

Techniques Used: Western Blot, Mutagenesis, Expressing, Two Tailed Test

Overexpressing Mulder causes mitochondrial morphology defects. ( A ) UAS-mldr-GFP expressing larvae driven by tubGAL4 do not develop past second instar. The sibling control larva is a third instar. ( B ) UAS-rswl-myc larvae, in contrast, are able to grow to the third instar stage driven by tubGAL4 . ( C ) Graph showing relative ATP levels for UAS-scu, UAS-rswl and UAS-mldr larvae overexpressed using tubGAL4 . OE = overexpression. ( D–I ) Germ cells expressing UAS-mldr-GFP under the control of nosGAL4 . (D–F) Germ cells with lower Mldr expression (D) have mitochondria that are of the normal shape and size (E, F is the merge). Germ cells with high expression of UAS-Mldr-GFP (G) have swollen mitochondria (H, I is the merge). The swollen, ring-shaped mitochondria (H, inset) have Mldr-GFP concentrated in the middle (G, inset, I inset is the merge). ( J–L ) A representative ovariole expressing UAS-mldr-GFP under control of nosGAL4 . Weaker expression is seen in younger germ cells (J, arrow) compared to strong Mldr-GFP expression in older ones (J, arrowhead). ATP synthase labeling shows all of the mitochondria throughout the ovariole (K). L is the merge of J and K. White = anti-GFP (D, G, J), anti-ATP synthase (E, H, K). Green = anti-GFP (F, I, L). Magenta = anti-ATP synthase (F, I, L). Scale bars = 5 μm in I for D-I, 1.5 μm in I inset for all insets, 50 μm in L for J–L. Error bars = s.e.m.. P -values were calculated in Microsoft Excel using a two-tailed Student's t -test.
Figure Legend Snippet: Overexpressing Mulder causes mitochondrial morphology defects. ( A ) UAS-mldr-GFP expressing larvae driven by tubGAL4 do not develop past second instar. The sibling control larva is a third instar. ( B ) UAS-rswl-myc larvae, in contrast, are able to grow to the third instar stage driven by tubGAL4 . ( C ) Graph showing relative ATP levels for UAS-scu, UAS-rswl and UAS-mldr larvae overexpressed using tubGAL4 . OE = overexpression. ( D–I ) Germ cells expressing UAS-mldr-GFP under the control of nosGAL4 . (D–F) Germ cells with lower Mldr expression (D) have mitochondria that are of the normal shape and size (E, F is the merge). Germ cells with high expression of UAS-Mldr-GFP (G) have swollen mitochondria (H, I is the merge). The swollen, ring-shaped mitochondria (H, inset) have Mldr-GFP concentrated in the middle (G, inset, I inset is the merge). ( J–L ) A representative ovariole expressing UAS-mldr-GFP under control of nosGAL4 . Weaker expression is seen in younger germ cells (J, arrow) compared to strong Mldr-GFP expression in older ones (J, arrowhead). ATP synthase labeling shows all of the mitochondria throughout the ovariole (K). L is the merge of J and K. White = anti-GFP (D, G, J), anti-ATP synthase (E, H, K). Green = anti-GFP (F, I, L). Magenta = anti-ATP synthase (F, I, L). Scale bars = 5 μm in I for D-I, 1.5 μm in I inset for all insets, 50 μm in L for J–L. Error bars = s.e.m.. P -values were calculated in Microsoft Excel using a two-tailed Student's t -test.

Techniques Used: Expressing, Over Expression, Labeling, Two Tailed Test

8) Product Images from "Steps to achieve quantitative measurements of microRNA using two step droplet digital PCR"

Article Title: Steps to achieve quantitative measurements of microRNA using two step droplet digital PCR

Journal: PLoS ONE

doi: 10.1371/journal.pone.0188085

Quantitative miRNA measurements in THP-1 cells. Total RNA was extracted from macrophage derived THP-1 cells and was (A) analyzed for integrity, purity, and concentration using the chip-based automated electrophoresis system. (B) Total RNA was reverse transcribed by cDNA synthesis kit “A”, “B”, or “C” and specific miRNA targets were measured using ddPCR. (C) Each kit, “A” (×), “B” (+), and”C” (ӿ), was used to make cDNA and total number of targets were counted via ddPCR. Average NTC and NEC were similarly measured for each experiment. For all targets, cel-miR-238 (gray), cel-miR-39 (orange), hsa-miR-223 (brown), and hsa-miR-155 (red), fraction positive targets per droplet were calculated by subtracting NEC and NTC positive and applying Poisson distribution. Predicted 10 4 miRNA copies/μL for cel-miR-238 (gray square), cel-miR-39 (orange square), and hsa-miR-223 (brown square) was calculated using pre-existing power curve values ( Table 6 ). For each respective kit, a new power curve was developed using experimental versus predicted cel-mir-238, cel-miR-39, and hsa-miR-223 concentration ( Table 7 ). This new power curve was applied to respective, endogenously measured, experimental hsa-miR-155 λ’ to generate predicted hsa-miR-155 (red circle) copies/μL. The standard uncertainty is shown on the graph for hsa-miR-155 for each respective point (dark red line). For visualization purposes, data is either graphed on one chart or separated out based on cDNA synthesis kit. New power models are calculated only for individual cDNA synthesis kits and both equation and correlation coefficient are interlayered. Graphs are single representations of repeated biological trials. Microsoft Excel was used to calculate and graph data.
Figure Legend Snippet: Quantitative miRNA measurements in THP-1 cells. Total RNA was extracted from macrophage derived THP-1 cells and was (A) analyzed for integrity, purity, and concentration using the chip-based automated electrophoresis system. (B) Total RNA was reverse transcribed by cDNA synthesis kit “A”, “B”, or “C” and specific miRNA targets were measured using ddPCR. (C) Each kit, “A” (×), “B” (+), and”C” (ӿ), was used to make cDNA and total number of targets were counted via ddPCR. Average NTC and NEC were similarly measured for each experiment. For all targets, cel-miR-238 (gray), cel-miR-39 (orange), hsa-miR-223 (brown), and hsa-miR-155 (red), fraction positive targets per droplet were calculated by subtracting NEC and NTC positive and applying Poisson distribution. Predicted 10 4 miRNA copies/μL for cel-miR-238 (gray square), cel-miR-39 (orange square), and hsa-miR-223 (brown square) was calculated using pre-existing power curve values ( Table 6 ). For each respective kit, a new power curve was developed using experimental versus predicted cel-mir-238, cel-miR-39, and hsa-miR-223 concentration ( Table 7 ). This new power curve was applied to respective, endogenously measured, experimental hsa-miR-155 λ’ to generate predicted hsa-miR-155 (red circle) copies/μL. The standard uncertainty is shown on the graph for hsa-miR-155 for each respective point (dark red line). For visualization purposes, data is either graphed on one chart or separated out based on cDNA synthesis kit. New power models are calculated only for individual cDNA synthesis kits and both equation and correlation coefficient are interlayered. Graphs are single representations of repeated biological trials. Microsoft Excel was used to calculate and graph data.

Techniques Used: Derivative Assay, Concentration Assay, Chromatin Immunoprecipitation, Electrophoresis

Model for miRNA quantification using synthetic oligonucleotides. miRNA titrations were performed with (A, D, G) cDNA Kit “A”, (B, E, H) cDNA Kit “B”, and (C, F, I) cDNA Kit “C”. The cDNA synthesis kits and targets were measured with droplet digital PCR system. Average no template control (NTC) and no enzyme control (NEC) were similarly measured for each experiment. Fraction positive targets per droplet were calculated either without subtracting average NEC and NTC positives (λ; open circles, purple line) or with subtracting NEC and NTC positive (λ’; closed red circles, red line) droplets. For each kit and each target (A to C) cel-miR-238, (D to F) cel-miR-39, and (G to I) hsa-miR-223, both λ (dashed purple line) or λ’ (solid red line) were graphed on a single x -axis versus estimated 10 4 miRNA copies/μL master mix. A simple power curve, y = a x b , was calculated for normalized data, λ’. Limit of quantification (LOQ) was predicted based on the lowest possible value that satisfied the power curve. Individual data points are shown with corresponding standard uncertainties. Microsoft Excel was used to calculate and graph data.
Figure Legend Snippet: Model for miRNA quantification using synthetic oligonucleotides. miRNA titrations were performed with (A, D, G) cDNA Kit “A”, (B, E, H) cDNA Kit “B”, and (C, F, I) cDNA Kit “C”. The cDNA synthesis kits and targets were measured with droplet digital PCR system. Average no template control (NTC) and no enzyme control (NEC) were similarly measured for each experiment. Fraction positive targets per droplet were calculated either without subtracting average NEC and NTC positives (λ; open circles, purple line) or with subtracting NEC and NTC positive (λ’; closed red circles, red line) droplets. For each kit and each target (A to C) cel-miR-238, (D to F) cel-miR-39, and (G to I) hsa-miR-223, both λ (dashed purple line) or λ’ (solid red line) were graphed on a single x -axis versus estimated 10 4 miRNA copies/μL master mix. A simple power curve, y = a x b , was calculated for normalized data, λ’. Limit of quantification (LOQ) was predicted based on the lowest possible value that satisfied the power curve. Individual data points are shown with corresponding standard uncertainties. Microsoft Excel was used to calculate and graph data.

Techniques Used: Digital PCR

9) Product Images from "Kinetic Analysis of the Effect of Poliovirus Receptor on Viral Uncoating: the Receptor as a Catalyst"

Article Title: Kinetic Analysis of the Effect of Poliovirus Receptor on Viral Uncoating: the Receptor as a Catalyst

Journal: Journal of Virology

doi: 10.1128/JVI.75.11.4984-4989.2001

) was modified to include sPvR at 0.25 μM. The plots show the natural logarithm of the concentration of unconverted 160S particle versus time. Each point is the average of three separate experiments; bars indicate the standard deviation of the average of the measurements. The data for the low-temperature reactions for all graphs were truncated for the sake of clarity of the higher-temperature data. Plots were generated using Microsoft Excel.
Figure Legend Snippet: ) was modified to include sPvR at 0.25 μM. The plots show the natural logarithm of the concentration of unconverted 160S particle versus time. Each point is the average of three separate experiments; bars indicate the standard deviation of the average of the measurements. The data for the low-temperature reactions for all graphs were truncated for the sake of clarity of the higher-temperature data. Plots were generated using Microsoft Excel.

Techniques Used: Modification, Concentration Assay, Standard Deviation, Generated

10) Product Images from "Prophylactic potential of aPanchgavya formulation against certain pathogenic bacteria"

Article Title: Prophylactic potential of aPanchgavya formulation against certain pathogenic bacteria

Journal: F1000Research

doi: 10.12688/f1000research.16485.1

Panchgavya -exposed Caenorhabditis elegans exhibit better resistance to pathogenic bacteria. Previous exposure to Panchgavya (for 72 or 96 h) enabled C. elegans population to register better survival in the face of bacterial challenge: ( A ) 42.50±2.52% (p=0.001) better survival till third day, and 17.50±3.54% (p=0.002) better survival on fifth day, against P. aeruginosa ; ( B ) 27.30±1.86% (p=0.0001) better survival on fifth day, against S. aureus ; ( C ) 21.50±1.04% (p=0.0003) better survival on fifth day, against C. violaceum ; ( D ) 23±1.50% (p=0.002) higher survival on fifth day, against S. marcescens ; ( E ) Panchgavya -exposure was not found to confer any protection on C. elegans against S. pyogenes challenge. Results pertaining to 72 h and 96 h exposure of worms to Panchgavya, prior to bacterial challenge, were not statistically different. Values reported are means of four independent experiments, whose statistical significance was assessed using t -test performed through Microsoft Excel. P values ≤0.05 were considered to be statistically significant.
Figure Legend Snippet: Panchgavya -exposed Caenorhabditis elegans exhibit better resistance to pathogenic bacteria. Previous exposure to Panchgavya (for 72 or 96 h) enabled C. elegans population to register better survival in the face of bacterial challenge: ( A ) 42.50±2.52% (p=0.001) better survival till third day, and 17.50±3.54% (p=0.002) better survival on fifth day, against P. aeruginosa ; ( B ) 27.30±1.86% (p=0.0001) better survival on fifth day, against S. aureus ; ( C ) 21.50±1.04% (p=0.0003) better survival on fifth day, against C. violaceum ; ( D ) 23±1.50% (p=0.002) higher survival on fifth day, against S. marcescens ; ( E ) Panchgavya -exposure was not found to confer any protection on C. elegans against S. pyogenes challenge. Results pertaining to 72 h and 96 h exposure of worms to Panchgavya, prior to bacterial challenge, were not statistically different. Values reported are means of four independent experiments, whose statistical significance was assessed using t -test performed through Microsoft Excel. P values ≤0.05 were considered to be statistically significant.

Techniques Used:

11) Product Images from "Integrating Phase Change Lines and Labels into Graphs in Microsoft Excel®"

Article Title: Integrating Phase Change Lines and Labels into Graphs in Microsoft Excel®

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-018-0248-6

Evolution of withdrawal design graph, steps 2–9, in Microsoft Excel® 2016 for Mac
Figure Legend Snippet: Evolution of withdrawal design graph, steps 2–9, in Microsoft Excel® 2016 for Mac

Techniques Used:

Evolution of withdrawal design graph, steps 10–12, in Microsoft Excel® 2016 for Mac
Figure Legend Snippet: Evolution of withdrawal design graph, steps 10–12, in Microsoft Excel® 2016 for Mac

Techniques Used:

Evolution of withdrawal design graph, step 1, in Microsoft Excel® 2016 for Mac
Figure Legend Snippet: Evolution of withdrawal design graph, step 1, in Microsoft Excel® 2016 for Mac

Techniques Used:

12) Product Images from "Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2"

Article Title: Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2

Journal: The Journal of Biological Chemistry

doi: 10.1074/jbc.RA118.005651

Peptide library analysis of Kin1 and Kin2 priming defective mutants. Heat maps show quantified peptide library analysis of WT and priming-deficient mutant ( AA ) forms of Kin1 and Kin2. Selectivity values are the average of normalized data from two separate experiments. Heat maps were generated in Microsoft Excel.
Figure Legend Snippet: Peptide library analysis of Kin1 and Kin2 priming defective mutants. Heat maps show quantified peptide library analysis of WT and priming-deficient mutant ( AA ) forms of Kin1 and Kin2. Selectivity values are the average of normalized data from two separate experiments. Heat maps were generated in Microsoft Excel.

Techniques Used: Mutagenesis, Generated

13) Product Images from "Successful Integration of Data Science in Undergraduate Biostatistics Courses Using Cognitive Load Theory"

Article Title: Successful Integration of Data Science in Undergraduate Biostatistics Courses Using Cognitive Load Theory

Journal: CBE Life Sciences Education

doi: 10.1187/cbe.19-02-0041

(a) Percentage of students in Biostatistics in the treatment cohort who made their graphs using R from previous assignment examples is high from the beginning of the course. (b) Percentage of students in Biostatistics in the treatment cohort who made their graphs using R from the textbook increases as the term progresses and replaces use of Microsoft Excel (“Excel”) or hand drawing (“Hand”) or other software. “NA” indicates students who did not submit either their homework assignments or this particular question from the homework assignments. The students who did not submit their homework assignments are not the same across all weeks.
Figure Legend Snippet: (a) Percentage of students in Biostatistics in the treatment cohort who made their graphs using R from previous assignment examples is high from the beginning of the course. (b) Percentage of students in Biostatistics in the treatment cohort who made their graphs using R from the textbook increases as the term progresses and replaces use of Microsoft Excel (“Excel”) or hand drawing (“Hand”) or other software. “NA” indicates students who did not submit either their homework assignments or this particular question from the homework assignments. The students who did not submit their homework assignments are not the same across all weeks.

