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a , Regional signal plot at the <t>ACSL1</t> locus, showing P values on a −log 10 scale ( y axis) in hg19 locations ( x axis) from DIBIG single-variant GWAS meta-analyses. Variants are coloured by their LD correlation ( r 2 ) with the lead variant ( rs10022124 ). Below, epigenomic datasets are shown, including ATAC-seq and ChIP-seq data in human pancreatic islets. Enhancer-gene assignments from pcHi-C data are represented as pink arcs; those inferred using pcHi-C data are in purple. Fine-mapped DI and DIBIG signals located in islet active enhancers connected to ACSL1 and CENPU , or identified as T2D-colocalizing islet ACSL1 eQTLs, are highlighted. b , Forest plot of the strongest functionally prioritized signal at the ACSL1 locus ( rs4862423 , DIBIG). For each of the BCF traits, glycaemic levels and T2D risk, the square represents the β estimate with 95% CI error bars. The square size reflects precision. The effect allele and variant RSID are provided at the top. Summary statistics data were generated in this study or obtained from previous publications , and FinnGen (release v.8). OR, odds ratio. c , d , Insulin secretion in human EndoC-β H1 cells following ACSL1 siRNA silencing in response to high glucose ( c ) and KCl stimuli ( d ). e – g , Insulin secretion in INS-1 832/13 cells upon Acsl1 gene silencing in response to high glucose ( e ), KCl ( f ) and pyruvate ( g ). Bar plots show the means of three (in c and d ) and four (in e – g ) independent replicates; error bars, s.e.m. Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test of each condition against the negative control group (scrambled siRNA).
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a , Regional signal plot at the <t>ACSL1</t> locus, showing P values on a −log 10 scale ( y axis) in hg19 locations ( x axis) from DIBIG single-variant GWAS meta-analyses. Variants are coloured by their LD correlation ( r 2 ) with the lead variant ( rs10022124 ). Below, epigenomic datasets are shown, including ATAC-seq and ChIP-seq data in human pancreatic islets. Enhancer-gene assignments from pcHi-C data are represented as pink arcs; those inferred using pcHi-C data are in purple. Fine-mapped DI and DIBIG signals located in islet active enhancers connected to ACSL1 and CENPU , or identified as T2D-colocalizing islet ACSL1 eQTLs, are highlighted. b , Forest plot of the strongest functionally prioritized signal at the ACSL1 locus ( rs4862423 , DIBIG). For each of the BCF traits, glycaemic levels and T2D risk, the square represents the β estimate with 95% CI error bars. The square size reflects precision. The effect allele and variant RSID are provided at the top. Summary statistics data were generated in this study or obtained from previous publications , and FinnGen (release v.8). OR, odds ratio. c , d , Insulin secretion in human EndoC-β H1 cells following ACSL1 siRNA silencing in response to high glucose ( c ) and KCl stimuli ( d ). e – g , Insulin secretion in INS-1 832/13 cells upon Acsl1 gene silencing in response to high glucose ( e ), KCl ( f ) and pyruvate ( g ). Bar plots show the means of three (in c and d ) and four (in e – g ) independent replicates; error bars, s.e.m. Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test of each condition against the negative control group (scrambled siRNA).
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a , Regional signal plot at the <t>ACSL1</t> locus, showing P values on a −log 10 scale ( y axis) in hg19 locations ( x axis) from DIBIG single-variant GWAS meta-analyses. Variants are coloured by their LD correlation ( r 2 ) with the lead variant ( rs10022124 ). Below, epigenomic datasets are shown, including ATAC-seq and ChIP-seq data in human pancreatic islets. Enhancer-gene assignments from pcHi-C data are represented as pink arcs; those inferred using pcHi-C data are in purple. Fine-mapped DI and DIBIG signals located in islet active enhancers connected to ACSL1 and CENPU , or identified as T2D-colocalizing islet ACSL1 eQTLs, are highlighted. b , Forest plot of the strongest functionally prioritized signal at the ACSL1 locus ( rs4862423 , DIBIG). For each of the BCF traits, glycaemic levels and T2D risk, the square represents the β estimate with 95% CI error bars. The square size reflects precision. The effect allele and variant RSID are provided at the top. Summary statistics data were generated in this study or obtained from previous publications , and FinnGen (release v.8). OR, odds ratio. c , d , Insulin secretion in human EndoC-β H1 cells following ACSL1 siRNA silencing in response to high glucose ( c ) and KCl stimuli ( d ). e – g , Insulin secretion in INS-1 832/13 cells upon Acsl1 gene silencing in response to high glucose ( e ), KCl ( f ) and pyruvate ( g ). Bar plots show the means of three (in c and d ) and four (in e – g ) independent replicates; error bars, s.e.m. Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test of each condition against the negative control group (scrambled siRNA).
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Image Search Results


