cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6958301
title: Multiple sclerosis as an adverse drug reaction: clues from the FDA Adverse Event Reporting System

description: <b>Background</b>: Possible relationship between drug exposure and multiple sclerosis (MS) development is insufficiently investigated, and further challenged by the incomplete understanding of MS etiopathogenesis. The study aims to investigate whether drug exposure could contribute to MS, by analyzing worldwide spontaneous reporting archives of adverse drug reaction (ADRs). <b>Research design and methods</b>: We retrieved information from the US Food and Drug Administration Adverse Event Reporting System (FAERS) over a 13-year period. Reporting odds ratio (ROR) for MS was calculated for each single substance. Disproportionality signals were considered when at least 10 cases were retrieved with a lower limit of the 95% confidence interval (CI) &gt;1. <b>Results</b>: After a customized data-mining process, 3,226 reports of MS were retrieved. ‘Antineoplastic and immunomodulating drugs’ (33% of total reports) were the most frequently reported, with 10 disproportionality signals, including etanercept (445 cases; ROR: 2.48; 95% Cl: 2.24–2.74), adalimumab (329; 2.05; 1.83–2.30), and infliximab (119; 2.25; 1.87–2.70). We also observed signals for drugs acting on hormone balance, bone density, and central nervous system. <b>Conclusion</b>: Our findings suggest that immunomodulatory drugs increase the risk of MS and point out that some other drug classes should be further investigated for this risk.
DOI: 10.6084/m9.figshare.6958313.v2
title: Supplemental Materials and Tables.docx

description: Supplemental Materials and Tables
DOI: 10.6084/m9.figshare.6958301.v1
title: Multiple sclerosis as an adverse drug reaction: clues from the FDA Adverse Event Reporting System

description: <b>Background</b>: Possible relationship between drug exposure and multiple sclerosis (MS) development is insufficiently investigated, and further challenged by the incomplete understanding of MS etiopathogenesis. The study aims to investigate whether drug exposure could contribute to MS, by analyzing worldwide spontaneous reporting archives of adverse drug reaction (ADRs). <b>Research design and methods</b>: We retrieved information from the US Food and Drug Administration Adverse Event Reporting System (FAERS) over a 13-year period. Reporting odds ratio (ROR) for MS was calculated for each single substance. Disproportionality signals were considered when at least 10 cases were retrieved with a lower limit of the 95% confidence interval (CI) &gt;1. <b>Results</b>: After a customized data-mining process, 3,226 reports of MS were retrieved. ‘Antineoplastic and immunomodulating drugs’ (33% of total reports) were the most frequently reported, with 10 disproportionality signals, including etanercept (445 cases; ROR: 2.48; 95% Cl: 2.24–2.74), adalimumab (329; 2.05; 1.83–2.30), and infliximab (119; 2.25; 1.87–2.70). We also observed signals for drugs acting on hormone balance, bone density, and central nervous system. <b>Conclusion</b>: Our findings suggest that immunomodulatory drugs increase the risk of MS and point out that some other drug classes should be further investigated for this risk.
DOI: 10.6084/m9.figshare.6958283
title: The latest developments with anti-CD20 monoclonal antibodies in chronic lymphocytic leukemia

description: <b>Introduction</b>: In more recent years, anti-CD20 monoclonal antibodies have become the backbone in the treatment of chronic lymphocytic leukemia (CLL). Historically, these antibodies were typically combined with chemotherapeutic agents. At present, therapeutic outcomes are significantly improving with the introduction of several novel targeted drugs to the clinical repertoire. <b>Areas covered</b>: In this review, we summarize the current clinical standard together with the latest developments in the field of anti-CD20 antibodies against CLL. In addition, novel promising drugs against CLL are discussed, as well as their potential for combination with anti-CD20 monoclonal antibodies. <b>Expert opinion</b>: At present, there are three different anti-CD20 monoclonal antibodies approved for the treatment of CLL with diverse effector mechanisms. These antibodies provide a robust foundation for combination therapy with novel molecules. Current research should be focused on reducing toxicity and reaching long-lasting remissions. There is still much to gain regarding the optimization of treatment combinations and dosing schedules for CLL. Overcoming the limitations of currently used anti-CD20 antibodies will be critical to further improve the efficacy of CLL therapy.
DOI: 10.6084/m9.figshare.6958283.v1
title: The latest developments with anti-CD20 monoclonal antibodies in chronic lymphocytic leukemia