Techniques Used: Software

14) Product Images from "Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2"

Article Title: Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2

Journal: The Journal of Biological Chemistry

doi: 10.1074/jbc.RA118.005651

Peptide library analysis of Kin1 and Kin2 priming defective mutants. Heat maps show quantified peptide library analysis of WT and priming-deficient mutant ( AA ) forms of Kin1 and Kin2. Selectivity values are the average of normalized data from two separate experiments. Heat maps were generated in Microsoft Excel.
Figure Legend Snippet: Peptide library analysis of Kin1 and Kin2 priming defective mutants. Heat maps show quantified peptide library analysis of WT and priming-deficient mutant ( AA ) forms of Kin1 and Kin2. Selectivity values are the average of normalized data from two separate experiments. Heat maps were generated in Microsoft Excel.

Techniques Used: Mutagenesis, Generated

15) Product Images from "The Saccharomyces cerevisiae YCC5 (YCL025c) Gene Encodes an Amino Acid Permease, Agp1, Which Transports Asparagine and Glutamine"

Article Title: The Saccharomyces cerevisiae YCC5 (YCL025c) Gene Encodes an Amino Acid Permease, Agp1, Which Transports Asparagine and Glutamine

Journal: Journal of Bacteriology

doi:

Kinetics of asparagine uptake in JGY51 ( gap1 gnp1 ) and JGY52 ( gap1 gnp1 agp1 ). The rate of [ 14 ). The data was plotted as Michaelis-Menten (A) and Eadie-Hofstee (B) graphs. The Michaelis-Menten graphs were fitted to curves assuming two permeases (JGY51) and one permease (JGY52) with the Solver program of Microsoft Excel. Each data point is the average of at least three measurements, with a standard error of
Figure Legend Snippet: Kinetics of asparagine uptake in JGY51 ( gap1 gnp1 ) and JGY52 ( gap1 gnp1 agp1 ). The rate of [ 14 ). The data was plotted as Michaelis-Menten (A) and Eadie-Hofstee (B) graphs. The Michaelis-Menten graphs were fitted to curves assuming two permeases (JGY51) and one permease (JGY52) with the Solver program of Microsoft Excel. Each data point is the average of at least three measurements, with a standard error of

Techniques Used:

16) Product Images from "Structure of Ca2+-binding protein-6 from Entamoeba histolytica and its involvement in trophozoite proliferation regulation"

Article Title: Structure of Ca2+-binding protein-6 from Entamoeba histolytica and its involvement in trophozoite proliferation regulation

Journal: PLoS Pathogens

doi: 10.1371/journal.ppat.1006332

EhCaBP6 modulates microtubule dynamics in a dose dependent manner. (A) The tubulin polymerization assay was performed with porcine tubulin at a final concentration of 5 μM in the presence of varying concentration of EhCaBP6. EhCaBP6 efficiently enhanced rate of polymerization subsequently affecting the total amount of polymerized microtubules. The light scattering experiment was repeated thrice in triplicates and the representation is an average of three independent run. (B) Image of the plate post tubulin polymerization light scattering experiment showing gradual increase in turbidity with increase in EhCaBP6 concentration as compared to Buffer alone, EhCaBP6 alone or Tubulin alone. (C) Densitometry analysis of the turbidity using AlphaEaseFc software. The reading was exported and plot in Microsoft Excel. The average value of three independent experiments has been represented graphically.
Figure Legend Snippet: EhCaBP6 modulates microtubule dynamics in a dose dependent manner. (A) The tubulin polymerization assay was performed with porcine tubulin at a final concentration of 5 μM in the presence of varying concentration of EhCaBP6. EhCaBP6 efficiently enhanced rate of polymerization subsequently affecting the total amount of polymerized microtubules. The light scattering experiment was repeated thrice in triplicates and the representation is an average of three independent run. (B) Image of the plate post tubulin polymerization light scattering experiment showing gradual increase in turbidity with increase in EhCaBP6 concentration as compared to Buffer alone, EhCaBP6 alone or Tubulin alone. (C) Densitometry analysis of the turbidity using AlphaEaseFc software. The reading was exported and plot in Microsoft Excel. The average value of three independent experiments has been represented graphically.

Techniques Used: Polymerization Assay, Concentration Assay, Software

17) Product Images from "Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti"

Article Title: Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

Journal: International Journal of Health Geographics

doi: 10.1186/1476-072X-12-3

Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using Microsoft Excel and the red boxes are households actually visited during the survey.
Figure Legend Snippet: Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using Microsoft Excel and the red boxes are households actually visited during the survey.

Techniques Used:

18) Product Images from "Summarizing and exploring data of a decade of cytokinin-related transcriptomics"

Article Title: Summarizing and exploring data of a decade of cytokinin-related transcriptomics

Journal: Frontiers in Plant Science

doi: 10.3389/fpls.2015.00029

Annotated subcellular localizations, molecular functions and biological processes of the core set of cytokinin-induced genes . The genes listed in Table 2A were evaluated with regard to their GO categorization using the GO categorization tool provided by TAIR ( http://www.arabidopsis.org/tools/bulk/go/index.jsp ), which matches a given set of genes with a reduced set of basic GO terms (GOslim). The resulting table was imported into Microsoft Excel for generating the cake diagrams. The Excel diagrams were reformatted using CorelDRAW to fit them into the frame of a figure.
Figure Legend Snippet: Annotated subcellular localizations, molecular functions and biological processes of the core set of cytokinin-induced genes . The genes listed in Table 2A were evaluated with regard to their GO categorization using the GO categorization tool provided by TAIR ( http://www.arabidopsis.org/tools/bulk/go/index.jsp ), which matches a given set of genes with a reduced set of basic GO terms (GOslim). The resulting table was imported into Microsoft Excel for generating the cake diagrams. The Excel diagrams were reformatted using CorelDRAW to fit them into the frame of a figure.

Techniques Used:

19) Product Images from "Ectopic Expression of Vaccinia Virus E3 and K3 Cannot Rescue Ectromelia Virus Replication in Rabbit RK13 Cells"

Article Title: Ectopic Expression of Vaccinia Virus E3 and K3 Cannot Rescue Ectromelia Virus Replication in Rabbit RK13 Cells

Journal: PLoS ONE

doi: 10.1371/journal.pone.0119189

Growth of VACVΔE3LΔK3L is restored in RK13 cells expressing VACV E3 and K3 proteins. (A) VACVΔE3LΔK3L was constructed using homologous recombination techniques and engineered to express GFP in place of the E3L gene. No plaque formation was visualized in wild-type RK13 cells whereas replication capacity was restored in RK13 cells stably expressing E3 and K3 proteins derived from VACV. Representative images are shown. (B) The total yield of VACV wild-type, VACVΔE3L, VACVΔK3L, and VACVΔE3LΔK3L was determined using wild-type RK13 (red bars) and RK13+E3L+K3L (gray bars) cells. Cells were initially infected with a low amount of virus (MOI = 0.01). Virus was harvested 30 hours post-infection and the total yield was determined using standard plaque assays with RK13+E3L+K3L cells. The data is the average of two independent experiments with error bars representing the standard deviation. P-values were determined in Microsoft Excel using the Student’s t-test.
Figure Legend Snippet: Growth of VACVΔE3LΔK3L is restored in RK13 cells expressing VACV E3 and K3 proteins. (A) VACVΔE3LΔK3L was constructed using homologous recombination techniques and engineered to express GFP in place of the E3L gene. No plaque formation was visualized in wild-type RK13 cells whereas replication capacity was restored in RK13 cells stably expressing E3 and K3 proteins derived from VACV. Representative images are shown. (B) The total yield of VACV wild-type, VACVΔE3L, VACVΔK3L, and VACVΔE3LΔK3L was determined using wild-type RK13 (red bars) and RK13+E3L+K3L (gray bars) cells. Cells were initially infected with a low amount of virus (MOI = 0.01). Virus was harvested 30 hours post-infection and the total yield was determined using standard plaque assays with RK13+E3L+K3L cells. The data is the average of two independent experiments with error bars representing the standard deviation. P-values were determined in Microsoft Excel using the Student’s t-test.

Techniques Used: Expressing, Construct, Homologous Recombination, Stable Transfection, Derivative Assay, Infection, Standard Deviation

20) Product Images from "QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL"

Article Title: QTL MatchMaker: a multi-species quantitative trait loci (QTL) database and query system for annotation of genes and QTL

Journal: Nucleic Acids Research

doi: 10.1093/nar/gkj027

QTL MatchMaker query and input screenshots. ( A ) A section of a Batch Search output page. The results can be downloaded in Microsoft Excel or HTML format. ( B ) Cross Species Search output page.
Figure Legend Snippet: QTL MatchMaker query and input screenshots. ( A ) A section of a Batch Search output page. The results can be downloaded in Microsoft Excel or HTML format. ( B ) Cross Species Search output page.

Techniques Used: Polyacrylamide Gel Electrophoresis

21) Product Images from "WRKY Transcription Factors Associated With NPR1-Mediated Acquired Resistance in Barley Are Potential Resources to Improve Wheat Resistance to Puccinia triticina"

Article Title: WRKY Transcription Factors Associated With NPR1-Mediated Acquired Resistance in Barley Are Potential Resources to Improve Wheat Resistance to Puccinia triticina

Journal: Frontiers in Plant Science

doi: 10.3389/fpls.2018.01486

Transcript levels of selected PR and BCI genes in the HvNPR1-Kd transgenic lines. Third leaves of HvNPR1-Kd barley transgenic lines and wild-type plants were infiltrated with water (control) or P. syringae pv. tomato DC3000. Then, samples for qRT-PCR assays were collected from the leaf region adjacent to the infection 48 h after inoculation, after a cell death phenotype observed. The transcript levels are expressed relative to those of the endogenous control HvEF1a using the 2 −ΔCT method. Two independent transgenic lines for the HvNPR1-Kd were used, and, each experiment, consisting of 4–11 biological replicates, was considered a block. Calculations of the mean and standard error were performed using Microsoft Excel software. Data were transformed to restore normality and general linearized model (GLM) ANOVA ( ∗ P
Figure Legend Snippet: Transcript levels of selected PR and BCI genes in the HvNPR1-Kd transgenic lines. Third leaves of HvNPR1-Kd barley transgenic lines and wild-type plants were infiltrated with water (control) or P. syringae pv. tomato DC3000. Then, samples for qRT-PCR assays were collected from the leaf region adjacent to the infection 48 h after inoculation, after a cell death phenotype observed. The transcript levels are expressed relative to those of the endogenous control HvEF1a using the 2 −ΔCT method. Two independent transgenic lines for the HvNPR1-Kd were used, and, each experiment, consisting of 4–11 biological replicates, was considered a block. Calculations of the mean and standard error were performed using Microsoft Excel software. Data were transformed to restore normality and general linearized model (GLM) ANOVA ( ∗ P

Techniques Used: Transgenic Assay, Quantitative RT-PCR, Infection, Blocking Assay, Software, Transformation Assay

Transcript levels of selected PR and BCI genes in the wNPR1-OE transgenic lines. Third leaves of wNPR1-OE barley transgenic lines and wild-type plants were infiltrated with water (control) or P. syringae pv. tomato DC3000. Samples for qRT-PCR assays were collected from the leaf region adjacent to the infection 48 h after inoculation, after a cell death phenotype observed. Using the 2 −ΔCT method, the transcript levels were expressed relative to those of the endogenous control HvEF1a . Two independent transgenic lines for the wNPR1-OE were used. Each experiment, consisting of 4–11 biological replicates, was considered as a block. Calculations of the mean and standard error were performed using Microsoft Excel software. Data were transformed to restore normality and general linearized model (GLM) ANOVA ( ∗ P
Figure Legend Snippet: Transcript levels of selected PR and BCI genes in the wNPR1-OE transgenic lines. Third leaves of wNPR1-OE barley transgenic lines and wild-type plants were infiltrated with water (control) or P. syringae pv. tomato DC3000. Samples for qRT-PCR assays were collected from the leaf region adjacent to the infection 48 h after inoculation, after a cell death phenotype observed. Using the 2 −ΔCT method, the transcript levels were expressed relative to those of the endogenous control HvEF1a . Two independent transgenic lines for the wNPR1-OE were used. Each experiment, consisting of 4–11 biological replicates, was considered as a block. Calculations of the mean and standard error were performed using Microsoft Excel software. Data were transformed to restore normality and general linearized model (GLM) ANOVA ( ∗ P

Techniques Used: Transgenic Assay, Quantitative RT-PCR, Infection, Blocking Assay, Software, Transformation Assay

22) Product Images from "Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays"

Article Title: Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays

Journal: BMC Immunology

doi: 10.1186/1471-2172-15-23

Western Blotting Results of the Monoclonal BRAA. Western blotting results showing the banding pattern of the five potential pathogenic monoclonal BRAA, MRL/lpr #2 (mouse used to create the monoclonal BRAA) and the NK-1R positive control. Microsoft Office 2010 Picture Manager was used to adjust the brightness and contrast for some images.
Figure Legend Snippet: Western Blotting Results of the Monoclonal BRAA. Western blotting results showing the banding pattern of the five potential pathogenic monoclonal BRAA, MRL/lpr #2 (mouse used to create the monoclonal BRAA) and the NK-1R positive control. Microsoft Office 2010 Picture Manager was used to adjust the brightness and contrast for some images.

Techniques Used: Western Blot, Positive Control

23) Product Images from "Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse"

Article Title: Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse

Journal: GigaScience

doi: 10.1186/s13742-015-0067-4

The workflow used to create LAGOS, including the research decisions needed to design the database. Once the research decisions have been made (grey boxes), the workflow is divided into three modules: building the multi-themed GEO data module (green boxes); georeferencing the site-level data (orange boxes); and building the site-level data module (blue boxes). The black boxes with white text identify the Additional files (AF) that describe each element in further detail and the red text provides the programming language or software used for each step. ARCGIS is ArcGIS, Ver 10.1 (ESRI); FGDC is the Federal Geographic Data Committee metadata standard; EXCEL is Microsoft Excel; TAUDEM is the TauDEM Version 5 suite of models to analyze topographical data; PYTHON is the Python programming language; SQL is structured query language used in the PostgreSQL database system; R is the R statistical language [ 36 ]; and EML is ecological metadata language
Figure Legend Snippet: The workflow used to create LAGOS, including the research decisions needed to design the database. Once the research decisions have been made (grey boxes), the workflow is divided into three modules: building the multi-themed GEO data module (green boxes); georeferencing the site-level data (orange boxes); and building the site-level data module (blue boxes). The black boxes with white text identify the Additional files (AF) that describe each element in further detail and the red text provides the programming language or software used for each step. ARCGIS is ArcGIS, Ver 10.1 (ESRI); FGDC is the Federal Geographic Data Committee metadata standard; EXCEL is Microsoft Excel; TAUDEM is the TauDEM Version 5 suite of models to analyze topographical data; PYTHON is the Python programming language; SQL is structured query language used in the PostgreSQL database system; R is the R statistical language [ 36 ]; and EML is ecological metadata language

Techniques Used: Software

24) Product Images from "HIV-1 envelope accessible surface and polarity: clade, blood, and brain"

Article Title: HIV-1 envelope accessible surface and polarity: clade, blood, and brain

Journal: Bioinformation

doi:

Mean Shannon entropy and polarity range of gp120 and gp41 sequences in brain and blood samples from different geographical locations. Shannon entropy of gp120 and gp41 sequences is calculated at the LANL website [ http://www.hiv.lanl.gov/ ]. The mean Shannon entropy is correlated with polarity range by regression coefficient (r) of 0.734 for gp120 (a) and 0.588 for gp41 (b) sequences. The Pearson correlation co-efficient was calculated using Microsoft EXCEL software.
Figure Legend Snippet: Mean Shannon entropy and polarity range of gp120 and gp41 sequences in brain and blood samples from different geographical locations. Shannon entropy of gp120 and gp41 sequences is calculated at the LANL website [ http://www.hiv.lanl.gov/ ]. The mean Shannon entropy is correlated with polarity range by regression coefficient (r) of 0.734 for gp120 (a) and 0.588 for gp41 (b) sequences. The Pearson correlation co-efficient was calculated using Microsoft EXCEL software.