a , Regional signal plot at the ACSL1 locus, showing P values on a −log 10 scale ( y axis) in hg19 locations ( x axis) from DIBIG single-variant GWAS meta-analyses. Variants are coloured by their LD correlation ( r 2 ) with the lead variant ( rs10022124 ). Below, epigenomic datasets are shown, including ATAC-seq and ChIP-seq data in human pancreatic islets. Enhancer-gene assignments from pcHi-C data are represented as pink arcs; those inferred using pcHi-C data are in purple. Fine-mapped DI and DIBIG signals located in islet active enhancers connected to ACSL1 and CENPU , or identified as T2D-colocalizing islet ACSL1 eQTLs, are highlighted. b , Forest plot of the strongest functionally prioritized signal at the ACSL1 locus ( rs4862423 , DIBIG). For each of the BCF traits, glycaemic levels and T2D risk, the square represents the β estimate with 95% CI error bars. The square size reflects precision. The effect allele and variant RSID are provided at the top. Summary statistics data were generated in this study or obtained from previous publications , and FinnGen (release v.8). OR, odds ratio. c , d , Insulin secretion in human EndoC-β H1 cells following ACSL1 siRNA silencing in response to high glucose ( c ) and KCl stimuli ( d ). e – g , Insulin secretion in INS-1 832/13 cells upon Acsl1 gene silencing in response to high glucose ( e ), KCl ( f ) and pyruvate ( g ). Bar plots show the means of three (in c and d ) and four (in e – g ) independent replicates; error bars, s.e.m. Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test of each condition against the negative control group (scrambled siRNA).

Journal: Nature Metabolism

Article Title: Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology

doi: 10.1038/s42255-024-01140-6

Figure Lengend Snippet: a , Regional signal plot at the ACSL1 locus, showing P values on a −log 10 scale ( y axis) in hg19 locations ( x axis) from DIBIG single-variant GWAS meta-analyses. Variants are coloured by their LD correlation ( r 2 ) with the lead variant ( rs10022124 ). Below, epigenomic datasets are shown, including ATAC-seq and ChIP-seq data in human pancreatic islets. Enhancer-gene assignments from pcHi-C data are represented as pink arcs; those inferred using pcHi-C data are in purple. Fine-mapped DI and DIBIG signals located in islet active enhancers connected to ACSL1 and CENPU , or identified as T2D-colocalizing islet ACSL1 eQTLs, are highlighted. b , Forest plot of the strongest functionally prioritized signal at the ACSL1 locus ( rs4862423 , DIBIG). For each of the BCF traits, glycaemic levels and T2D risk, the square represents the β estimate with 95% CI error bars. The square size reflects precision. The effect allele and variant RSID are provided at the top. Summary statistics data were generated in this study or obtained from previous publications , and FinnGen (release v.8). OR, odds ratio. c , d , Insulin secretion in human EndoC-β H1 cells following ACSL1 siRNA silencing in response to high glucose ( c ) and KCl stimuli ( d ). e – g , Insulin secretion in INS-1 832/13 cells upon Acsl1 gene silencing in response to high glucose ( e ), KCl ( f ) and pyruvate ( g ). Bar plots show the means of three (in c and d ) and four (in e – g ) independent replicates; error bars, s.e.m. Statistical significance was assessed using one-way ANOVA followed by Tukey’s post hoc test of each condition against the negative control group (scrambled siRNA).