description: <b>Introduction</b>: In more recent years, anti-CD20 monoclonal antibodies have become the backbone in the treatment of chronic lymphocytic leukemia (CLL). Historically, these antibodies were typically combined with chemotherapeutic agents. At present, therapeutic outcomes are significantly improving with the introduction of several novel targeted drugs to the clinical repertoire. <b>Areas covered</b>: In this review, we summarize the current clinical standard together with the latest developments in the field of anti-CD20 antibodies against CLL. In addition, novel promising drugs against CLL are discussed, as well as their potential for combination with anti-CD20 monoclonal antibodies. <b>Expert opinion</b>: At present, there are three different anti-CD20 monoclonal antibodies approved for the treatment of CLL with diverse effector mechanisms. These antibodies provide a robust foundation for combination therapy with novel molecules. Current research should be focused on reducing toxicity and reaching long-lasting remissions. There is still much to gain regarding the optimization of treatment combinations and dosing schedules for CLL. Overcoming the limitations of currently used anti-CD20 antibodies will be critical to further improve the efficacy of CLL therapy.
DOI: 10.6084/m9.figshare.6958109
title: MOESM3 of Travel to farms in the lowlands and inadequate malaria information significantly predict malaria in villages around Lake Tana, northwest Ethiopia: a matched caseâ control study

description: Additional file 3. Characteristics of determinants of malaria by travel to lowlands in villages around Lake Tana, Ethiopia, October 2016-June 2017.
DOI: 10.6084/m9.figshare.6958109.v1
title: MOESM3 of Travel to farms in the lowlands and inadequate malaria information significantly predict malaria in villages around Lake Tana, northwest Ethiopia: a matched caseâ control study

description: Additional file 3. Characteristics of determinants of malaria by travel to lowlands in villages around Lake Tana, Ethiopia, October 2016-June 2017.
DOI: 10.6084/m9.figshare.6958100
title: MOESM1 of The interhospital transfer network for very low birth weight infants in the United States

description: Hospital List (CSV 40 kB)
DOI: 10.6084/m9.figshare.6958103
title: Additional file 7: of Repetitive somatic embryogenesis induced cytological and proteomic changes in embryogenic lines of Pseudotsuga menziesii [Mirb.]

description: Differentially expressed proteins in 2ry vs 1ry and 3ry vs 2ry embryogenic lines of two Douglas-fir genotypes. (XLSX 2224 kb)
DOI: 10.6084/m9.figshare.6958103.v1
title: Additional file 7: of Repetitive somatic embryogenesis induced cytological and proteomic changes in embryogenic lines of Pseudotsuga menziesii [Mirb.]

description: Differentially expressed proteins in 2ry vs 1ry and 3ry vs 2ry embryogenic lines of two Douglas-fir genotypes. (XLSX 2224 kb)
DOI: 10.6084/m9.figshare.6958097
title: MOESM2 of Travel to farms in the lowlands and inadequate malaria information significantly predict malaria in villages around Lake Tana, northwest Ethiopia: a matched caseâ control study

description: Additional file 2. Characteristics of determinants of malaria by HH elevation in villages around Lake Tana, Ethiopia, October 2016-June 2017.
DOI: 10.6084/m9.figshare.6958100.v1
title: MOESM1 of The interhospital transfer network for very low birth weight infants in the United States

description: Hospital List (CSV 40 kB)
DOI: 10.6084/m9.figshare.6958097.v1
title: MOESM2 of Travel to farms in the lowlands and inadequate malaria information significantly predict malaria in villages around Lake Tana, northwest Ethiopia: a matched caseâ control study

description: Additional file 2. Characteristics of determinants of malaria by HH elevation in villages around Lake Tana, Ethiopia, October 2016-June 2017.
DOI: 10.6084/m9.figshare.6958022
title: MOESM5 of PubChem chemical structure standardization

