Journal: Scientific Reports

Article Title: ALF-Score++, a novel approach to transfer knowledge and predict network-based walkability scores across cities

doi: 10.1038/s41598-022-17713-y

Figure Lengend Snippet: Walkability results produced by 3 separate variations of ALF-Score and ALF-Score++ for the city of Montréal, QC and their correlation. Top left: predictions based on a model only trained for Montréal’s user data. Top right: predictions based on a transferred model only trained for a single city’s user data (St. John’s). Bottom left: predictions based on a model trained for Montréal’s user data while having the previously trained weights for St. John’s user data transferred in its transfer learned training process. Bottom right: correlation between the three variations. The road network for Montréal maintains over 76 thousand nodes. ALF-Score’s walkability scores range between 0 and 100 units. This range can be adjusted if needed. (Maps generated through RStudio Version 1.2 using mapview package from rstudio.com. Correlation figure generated through RStudio Version 1.2 using PerformanceAnalytics package from rstudio.com).

Article Snippet: Top left: Montréal QC, Top right: Kingston ON, Bottom left: Vancouver BC, Bottom right: St. John’s NL. (Correlation figures generated through RStudio Version 1.2 using PerformanceAnalytics package from rstudio.com).

Techniques: Produced, Generated

Journal: Scientific Reports

Article Title: ALF-Score++, a novel approach to transfer knowledge and predict network-based walkability scores across cities

doi: 10.1038/s41598-022-17713-y

Figure Lengend Snippet: Left: Can-ALE for the city of Kingston, ON. Right: walkability results produced by ALF-Score++ for the city of Kingston, ON using the zero-user-input approach of a model trained through transfer learning based on user data from two cities of St. John’s and Montréal. The road network for Kingston maintains over 3400 nodes. ALF-Score’s walkability scores range between 0 and 100 units. This range can be adjusted if needed. (Maps generated through RStudio Version 1.2 using mapview package from rstudio.com).

Article Snippet: Top left: Montréal QC, Top right: Kingston ON, Bottom left: Vancouver BC, Bottom right: St. John’s NL. (Correlation figures generated through RStudio Version 1.2 using PerformanceAnalytics package from rstudio.com).

Techniques: Produced, Generated

Journal: Scientific Reports

Article Title: ALF-Score++, a novel approach to transfer knowledge and predict network-based walkability scores across cities

doi: 10.1038/s41598-022-17713-y

Figure Lengend Snippet: Left: Can-ALE for the city of Vancouver, BC. Right: walkability results produced by ALF-Score++ for the city of Vancouver, BC using the zero-user-input approach of a model trained through transfer learning based on user data from two cities of St. John’s and Montréal. The road network for Vancouver maintains over 45 thousand nodes. (Maps generated through RStudio Version 1.2 using mapview package from rstudio.com).

Article Snippet: Top left: Montréal QC, Top right: Kingston ON, Bottom left: Vancouver BC, Bottom right: St. John’s NL. (Correlation figures generated through RStudio Version 1.2 using PerformanceAnalytics package from rstudio.com).

Techniques: Produced, Generated

Journal: Scientific Reports

Article Title: ALF-Score++, a novel approach to transfer knowledge and predict network-based walkability scores across cities

doi: 10.1038/s41598-022-17713-y

Figure Lengend Snippet: Correlation between ALF-Score++ and Can-ALE for four different cities. Top left: Montréal QC, Top right: Kingston ON, Bottom left: Vancouver BC, Bottom right: St. John’s NL. (Correlation figures generated through RStudio Version 1.2 using PerformanceAnalytics package from rstudio.com).

Article Snippet: Top left: Montréal QC, Top right: Kingston ON, Bottom left: Vancouver BC, Bottom right: St. John’s NL. (Correlation figures generated through RStudio Version 1.2 using PerformanceAnalytics package from rstudio.com).

Techniques: Generated

Journal: Scientific Reports

Article Title: Modulating the unfolded protein response with ONC201 to impact on radiation response in prostate cancer cells

doi: 10.1038/s41598-021-83215-y

Figure Lengend Snippet: RNA-Seq analysis reveals that ONC201 restricts the expression of cell cycle progression and DNA repair pathway genes. ( a ) Schematic representation of the treatment in which PC3 cells have been primed with ONC201 before being radiated with single doses of Xrad (CorelDRAW Graphics Suite 2019, 64-Bit). ( b ) Pathway analysis of our genes of interest in KEGG Human 2019 pathway database, after RNA-seq analysis of PC3 cells treated as shown in ( a ), revealed that the most impacted pathway is cell cycle related (iEnrichr web tool , ). ( c ) Heatmaps analysis of RNAseq data (log2 of gene counts) of PC3 cells treated as shown in ( a ). Cells were harvested at 24 h ( c , i and ii top) and 72 h after the irradiation ( c , i and ii bottom). The genes listed are the most differentially regulated (see Methods for details on the analysis with RStudio software, Version 1.2.5033, release name "Orange Blossom" (RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/ ). ( d ) Validation through TR-PCR of the five most relevant and differentially regulated genes at 72 h from the final radiation dose (RRM2, CDK2, PLK1, MKI67, CDK1). One-way ANOVA test has been run comparing treated vs Vehicle and No Radiation on n = 3 experiments, **p < 0.01; ***p < 0.001 (± SD). ( e ) Schematic representation of the cell cycle check points (RRM2, CDK2, PLK1, MIK67, CDK1) were drawn utilizing CorelDRAW Graphics Suite (CorelDRAW Graphics Suite 2019, 64-Bit).

Article Snippet: Read counts per genes files were generated and principal component analysis (PCA) performed (RStudio, Version 1.2.5033, release name "Orange Blossom" (RStudio Team (2020).

Techniques: RNA Sequencing Assay, Expressing, Irradiation, Software