Article Snippet: For qPCR, 10 ng of cDNA per well (in duplicates) was used with human ACSL1 and FAM46C , or rat Acsl1 , Fam46c and Cenpu Taqman gene expression assays (Thermo Fisher Scientific; code: Rn01488229_m1, Rn01534138_m1, Rn01488384_m1, Hs00960561_m1, Hs01933465_s1). qPCR assays were performed using the Applied Biosystems QuantStudio7 Flex Real-Time PCR System (Thermo Fisher).

Techniques: Variant Assay, ChIP-sequencing, Generated, Negative Control

(a) ACSL1 mRNA expression levels assessed by qPCR after 72h transfection with scramble (control) and ACSL1 siRNA 1-2 in human EndoC-βH1 cells. (b) Acsl1 mRNA expression levels after 72h transfection with scramble (control) and Acsl1 siRNA 1-2 in INS-1 832/13 rat insulinoma cells, measured by qPCR. (c) Measurement of insulin content relative to total protein level in INS-1 832/13 cells. (d) Insulin secretion levels normalized by total insulin content in response to high glucose (16.7 mM) in INS-1 832/13 cells. (e) Cenpu mRNA expression levels assessed by qPCR after 72h transfection with scramble (control) and Cenpu siRNA 1 in INS-1 832/13 cells. (f) Insulin secretion levels in response to high glucose (16.7 mM) concentration in INS-1 832/13 cells. (g) Measurement of total insulin content in INS-1 832/13 cells. (h) Insulin secretion normalization for total insulin content in response to high glucose (16.7 mM) concentration. Bar plots in panels (a-h) depict mean +/- SE from three (a) and four (b-h) independent replicates. Two-sided Student’s t-test was used for panels (c,e,g) . One-way analysis of variance (ANOVA) followed by Tukey post-hoc test was used for panels (a,b,d,f,h) . Panels (i) and (j) show morphology changes in INS-1 832/13 cells after transfection with scramble and Cenpu siRNA 1 , respectively. Images from a basic optical microscope, where scale bars are not available.

Journal: Nature Metabolism

Article Title: Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology

doi: 10.1038/s42255-024-01140-6

Figure Lengend Snippet: (a) ACSL1 mRNA expression levels assessed by qPCR after 72h transfection with scramble (control) and ACSL1 siRNA 1-2 in human EndoC-βH1 cells. (b) Acsl1 mRNA expression levels after 72h transfection with scramble (control) and Acsl1 siRNA 1-2 in INS-1 832/13 rat insulinoma cells, measured by qPCR. (c) Measurement of insulin content relative to total protein level in INS-1 832/13 cells. (d) Insulin secretion levels normalized by total insulin content in response to high glucose (16.7 mM) in INS-1 832/13 cells. (e) Cenpu mRNA expression levels assessed by qPCR after 72h transfection with scramble (control) and Cenpu siRNA 1 in INS-1 832/13 cells. (f) Insulin secretion levels in response to high glucose (16.7 mM) concentration in INS-1 832/13 cells. (g) Measurement of total insulin content in INS-1 832/13 cells. (h) Insulin secretion normalization for total insulin content in response to high glucose (16.7 mM) concentration. Bar plots in panels (a-h) depict mean +/- SE from three (a) and four (b-h) independent replicates. Two-sided Student’s t-test was used for panels (c,e,g) . One-way analysis of variance (ANOVA) followed by Tukey post-hoc test was used for panels (a,b,d,f,h) . Panels (i) and (j) show morphology changes in INS-1 832/13 cells after transfection with scramble and Cenpu siRNA 1 , respectively. Images from a basic optical microscope, where scale bars are not available.

Article Snippet: For qPCR, 10 ng of cDNA per well (in duplicates) was used with human ACSL1 and FAM46C , or rat Acsl1 , Fam46c and Cenpu Taqman gene expression assays (Thermo Fisher Scientific; code: Rn01488229_m1, Rn01534138_m1, Rn01488384_m1, Hs00960561_m1, Hs01933465_s1). qPCR assays were performed using the Applied Biosystems QuantStudio7 Flex Real-Time PCR System (Thermo Fisher).