Techniques Used: Software

25) Product Images from "Analysis of focal adhesion turnover: A quantitative live cell imaging example"

Article Title: Analysis of focal adhesion turnover: A quantitative live cell imaging example

Journal: Methods in cell biology

doi: 10.1016/B978-0-12-420138-5.00018-5

Example spreadsheet layout to use the Microsoft Excel ‘Solver’ for least square curve fitting of FA turnover dynamics, which can be adapted to fit any non-linear function. Columns D–F contain the data for the assembly, logistic
Figure Legend Snippet: Example spreadsheet layout to use the Microsoft Excel ‘Solver’ for least square curve fitting of FA turnover dynamics, which can be adapted to fit any non-linear function. Columns D–F contain the data for the assembly, logistic

Techniques Used:

26) Product Images from "Analysis of focal adhesion turnover: A quantitative live cell imaging example"

Article Title: Analysis of focal adhesion turnover: A quantitative live cell imaging example

Journal: Methods in cell biology

doi: 10.1016/B978-0-12-420138-5.00018-5

Example spreadsheet layout to use the Microsoft Excel ‘Solver’ for least square curve fitting of FA turnover dynamics, which can be adapted to fit any non-linear function. Columns D–F contain the data for the assembly, logistic
Figure Legend Snippet: Example spreadsheet layout to use the Microsoft Excel ‘Solver’ for least square curve fitting of FA turnover dynamics, which can be adapted to fit any non-linear function. Columns D–F contain the data for the assembly, logistic

Techniques Used:

27) Product Images from "Characterization of a Replicating Mammalian Orthoreovirus with Tetracysteine-Tagged μNS for Live-Cell Visualization of Viral Factories"

Article Title: Characterization of a Replicating Mammalian Orthoreovirus with Tetracysteine-Tagged μNS for Live-Cell Visualization of Viral Factories

Journal: Journal of Virology

doi: 10.1128/JVI.01371-17

Recombinant TC-μNS virus replication. L929 cells were infected with T1L, rTC-μNS(C-term-T1L)/P2, or rTC-μNS(#7-T1L)/P2 and at 0, 12, 24, 36, and 48 h p.i. cells were harvested. Harvested cells were subjected to standard MRV plaque assay. (A) Plaques from each time point were counted, and the relative viral titer increase from time zero is plotted. The means and standard deviations were calculated from two experimental replicates within two different biological replicates. A two-tailed Student t test was used to calculate P values for significant differences between recombinant virus and wild-type virus in Microsoft Excel: *, P
Figure Legend Snippet: Recombinant TC-μNS virus replication. L929 cells were infected with T1L, rTC-μNS(C-term-T1L)/P2, or rTC-μNS(#7-T1L)/P2 and at 0, 12, 24, 36, and 48 h p.i. cells were harvested. Harvested cells were subjected to standard MRV plaque assay. (A) Plaques from each time point were counted, and the relative viral titer increase from time zero is plotted. The means and standard deviations were calculated from two experimental replicates within two different biological replicates. A two-tailed Student t test was used to calculate P values for significant differences between recombinant virus and wild-type virus in Microsoft Excel: *, P

Techniques Used: Recombinant, Infection, Plaque Assay, Two Tailed Test

28) Product Images from "Pacific-wide simplified syndromic surveillance for early warning of outbreaks"

Article Title: Pacific-wide simplified syndromic surveillance for early warning of outbreaks

Journal: Global Public Health

doi: 10.1080/17441692.2012.699536

Syndromic Surveillance weekly summary table for week 47, 2011, as distributed through the PacNet email list server. The table is generated by a Microsoft Excel spreadsheet, automatically highlighting case numbers that exceed 90% of historical values. The high numbers of cases in the Marshall Islands were caused by an epidemic of dengue.
Figure Legend Snippet: Syndromic Surveillance weekly summary table for week 47, 2011, as distributed through the PacNet email list server. The table is generated by a Microsoft Excel spreadsheet, automatically highlighting case numbers that exceed 90% of historical values. The high numbers of cases in the Marshall Islands were caused by an epidemic of dengue.

Techniques Used: Generated

29) Product Images from "Comparative population structure of Plasmodium falciparum circumsporozoite protein NANP repeat lengths in Lilongwe, Malawi"

Article Title: Comparative population structure of Plasmodium falciparum circumsporozoite protein NANP repeat lengths in Lilongwe, Malawi

Journal: Scientific Reports

doi: 10.1038/srep01990

Analysis of genetic similarity between different parts of the city of Lilongwe. Panel A shows the geographic regions within and around Lilongwe used for the spatial analysis. Arrows show the pairwise comparison between each region and Nei's standard genetic distance between parasites identified in each population. The East Urban Region was the most diverse and had the highest number of participants (48 individuals, 61 variants), followed by the West Urban (25 individuals, 32 variants), West Peri-urban (10 individuals, 11 variants), and East Peri-urban (9 individuals, 11 variants). The map was prepared using ArcGIS (ESRI, Redlands, CA) and Microsoft Powerpoint (Microsoft, Seattle, WA). Panel B shows a principle coordinate analysis of genetic relatedness between regions. East and west urban regions cluster more closely to each other than either periurban region. Coordinate 1 explains 78.9% of the variation and coordinate 2 explains 18.8% of the variation.
Figure Legend Snippet: Analysis of genetic similarity between different parts of the city of Lilongwe. Panel A shows the geographic regions within and around Lilongwe used for the spatial analysis. Arrows show the pairwise comparison between each region and Nei's standard genetic distance between parasites identified in each population. The East Urban Region was the most diverse and had the highest number of participants (48 individuals, 61 variants), followed by the West Urban (25 individuals, 32 variants), West Peri-urban (10 individuals, 11 variants), and East Peri-urban (9 individuals, 11 variants). The map was prepared using ArcGIS (ESRI, Redlands, CA) and Microsoft Powerpoint (Microsoft, Seattle, WA). Panel B shows a principle coordinate analysis of genetic relatedness between regions. East and west urban regions cluster more closely to each other than either periurban region. Coordinate 1 explains 78.9% of the variation and coordinate 2 explains 18.8% of the variation.

Techniques Used:

30) Product Images from "Virus-Like Attachment Sites and Plastic CpG Islands: Landmarks of Diversity in Plant Del Retrotransposons"

Article Title: Virus-Like Attachment Sites and Plastic CpG Islands: Landmarks of Diversity in Plant Del Retrotransposons

Journal: PLoS ONE

doi: 10.1371/journal.pone.0097099

Correlation between LTR length and length of the entire element. The length of the LTR and the complete element were taken from the LTR_STRUC output. R 2 was calculated using Microsoft Excel. There is a strong positive correlation between the length of LTR and the complete element (R 2 = 0.92141).
Figure Legend Snippet: Correlation between LTR length and length of the entire element. The length of the LTR and the complete element were taken from the LTR_STRUC output. R 2 was calculated using Microsoft Excel. There is a strong positive correlation between the length of LTR and the complete element (R 2 = 0.92141).

Techniques Used:

31) Product Images from "Tumor cell invasion of collagen matrices requires coordinate lipid agonist-induced G-protein and membrane-type matrix metalloproteinase-1-dependent signaling"

Article Title: Tumor cell invasion of collagen matrices requires coordinate lipid agonist-induced G-protein and membrane-type matrix metalloproteinase-1-dependent signaling

Journal: Molecular Cancer

doi: 10.1186/1476-4598-5-69

HT1080 cell motility using modified Boyden chambers does not require MMPs . HT1080 cells were seeded onto porous (8 μm) polycarbonate membranes coated with type I collagen (1 mg/ml) and allowed to migrate for four hours in the presence of 1 μM LPA or S1P in the presence or absence of synthetic MMP inhibitors (5 μM GM6001, 5 μM TAPI-0, or 5 μM TAPI-1). Membranes were removed, stained, and migrating cells were quantitated using Scion ® software and Microsoft Excel ® . Data are expressed as mean number of migrating cells × 10 3 (± S.D.) and represent the results of quadruplicate experiments.
Figure Legend Snippet: HT1080 cell motility using modified Boyden chambers does not require MMPs . HT1080 cells were seeded onto porous (8 μm) polycarbonate membranes coated with type I collagen (1 mg/ml) and allowed to migrate for four hours in the presence of 1 μM LPA or S1P in the presence or absence of synthetic MMP inhibitors (5 μM GM6001, 5 μM TAPI-0, or 5 μM TAPI-1). Membranes were removed, stained, and migrating cells were quantitated using Scion ® software and Microsoft Excel ® . Data are expressed as mean number of migrating cells × 10 3 (± S.D.) and represent the results of quadruplicate experiments.

Techniques Used: Modification, Staining, Software

LPA stimulates and S1P inhibits migration of most tumor cell lines . Tumor cell migration analysis was performed on 8 μm polycarbonate gelatin-coated membranes and 20 μg/ml of fibronectin. LPA and/or S1P (1 μM) were added to the lower chambers and cells were allowed to migrate for 4 hours. Membranes were removed, stained, and migrating cells were quantitated using Scion ® software and Microsoft Excel ® . Data are expressed as mean number of migrating cells × 10 3 (± S.D.) and represent the results of quadruplicate experiments.
Figure Legend Snippet: LPA stimulates and S1P inhibits migration of most tumor cell lines . Tumor cell migration analysis was performed on 8 μm polycarbonate gelatin-coated membranes and 20 μg/ml of fibronectin. LPA and/or S1P (1 μM) were added to the lower chambers and cells were allowed to migrate for 4 hours. Membranes were removed, stained, and migrating cells were quantitated using Scion ® software and Microsoft Excel ® . Data are expressed as mean number of migrating cells × 10 3 (± S.D.) and represent the results of quadruplicate experiments.

Techniques Used: Migration, Staining, Software

32) Product Images from "Using Heatmaps to Identify Opportunities for Optimization of Test Utilization and Care Delivery"

Article Title: Using Heatmaps to Identify Opportunities for Optimization of Test Utilization and Care Delivery

Journal: Journal of Pathology Informatics

doi: 10.4103/jpi.jpi_7_18

Workflow: The workflow to calculate utilization indices and create heatmaps involves 12 steps using Microsoft Excel
Figure Legend Snippet: Workflow: The workflow to calculate utilization indices and create heatmaps involves 12 steps using Microsoft Excel

Techniques Used:

33) Product Images from "Effects of the stimuli-dependent enrichment of 8-oxoguanine DNA glycosylase1 on chromatinized DNA"

Article Title: Effects of the stimuli-dependent enrichment of 8-oxoguanine DNA glycosylase1 on chromatinized DNA

Journal: Redox Biology

doi: 10.1016/j.redox.2018.06.002

Location of OGG1 and NF-κB enrichment peaks and overrepresented IIR processes associated with OGG1 Ab-ChIP-ed genes. A , Unique and overlapping genes ChIP-ed by OGG1- and RelA(NF-κB)-Abs in the IIR pathway. IIR genes (1294) identified by GeneCards database was “overlaid” onto the OGG1 and NF-κB Ab-ChIP-ed genes. B , Genomic location of OGG1 and NF-κB enrichment peaks in the IIR genes. C , Gene ontology categories defined by Gorilla, based on OGG1 ChIP-ed genes. The ranked list of genes was submitted to GOrilla online system, and the GOrilla-defined overrepresentation levels of each biological process are expressed as –log ( P value), as depicted utilizing the Microsoft Excel program. D . GOrilla, gene ontology enRIchment anaLysis and visuaLizAtion system; IIR, innate immune response; 5’UTR, five prime un-translated region.
Figure Legend Snippet: Location of OGG1 and NF-κB enrichment peaks and overrepresented IIR processes associated with OGG1 Ab-ChIP-ed genes. A , Unique and overlapping genes ChIP-ed by OGG1- and RelA(NF-κB)-Abs in the IIR pathway. IIR genes (1294) identified by GeneCards database was “overlaid” onto the OGG1 and NF-κB Ab-ChIP-ed genes. B , Genomic location of OGG1 and NF-κB enrichment peaks in the IIR genes. C , Gene ontology categories defined by Gorilla, based on OGG1 ChIP-ed genes. The ranked list of genes was submitted to GOrilla online system, and the GOrilla-defined overrepresentation levels of each biological process are expressed as –log ( P value), as depicted utilizing the Microsoft Excel program. D . GOrilla, gene ontology enRIchment anaLysis and visuaLizAtion system; IIR, innate immune response; 5’UTR, five prime un-translated region.

Techniques Used: Chromatin Immunoprecipitation

34) Product Images from "Kinetic Analysis of the Effect of Poliovirus Receptor on Viral Uncoating: the Receptor as a Catalyst"

Article Title: Kinetic Analysis of the Effect of Poliovirus Receptor on Viral Uncoating: the Receptor as a Catalyst

Journal: Journal of Virology

doi: 10.1128/JVI.75.11.4984-4989.2001

) was modified to include sPvR at 0.25 μM. The plots show the natural logarithm of the concentration of unconverted 160S particle versus time. Each point is the average of three separate experiments; bars indicate the standard deviation of the average of the measurements. The data for the low-temperature reactions for all graphs were truncated for the sake of clarity of the higher-temperature data. Plots were generated using Microsoft Excel.
Figure Legend Snippet: ) was modified to include sPvR at 0.25 μM. The plots show the natural logarithm of the concentration of unconverted 160S particle versus time. Each point is the average of three separate experiments; bars indicate the standard deviation of the average of the measurements. The data for the low-temperature reactions for all graphs were truncated for the sake of clarity of the higher-temperature data. Plots were generated using Microsoft Excel.

Techniques Used: Modification, Concentration Assay, Standard Deviation, Generated

35) Product Images from "Mining plant genome browsers as a means for efficient connection of physical, genetic and cytogenetic mapping: An example using soybean"

Article Title: Mining plant genome browsers as a means for efficient connection of physical, genetic and cytogenetic mapping: An example using soybean

Journal: Genetics and Molecular Biology

doi: 10.1590/S1415-47572012000200015

In silico of (AAC) 5 SSR oligonucleotide. (a) Anchoring by using the BLASTn algorithm at http://www.phytozome.com/search.php ; (b) screen print of the UltraEdit text editor for organizing data sheets; (c) Microsoft Office Excel sheet for data handling; (d) sequence location in the soybean genome at http://soybase.org/gbrowse/cgi-bin/gbrowse/gmax1.01/ .
Figure Legend Snippet: In silico of (AAC) 5 SSR oligonucleotide. (a) Anchoring by using the BLASTn algorithm at http://www.phytozome.com/search.php ; (b) screen print of the UltraEdit text editor for organizing data sheets; (c) Microsoft Office Excel sheet for data handling; (d) sequence location in the soybean genome at http://soybase.org/gbrowse/cgi-bin/gbrowse/gmax1.01/ .

