cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6194159
title: Clinical and molecular characterization of neurofibromatosis in southern Brazil

description: <b>Objectives</b>: Neurofibromatoses (type 1: NF1; type 2: NF2) are autosomal dominant tumor predisposition syndromes mostly caused by loss-of-function mutations in the tumor suppressor genes NF1 and NF2, respectively. Genotyping is important for correct diagnosis of these diseases. The authors aimed to characterize <i>NF1</i> and <i>NF2</i> variants in patients from Southern Brazil. <b>Methods</b>: Ninety-three unrelated probands with NF1 and 7 unrelated probands with NF2 features were recruited from an Oncogenetics center in Southern Brazil. Two next generation sequencing panels were customized to identify point mutations: NF1 (<i>NF1, RNF135</i>, and <i>SUZ12</i> genes) and NF2 (<i>NF2</i> and <i>SMARCB1</i> genes). Large rearrangements were assessed by Multiplex Ligation-dependent Probe Amplification. <b>Results</b>: Sixty-eight heterozygous <i>NF1</i> variants were identified in 75/93 probands (80%) and 3 heterozygous <i>NF2</i> variants were identified in 3/7 probands (43%). In <i>NF1</i>, 59 (87%) variants were pathogenic (4 large rearrangements – 6%), 6 (9%) were likely pathogenic, 3 (4%) were variants of uncertain significance and 28 (41%) were novel. In <i>NF2</i>, all variants were pathogenic. No novel genotype-phenotype correlations were observed; however, previously described correlations were confirmed in our cohort. <b>Conclusion</b>: The clinical and molecular characterization of neurofibromatoses in different populations is very important to provide further insights into the pathogenesis of these diseases.
DOI: 10.6084/m9.figshare.6194159.v1
title: Clinical and molecular characterization of neurofibromatosis in southern Brazil

description: <b>Objectives</b>: Neurofibromatoses (type 1: NF1; type 2: NF2) are autosomal dominant tumor predisposition syndromes mostly caused by loss-of-function mutations in the tumor suppressor genes NF1 and NF2, respectively. Genotyping is important for correct diagnosis of these diseases. The authors aimed to characterize <i>NF1</i> and <i>NF2</i> variants in patients from Southern Brazil. <b>Methods</b>: Ninety-three unrelated probands with NF1 and 7 unrelated probands with NF2 features were recruited from an Oncogenetics center in Southern Brazil. Two next generation sequencing panels were customized to identify point mutations: NF1 (<i>NF1, RNF135</i>, and <i>SUZ12</i> genes) and NF2 (<i>NF2</i> and <i>SMARCB1</i> genes). Large rearrangements were assessed by Multiplex Ligation-dependent Probe Amplification. <b>Results</b>: Sixty-eight heterozygous <i>NF1</i> variants were identified in 75/93 probands (80%) and 3 heterozygous <i>NF2</i> variants were identified in 3/7 probands (43%). In <i>NF1</i>, 59 (87%) variants were pathogenic (4 large rearrangements – 6%), 6 (9%) were likely pathogenic, 3 (4%) were variants of uncertain significance and 28 (41%) were novel. In <i>NF2</i>, all variants were pathogenic. No novel genotype-phenotype correlations were observed; however, previously described correlations were confirmed in our cohort. <b>Conclusion</b>: The clinical and molecular characterization of neurofibromatoses in different populations is very important to provide further insights into the pathogenesis of these diseases.
DOI: 10.6084/m9.figshare.6194150
title: Snow Tracer - Observation and model simulations for laboratory and field experiments

description: The fileset includes several observation and model data used for figures in a manuscript about the application of snowmelt as an active and inexpensive dual isotope groundwater tracer. This includes 1.) observation data from two 1D laboratory column displacement tests and model simulations using CXT-Fit as well as 2.) observation data from a push-pull tracer experiment in Pirna, Saxony, Germany and model simulations using MT3D-MS.
DOI: 10.6084/m9.figshare.6194150.v1
title: Snow Tracer - Observation and model simulations for laboratory and field experiments