description: Additional file 5. Substances that failed the PubChem valence check but succeeded InChI generation. List of 364,946 substances that failed the PubChem valence check but whose InChI strings were successfully generated.
DOI: 10.6084/m9.figshare.6958022.v1
title: MOESM5 of PubChem chemical structure standardization

description: Additional file 5. Substances that failed the PubChem valence check but succeeded InChI generation. List of 364,946 substances that failed the PubChem valence check but whose InChI strings were successfully generated.
DOI: 10.6084/m9.figshare.6958016
title: MOESM4 of PubChem chemical structure standardization

description: Additional file 4. Substances that failed PubChem standardization but succeed InChI normalization. List of 375,397 substances that failed PubChem standardization but whose InChI strings were successfully generated.
DOI: 10.6084/m9.figshare.6958016.v1
title: MOESM4 of PubChem chemical structure standardization

description: Additional file 4. Substances that failed PubChem standardization but succeed InChI normalization. List of 375,397 substances that failed PubChem standardization but whose InChI strings were successfully generated.
DOI: 10.6084/m9.figshare.6958010
title: MOESM3 of PubChem chemical structure standardization

description: Additional file 3. Valence Bond Canonicalization Limitlist. List of 1746 structures as SMILES that are subject to a limited processing during valence bond canonicalization (2500 instead of 250,000 enumerated tautomers).
DOI: 10.6084/m9.figshare.6958010.v1
title: MOESM3 of PubChem chemical structure standardization

description: Additional file 3. Valence Bond Canonicalization Limitlist. List of 1746 structures as SMILES that are subject to a limited processing during valence bond canonicalization (2500 instead of 250,000 enumerated tautomers).
DOI: 10.6084/m9.figshare.6957995
title: MOESM2 of PubChem chemical structure standardization

description: Additional file 2. Valence Bond Canonicalization Blacklist. List of 65 structures as SMILES that will not be processed during valence bond canonicalization.
DOI: 10.6084/m9.figshare.6957995.v1
title: MOESM2 of PubChem chemical structure standardization

description: Additional file 2. Valence Bond Canonicalization Blacklist. List of 65 structures as SMILES that will not be processed during valence bond canonicalization.
DOI: 10.6084/m9.figshare.6957986
title: MOESM1 of PubChem chemical structure standardization

description: Additional file 1. Valence list. List of valid valences and configurations of atoms with respect to atomic number (column 1), charge (column 2), number of Ď bonds (column 3), number of Ď bonds (column 4) and the maximum number of implicit hydrogens (column 5).
DOI: 10.6084/m9.figshare.6957986.v1
title: MOESM1 of PubChem chemical structure standardization

description: Additional file 1. Valence list. List of valid valences and configurations of atoms with respect to atomic number (column 1), charge (column 2), number of Ď bonds (column 3), number of Ď bonds (column 4) and the maximum number of implicit hydrogens (column 5).
DOI: 10.6084/m9.figshare.6957968
title: Additional file 1: of Microevolutionary processes impact macroevolutionary patterns

description: Table S1. All parameters used in simulating the protracted genealogies and all estimated speciation and extinction rates of these genealogies based on traditional birth-death models. Figure S1. Estimated extinction rates (color blocks) based on phylogenies generated from 125 combination of protracted speciation parameters (rates of population splitting, population conversion, and population extirpation). Note that this figure is different from Fig. 3, which reports on speciation rates. Red squares represent examples of similar estimated extinction rates based on phylogenies generated from different protracted speciation parameters. Their different placement across parameter space shows that very different mechanism (e.g., different combinations of population splitting, conversion, and extinction rates) may underlie a single â extinction rateâ , as measured under traditional macroevolutionary birth-death models (ZIP 155 kb)
DOI: 10.6084/m9.figshare.6957968.v1
title: Additional file 1: of Microevolutionary processes impact macroevolutionary patterns