Techniques Used: In Silico, Sequencing

36) Product Images from "The CTCF insulator protein forms an unusual DNA structure"

Article Title: The CTCF insulator protein forms an unusual DNA structure

Journal: BMC Molecular Biology

doi: 10.1186/1471-2199-11-101

CTCF exhibits orientation dependent directed bend at FII insulator element . (A) κ-DNA contains phased A rich tracts with an intrinsic bend toward the minor groove. FII insulator element points towards κ-DNA (forward) or away from it (reverse). Helical phasing between sites is varied by increasing length of DNA spacer (black box) by 2 bp increments (10 to 20 bp) over one helical turn of the DNA. Plasmids digested with RsaI and PvuII gave 391bp to 401bp probes containing FII site. NheI was included to cleave a plasmid backbone fragment. (marked with asterisk, does not bind CTCF). (B) Schematic diagram of cis and trans isomers. C is isomer migrates more slowly than trans isomer. (C) Phasing experiment: FII site in forward orientation. Two CTCF DNA complexes are seen. Lower complex, formed by truncated CTCF, is obscured by vector backbone fragment (*, lane 5). Complex migrates most slowly when the protein-induced and sequence-directed bends are additive (
Figure Legend Snippet: CTCF exhibits orientation dependent directed bend at FII insulator element . (A) κ-DNA contains phased A rich tracts with an intrinsic bend toward the minor groove. FII insulator element points towards κ-DNA (forward) or away from it (reverse). Helical phasing between sites is varied by increasing length of DNA spacer (black box) by 2 bp increments (10 to 20 bp) over one helical turn of the DNA. Plasmids digested with RsaI and PvuII gave 391bp to 401bp probes containing FII site. NheI was included to cleave a plasmid backbone fragment. (marked with asterisk, does not bind CTCF). (B) Schematic diagram of cis and trans isomers. C is isomer migrates more slowly than trans isomer. (C) Phasing experiment: FII site in forward orientation. Two CTCF DNA complexes are seen. Lower complex, formed by truncated CTCF, is obscured by vector backbone fragment (*, lane 5). Complex migrates most slowly when the protein-induced and sequence-directed bends are additive (" cis " isoform, lanes 1 and 6). When bends are out of phase (" trans " isoform), complex has greatest mobility (lanes 4 and 5). Relative mobilities of protein-DNA complexes normalized to those of free probes are plotted relative to spacer length. Best fit polynomial curve was determined using Microsoft Excel. (D) Phasing experiment: FII site in reverse orientation. Two CTCF DNA complexes are seen. Lower complex is obscured by contaminating radiolabeled vector fragment (7, 9 and 11). " Cis " isomer and " trans " isomers are formed in alternating manner when spacer length increases by 2 bp.

Techniques Used: Plasmid Preparation, Sequencing

37) Product Images from "Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data"

Article Title: Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data

Journal: International Journal of Health Geographics

doi: 10.1186/1476-072X-10-19

A snippet from the collection.html file used in the authors' Microsoft Pivot WHO mortality data demonstration . The URL (Universal Resource Locator) of the associated collection.cxml file is marked by a red arrow. The complete collection.html file used in this demonstration can be found in the 'Additional file 1 ' archive.
Figure Legend Snippet: A snippet from the collection.html file used in the authors' Microsoft Pivot WHO mortality data demonstration . The URL (Universal Resource Locator) of the associated collection.cxml file is marked by a red arrow. The complete collection.html file used in this demonstration can be found in the 'Additional file 1 ' archive.

Techniques Used:

Microsoft Excel plug-in for Pivot collections . Screenshot showing a new spreadsheet for Pivot collection tool using the free Excel add-in for Pivot collections from Microsoft [ 34 ].
Figure Legend Snippet: Microsoft Excel plug-in for Pivot collections . Screenshot showing a new spreadsheet for Pivot collection tool using the free Excel add-in for Pivot collections from Microsoft [ 34 ].

Techniques Used:

A snippet from the collection.cxml file used in the authors' Microsoft Pivot WHO mortality data demonstration . The complete collection.cxml file used in this demonstration can be found in the 'Additional file 1 ' archive.
Figure Legend Snippet: A snippet from the collection.cxml file used in the authors' Microsoft Pivot WHO mortality data demonstration . The complete collection.cxml file used in this demonstration can be found in the 'Additional file 1 ' archive.

Techniques Used:

A snippet from the collection.xml file used in the authors' Microsoft Pivot WHO mortality data demonstration . The complete collection.xml file used in this demonstration can be found in the 'Additional file 1 ' archive.
Figure Legend Snippet: A snippet from the collection.xml file used in the authors' Microsoft Pivot WHO mortality data demonstration . The complete collection.xml file used in this demonstration can be found in the 'Additional file 1 ' archive.

Techniques Used:

Pivot worksheet populated with a sample of WHO mortality data in Microsoft Excel . Images used in this collection are a blue man icon for males records, a pink woman icon for females records, and a black man-and-woman-together icon for records of both sexes.
Figure Legend Snippet: Pivot worksheet populated with a sample of WHO mortality data in Microsoft Excel . Images used in this collection are a blue man icon for males records, a pink woman icon for females records, and a black man-and-woman-together icon for records of both sexes.

Techniques Used:

38) Product Images from "Prioritizing Health: A Systematic Approach to Scoping Determinants in Health Impact Assessment"

Article Title: Prioritizing Health: A Systematic Approach to Scoping Determinants in Health Impact Assessment

Journal: Frontiers in Public Health

doi: 10.3389/fpubh.2016.00170

Systematic HIA Scoping Tool: example (automated in Microsoft Excel) .
Figure Legend Snippet: Systematic HIA Scoping Tool: example (automated in Microsoft Excel) .

Techniques Used:

39) Product Images from "Evaluating Behavioral Skills Training to Teach Basic Computer Skills to a Young Adult with Autism"

Article Title: Evaluating Behavioral Skills Training to Teach Basic Computer Skills to a Young Adult with Autism

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-018-00295-5

Percentage of correct responses for John across Microsoft Word® (top panel), PowerPoint® (middle panel), and Excel® (bottom panel) during baseline, posttraining, and maintenance. Maintenance data were collected at 14, 13, and 11 weeks following posttraining for Word®, PowerPoint®, and Excel® consecutively
Figure Legend Snippet: Percentage of correct responses for John across Microsoft Word® (top panel), PowerPoint® (middle panel), and Excel® (bottom panel) during baseline, posttraining, and maintenance. Maintenance data were collected at 14, 13, and 11 weeks following posttraining for Word®, PowerPoint®, and Excel® consecutively

Techniques Used:

40) Product Images from "Evaluating Behavioral Skills Training to Teach Basic Computer Skills to a Young Adult with Autism"

Article Title: Evaluating Behavioral Skills Training to Teach Basic Computer Skills to a Young Adult with Autism

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-018-00295-5

Percentage of correct responses for John across Microsoft Word® (top panel), PowerPoint® (middle panel), and Excel® (bottom panel) during baseline, posttraining, and maintenance. Maintenance data were collected at 14, 13, and 11 weeks following posttraining for Word®, PowerPoint®, and Excel® consecutively
Figure Legend Snippet: Percentage of correct responses for John across Microsoft Word® (top panel), PowerPoint® (middle panel), and Excel® (bottom panel) during baseline, posttraining, and maintenance. Maintenance data were collected at 14, 13, and 11 weeks following posttraining for Word®, PowerPoint®, and Excel® consecutively

Techniques Used:

41) Product Images from "Inserting Phase Change Lines into Microsoft Excel® Graphs"

Article Title: Inserting Phase Change Lines into Microsoft Excel® Graphs

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-015-0078-8

Formatting the phase change line data series in Microsoft Excel® 2013 for PC
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2013 for PC

Techniques Used:

Formatting the phase change line data series in Microsoft Excel® 2011 for Mac
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2011 for Mac

Techniques Used:

42) Product Images from "Inserting Phase Change Lines into Microsoft Excel® Graphs"

Article Title: Inserting Phase Change Lines into Microsoft Excel® Graphs

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-015-0078-8

Formatting the phase change line data series in Microsoft Excel® 2013 for PC
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2013 for PC

Techniques Used:

Formatting the phase change line data series in Microsoft Excel® 2011 for Mac
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2011 for Mac

Techniques Used:

43) Product Images from "A Survey of Quantitative Descriptions of Molecular Structure"

Article Title: A Survey of Quantitative Descriptions of Molecular Structure

Journal: Current topics in medicinal chemistry

doi:

Four tools to calculate descriptors: Bioclipse (top left), which allows selecting descriptor implementations from various independent tools, CDK-Taverna (top right), which is an extension to Taverna to calculate descriptors with the CDK, Ambit2 (bottom left), which implements the OpenTox API providing a REST-based API for descriptor calculation and wraps various descriptor calculation tools. The bottom right screenshot shows the Microsoft Excel plugin LICSS that uses the CDK for 2D diagrams and descriptor calculation. This screenshot is provided by Kevin Lawson, Syngenta, UK, and reproduced with permission.
Figure Legend Snippet: Four tools to calculate descriptors: Bioclipse (top left), which allows selecting descriptor implementations from various independent tools, CDK-Taverna (top right), which is an extension to Taverna to calculate descriptors with the CDK, Ambit2 (bottom left), which implements the OpenTox API providing a REST-based API for descriptor calculation and wraps various descriptor calculation tools. The bottom right screenshot shows the Microsoft Excel plugin LICSS that uses the CDK for 2D diagrams and descriptor calculation. This screenshot is provided by Kevin Lawson, Syngenta, UK, and reproduced with permission.

Techniques Used:

44) Product Images from "Development of a standardised set of metrics for monitoring site performance in multicentre randomised trials: a Delphi study"

Article Title: Development of a standardised set of metrics for monitoring site performance in multicentre randomised trials: a Delphi study

Journal: Trials

doi: 10.1186/s13063-018-2940-9

Worked example of site performance metrics reporting tool in Microsoft Excel. a Summary worksheet, b thresholds worksheet and c trial data worksheet
Figure Legend Snippet: Worked example of site performance metrics reporting tool in Microsoft Excel. a Summary worksheet, b thresholds worksheet and c trial data worksheet

Techniques Used:

45) Product Images from "Integrating Phase Change Lines and Labels into Graphs in Microsoft Excel®"

Article Title: Integrating Phase Change Lines and Labels into Graphs in Microsoft Excel®

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-018-0248-6

Evolution of withdrawal design graph, steps 2–9, in Microsoft Excel® 2016 for Mac
Figure Legend Snippet: Evolution of withdrawal design graph, steps 2–9, in Microsoft Excel® 2016 for Mac

Techniques Used:

Evolution of withdrawal design graph, steps 10–12, in Microsoft Excel® 2016 for Mac
Figure Legend Snippet: Evolution of withdrawal design graph, steps 10–12, in Microsoft Excel® 2016 for Mac

Techniques Used:

Evolution of withdrawal design graph, step 1, in Microsoft Excel® 2016 for Mac
Figure Legend Snippet: Evolution of withdrawal design graph, step 1, in Microsoft Excel® 2016 for Mac

Techniques Used:

46) Product Images from "Analysis of whole genome sequences of 16 strains of rubella virus from the United States, 1961-2009"

Article Title: Analysis of whole genome sequences of 16 strains of rubella virus from the United States, 1961-2009

Journal: Virology Journal

doi: 10.1186/1743-422X-10-32

Identity plots of nucleotide (A) and amino acid (B) sequences of 30 rubella viruses. The genes and putative domains are shown at the top of the panels. This includes: the methyltransferase (MT), hypervariable region (HVR), X-domain (X), the protease (Pro), helicase (Hel) and RNA-dependent RNA polymerase (RdRp) in NSP and the nucleocapid (C), membrane glycoprotein 2 (E2) and membrane glycoprotein 1 (E1) in SP. The nt analysis was done by counting the number of identical residues at the specific positions of all (green), clade 1 (blue) or clade 2 (red) viruses using Microsoft Office Excel. Comparisons were done using the consensus sequence from all 30 viruses or the clade-specific consensus sequences. Thus, any position at which each virus contains identical nt or aa residues will be 1. The nucleotide identity was plotted using a sliding 30-nt window; data are plotted as moving averages of the number of nucleotide changes. Each line in the amino acid identity plot represents the amount of amino acid identity at the indicated position.
Figure Legend Snippet: Identity plots of nucleotide (A) and amino acid (B) sequences of 30 rubella viruses. The genes and putative domains are shown at the top of the panels. This includes: the methyltransferase (MT), hypervariable region (HVR), X-domain (X), the protease (Pro), helicase (Hel) and RNA-dependent RNA polymerase (RdRp) in NSP and the nucleocapid (C), membrane glycoprotein 2 (E2) and membrane glycoprotein 1 (E1) in SP. The nt analysis was done by counting the number of identical residues at the specific positions of all (green), clade 1 (blue) or clade 2 (red) viruses using Microsoft Office Excel. Comparisons were done using the consensus sequence from all 30 viruses or the clade-specific consensus sequences. Thus, any position at which each virus contains identical nt or aa residues will be 1. The nucleotide identity was plotted using a sliding 30-nt window; data are plotted as moving averages of the number of nucleotide changes. Each line in the amino acid identity plot represents the amount of amino acid identity at the indicated position.

Techniques Used: Sequencing

Sequence variation among 30 rubella viruses. The percentage of nucleotide variability ( A ) and amino acid variability ( B ) in each domain, as denoted on the X-axis, of 30 rubella viruses relative to overall consensus sequence was calculated using Microsoft Office Excel. The Y-axis indicates the percentage of variability. The amino acid alignment was determined by ClustalW according to the Gonnet PAM 250 matrix. Panels ( C and D) show the variation of nucleic acid and amino acid sequences for the 6 regions shown in Figure 2 . The conserved, semi-conserved, or non-conserved designation of each aa position was enumerated based on the most variable aa that was observed at that position amongst the 30 viruses. The clade-specific variations in nucleic acid sequences are compared using clade-specific consensus sequences. The range of each domain is indicated at the bottom of the graphs.
Figure Legend Snippet: Sequence variation among 30 rubella viruses. The percentage of nucleotide variability ( A ) and amino acid variability ( B ) in each domain, as denoted on the X-axis, of 30 rubella viruses relative to overall consensus sequence was calculated using Microsoft Office Excel. The Y-axis indicates the percentage of variability. The amino acid alignment was determined by ClustalW according to the Gonnet PAM 250 matrix. Panels ( C and D) show the variation of nucleic acid and amino acid sequences for the 6 regions shown in Figure 2 . The conserved, semi-conserved, or non-conserved designation of each aa position was enumerated based on the most variable aa that was observed at that position amongst the 30 viruses. The clade-specific variations in nucleic acid sequences are compared using clade-specific consensus sequences. The range of each domain is indicated at the bottom of the graphs.