description: The fileset includes several observation and model data used for figures in a manuscript about the application of snowmelt as an active and inexpensive dual isotope groundwater tracer. This includes 1.) observation data from two 1D laboratory column displacement tests and model simulations using CXT-Fit as well as 2.) observation data from a push-pull tracer experiment in Pirna, Saxony, Germany and model simulations using MT3D-MS
DOI: 10.6084/m9.figshare.6194150.v3
title: Snow Tracer - Observation and model simulations for laboratory and field experiments

description: The fileset includes several observation and model data used for figures in a manuscript about the application of snowmelt as an active and inexpensive dual isotope groundwater tracer. This includes 1.) observation data from two 1D laboratory column displacement tests and model simulations using CXT-Fit as well as 2.) observation data from a push-pull tracer experiment in Pirna, Saxony, Germany and model simulations using MT3D-MS.
DOI: 10.6084/m9.figshare.6194150.v2
title: Snow Tracer - Observation and model simulations for laboratory and field experiments

description: The fileset includes several observation and model data used for figures in a manuscript about the application of snowmelt as an active and inexpensive dual isotope groundwater tracer. This includes 1.) observation data from two 1D laboratory column displacement tests and model simulations using CXT-Fit as well as 2.) observation data from a push-pull tracer experiment in Pirna, Saxony, Germany and model simulations using MT3D-MS
DOI: 10.6084/m9.figshare.6194111
title: Supplementary Material for: Actionable Locoregional Relapses after Therapy of Localized Esophageal Cancer: Insights from a Large Cohort

description: <b><i>Objective:</i></b> The goal of surveillance after therapy of localized esophageal cancer (LEC) is to identify actionable relapses amenable to salvage; however, the current surveillance algorithms are not optimized. We report on a large cohort of LEC patients with actionable locoregional relapses (LRRs). <b><i>Methods:</i></b> Between 2000 and 2013, 127 (denominator = 752) patients with actionable LRR were identified. Histologic/cytologic confirmation was the gold standard. All surveillance tools (imaging, endoscopy, fine needle aspiration) were assessed. <b><i>Results:</i></b> Most patients were men (89%), had adenocarcinoma (79%), and had no new symptoms (72%) when diagnosed with LRR. In trimodality patients, endoscopic confirmation of positron emission tomography-computed tomography-suspected LRR occurred in only 44%, and 56% required additional tools (e.g., fine needle aspiration). Alternatively, in bimodality patients, endoscopy confirmed LRRs in 81%. Trimodality patients had a higher risk of subsequent LRR/distant metastases after the first LRR than the bimodality patients (<i>p</i> = 0.03). In all patients, 78% of the subsequent relapses were distant. For patients who were salvaged, survival was significantly prolonged (50.6 vs. 25.1 months, <i>p</i> &lt; 0.01). <b><i>Conclusions:</i></b> Patients live longer after successful salvage of the LRR than if salvage is not possible. After LRR, patients have a high risk of subsequent distant metastasis and whether the second relapse is local or distant, survival is uniformly poor.
DOI: 10.6084/m9.figshare.6194111.v1
title: Supplementary Material for: Actionable Locoregional Relapses after Therapy of Localized Esophageal Cancer: Insights from a Large Cohort

description: <b><i>Objective:</i></b> The goal of surveillance after therapy of localized esophageal cancer (LEC) is to identify actionable relapses amenable to salvage; however, the current surveillance algorithms are not optimized. We report on a large cohort of LEC patients with actionable locoregional relapses (LRRs). <b><i>Methods:</i></b> Between 2000 and 2013, 127 (denominator = 752) patients with actionable LRR were identified. Histologic/cytologic confirmation was the gold standard. All surveillance tools (imaging, endoscopy, fine needle aspiration) were assessed. <b><i>Results:</i></b> Most patients were men (89%), had adenocarcinoma (79%), and had no new symptoms (72%) when diagnosed with LRR. In trimodality patients, endoscopic confirmation of positron emission tomography-computed tomography-suspected LRR occurred in only 44%, and 56% required additional tools (e.g., fine needle aspiration). Alternatively, in bimodality patients, endoscopy confirmed LRRs in 81%. Trimodality patients had a higher risk of subsequent LRR/distant metastases after the first LRR than the bimodality patients (<i>p</i> = 0.03). In all patients, 78% of the subsequent relapses were distant. For patients who were salvaged, survival was significantly prolonged (50.6 vs. 25.1 months, <i>p</i> &lt; 0.01). <b><i>Conclusions:</i></b> Patients live longer after successful salvage of the LRR than if salvage is not possible. After LRR, patients have a high risk of subsequent distant metastasis and whether the second relapse is local or distant, survival is uniformly poor.
DOI: 10.6084/m9.figshare.6193859
title: Additional file 1: of Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