Techniques: Expressing, Transfection, Control, Concentration Assay, Microscopy

Key Resources Table

Journal: Neuron

Article Title: Causal role of motor preparation during error-driven learning

doi: 10.1016/j.neuron.2020.01.019

Figure Lengend Snippet: Key Resources Table

Article Snippet: Simulink RealTime , The MathWorks, Inc. , https://www.mathworks.com/products/simulink-real-time.html.

Techniques: Software, Microelectrode Array, Northern Blot

Comparison of quantitative methods for  HBV  DNA

Journal: Annals of Translational Medicine

Article Title: Diagnosis of hepatitis B

doi: 10.21037/atm.2016.09.11

Figure Lengend Snippet: Comparison of quantitative methods for HBV DNA

Article Snippet: Furthermore, it can be fully automated and does not generate carry-over contamination ( 23 ). displays the comparison of assays for quantitative measurement of HBV DNA. table ft1 table-wrap mode="anchored" t5 caption a7 Methods Commercial assay name Manufacturer Measurable range (IU/mL) Limit of detection (IU/mL) (using WHO HBV standard) Semi-automated qPCR COBAS AmpliPrep/COBAS TaqMan HBV Test v2.0 Roche Molecular System, California, United States 20–1.7× 10 7 20 Semi-automated real-time PCR COBAS TaqMan HBV Test for use with high pure system Roche Molecular System, California, United States 29–1.1×10 7 6 Automated real-time PCR Abbott RealTime HBV Abbott Diagnostic, Chicago, United States 10–1×10 9 10 Branched DNA VERSANT HBV 3.0 Assay Siemens Healthcare, United States 2,000–1×10 8 2,000 Open in a separate window WHO, World Health Organization; HBV, hepatitis B virus; PCR, polymerase chain reaction; qPCR, quantitative PCR. caption a8 Comparison of quantitative methods for HBV DNA

Techniques: Comparison, Real-time Polymerase Chain Reaction, Diagnostic Assay

Methods of  HBV  genotyping

Journal: Annals of Translational Medicine

Article Title: Diagnosis of hepatitis B

doi: 10.21037/atm.2016.09.11

Figure Lengend Snippet: Methods of HBV genotyping

Article Snippet: Furthermore, it can be fully automated and does not generate carry-over contamination ( 23 ). displays the comparison of assays for quantitative measurement of HBV DNA. table ft1 table-wrap mode="anchored" t5 caption a7 Methods Commercial assay name Manufacturer Measurable range (IU/mL) Limit of detection (IU/mL) (using WHO HBV standard) Semi-automated qPCR COBAS AmpliPrep/COBAS TaqMan HBV Test v2.0 Roche Molecular System, California, United States 20–1.7× 10 7 20 Semi-automated real-time PCR COBAS TaqMan HBV Test for use with high pure system Roche Molecular System, California, United States 29–1.1×10 7 6 Automated real-time PCR Abbott RealTime HBV Abbott Diagnostic, Chicago, United States 10–1×10 9 10 Branched DNA VERSANT HBV 3.0 Assay Siemens Healthcare, United States 2,000–1×10 8 2,000 Open in a separate window WHO, World Health Organization; HBV, hepatitis B virus; PCR, polymerase chain reaction; qPCR, quantitative PCR. caption a8 Comparison of quantitative methods for HBV DNA

Techniques: Hybridization, Sequencing, Infection, Recombinant

Clinical Features and Radiological Findings of 19 Patients with Adenovirus Pneumonia

Journal: Korean Journal of Radiology

Article Title: Clinical Features and Radiological Findings of Adenovirus Pneumonia Associated with Progression to Acute Respiratory Distress Syndrome: A Single Center Study in 19 Adult Patients

doi: 10.3348/kjr.2016.17.6.940

Figure Lengend Snippet: Clinical Features and Radiological Findings of 19 Patients with Adenovirus Pneumonia

Article Snippet: In nine patients, BAL fluid was analyzed using the one-step multiplex realtime AdvanSure RV real-time PCR kit (LG Life Sciences, Seoul, Korea) or conventional multiplex reverse transcription PCR (RT-PCR) assay (Seeplex RV12 Detection Kit; Seegene, Seoul, Korea) ( ).

Techniques: Biomarker Discovery, Real-time Polymerase Chain Reaction