Techniques Used: Sequencing

47) Product Images from "Influenza polymerase encoding mRNAs utilize atypical mRNA nuclear export"

Article Title: Influenza polymerase encoding mRNAs utilize atypical mRNA nuclear export

Journal: Virology Journal

doi: 10.1186/1743-422X-11-154

Expression of dominant negative Nxf1 decreases virus production and results in cytoplasmic reduction of select influenza mRNAs. A549 cells were transfected with plasmid to express dominant negative Nxf1 (DN) or vector control (vec) and infected with influenza A Udorn at 2.5 MOI 48 hours post transfection. A . Virus production at 12 hours post infection with influenza A Udorn. An asterisk indicates statistical difference between cells transfected with DN-Nxf1 compared to vec-control. Data presented is from biological triplicate trials. B . Cells transfected with DN-Nxf1 or vector for 48 hours and subsequently infected with influenza A Udorn at 2.5 MOI for 3.5 hours were fractionated. Cytoplasm and nuclear protein fractions were separated by SDS-PAGE and subject to Western blot to detect SP1 and Hsp90. Shown is a representative blot from one biological trial. C . RT-semi-qPCR of RNA isolated 3.5 hours post infection from the cytoplasm fraction. RNA was quantified and equal concentrations subject to RT with oligo dT. Gene specific PCR was performed using primers to amplify NP, PA, PB1 and PB2 as indicated. Data show sequential PCR cycles from three biological independent trials. D . RT-qPCR of RNA isolated from one of the above biological trials performed in triplicate. Delta Ct was calculated to determine relative RNA expression. Raw CT values were analyzed in Microsoft Excel using 2 ΔCt(average control- average treated) . Standard error was obtained by calculating the standard deviation of the sample set divided by the square root of the sample set size, and indicated using error bars. Significance was determined using a two-tailed T-Test conducted in Microsoft Excel, and judging any p value less than .05 as significant, indicated by an asterisk.
Figure Legend Snippet: Expression of dominant negative Nxf1 decreases virus production and results in cytoplasmic reduction of select influenza mRNAs. A549 cells were transfected with plasmid to express dominant negative Nxf1 (DN) or vector control (vec) and infected with influenza A Udorn at 2.5 MOI 48 hours post transfection. A . Virus production at 12 hours post infection with influenza A Udorn. An asterisk indicates statistical difference between cells transfected with DN-Nxf1 compared to vec-control. Data presented is from biological triplicate trials. B . Cells transfected with DN-Nxf1 or vector for 48 hours and subsequently infected with influenza A Udorn at 2.5 MOI for 3.5 hours were fractionated. Cytoplasm and nuclear protein fractions were separated by SDS-PAGE and subject to Western blot to detect SP1 and Hsp90. Shown is a representative blot from one biological trial. C . RT-semi-qPCR of RNA isolated 3.5 hours post infection from the cytoplasm fraction. RNA was quantified and equal concentrations subject to RT with oligo dT. Gene specific PCR was performed using primers to amplify NP, PA, PB1 and PB2 as indicated. Data show sequential PCR cycles from three biological independent trials. D . RT-qPCR of RNA isolated from one of the above biological trials performed in triplicate. Delta Ct was calculated to determine relative RNA expression. Raw CT values were analyzed in Microsoft Excel using 2 ΔCt(average control- average treated) . Standard error was obtained by calculating the standard deviation of the sample set divided by the square root of the sample set size, and indicated using error bars. Significance was determined using a two-tailed T-Test conducted in Microsoft Excel, and judging any p value less than .05 as significant, indicated by an asterisk.

Techniques Used: Expressing, Dominant Negative Mutation, Transfection, Plasmid Preparation, Infection, SDS Page, Western Blot, Real-time Polymerase Chain Reaction, Isolation, Polymerase Chain Reaction, Quantitative RT-PCR, RNA Expression, Standard Deviation, Two Tailed Test

Leptomycin B treatment does not alter cytoplasmic influenza PA, PB1, or PB2 mRNA in A549 cells. A549 cells were infected with influenza A and virus allowed to adhere for 1 hour at which time virus inoculum was removed and replaced with media containing 10nM leptomycin B (LMB) to inhibit Crm1-mediate nuclear export or untreated media as control. A . Media samples from mock infected, LMB treated and untreated infected cells (top rows infected at MOI 1.4, bottom row infected at 2.8 MOI) were collected 36 hours post infection and subject to HA assay using two-fold dilutions. B . Infected LMB treated and untreated cells were fractionated at 3.5 hours post infection. Cytoplasm and nuclear protein fractions were separated by SDS-PAGE and subject to Western blot to detect Nxf1 and Hsp90. C . RT-qPCR of RNA isolated from the cytoplasm fraction 3.5 hours post infection. RNA was quantified and equal concentrations subject to RT with oligo dT. Gene specific PCR was performed using primers to amplify PA, PB1, PB2, HA, and NP as indicated. Data shown is from one biological trial performed in triplicate. Delta Ct was calculated to determine relative RNA expression. Raw CT values were analyzed in Microsoft Excel using 2 ΔCt(average control- average treated) . Standard error was obtained by calculating the standard deviation of the sample set divided by the square root of the sample set size, and indicated using error bars. Significance was determined using a two-tailed T-Test conducted in Microsoft Excel, and judging any p value less than 0.05 as significant, no genes showed statistical difference in relative expression of RNA. PB2 p value was 0.105.
Figure Legend Snippet: Leptomycin B treatment does not alter cytoplasmic influenza PA, PB1, or PB2 mRNA in A549 cells. A549 cells were infected with influenza A and virus allowed to adhere for 1 hour at which time virus inoculum was removed and replaced with media containing 10nM leptomycin B (LMB) to inhibit Crm1-mediate nuclear export or untreated media as control. A . Media samples from mock infected, LMB treated and untreated infected cells (top rows infected at MOI 1.4, bottom row infected at 2.8 MOI) were collected 36 hours post infection and subject to HA assay using two-fold dilutions. B . Infected LMB treated and untreated cells were fractionated at 3.5 hours post infection. Cytoplasm and nuclear protein fractions were separated by SDS-PAGE and subject to Western blot to detect Nxf1 and Hsp90. C . RT-qPCR of RNA isolated from the cytoplasm fraction 3.5 hours post infection. RNA was quantified and equal concentrations subject to RT with oligo dT. Gene specific PCR was performed using primers to amplify PA, PB1, PB2, HA, and NP as indicated. Data shown is from one biological trial performed in triplicate. Delta Ct was calculated to determine relative RNA expression. Raw CT values were analyzed in Microsoft Excel using 2 ΔCt(average control- average treated) . Standard error was obtained by calculating the standard deviation of the sample set divided by the square root of the sample set size, and indicated using error bars. Significance was determined using a two-tailed T-Test conducted in Microsoft Excel, and judging any p value less than 0.05 as significant, no genes showed statistical difference in relative expression of RNA. PB2 p value was 0.105.

Techniques Used: Infection, Hemagglutination Assay, SDS Page, Western Blot, Quantitative RT-PCR, Isolation, Polymerase Chain Reaction, RNA Expression, Standard Deviation, Two Tailed Test, Expressing

NP mRNA analysis reveals a cell type difference in dependence of Nxf1-mediated nuclear export. A549 and 293 T cells were transfected with plasmid to express dominant negative Nxf1 (DN) or vector control (vec), infected with influenza A Udorn at 2.5 MOI 48 hours post transfection, and fractionated 3.5 hours post infection. A . Cytoplasm and nuclear protein fractions were separated by SDS-PAGE and subject to Western blot to detect SP1, TAT-SF1, or tubulin. Shown is a representative blot from one biological trial. B . RT-qPCR of RNA isolated from the cytoplasm fraction. RNA was quantified and equal concentrations subject to RT with oligo dT. Gene specific PCR was performed using primers to amplify NP, PA, PB1 and PB2 as indicated. Data shown is from two biological independent trials of more than 5 repeats, each trial performed in triplicate PCR. Delta Ct was calculated to determine relative RNA expression. Raw CT values were analyzed in Microsoft Excel using 2 ΔCt(average control- average treated) . Standard error was obtained by calculating the standard deviation of the sample set divided by the square root of the sample set size, and indicated using error bars. Significance was determined using a two-tailed T-Test conducted in Microsoft Excel, and judging any p value less than .05 as significant, indicated by an asterisk.
Figure Legend Snippet: NP mRNA analysis reveals a cell type difference in dependence of Nxf1-mediated nuclear export. A549 and 293 T cells were transfected with plasmid to express dominant negative Nxf1 (DN) or vector control (vec), infected with influenza A Udorn at 2.5 MOI 48 hours post transfection, and fractionated 3.5 hours post infection. A . Cytoplasm and nuclear protein fractions were separated by SDS-PAGE and subject to Western blot to detect SP1, TAT-SF1, or tubulin. Shown is a representative blot from one biological trial. B . RT-qPCR of RNA isolated from the cytoplasm fraction. RNA was quantified and equal concentrations subject to RT with oligo dT. Gene specific PCR was performed using primers to amplify NP, PA, PB1 and PB2 as indicated. Data shown is from two biological independent trials of more than 5 repeats, each trial performed in triplicate PCR. Delta Ct was calculated to determine relative RNA expression. Raw CT values were analyzed in Microsoft Excel using 2 ΔCt(average control- average treated) . Standard error was obtained by calculating the standard deviation of the sample set divided by the square root of the sample set size, and indicated using error bars. Significance was determined using a two-tailed T-Test conducted in Microsoft Excel, and judging any p value less than .05 as significant, indicated by an asterisk.

Techniques Used: Transfection, Plasmid Preparation, Dominant Negative Mutation, Infection, SDS Page, Western Blot, Quantitative RT-PCR, Isolation, Polymerase Chain Reaction, RNA Expression, Standard Deviation, Two Tailed Test

48) Product Images from "Synthesis and Evaluation of a Well-defined HPMA Copolymer-Dexamethasone Conjugate for Effective Treatment of Rheumatoid Arthritis"

Article Title: Synthesis and Evaluation of a Well-defined HPMA Copolymer-Dexamethasone Conjugate for Effective Treatment of Rheumatoid Arthritis

Journal: Pharmaceutical research

doi: 10.1007/s11095-008-9683-3

In vitro Dex release from P-Dex at pH = 5.0 and 7.4. Each sample was measured 3 times. The mean values and standard deviation were calculated with Microsoft Excel. For the linear regression, R 2 > 0.99.
Figure Legend Snippet: In vitro Dex release from P-Dex at pH = 5.0 and 7.4. Each sample was measured 3 times. The mean values and standard deviation were calculated with Microsoft Excel. For the linear regression, R 2 > 0.99.

Techniques Used: In Vitro, Standard Deviation

49) Product Images from "A critical evaluation of the electronic surgical logbook"

Article Title: A critical evaluation of the electronic surgical logbook

Journal: BMC Medical Education

doi: 10.1186/1472-6920-6-15

Microsoft Access version of the ASGBI logbook (version 2.4). The various fields for collecting the data are demonstrated.
Figure Legend Snippet: Microsoft Access version of the ASGBI logbook (version 2.4). The various fields for collecting the data are demonstrated.

Techniques Used:

50) Product Images from "PubChemSR: A search and retrieval tool for PubChem"

Article Title: PubChemSR: A search and retrieval tool for PubChem

Journal: Chemistry Central Journal

doi: 10.1186/1752-153X-2-11

Property data exported into Microsoft Excel . Selected property-related fields of the 25 'acetaminophen' related compounds were exported into an Excel file. The filtering, sorting and graphing features of Excel can then be used to examine this data.
Figure Legend Snippet: Property data exported into Microsoft Excel . Selected property-related fields of the 25 'acetaminophen' related compounds were exported into an Excel file. The filtering, sorting and graphing features of Excel can then be used to examine this data.

Techniques Used:

51) Product Images from "Virus-Like Attachment Sites and Plastic CpG Islands: Landmarks of Diversity in Plant Del Retrotransposons"

Article Title: Virus-Like Attachment Sites and Plastic CpG Islands: Landmarks of Diversity in Plant Del Retrotransposons

Journal: PLoS ONE

doi: 10.1371/journal.pone.0097099

Correlation between LTR length and length of the entire element. The length of the LTR and the complete element were taken from the LTR_STRUC output. R 2 was calculated using Microsoft Excel. There is a strong positive correlation between the length of LTR and the complete element (R 2 = 0.92141).
Figure Legend Snippet: Correlation between LTR length and length of the entire element. The length of the LTR and the complete element were taken from the LTR_STRUC output. R 2 was calculated using Microsoft Excel. There is a strong positive correlation between the length of LTR and the complete element (R 2 = 0.92141).

Techniques Used:

52) Product Images from "Gene density and transcription influence the localization of chromatin outside of chromosome territories detectable by FISH"

Article Title: Gene density and transcription influence the localization of chromatin outside of chromosome territories detectable by FISH

Journal: The Journal of Cell Biology

doi: 10.1083/jcb.200207115

Correlation between gene density and localization relative to chromosome territories. Mean probe positions (normalized for territory radius) relative to the edge of chromosome territories measured in hybridizations to two-dimensional MAA-fixed lymphoblast nuclei, plotted against gene density (Genes/Mb) for all of the regions considered in this analysis. A value of 0 on the y-axis represents the edge of the chromosome territory and negative values indicate that the mean locus position is outside of the chromosome territory. The best-fit line was determined using Microsoft Excel. The equation for the line is y = −0.0242x + 0.315 and r 2 = 67%.
Figure Legend Snippet: Correlation between gene density and localization relative to chromosome territories. Mean probe positions (normalized for territory radius) relative to the edge of chromosome territories measured in hybridizations to two-dimensional MAA-fixed lymphoblast nuclei, plotted against gene density (Genes/Mb) for all of the regions considered in this analysis. A value of 0 on the y-axis represents the edge of the chromosome territory and negative values indicate that the mean locus position is outside of the chromosome territory. The best-fit line was determined using Microsoft Excel. The equation for the line is y = −0.0242x + 0.315 and r 2 = 67%.

Techniques Used:

53) Product Images from "Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype"

Article Title: Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype

Journal: PLoS ONE

doi: 10.1371/journal.pone.0146019

Association of skeletal features in individual Hoxb6 hd mutants. Regression analyses were performed using a simplified scoring scheme for each character: two points were assigned for bilateral abnormalities, one point for unilateral abnormalities and 0 for wildtype manifestation. Each animal is represented by a square. The correlation coefficients (R) were determined using Microsoft Excel. Significance for relationships was assessed by ANOVA and was smaller than p = 0.05 (adjusted p
Figure Legend Snippet: Association of skeletal features in individual Hoxb6 hd mutants. Regression analyses were performed using a simplified scoring scheme for each character: two points were assigned for bilateral abnormalities, one point for unilateral abnormalities and 0 for wildtype manifestation. Each animal is represented by a square. The correlation coefficients (R) were determined using Microsoft Excel. Significance for relationships was assessed by ANOVA and was smaller than p = 0.05 (adjusted p

Techniques Used:

54) Product Images from "Multiple metabolic requirements for size homeostasis and initiation of division in Saccharomyces cerevisiae"

Article Title: Multiple metabolic requirements for size homeostasis and initiation of division in Saccharomyces cerevisiae

Journal: Microbial Cell

doi: 10.15698/mic2014.08.160

FIGURE 4: Adenylate kinase has a role in the efficiency of size control, but cells lacking Adk1p still adjust their size in response to nutrients. (A) In most mutants we examined (shown with open circles) size control operates efficiently. The filled square is the wild type value. On the x-axis is the natural logarithm of the normalized birth size values used in Fig. 3 (with the wild type values equal to one), which were obtained from the data in Table 2. These were plotted against their relative growth in size during the G1 phase ( k T G1 , y-axis). The values we used were the average from the two strain backgrounds. The line is a linear fit obtained with the regression function of Microsoft Excel, from all the strains except those shown in red. (B-D) Cell size histograms of exponentially and asynchronously proliferating wild type haploid cells of the indicated genotype (all in the Y7092 background) cultured in 1% w/v yeast extract, 2% w/v peptone and the indicated amount of the carbon source shown. The x-axis is cell size and the y-axis is the number of cells.
Figure Legend Snippet: FIGURE 4: Adenylate kinase has a role in the efficiency of size control, but cells lacking Adk1p still adjust their size in response to nutrients. (A) In most mutants we examined (shown with open circles) size control operates efficiently. The filled square is the wild type value. On the x-axis is the natural logarithm of the normalized birth size values used in Fig. 3 (with the wild type values equal to one), which were obtained from the data in Table 2. These were plotted against their relative growth in size during the G1 phase ( k T G1 , y-axis). The values we used were the average from the two strain backgrounds. The line is a linear fit obtained with the regression function of Microsoft Excel, from all the strains except those shown in red. (B-D) Cell size histograms of exponentially and asynchronously proliferating wild type haploid cells of the indicated genotype (all in the Y7092 background) cultured in 1% w/v yeast extract, 2% w/v peptone and the indicated amount of the carbon source shown. The x-axis is cell size and the y-axis is the number of cells.