description: The source code of the database queries and workflow scripts for the three use cases reported in the paper. The results can be reproduced using the query results and analysis scripts provided. File query1.csv contains the barcodes of all samples for which mutation data do exist. File query2.csv contains the barcodes of all samples which carry a mutation in the gene of interest. Finally, query3.csv contains the survival data (according to Fig. 1a), a list of all mutations of patients in the cohort of interest (according to Fig. 1b), or a list of all genomic segments with aberrant copy number in the cohort of interest (according to Fig. 1c). There are small discrepancies between the number of patients with mutation data and the number of patients with survival data (Fig. 1a) and copy number data (Fig. 1c). (ZIP 4981 kb)
DOI: 10.6084/m9.figshare.6193859.v1
title: Additional file 1: of Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

description: The source code of the database queries and workflow scripts for the three use cases reported in the paper. The results can be reproduced using the query results and analysis scripts provided. File query1.csv contains the barcodes of all samples for which mutation data do exist. File query2.csv contains the barcodes of all samples which carry a mutation in the gene of interest. Finally, query3.csv contains the survival data (according to Fig. 1a), a list of all mutations of patients in the cohort of interest (according to Fig. 1b), or a list of all genomic segments with aberrant copy number in the cohort of interest (according to Fig. 1c). There are small discrepancies between the number of patients with mutation data and the number of patients with survival data (Fig. 1a) and copy number data (Fig. 1c). (ZIP 4981 kb)
DOI: 10.6084/m9.figshare.6193856
title: Additional file 7: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S4. Top 500 upstream regulators of differentially expressed genes in canine iUC. Predicted activity based on gene expression values in canine iUC relative to normal bladder. A z-score &gt; 2 indicates activation, while a z-score
DOI: 10.6084/m9.figshare.6193856.v1
title: Additional file 7: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S4. Top 500 upstream regulators of differentially expressed genes in canine iUC. Predicted activity based on gene expression values in canine iUC relative to normal bladder. A z-score &gt; 2 indicates activation, while a z-score
DOI: 10.6084/m9.figshare.6193832
title: Additional file 4: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S3. Top 500 downregulated differentially expressed genes (DEGs) in canine iUC. (XLSX 25 kb)
DOI: 10.6084/m9.figshare.6193832.v1
title: Additional file 4: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S3. Top 500 downregulated differentially expressed genes (DEGs) in canine iUC. (XLSX 25 kb)
DOI: 10.6084/m9.figshare.6193820
title: Additional file 3: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S2. Top 500 upregulated differentially expressed genes (DEGs) in canine iUC. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.6193820.v1
title: Additional file 3: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S2. Top 500 upregulated differentially expressed genes (DEGs) in canine iUC. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.6193805
title: Additional file 9: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Oxidative phosphorylation. Identification of respiratory complex subunit putative orthologs and classification according to protein sequence conservation (nr-dataset and mitochondrial_mapped datasets. Data for Fig. 7) (XLS 69 kb)
DOI: 10.6084/m9.figshare.6193805.v1
title: Additional file 9: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Oxidative phosphorylation. Identification of respiratory complex subunit putative orthologs and classification according to protein sequence conservation (nr-dataset and mitochondrial_mapped datasets. Data for Fig. 7) (XLS 69 kb)
DOI: 10.6084/m9.figshare.6193802
title: Additional file 2: of Ioncopy: an R Shiny app to call copy number alterations in targeted NGS data