description: Table S1. All parameters used in simulating the protracted genealogies and all estimated speciation and extinction rates of these genealogies based on traditional birth-death models. Figure S1. Estimated extinction rates (color blocks) based on phylogenies generated from 125 combination of protracted speciation parameters (rates of population splitting, population conversion, and population extirpation). Note that this figure is different from Fig. 3, which reports on speciation rates. Red squares represent examples of similar estimated extinction rates based on phylogenies generated from different protracted speciation parameters. Their different placement across parameter space shows that very different mechanism (e.g., different combinations of population splitting, conversion, and extinction rates) may underlie a single â extinction rateâ , as measured under traditional macroevolutionary birth-death models (ZIP 155 kb)
DOI: 10.6084/m9.figshare.6957836
title: Additional file 6 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S5. Predicted results of miREM using different HP p-values and EM parameters. (XLSX 115 kb)
DOI: 10.25387/g3.11944890
title: Supplemental Material for Yu et al., 2020

description: Supplemental Tables
DOI: 10.6084/m9.figshare.6957836.v1
title: Additional file 6 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S5. Predicted results of miREM using different HP p-values and EM parameters. (XLSX 115 kb)
DOI: 10.25387/g3.11944890.v1
title: Supplemental Material for Yu et al., 2020

description: Supplemental Tables
DOI: 10.6084/m9.figshare.6957830
title: Additional file 5 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S4. Predicted results of miREM and CORNA with same database. (XLSX 47 kb)
DOI: 10.6084/m9.figshare.6957830.v1
title: Additional file 5 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S4. Predicted results of miREM and CORNA with same database. (XLSX 47 kb)
DOI: 10.6084/m9.figshare.6957824
title: Additional file 4 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S3. Full predicted results for four tested experiments. (XLSX 514 kb)
DOI: 10.6084/m9.figshare.6957824.v1
title: Additional file 4 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S3. Full predicted results for four tested experiments. (XLSX 514 kb)
DOI: 10.6084/m9.figshare.6957818
title: Additional file 3 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S2. List of genes differentially expressed used in the case studies. (XLSX 75 kb)
DOI: 10.6084/m9.figshare.6957818.v1
title: Additional file 3 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S2. List of genes differentially expressed used in the case studies. (XLSX 75 kb)
DOI: 10.6084/m9.figshare.6957809
title: Additional file 1 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S1. Release notes of human and mouse miRNA reference databases in miREM. (XLSX 35 kb)
DOI: 10.6084/m9.figshare.6957809.v1
title: Additional file 1 of miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set

description: Table S1. Release notes of human and mouse miRNA reference databases in miREM. (XLSX 35 kb)
DOI: 10.6084/m9.figshare.6957632
title: Stable C and N isotope changes in LML food web (.csv file)

description: Dataset contains ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N during different time intervals for top predator fish and select lower trophic level organisms for use as input for "Stable C and N changes in LML food web R code".
DOI: 10.6084/m9.figshare.6957632.v1
title: Stable C and N isotope changes in LML food web (.csv file)

description: Dataset contains ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N during different time intervals for top predator fish and select lower trophic level organisms for use as input for "Stable C and N changes in LML food web R code".
DOI: 10.6084/m9.figshare.6957623
title: Smallmouth Bass growth data (.csv file)

description: Total length, weight and age data for Smallmouth Bass from Little Moose Lake (NY, USA) in CSV format to be used to graph using code file: "Fish Length-at-Age and Growth R file".
DOI: 10.6084/m9.figshare.6957620
title: Lake Trout growth data (.csv file)

description: Total length, weight and age data for Lake Trout from Little Moose Lake in CSV format to be used to graph using code file: "Fish Length-at-Age and Growth R file".
DOI: 10.6084/m9.figshare.6957533
title: Smallmouth Bass THg and stable C and N isotope trend test (.csv file)

description: CSV file associated with code that computes Kendall's Tau statistics and creates figures depicting Smallmouth Bass wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957533.v1
title: Smallmouth Bass THg and stable C and N isotope trend test (.csv file)

description: CSV file associated with code that computes Kendall's Tau statistics and creates figures depicting Smallmouth Bass wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957527
title: Lake Trout THg and stable C and N isotope trend test (.csv file)

description: CSV file associated with code that computes Kendall's Tau statistics and creates figures depicting Lake Trout wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957527.v1
title: Lake Trout THg and stable C and N isotope trend test (.csv file)