Techniques Used: Cell Culture

55) Product Images from "Burden of psychiatric morbidity among attendees of a secondary level hospital in Northern India: Implications for integration of mental health care at subdistrict level"

Article Title: Burden of psychiatric morbidity among attendees of a secondary level hospital in Northern India: Implications for integration of mental health care at subdistrict level

Journal: Indian Journal of Psychiatry

doi: 10.4103/psychiatry.IndianJPsychiatry_324_16

Trend of patient attendance, by month, for data from Jan 2010, to Jun 2014. The trend line is a linear plotted using a linear regression based forecast using Microsoft Excel, the equation for which is given in the figure. y axis: Number of patients
Figure Legend Snippet: Trend of patient attendance, by month, for data from Jan 2010, to Jun 2014. The trend line is a linear plotted using a linear regression based forecast using Microsoft Excel, the equation for which is given in the figure. y axis: Number of patients

Techniques Used:

56) Product Images from "Development of a standardised set of metrics for monitoring site performance in multicentre randomised trials: a Delphi study"

Article Title: Development of a standardised set of metrics for monitoring site performance in multicentre randomised trials: a Delphi study

Journal: Trials

doi: 10.1186/s13063-018-2940-9

Worked example of site performance metrics reporting tool in Microsoft Excel. a Summary worksheet, b thresholds worksheet and c trial data worksheet
Figure Legend Snippet: Worked example of site performance metrics reporting tool in Microsoft Excel. a Summary worksheet, b thresholds worksheet and c trial data worksheet

Techniques Used:

57) Product Images from "Three-dimensional imaging and quantitative analysis in CLARITY processed breast cancer tissues"

Article Title: Three-dimensional imaging and quantitative analysis in CLARITY processed breast cancer tissues

Journal: Scientific Reports

doi: 10.1038/s41598-019-41957-w

A 0.01% limit of detection can be observed in CLARITY processed cell pellets. ( a ) The mixed cell pellets ratios generated with HEK293-GFP and SUP-T1 cells. ( b ) A representative mixed cell pellet imaged before clearing and 10 days after clearing under a dissecting microscope. ( c ) Confocal microscopy (Leica SP8) images of the cell pellets at different ratios (25X). Top row: 3D z-stack images, Bottom row: a corresponding representative 2D optical section image. The HEK293-GFP cells (green) can be detected in the FOV for all ratio groups, including the rare event level of 0.01%. ( d ) Manual counting of HEK293-GFP (green) was accomplished by calculating the ratio of positive GFP cells/total DAPI (blue) cells (optical sections were used for manual counting, n ≥ 5 for each sample). Statistics were calculated by Microsoft Excel and GraphPad Prism 7.0. ( e ) The automated analysis and quantification of the GFP positive cell pellets was performed using a spot detection strategy generated with Imaris 9.1.2 software.
Figure Legend Snippet: A 0.01% limit of detection can be observed in CLARITY processed cell pellets. ( a ) The mixed cell pellets ratios generated with HEK293-GFP and SUP-T1 cells. ( b ) A representative mixed cell pellet imaged before clearing and 10 days after clearing under a dissecting microscope. ( c ) Confocal microscopy (Leica SP8) images of the cell pellets at different ratios (25X). Top row: 3D z-stack images, Bottom row: a corresponding representative 2D optical section image. The HEK293-GFP cells (green) can be detected in the FOV for all ratio groups, including the rare event level of 0.01%. ( d ) Manual counting of HEK293-GFP (green) was accomplished by calculating the ratio of positive GFP cells/total DAPI (blue) cells (optical sections were used for manual counting, n ≥ 5 for each sample). Statistics were calculated by Microsoft Excel and GraphPad Prism 7.0. ( e ) The automated analysis and quantification of the GFP positive cell pellets was performed using a spot detection strategy generated with Imaris 9.1.2 software.

Techniques Used: Generated, Microscopy, Confocal Microscopy, Software

58) Product Images from "CHARACTERIZATION OF RAT PAROTID AND SUBMANDIBULAR ACINAR CELL APOPTOSIS IN PRIMARY CULTURE"

Article Title: CHARACTERIZATION OF RAT PAROTID AND SUBMANDIBULAR ACINAR CELL APOPTOSIS IN PRIMARY CULTURE

Journal: In vitro cellular & developmental biology. Animal

doi: 10.1007/s11626-003-0012-1

Induction of apoptosis in primary cultures of rat parotid and submandibular acinar cells by etoposide and brefeldin A (BFA). Subconfluent primary cultures of parotid and submandibular acinar cells were stimulated with increasing concentrations of etoposide ( A ) or BFA ( B ) for 24 h. The concentrations of etoposide and BFA are indicated under each column. All adherent and nonadherent cells were collected and lysed in caspase lysis buffer (BioMol QuantiZyme Colormetric Assay kit). Fifteen micrograms of cell lysate was used to analyze the level of enzyme-specific activity (pmol/min/μg protein) for each sample, and samples were measured in quadruplicate as described in the Materials and Methods. The results obtained with the primary parotid cells are indicated in black columns, whereas the results obtained with the primary submandibular cells are indicated in the stippled columns. Error bars represent standard error of the mean from four independent experiments. Student’s t -test P values were calculated using Microsoft Excel, and asterisks designate statistical significance ( P ≤ 0.1) from the respective untreated control.
Figure Legend Snippet: Induction of apoptosis in primary cultures of rat parotid and submandibular acinar cells by etoposide and brefeldin A (BFA). Subconfluent primary cultures of parotid and submandibular acinar cells were stimulated with increasing concentrations of etoposide ( A ) or BFA ( B ) for 24 h. The concentrations of etoposide and BFA are indicated under each column. All adherent and nonadherent cells were collected and lysed in caspase lysis buffer (BioMol QuantiZyme Colormetric Assay kit). Fifteen micrograms of cell lysate was used to analyze the level of enzyme-specific activity (pmol/min/μg protein) for each sample, and samples were measured in quadruplicate as described in the Materials and Methods. The results obtained with the primary parotid cells are indicated in black columns, whereas the results obtained with the primary submandibular cells are indicated in the stippled columns. Error bars represent standard error of the mean from four independent experiments. Student’s t -test P values were calculated using Microsoft Excel, and asterisks designate statistical significance ( P ≤ 0.1) from the respective untreated control.

Techniques Used: Lysis, Activity Assay

Kinetics of caspase-3 activation induced by etoposide and brefeldin A (BFA) in primary parotid acinar cells. Subconfluent primary cultures of parotid acinar cells were treated for various times with etoposide or BFA as indicated. Caspase-3 activation (pmol/min/μg protein) was quantified as described in the Materials and Methods. Error bars represent standard error from four caspase-independent experiments. Student’s t -test P values were calculated using Microsoft Excel, and asterisks designate statistical significance ( P ≤ 0.1) from the respective untreated control.
Figure Legend Snippet: Kinetics of caspase-3 activation induced by etoposide and brefeldin A (BFA) in primary parotid acinar cells. Subconfluent primary cultures of parotid acinar cells were treated for various times with etoposide or BFA as indicated. Caspase-3 activation (pmol/min/μg protein) was quantified as described in the Materials and Methods. Error bars represent standard error from four caspase-independent experiments. Student’s t -test P values were calculated using Microsoft Excel, and asterisks designate statistical significance ( P ≤ 0.1) from the respective untreated control.

Techniques Used: Activation Assay

Kinetics of deoxyribonucleic acid fragmentation induced by etoposide and brefeldin A (BFA) in primary submandibular acinar cells. Sub-confluent primary cultures of submandibular acinar cells were treated for various times with etoposide ( A ) or BFA ( B ). Deoxyribonucleic acid fragmentation was quantified as described in the Materials and Methods. Error bars represent standard error from two histone-independent experiments. Student’s t -test P values were calculated using Microsoft Excel, and asterisks designate statistical significance ( P ≤ 0.05) from the respective untreated control.
Figure Legend Snippet: Kinetics of deoxyribonucleic acid fragmentation induced by etoposide and brefeldin A (BFA) in primary submandibular acinar cells. Sub-confluent primary cultures of submandibular acinar cells were treated for various times with etoposide ( A ) or BFA ( B ). Deoxyribonucleic acid fragmentation was quantified as described in the Materials and Methods. Error bars represent standard error from two histone-independent experiments. Student’s t -test P values were calculated using Microsoft Excel, and asterisks designate statistical significance ( P ≤ 0.05) from the respective untreated control.

Techniques Used:

59) Product Images from "Inserting Phase Change Lines into Microsoft Excel® Graphs"

Article Title: Inserting Phase Change Lines into Microsoft Excel® Graphs

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-015-0078-8

Formatting the phase change line data series in Microsoft Excel® 2013 for PC
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2013 for PC

Techniques Used:

Formatting the phase change line data series in Microsoft Excel® 2011 for Mac
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2011 for Mac

Techniques Used:

60) Product Images from "Therapeutic potential of a tumor-specific, MHC-unrestricted T-cell receptor expressed on effector cells of the innate and the adaptive immune system through bone marrow transduction and immune reconstitution"

Article Title: Therapeutic potential of a tumor-specific, MHC-unrestricted T-cell receptor expressed on effector cells of the innate and the adaptive immune system through bone marrow transduction and immune reconstitution

Journal: Blood

doi: 10.1182/blood-2004-10-3848

SCID mice reconstituted with transduced BM cells can control the growth of the MUC1-positive tumor xenograft. (A) Control (▴) or scTCR-reconstituted (○) mice were injected subcutaneously with 2 × 10 6 HPAF (MUC1-positive) tumor cells. Tumor size is shown on the y-axis while days after tumor challenge is plotted on the x-axis. P values were calculated by running t test using Microsoft Excel software. Data are presented as mean ± SE. (B) H E staining of HPAF tumor sections from control mice (left) or from scTCR-reconstituted mice (right). (C) Staining of tumor sections from scTCR-reconstituted mice for myeloperoxidase (neutrophil marker), F4/80 (monocyte/macrophage marker), or granzyme B (NK cell marker). Images were taken under × 20 magnification. Images in lower right squares were taken under × 100 magnification.
Figure Legend Snippet: SCID mice reconstituted with transduced BM cells can control the growth of the MUC1-positive tumor xenograft. (A) Control (▴) or scTCR-reconstituted (○) mice were injected subcutaneously with 2 × 10 6 HPAF (MUC1-positive) tumor cells. Tumor size is shown on the y-axis while days after tumor challenge is plotted on the x-axis. P values were calculated by running t test using Microsoft Excel software. Data are presented as mean ± SE. (B) H E staining of HPAF tumor sections from control mice (left) or from scTCR-reconstituted mice (right). (C) Staining of tumor sections from scTCR-reconstituted mice for myeloperoxidase (neutrophil marker), F4/80 (monocyte/macrophage marker), or granzyme B (NK cell marker). Images were taken under × 20 magnification. Images in lower right squares were taken under × 100 magnification.

Techniques Used: Mouse Assay, Injection, Software, Staining, Marker

61) Product Images from "Development of a standardised set of metrics for monitoring site performance in multicentre randomised trials: a Delphi study"

Article Title: Development of a standardised set of metrics for monitoring site performance in multicentre randomised trials: a Delphi study

Journal: Trials

doi: 10.1186/s13063-018-2940-9

Worked example of site performance metrics reporting tool in Microsoft Excel. a Summary worksheet, b thresholds worksheet and c trial data worksheet
Figure Legend Snippet: Worked example of site performance metrics reporting tool in Microsoft Excel. a Summary worksheet, b thresholds worksheet and c trial data worksheet

Techniques Used:

62) Product Images from "Triple Fluorescence Anisotropy Reporter Imaging in Living Cells"

Article Title: Triple Fluorescence Anisotropy Reporter Imaging in Living Cells

Journal: Bio-protocol

doi: 10.21769/BioProtoc.3226

Drawing regions and extracting data. A. Aligned stack for cyan channel of experiment mCer3-mCer3 FLARE Cameleon, Venus-cpVenus FLARE EKAR, and mCherry-mCherry FLARE AKAR, with ROIs of interest drawn and logged with FIJI’s ROI Manager tool. The first ROI is of the background, while the rest are of the cells. B. Raw data extracted from the ROI manager using Multi Measure. The values reflect the mean intensity values for each ROI. All odd-numbered rows reflect the time-course for the P -polarized light, while the even-numbered rows reflect the time-course for the S -polarized light. The first column represents the background ROI, while the remaining columns display the mean intensity values for each cell. These data can be copied and pasted into Microsoft Excel to calculate anisotropy values for each cell at each time point.
Figure Legend Snippet: Drawing regions and extracting data. A. Aligned stack for cyan channel of experiment mCer3-mCer3 FLARE Cameleon, Venus-cpVenus FLARE EKAR, and mCherry-mCherry FLARE AKAR, with ROIs of interest drawn and logged with FIJI’s ROI Manager tool. The first ROI is of the background, while the rest are of the cells. B. Raw data extracted from the ROI manager using Multi Measure. The values reflect the mean intensity values for each ROI. All odd-numbered rows reflect the time-course for the P -polarized light, while the even-numbered rows reflect the time-course for the S -polarized light. The first column represents the background ROI, while the remaining columns display the mean intensity values for each cell. These data can be copied and pasted into Microsoft Excel to calculate anisotropy values for each cell at each time point.