description: Breast cancer example data set. Coverage matrix of 152 amplicons (48 genes) in 184 breast cancer samples. (XLS 196Â kb)
DOI: 10.6084/m9.figshare.6193802.v1
title: Additional file 2: of Ioncopy: an R Shiny app to call copy number alterations in targeted NGS data

description: Breast cancer example data set. Coverage matrix of 152 amplicons (48 genes) in 184 breast cancer samples. (XLS 196Â kb)
DOI: 10.6084/m9.figshare.6193799
title: Additional file 1: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S1. Sequences of the oligonucleotide primers used for quantitative PCR. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.6193799.v1
title: Additional file 1: of Comprehensive gene expression analysis of canine invasive urothelial bladder carcinoma by RNA-Seq

description: Table S1. Sequences of the oligonucleotide primers used for quantitative PCR. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.6193793
title: Additional file 8: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Identification of Glycolysis, gluconeogenesis and pentose-phosphate putative orthologs and classification according to protein sequence conservation (RproC3.2_mapped dataset. Data for Fig. 6. (XLS 62 kb)
DOI: 10.6084/m9.figshare.6193793.v1
title: Additional file 8: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Identification of Glycolysis, gluconeogenesis and pentose-phosphate putative orthologs and classification according to protein sequence conservation (RproC3.2_mapped dataset. Data for Fig. 6. (XLS 62 kb)
DOI: 10.6084/m9.figshare.6193781
title: Additional file 7: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Gene ontology term enrichment in divergent vs. conserved group putative 1:1 orthologs (isotig dataset). (XLS 43 kb)
DOI: 10.6084/m9.figshare.6193781.v1
title: Additional file 7: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Gene ontology term enrichment in divergent vs. conserved group putative 1:1 orthologs (isotig dataset). (XLS 43 kb)
DOI: 10.6084/m9.figshare.6193757
title: Additional file 5: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Protein sequence divergence in putative 1:1 orthologs according to Gene Ontology terms (Level 3). Isotig dataset. Data for Fig. 5. (XLS 54 kb)
DOI: 10.6084/m9.figshare.6193757.v1
title: Additional file 5: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Protein sequence divergence in putative 1:1 orthologs according to Gene Ontology terms (Level 3). Isotig dataset. Data for Fig. 5. (XLS 54 kb)
DOI: 10.6084/m9.figshare.6193742
title: Additional file 4: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Transcripts coding for odorant receptors and odorant binding proteins in Triatoma. (XLS 78 kb)
DOI: 10.6084/m9.figshare.6193742.v1
title: Additional file 4: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Transcripts coding for odorant receptors and odorant binding proteins in Triatoma. (XLS 78 kb)
DOI: 10.6084/m9.figshare.6193730
title: Additional file 7: of Genes and functions from breast cancer signatures

description: Table S7. The number of common function terms between every two signatures. A matrix of 29 signatures by 29 signatures with the number of common function terms shared by every two signatures. No significantly enriched function terms were found for four signatures (HI, IHC4, Multigene and MAGEA), 29 of the 33 signatures were used for analysis. (CSV 3 kb)
DOI: 10.6084/m9.figshare.6193730.v1
title: Additional file 7: of Genes and functions from breast cancer signatures

description: Table S7. The number of common function terms between every two signatures. A matrix of 29 signatures by 29 signatures with the number of common function terms shared by every two signatures. No significantly enriched function terms were found for four signatures (HI, IHC4, Multigene and MAGEA), 29 of the 33 signatures were used for analysis. (CSV 3 kb)
DOI: 10.6084/m9.figshare.6193727
title: Additional file 3: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Transcriptionally active transposable elements in Triatoma. BLASTn analysis search in the RepBase database. Data for Fig. 4. (XLS 64 kb)
DOI: 10.6084/m9.figshare.6193727.v1
title: Additional file 3: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Transcriptionally active transposable elements in Triatoma. BLASTn analysis search in the RepBase database. Data for Fig. 4. (XLS 64 kb)
DOI: 10.6084/m9.figshare.6193718
title: Additional file 6: of Genes and functions from breast cancer signatures