description: CSV file associated with code that computes Kendall's Tau statistics and creates figures depicting Lake Trout wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957521
title: Smallmouth Bass THg and stable C and N isotope trend test (R code)

description: Code computes Kendall's Tau statistics and creates figures depicting Smallmouth Bass wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957521.v1
title: Smallmouth Bass THg and stable C and N isotope trend test (R code)

description: Code computes Kendall's Tau statistics and creates figures depicting Smallmouth Bass wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957509
title: Lake Trout THg and stable C and N isotope trend test (R code)

description: Code computes Kendall's Tau statistics and creates figures depicting Lake Trout wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957509.v1
title: Lake Trout THg and stable C and N isotope trend test (R code)

description: Code computes Kendall's Tau statistics and creates figures depicting Lake Trout wet-weight total mercury concentrations, ratios of <sup>13</sup>C/<sup>12</sup>C and <sup>15</sup>N/<sup>14</sup>N over time with data from Little Moose Lake (NY, USA) from 2000-2015.
DOI: 10.6084/m9.figshare.6957470
title: Dynamic demethylation of the <i>IL2RA</i> promoter during <i>in vitro</i> CD4+ T cell activation in association with IL2RA expression

description: IL2RA, a subunit of the high affinity receptor for interleukin-2 (IL2), plays a crucial role in immune homeostasis. Notably, IL2RA expression is induced in CD4+ T cells in response to various stimuli and is constitutive in regulatory T cells (Tregs). We selected for our study 18 CpGs located within cognate regulatory regions of the <i>IL2RA</i> locus and characterized their methylation in naive, regulatory, and memory CD4+ T cells. We found that 5/18 CpGs (notably CpG + 3502) show dynamic, active demethylation during the <i>in vitro</i> activation of naive CD4+ T cells. Demethylation of these CpGs correlates with appearance of IL2RA protein at the cell surface. We found no influence of <i>cis</i> located SNP alleles upon CpG methylation. Treg cells show constitutive demethylation at all studied CpGs. Methylation of 9/18 CpGs, including CpG +3502, decreases with age. Our data thus identify CpG +3502 and a few other CpGs at the <i>IL2RA</i> locus as coordinated epigenetic regulators of IL2RA expression in CD4+ T cells. This may contribute to unravel how the <i>IL2RA</i> locus can be involved in immune physiology and pathology.
DOI: 10.6084/m9.figshare.6957470.v1
title: Dynamic demethylation of the <i>IL2RA</i> promoter during <i>in vitro</i> CD4+ T cell activation in association with IL2RA expression

description: IL2RA, a subunit of the high affinity receptor for interleukin-2 (IL2), plays a crucial role in immune homeostasis. Notably, IL2RA expression is induced in CD4+ T cells in response to various stimuli and is constitutive in regulatory T cells (Tregs). We selected for our study 18 CpGs located within cognate regulatory regions of the <i>IL2RA</i> locus and characterized their methylation in naive, regulatory, and memory CD4+ T cells. We found that 5/18 CpGs (notably CpG + 3502) show dynamic, active demethylation during the <i>in vitro</i> activation of naive CD4+ T cells. Demethylation of these CpGs correlates with appearance of IL2RA protein at the cell surface. We found no influence of <i>cis</i> located SNP alleles upon CpG methylation. Treg cells show constitutive demethylation at all studied CpGs. Methylation of 9/18 CpGs, including CpG +3502, decreases with age. Our data thus identify CpG +3502 and a few other CpGs at the <i>IL2RA</i> locus as coordinated epigenetic regulators of IL2RA expression in CD4+ T cells. This may contribute to unravel how the <i>IL2RA</i> locus can be involved in immune physiology and pathology.
DOI: 10.6084/m9.figshare.6957455
title: Experiment Data

description: Samples obtained in the experiments<br>
DOI: 10.6084/m9.figshare.6957434
title: NPI-012-Segmented-Water

description: Segmented water phase for image: NPI-012-Filtered Segmentation performed using Watershed segmentation in Avizo. Image Dimension: 1024×1024×845 Image Type: 8 bit