Techniques Used:

63) Product Images from "Inserting Phase Change Lines into Microsoft Excel® Graphs"

Article Title: Inserting Phase Change Lines into Microsoft Excel® Graphs

Journal: Behavior Analysis in Practice

doi: 10.1007/s40617-015-0078-8

Formatting the phase change line data series in Microsoft Excel® 2013 for PC
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2013 for PC

Techniques Used:

Formatting the phase change line data series in Microsoft Excel® 2011 for Mac
Figure Legend Snippet: Formatting the phase change line data series in Microsoft Excel® 2011 for Mac

Techniques Used:

64) Product Images from "The gut microbiome of the sea urchin, Lytechinus variegatus, from its natural habitat demonstrates selective attributes of microbial taxa and predictive metabolic profiles"

Article Title: The gut microbiome of the sea urchin, Lytechinus variegatus, from its natural habitat demonstrates selective attributes of microbial taxa and predictive metabolic profiles

Journal: FEMS Microbiology Ecology

doi: 10.1093/femsec/fiw146

PICRUSt (v1.0.0) analysis of predicted metagenomes generated by using the 16S rRNA gene data of the gut tissue ( n = 3) and gut digesta ( n = 3) samples. OTUs were picked using closed-reference picking, as suggested by PICRUSt (v1.0.0), and merged with open-reference picked de novo OTUs (occurring at > 100 per sample) which included each OTU's respective representative Greengenes ID. KEGG pathways were assigned (KO IDs) using the ‘predict_metagenomes.py’ module, and collapsed into hierarchical KEGG pathways (KEGG-Level-2 and 3). ( A ) The mean relative abundance of KEGG-Level-2 metadata categories are listed along with the associated KEGG-Level-3 pathways. ( B ) Box plots of the KEGG-Level-2 category of carbohydrate metabolism, amino acid metabolism, lipid metabolism and energy metabolism were generated using STAMP (v2.1.3) analytical software according to two-group statistics, using a two-sided Welch's t-test (not assuming equal variance) along with Benjamini–Hochberg FDR. Confidence intervals were selected as 95% ( i.e. : 0.95), and P -value of each KEGG-Level-2 two-group analyses is listed in the respective box plot. Relative abundance data were graphed using Microsoft Excel software (Microsoft), and box plots generated using STAMP (v2.1.3).
Figure Legend Snippet: PICRUSt (v1.0.0) analysis of predicted metagenomes generated by using the 16S rRNA gene data of the gut tissue ( n = 3) and gut digesta ( n = 3) samples. OTUs were picked using closed-reference picking, as suggested by PICRUSt (v1.0.0), and merged with open-reference picked de novo OTUs (occurring at > 100 per sample) which included each OTU's respective representative Greengenes ID. KEGG pathways were assigned (KO IDs) using the ‘predict_metagenomes.py’ module, and collapsed into hierarchical KEGG pathways (KEGG-Level-2 and 3). ( A ) The mean relative abundance of KEGG-Level-2 metadata categories are listed along with the associated KEGG-Level-3 pathways. ( B ) Box plots of the KEGG-Level-2 category of carbohydrate metabolism, amino acid metabolism, lipid metabolism and energy metabolism were generated using STAMP (v2.1.3) analytical software according to two-group statistics, using a two-sided Welch's t-test (not assuming equal variance) along with Benjamini–Hochberg FDR. Confidence intervals were selected as 95% ( i.e. : 0.95), and P -value of each KEGG-Level-2 two-group analyses is listed in the respective box plot. Relative abundance data were graphed using Microsoft Excel software (Microsoft), and box plots generated using STAMP (v2.1.3).

Techniques Used: Generated, Software

Stacked column bar graph of the top 100 most resolved taxa (to the genus level where possible) across all samples are presented. Replicates ( n = 3) were merged, and OTUs were left untrimmed. Proteobacteria was found to be considerably abundant across all samples, as well as Bacteroidetes in the gut digesta, egested fecal pellets and water samples. The seagrass contained a high abundance of Cyanobacteria, and the pharynx tissue was dominated by class Mollicutes of phylum Tenericutes. Family Campylobacteraceae was determined to be the most abundant taxa in the gut tissue. In the gut digesta and egested fecal pellets, Vibrio , Propionigenium , and Flavobacteriales, and Photobacterium were most abundant. Relative abundances were calculated in QIIME (v1.8.0), and graphed using Microsoft Excel software (Microsoft).
Figure Legend Snippet: Stacked column bar graph of the top 100 most resolved taxa (to the genus level where possible) across all samples are presented. Replicates ( n = 3) were merged, and OTUs were left untrimmed. Proteobacteria was found to be considerably abundant across all samples, as well as Bacteroidetes in the gut digesta, egested fecal pellets and water samples. The seagrass contained a high abundance of Cyanobacteria, and the pharynx tissue was dominated by class Mollicutes of phylum Tenericutes. Family Campylobacteraceae was determined to be the most abundant taxa in the gut tissue. In the gut digesta and egested fecal pellets, Vibrio , Propionigenium , and Flavobacteriales, and Photobacterium were most abundant. Relative abundances were calculated in QIIME (v1.8.0), and graphed using Microsoft Excel software (Microsoft).

Techniques Used: Software

65) Product Images from "Plant growth strategies are remodeled by spaceflight"

Article Title: Plant growth strategies are remodeled by spaceflight

Journal: BMC Plant Biology

doi: 10.1186/1471-2229-12-232

Quantification and mapping of growth patterns. The direction of root growth over time was quantified by taking measurements of the angle of a root segment in relation to a vertical line, with right being positive degrees and left as negative degrees. Values for each plant cultivar in ground control ( A ) and flight ( B ) in each image, spanning growth through 8.5 days, were averaged and then plotted with Microsoft Excel (see Methods for operational details). The two different cultivars represented on the imaging plate are WS (blue line) and Col-0 (green line). The y-axis shows the degree of deviation from the vertical the root presents at each 6 hour time point and the x-axis shows the corresponding dates the images were taken. Each cultivar plot line is an average taken from measurements of several roots: GC WS: 8 roots; GC Col-0: 3 roots; FLT WS: 7 roots; FLT Col-0: 4 roots. The error bars included with each time point reflect the Standard Error of the Mean.
Figure Legend Snippet: Quantification and mapping of growth patterns. The direction of root growth over time was quantified by taking measurements of the angle of a root segment in relation to a vertical line, with right being positive degrees and left as negative degrees. Values for each plant cultivar in ground control ( A ) and flight ( B ) in each image, spanning growth through 8.5 days, were averaged and then plotted with Microsoft Excel (see Methods for operational details). The two different cultivars represented on the imaging plate are WS (blue line) and Col-0 (green line). The y-axis shows the degree of deviation from the vertical the root presents at each 6 hour time point and the x-axis shows the corresponding dates the images were taken. Each cultivar plot line is an average taken from measurements of several roots: GC WS: 8 roots; GC Col-0: 3 roots; FLT WS: 7 roots; FLT Col-0: 4 roots. The error bars included with each time point reflect the Standard Error of the Mean.

Techniques Used: Imaging

66) Product Images from "Solid State pH Sensor Based on Light Emitting Diodes (LED) As Detector Platform"

Article Title: Solid State pH Sensor Based on Light Emitting Diodes (LED) As Detector Platform

Journal: Sensors (Basel, Switzerland)

doi:

Response curve obtained from LDR sensor. The solid sigmoidal line is the best-fit line obtained by using MicroSoft Excel Solver. The Error bars represent standard deviations of three repeats. The Gaussian curve is the first derivative of the best-fit line to obtain the pKa value for the dye.
Figure Legend Snippet: Response curve obtained from LDR sensor. The solid sigmoidal line is the best-fit line obtained by using MicroSoft Excel Solver. The Error bars represent standard deviations of three repeats. The Gaussian curve is the first derivative of the best-fit line to obtain the pKa value for the dye.

Techniques Used:

The Response curve obtained for the LED sensor. The solid sigmoidal line is the best-fit line obtained by using MicroSoft Excel Solver. The Gaussian curve is the first derivative of the best-fit line to obtain the pKa value for the dye. The inset is the colour change of the LED pH sensor at pH 2 and pH 7.
Figure Legend Snippet: The Response curve obtained for the LED sensor. The solid sigmoidal line is the best-fit line obtained by using MicroSoft Excel Solver. The Gaussian curve is the first derivative of the best-fit line to obtain the pKa value for the dye. The inset is the colour change of the LED pH sensor at pH 2 and pH 7.

Techniques Used:

Averaged response curve obtained from LED sensor. The solid sigmoidal line is the best-fit line obtained by using MicroSoft Excel Solver. The Error bars represent standard deviations of three repeats. The Gaussian curve is the first derivative of the best-fit line to obtain the pKa value for the dye.
Figure Legend Snippet: Averaged response curve obtained from LED sensor. The solid sigmoidal line is the best-fit line obtained by using MicroSoft Excel Solver. The Error bars represent standard deviations of three repeats. The Gaussian curve is the first derivative of the best-fit line to obtain the pKa value for the dye.

Techniques Used:

67) Product Images from "Mimer: an automated spreadsheet-based crystallization screening system"

Article Title: Mimer: an automated spreadsheet-based crystallization screening system

Journal: Acta Crystallographica Section F: Structural Biology and Crystallization Communications

doi: 10.1107/S1744309113014425

Manual crystallization-screen setup using Mimer . ( a ) The Concentrations view of Mimer in Microsoft Excel 2010 on running on Windows XP. This view allows the user to enter stock concentrations and corresponding desired final concentrations for each crystallization
Figure Legend Snippet: Manual crystallization-screen setup using Mimer . ( a ) The Concentrations view of Mimer in Microsoft Excel 2010 on running on Windows XP. This view allows the user to enter stock concentrations and corresponding desired final concentrations for each crystallization

Techniques Used: Crystallization Assay

68) Product Images from "Mimer: an automated spreadsheet-based crystallization screening system"

Article Title: Mimer: an automated spreadsheet-based crystallization screening system

Journal: Acta Crystallographica Section F: Structural Biology and Crystallization Communications

doi: 10.1107/S1744309113014425

Manual crystallization-screen setup using Mimer . ( a ) The Concentrations view of Mimer in Microsoft Excel 2010 on running on Windows XP. This view allows the user to enter stock concentrations and corresponding desired final concentrations for each crystallization
Figure Legend Snippet: Manual crystallization-screen setup using Mimer . ( a ) The Concentrations view of Mimer in Microsoft Excel 2010 on running on Windows XP. This view allows the user to enter stock concentrations and corresponding desired final concentrations for each crystallization

Techniques Used: Crystallization Assay

69) Product Images from "Myeloid Disease Mutations of Splicing Factor SRSF2 Cause G2‐M Arrest and Skewed Differentiation of Human Hematopoietic Stem and Progenitor Cells"

Article Title: Myeloid Disease Mutations of Splicing Factor SRSF2 Cause G2‐M Arrest and Skewed Differentiation of Human Hematopoietic Stem and Progenitor Cells

Journal: Stem Cells (Dayton, Ohio)

doi: 10.1002/stem.2885

SRSF2 mutations alter splicing profiles of CD34 + cells. (A): Frequency of occurrence of nucleotides G, C, A, and T showing C → A and C → G change in the reads spanning exon 2 from RNA‐Seq libraries from cells expressing SRSF2‐P95H and SRSF2‐P95R, respectively. (B): Venn diagrams showing the overlap among the genes that were aberrantly spliced upon expression of SRSF2 mutations in CD34 + cells, patients with acute myeloid leukemia and chronic myelomonocytic leukemia carrying SRSF2 mutations (Kim et al. 17 ). (C): RT‐PCR analysis showing validation of targets of SRSF2 mutations in TF1a and K562 cells. Gel images showing mRNA isoforms that include and skip cassette exons 10a, 6, and 4 in ANKLE1, DLG1, and SETD5, respectively. Isoforms for mutually exclusive exons 3 and 4 in LST1 and exons 4 and 5 in PPIL3 and change in use of alternative 3′ splice site in PPP4R1 are also shown. Percentages of exon inclusion are represented as mean ± standard error of three independent experiments. The p values were calculated using the Student t ‐test in Microsoft Excel. The p values ≤.05 were considered significant and are shown.
Figure Legend Snippet: SRSF2 mutations alter splicing profiles of CD34 + cells. (A): Frequency of occurrence of nucleotides G, C, A, and T showing C → A and C → G change in the reads spanning exon 2 from RNA‐Seq libraries from cells expressing SRSF2‐P95H and SRSF2‐P95R, respectively. (B): Venn diagrams showing the overlap among the genes that were aberrantly spliced upon expression of SRSF2 mutations in CD34 + cells, patients with acute myeloid leukemia and chronic myelomonocytic leukemia carrying SRSF2 mutations (Kim et al. 17 ). (C): RT‐PCR analysis showing validation of targets of SRSF2 mutations in TF1a and K562 cells. Gel images showing mRNA isoforms that include and skip cassette exons 10a, 6, and 4 in ANKLE1, DLG1, and SETD5, respectively. Isoforms for mutually exclusive exons 3 and 4 in LST1 and exons 4 and 5 in PPIL3 and change in use of alternative 3′ splice site in PPP4R1 are also shown. Percentages of exon inclusion are represented as mean ± standard error of three independent experiments. The p values were calculated using the Student t ‐test in Microsoft Excel. The p values ≤.05 were considered significant and are shown.

Techniques Used: RNA Sequencing Assay, Expressing, Reverse Transcription Polymerase Chain Reaction

70) Product Images from "Health risk assessment of nitrate in groundwater resources of Iranshahr using Monte Carlo simulation and geographic information system (GIS)"

Article Title: Health risk assessment of nitrate in groundwater resources of Iranshahr using Monte Carlo simulation and geographic information system (GIS)

Journal: MethodsX

doi: 10.1016/j.mex.2019.07.024

The Status bar of Crystal Ball® ribbon in Microsoft Excel.
Figure Legend Snippet: The Status bar of Crystal Ball® ribbon in Microsoft Excel.

Techniques Used:

71) Product Images from "PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results"

Article Title: PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

Journal: BMC Bioinformatics

doi: 10.1186/1471-2105-8-53

An example of multiple tab-delimited annotations of three sequences viewed in Microsoft Excel.
Figure Legend Snippet: An example of multiple tab-delimited annotations of three sequences viewed in Microsoft Excel.

Techniques Used:

72) Product Images from "Nucleocytoplasmic shuttling of SOX14A and SOX14B transcription factors"

Article Title: Nucleocytoplasmic shuttling of SOX14A and SOX14B transcription factors

Journal: Oncotarget

doi: 10.18632/oncotarget.15134

The ratios of different subcellular locations of SOX14A/B-EGFP/RFP fusion proteins in 293T cells A and B . Quantification of the total cell numbers of wild type or mutant SOX14A/B-EGFP/RFP locations in the nucleus and the cytoplasm from three independent experiments. The total numbers of the different types were shown as the percentage (%) in the tables. Four different kinds of cells are counted and the ratio of each kind are indicated, including nucleus (N), nucleus more than cytoplasm (N > C), cytoplasm more than nucleus (C > N), cytoplasm (C). Total cells from three independent experiments were collected and analysis for the distribution of fluorescent proteins in nucleus or cytoplasm by ImageJ software and Microsoft Excel tools.
Figure Legend Snippet: The ratios of different subcellular locations of SOX14A/B-EGFP/RFP fusion proteins in 293T cells A and B . Quantification of the total cell numbers of wild type or mutant SOX14A/B-EGFP/RFP locations in the nucleus and the cytoplasm from three independent experiments. The total numbers of the different types were shown as the percentage (%) in the tables. Four different kinds of cells are counted and the ratio of each kind are indicated, including nucleus (N), nucleus more than cytoplasm (N > C), cytoplasm more than nucleus (C > N), cytoplasm (C). Total cells from three independent experiments were collected and analysis for the distribution of fluorescent proteins in nucleus or cytoplasm by ImageJ software and Microsoft Excel tools.

Techniques Used: Mutagenesis, Software

73) Product Images from "On the exponent in the Von Bertalanffy growth model"

Article Title: On the exponent in the Von Bertalanffy growth model

Journal: PeerJ

doi: 10.7717/peerj.4205

Comparing the fit of model (1) with different exponents to growth data. Figure generated in Microsoft EXCEL, based on data set #3 and the least squares fit to these data of model (1); squares: data (weight as length 3 ); dashed line: model curve for the exponent a = 0.67 ( m 0 = 0.14, m max = 23, 538, q = 0.18); thick line: model curve for the optimal exponent a = 0.99 ( m 0 = 0.14, m max = 23, 538, q = 26.4).
Figure Legend Snippet: Comparing the fit of model (1) with different exponents to growth data. Figure generated in Microsoft EXCEL, based on data set #3 and the least squares fit to these data of model (1); squares: data (weight as length 3 ); dashed line: model curve for the exponent a = 0.67 ( m 0 = 0.14, m max = 23, 538, q = 0.18); thick line: model curve for the optimal exponent a = 0.99 ( m 0 = 0.14, m max = 23, 538, q = 26.4).