description: Table S6. The number of signatures involved in each function term. In this table, for each signature function term, the number of signatures including this gene was counted. (CSV 57 kb)
DOI: 10.6084/m9.figshare.6193718.v1
title: Additional file 6: of Genes and functions from breast cancer signatures

description: Table S6. The number of signatures involved in each function term. In this table, for each signature function term, the number of signatures including this gene was counted. (CSV 57 kb)
DOI: 10.6084/m9.figshare.6193715
title: Additional file 2: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Analysis of the calycin family in Triatoma. Data for Fig. 3. (XLS 58 kb)
DOI: 10.6084/m9.figshare.6193715.v1
title: Additional file 2: of Adaptations in energy metabolism and gene family expansions revealed by comparative transcriptomics of three Chagas disease triatomine vectors

description: Analysis of the calycin family in Triatoma. Data for Fig. 3. (XLS 58 kb)
DOI: 10.6084/m9.figshare.6193709
title: MOESM5 of Accurate and easy method for systemin quantification and examining metabolic changes under different endogenous levels

description: Additional file 5: Table S2. Relevant pathways and compounds under SYS control. List of compounds that show higher level intensities in PS+ , and lower ones in PS− respect to BB and PS+ . All the masses presented in the table have been annotated at a tentative level, although in some of them a further identification by using fragmentation spectrum has been performed. Abbreviations: fs, identification by exact mass and fragmentation spectrum level 2 of identification [43]; ti, is a tentative identification of the compound referred-to level 3 [43].
DOI: 10.6084/m9.figshare.6193709.v1
title: MOESM5 of Accurate and easy method for systemin quantification and examining metabolic changes under different endogenous levels

description: Additional file 5: Table S2. Relevant pathways and compounds under SYS control. List of compounds that show higher level intensities in PS+ , and lower ones in PS− respect to BB and PS+ . All the masses presented in the table have been annotated at a tentative level, although in some of them a further identification by using fragmentation spectrum has been performed. Abbreviations: fs, identification by exact mass and fragmentation spectrum level 2 of identification [43]; ti, is a tentative identification of the compound referred-to level 3 [43].
DOI: 10.6084/m9.figshare.6193706
title: Additional file 5: of Genes and functions from breast cancer signatures

description: Table S5. Function terms distribution among the signatures. A matrix with each of all signature genes against each of the 29 signatures to see how the function terms distribute among those signatures. Since no significantly enriched function terms were found for four signatures (HI, IHC4, Multigene and MAGEA), 29 of the 33 signatures were used for analysis. (CSV 194 kb)
DOI: 10.6084/m9.figshare.6193703
title: Additional file 2: of Emergence of the Asian lineage dengue virus type 3 genotype III in Malaysia

description: Phylogeography of DENV3/III-C. (KML 1198 kb)
DOI: 10.6084/m9.figshare.6193706.v1
title: Additional file 5: of Genes and functions from breast cancer signatures

description: Table S5. Function terms distribution among the signatures. A matrix with each of all signature genes against each of the 29 signatures to see how the function terms distribute among those signatures. Since no significantly enriched function terms were found for four signatures (HI, IHC4, Multigene and MAGEA), 29 of the 33 signatures were used for analysis. (CSV 194 kb)
DOI: 10.6084/m9.figshare.6193703.v1
title: Additional file 2: of Emergence of the Asian lineage dengue virus type 3 genotype III in Malaysia

description: Phylogeography of DENV3/III-C. (KML 1198 kb)
DOI: 10.6084/m9.figshare.6193700
title: Additional file 1: of Delineation of the genetic and clinical spectrum of Phelan-McDermid syndrome caused by SHANK3 point mutations

description: Table S1. Loss of function and de novo missense variants in SHANK3 reported previously. Table S2. Clinical features of individuals with pathogenic or likely pathogenic SHANK3 variants reported in the literature. Table S3. In silico prediction of pathogenicity of missense variants in SHANK3 identified in this study and in the literature. Table S4. Reported truncating and in-frame variants in SHANK3 unlikely to be pathogenic. (XLSX 84Â kb)