Techniques Used: Generated

Right hand side of Eq. (1) compared to observed values for the left hand side of (1) . Figure generated in Microsoft EXCEL based on data set #10 (outlier removed). Squares indicate observed growth rates, the left hand side of Eq. (1) , whereby dm / dt was computed by numeric differentiation (quadratic interpolation taking care of unequal dt -interval length; Burden Faires, 1993 ). The line (model) is the right hand side of Eq. (1) . Its parameters ( p = 323, q = 0.73) were obtained from a linear fit to the observed growth rates (LINEST function of EXCEL applied to dm / dt , m a , and m with a = 2∕3). This method of fitting parameters is a modification of the Walford plot ( Walford, 1946 ).
Figure Legend Snippet: Right hand side of Eq. (1) compared to observed values for the left hand side of (1) . Figure generated in Microsoft EXCEL based on data set #10 (outlier removed). Squares indicate observed growth rates, the left hand side of Eq. (1) , whereby dm / dt was computed by numeric differentiation (quadratic interpolation taking care of unequal dt -interval length; Burden Faires, 1993 ). The line (model) is the right hand side of Eq. (1) . Its parameters ( p = 323, q = 0.73) were obtained from a linear fit to the observed growth rates (LINEST function of EXCEL applied to dm / dt , m a , and m with a = 2∕3). This method of fitting parameters is a modification of the Walford plot ( Walford, 1946 ).

Techniques Used: Generated, Modification

Akaike weights for different exponents, for data with and without outliers. Graphical multi-model comparison, generated in Microsoft EXCEL, based on data set #10 with and without outlier. The Akaike weight prob ( a ) for model (1) with exponent a was computed in comparison with the optimal exponent; dashed/fat line Akaike weights for data with/without outlier. Without outlier, the optimal exponent became larger (0.64) and exponents with poor fit could be discerned more easily.
Figure Legend Snippet: Akaike weights for different exponents, for data with and without outliers. Graphical multi-model comparison, generated in Microsoft EXCEL, based on data set #10 with and without outlier. The Akaike weight prob ( a ) for model (1) with exponent a was computed in comparison with the optimal exponent; dashed/fat line Akaike weights for data with/without outlier. Without outlier, the optimal exponent became larger (0.64) and exponents with poor fit could be discerned more easily.

Techniques Used: Generated

Optimizing the asymptotic weight limit (fit to weight-time data). Figure generated in Microsoft EXCEL, based on data set #14, plotting the sum of squared residuals SSR inv (fit to the weight-time data) in dependency on m max for an exponent a = 0.67. The minimum was attained for m max = 0.165 g (maximal observed weight: m obs = 0.145 g) resulting in the estimates q = 0.1/day and m 0 = 0.03 g. These were used as a starting value for the minimization of SSR (fit to the time-weight data). The resulting optimal parameters for a = 0.67 were q = 0.139/day, m 0 = 0.002 g and m max = 0.149 g.
Figure Legend Snippet: Optimizing the asymptotic weight limit (fit to weight-time data). Figure generated in Microsoft EXCEL, based on data set #14, plotting the sum of squared residuals SSR inv (fit to the weight-time data) in dependency on m max for an exponent a = 0.67. The minimum was attained for m max = 0.165 g (maximal observed weight: m obs = 0.145 g) resulting in the estimates q = 0.1/day and m 0 = 0.03 g. These were used as a starting value for the minimization of SSR (fit to the time-weight data). The resulting optimal parameters for a = 0.67 were q = 0.139/day, m 0 = 0.002 g and m max = 0.149 g.

Techniques Used: Generated

Confidence intervals for the percentage of data sets not rejecting an exponent. Figure generated in Microsoft EXCEL. Fat curve counts the percentage of how many of the 60 data sets did not reject the exponent a ; thin curves one-sided Clopper–Pearson confidence limits (95% significance).
Figure Legend Snippet: Confidence intervals for the percentage of data sets not rejecting an exponent. Figure generated in Microsoft EXCEL. Fat curve counts the percentage of how many of the 60 data sets did not reject the exponent a ; thin curves one-sided Clopper–Pearson confidence limits (95% significance).

Techniques Used: Generated

Effect of combining males and females on the Akaike weights. Figure generated in Microsoft EXCEL, based on data sets #18 and #19, plotting Akaike weights for data separated by sex and for the combined data.
Figure Legend Snippet: Effect of combining males and females on the Akaike weights. Figure generated in Microsoft EXCEL, based on data sets #18 and #19, plotting Akaike weights for data separated by sex and for the combined data.

Techniques Used: Generated

Effect on the Akaike weights of using different length-mass relations. Figure generated in Microsoft EXCEL, based data set #2, plotting Akaike weights for modifications of the data set, using different powers of length to estimate mass.
Figure Legend Snippet: Effect on the Akaike weights of using different length-mass relations. Figure generated in Microsoft EXCEL, based data set #2, plotting Akaike weights for modifications of the data set, using different powers of length to estimate mass.

Techniques Used: Generated

Transformation of time-mass-data and a regression line for the transformed data set. Generalized Bertalanffy-Beverton plot generated in Microsoft EXCEL, based on data set #47; squares: transformation of data ( t , m ) into ( u , t ) = ( f ( m ), t ); line: regression line t = A + B ⋅ u with A = − 55.64 and B = − 14.03. The function f was defined in Eq. (3) using the exponent a = 0.83 and assuming an asymptotic weight limit m max = 32, 163 g. The transformation required m max to exceed the maximal observed weight (31.8 kg), as otherwise the transformation would not be defined for all data points.
Figure Legend Snippet: Transformation of time-mass-data and a regression line for the transformed data set. Generalized Bertalanffy-Beverton plot generated in Microsoft EXCEL, based on data set #47; squares: transformation of data ( t , m ) into ( u , t ) = ( f ( m ), t ); line: regression line t = A + B ⋅ u with A = − 55.64 and B = − 14.03. The function f was defined in Eq. (3) using the exponent a = 0.83 and assuming an asymptotic weight limit m max = 32, 163 g. The transformation required m max to exceed the maximal observed weight (31.8 kg), as otherwise the transformation would not be defined for all data points.

Techniques Used: Transformation Assay, Generated

74) Product Images from "A conserved role for the zinc finger polyadenosine RNA binding protein, ZC3H14, in control of poly(A) tail length"

Article Title: A conserved role for the zinc finger polyadenosine RNA binding protein, ZC3H14, in control of poly(A) tail length

Journal: RNA

doi: 10.1261/rna.043984.113

Neuronal expression of ZC3H14-iso1 rescues the poly(A) tail length defect of homozygous dNab2 null flies. ( A ) Total RNA was isolated from flies of the indicated genotypes (“WT dNab2 ”=control , “ dNab2 null”= ex3/ex3, “ +dNab2 ” or + “ ZC3H14-iso1 ” = the corresponding protein expressed in dNab2 null neurons with elav-Gal4 ), end-labeled with [ 32 P]pCp, and non-poly(A) tracts were digested with RNAses A and T1. Labeled RNA was processed as described in Materials and Methods. The position of a 100-nt marker is indicated on the gel. ( B ) Bulk poly(A) tail length from fly heads of the indicated genotypes corresponding to the samples shown in the gel in A was analyzed by densitometric quantification of poly(A) tracts using ImageJ and plotted as normalized signal intensity (Relative Intensity) as a function of Poly(A) Tail Length in base pairs using Microsoft Excel. The approximate positions of the nucleotide size markers (nt) are indicated.
Figure Legend Snippet: Neuronal expression of ZC3H14-iso1 rescues the poly(A) tail length defect of homozygous dNab2 null flies. ( A ) Total RNA was isolated from flies of the indicated genotypes (“WT dNab2 ”=control , “ dNab2 null”= ex3/ex3, “ +dNab2 ” or + “ ZC3H14-iso1 ” = the corresponding protein expressed in dNab2 null neurons with elav-Gal4 ), end-labeled with [ 32 P]pCp, and non-poly(A) tracts were digested with RNAses A and T1. Labeled RNA was processed as described in Materials and Methods. The position of a 100-nt marker is indicated on the gel. ( B ) Bulk poly(A) tail length from fly heads of the indicated genotypes corresponding to the samples shown in the gel in A was analyzed by densitometric quantification of poly(A) tracts using ImageJ and plotted as normalized signal intensity (Relative Intensity) as a function of Poly(A) Tail Length in base pairs using Microsoft Excel. The approximate positions of the nucleotide size markers (nt) are indicated.

Techniques Used: Expressing, Isolation, Labeling, Marker

75) Product Images from "Comparison of chromosomal and array-based comparative genomic hybridization for the detection of genomic imbalances in primary prostate carcinomas"

Article Title: Comparison of chromosomal and array-based comparative genomic hybridization for the detection of genomic imbalances in primary prostate carcinomas

Journal: Molecular Cancer

doi: 10.1186/1476-4598-5-33

Comparison of aCGH score results for sample
Figure Legend Snippet: Comparison of aCGH score results for sample "Bp22" using different automated scoring approaches . ( A ) Normalized log-2 ratios, with clones ordered according to their genomic position. Note that the theoretical intensity values for gains and losses are not reached. ( B ) Results using aCGH-Smooth. ( C ) Results using sample-specific fixed thresholds calculated in Normalization Suite. ( D ) Results using CGH-Plotter. For the purposes of visualization and comparison, all diagrams were generated in Microsoft Excel based on data provided by the different analysis tools, and thus do not correspond to the visual outputs provided by each individual software.

Techniques Used: Clone Assay, Generated, Software

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Produced:

Article Title: Reducing number entry errors: solving a widespread, serious problem
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Two Tailed Test:

Article Title: Loss of the mitochondrial protein-only ribonuclease P complex causes aberrant tRNA processing and lethality in Drosophila
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other:

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Article Title: Prophylactic potential of aPanchgavya formulation against certain pathogenic bacteria
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Article Title: Successful Integration of Data Science in Undergraduate Biostatistics Courses Using Cognitive Load Theory
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Article Title: Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti
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Article Title: PubChemSR: A search and retrieval tool for PubChem
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Article Title: Kinetic Analysis of the Effect of Poliovirus Receptor on Viral Uncoating: the Receptor as a Catalyst
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Sequencing:

Article Title: Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2
Article Snippet: Heat maps were generated using Microsoft Excel. .. Candidate substrates were identified from published phosphoproteomics studies ( ) that conformed to the consensus sequence N X (pS/pT) X S X (I/L).

Kinase Assay:

Article Title: Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2
Article Snippet: Kinase reactions (2 μl) were performed in 1536-well plates in kinase assay buffer (50 m m HEPES, pH 7.4, 10 m m MgCl2 , 1 m m DTT, 0.1% Tween 20) containing 50 μ m peptide substrate, and 50 μ m ATP containing 0.03 μCi/ml [γ-33 P]ATP (PerkinElmer Life Sciences). .. Heat maps were generated using Microsoft Excel.

Software:

Article Title: Steps to achieve quantitative measurements of microRNA using two step droplet digital PCR
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Article Title: Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000
Article Snippet: However, due to issues associated with the font of the printed book, which was not easily recognized by the Kirtas machine, and the variable quality of the printed pages, (e.g., ), none of the OCR software we tested—Microsoft One Note , Adobe Acrobat Pro , and Free OCR —were able to accurately convert the printed text. .. After multiple attempts with the Kirtas machine, this approach was discarded and the text was manually transcribed into Microsoft Excel ( ).

Article Title: A Systematic Analysis of Cell Cycle Regulators in Yeast Reveals That Most Factors Act Independently of Cell Size to Control Initiation of Division
Article Snippet: Statistical analysis Non-parametric Spearman tests were done with the Analyze-it software package. .. In all other cases, statistical calculations were done with Microsoft Excel.

Generated:

Article Title: Substrate priming enhances phosphorylation by the budding yeast kinases Kin1 and Kin2
Article Snippet: .. Heat maps were generated using Microsoft Excel. .. Candidate substrates were identified from published phosphoproteomics studies ( ) that conformed to the consensus sequence N X (pS/pT) X S X (I/L).

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    Microsoft p2i tool
    Conceptual overview of the <t>P2I</t> financial portfolio model.
    P2i Tool, supplied by Microsoft, used in various techniques. Bioz Stars score: 88/100, based on 8 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Microsoft microsoft excel format
    <t>Microsoft</t> HoloLens for VCI and feedback ( ProRegio, 2017 ).
    Microsoft Excel Format, supplied by Microsoft, used in various techniques. Bioz Stars score: 99/100, based on 10578 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Microsoft microsoft excel 2003
    Time-dependent changes in the similarities between the volatiles and each type of standard gas. The volatile production patterns of A. hydrophila in LB are shown. The approximated curves and correlation factors were calculated using <t>Microsoft</t> Excel 2003. The graphs were categorized on the basis of the correlation factors. The measurements were conducted twice, and the mean ± standard deviation data are shown.
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    Image Search Results


    Conceptual overview of the P2I financial portfolio model.

    Journal: Gates Open Research

    Article Title: Funding global health product R D: the Portfolio-To-Impact Model (P2I), a new tool for modelling the impact of different research portfolios

    doi: 10.12688/gatesopenres.12816.2

    Figure Lengend Snippet: Conceptual overview of the P2I financial portfolio model.

    Article Snippet: The P2I tool (Microsoft Excel) Click here for additional data file.

    Techniques:

    Microsoft HoloLens for VCI and feedback ( ProRegio, 2017 ).

    Journal: Computers & Industrial Engineering

    Article Title: Gathering, evaluating and managing customer feedback during aircraft production

    doi: 10.1016/j.cie.2017.12.012

    Figure Lengend Snippet: Microsoft HoloLens for VCI and feedback ( ProRegio, 2017 ).

    Article Snippet: Data is exchanged in XML format, either as a proprietary format for defining the inspection data including the AR visualization data, or in Microsoft Excel format to enable easy editing of feedback data for evaluation.

    Techniques:

    Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using Microsoft Excel and the red boxes are households actually visited during the survey.

    Journal: International Journal of Health Geographics

    Article Title: Using ArcMap, Google Earth, and Global Positioning Systems to select and locate random households in rural Haiti

    doi: 10.1186/1476-072X-12-3

    Figure Lengend Snippet: Example of a Google Earth aerial photo onto which homes were mapped (white dots). Green Boxes are the homes randomly selected using Microsoft Excel and the red boxes are households actually visited during the survey.

    Article Snippet: A remote sensing technique was developed which combines a Geographic Information System (GIS); Google Earth, and Microsoft Excel to identify home locations for a random sample of households in rural Haiti.

    Techniques:

    Time-dependent changes in the similarities between the volatiles and each type of standard gas. The volatile production patterns of A. hydrophila in LB are shown. The approximated curves and correlation factors were calculated using Microsoft Excel 2003. The graphs were categorized on the basis of the correlation factors. The measurements were conducted twice, and the mean ± standard deviation data are shown.

    Journal: Sensors (Basel, Switzerland)

    Article Title: Detection of Aeromonas hydrophila in Liquid Media by Volatile Production Similarity Patterns, Using a FF-2A Electronic Nose

    doi: 10.3390/s130100736

    Figure Lengend Snippet: Time-dependent changes in the similarities between the volatiles and each type of standard gas. The volatile production patterns of A. hydrophila in LB are shown. The approximated curves and correlation factors were calculated using Microsoft Excel 2003. The graphs were categorized on the basis of the correlation factors. The measurements were conducted twice, and the mean ± standard deviation data are shown.

    Article Snippet: The approximated curves and correlation factors (similarity vs. culture time) in the figures were calculated using Microsoft Excel 2003.

    Techniques: Standard Deviation