cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3593286
title: Supplementary Material for: A Double-Blind, Placebo Controlled, Randomized Phase 1 Cross-Over Study with ALLN-177, an Orally Administered Oxalate Degrading Enzyme

description: <b><i>Background:</i></b> Hyperoxaluria may result from increased endogenous production or overabsorption of dietary oxalate in the gastrointestinal tract leading to nephrolithiasis and, in some, to oxalate nephropathy and chronic kidney disease. ALLN-177 is an oral formulation of a recombinant, oxalate specific, microbial enzyme oxalate decarboxylase intended to treat secondary hyperoxaluria by degrading dietary oxalate in the gastrointestinal tract, thereby reducing its absorption and subsequent excretion in the urine. <b><i>Methods:</i></b> This double-blind, placebo controlled, randomized, cross-over, phase 1 study of ALLN-177 evaluated the tolerability of ALLN-177 and its effect on urinary oxalate excretion in 30 healthy volunteers with hyperoxaluria induced by ingestion of a high oxalate, low calcium (HOLC) diet. The primary end point was the difference in the mean 24-hour urinary oxalate excretion during the ALLN-177 treatment period compared with the placebo treatment period. <b><i>Results:</i></b> The daily urinary oxalate excretion increased in the study population from 27.2 ± 9.5 mg/day during screening to 80.8 ± 24.1 mg/day (mean ± SD) on the HOLC diet before introducing ALLN-177 or placebo therapy for 7 days. Compared to placebo, ALLN-177 treatment reduced urinary oxalate by 11.6 ± 2.7 mg/day, p = 0.0002 (least squares mean ± SD). <b><i>Conclusions:</i></b> In healthy volunteers, with diet-induced hyperoxaluria treatment with ALLN-177, when compared to placebo, significantly reduced urinary oxalate excretion by degrading dietary oxalate in the gastrointestinal tract and thereby reducing its absorption. ALLN-177 may represent a new approach for managing secondary hyperoxaluria and its complications.
DOI: 10.6084/m9.figshare.3593277
title: PowerPoint Slides for: Chronic Kidney Disease Classification in Systolic Blood Pressure Intervention Trial: Comparison Using Modification of Diet in Renal Disease and CKD-Epidemiology Collaboration Definitions

description: <b><i>Background:</i></b> Interventional trials have used either the Modification of Diet in Renal Disease (MDRD) or chronic kidney disease (CKD)-Epidemiology Collaboration (CKD-EPI) equation for determination of estimated glomerular filtration rate (eGFR) to define whether participants have stages 3-5 CKD. The equation used to calculate eGFR may influence the number and characteristics of participants designated as having CKD. <b><i>Methods:</i></b> We examined the classification of CKD at baseline using both equations in the Systolic Blood Pressure Intervention Trial (SPRINT). eGFR was calculated at baseline using fasting serum creatinine values from a central laboratory. <b><i>Results:</i></b> Among 9,308 participants with baseline CKD classification using the 4-variable MDRD equation specified in the SPRINT protocol, 681 (7.3%) participants were reclassified to a less advanced CKD stage (higher eGFR) and 346 (3.7%) were reclassified to a more advanced CKD stage (lower eGFR) when the CKD-EPI equation was used to calculate eGFR. For eGFRs &lt;90 ml/min/1.73 m<sup>2</sup>, participants &lt;75 years were more likely to be reclassified to a less advanced CKD stage; this reclassification was more likely to occur in non-blacks rather than blacks. Participants aged ≥75 years were more likely to be reclassified to a more advanced than a less advanced CKD stage, regardless of baseline CKD stage. Reclassification of baseline CKD status (eGFR &lt;60 ml/min/1.73 m<sup>2</sup>) occurred in 3% of participants. <b><i>Conclusions:</i></b> Use of the MDRD equation led to a higher percentage of participants being classified as having CKD stages 3-4. Younger and non-black participants were more likely to be reclassified as not having CKD using the CKD-EPI equation.
DOI: 10.6084/m9.figshare.3593265
title: Otsu Thresholding Program Code in C

description: It is program written in C language for Otsu Thresholding
DOI: 10.6084/m9.figshare.3593259
title: planck keymap

description: keymap for the planck
DOI: 10.4225/03/57c169a6d3720
title: A manually traced vein mask from susceptibility-based MRI images of a healthy young subject (S4).

description: Susceptibility-weighted image (SWI), quantitative susceptibility map (QSM), manually-traced vein mask (Vein) and dilated brain mask (Mask) for subject 4.
DOI: 10.4225/03/57c1699c28a8b
title: A manually traced vein mask from susceptibility-based MRI images of a healthy young subject (S3).

description: Susceptibility-weighted image (SWI), quantitative susceptibility map (QSM), manually-traced vein mask (Vein) and dilated brain mask (Mask) for subject 3.<br><br>Note: Falcine calcifications.<br>
DOI: 10.4225/03/57c1698fc2f34
title: A manually traced vein mask from susceptibility-based MRI images of a healthy young subject (S2).

description: Susceptibility-weighted image (SWI), quantitative susceptibility map (QSM), manually-traced vein mask (Vein) and dilated brain mask (Mask) for subject 2.
DOI: 10.4225/03/57c1698020d1d
title: A manually traced vein mask from susceptibility-based MRI images of a healthy young subject (S1).

description: Susceptibility-weighted image (SWI), quantitative susceptibility map (QSM), manually-traced vein mask (Vein) and dilated brain mask (Mask) for subject 1.
DOI: 10.6084/m9.figshare.3593088
title: Genetic and fitness consequences of decreased immigration in the Florida Scrub-Jay

description: Data for "Genomic Consequences of Population Decline in the Endangered Florida Scrub-Jay"<br>by N Chen, EJ Cosgrove, R Bowman, JW Fitzpatrick, AG Clark, 2016.<br><br>Details in README.txt. Please contact the authors if you plan on using these data.<br>
DOI: 10.6084/m9.figshare.3593088.v1
title: Genetic and fitness consequences of decreased immigration in the Florida Scrub-Jay

description: Data for "Genomic Consequences of Population Decline in the Endangered Florida Scrub-Jay"<br>by N Chen, EJ Cosgrove, R Bowman, JW Fitzpatrick, AG Clark, 2016.<br><br>Details in README.txt. Please contact the authors if you plan on using these data.<br>
DOI: 10.6084/m9.figshare.3593049
title: Data achieve A. altissima.xlsx

description: This data is data achieve from article "Ecological application of biotic resistance to control invasion by an invasive plant, Ageratina altissima"<br>
DOI: 10.6084/m9.figshare.3593049.v1
title: Data achieve A. altissima.xlsx

description: This data is data achieve from article "Ecological application of biotic resistance to control invasion by an invasive plant, Ageratina altissima"<br>
DOI: 10.6084/m9.figshare.3593046
title: Direct correlation between motile behavior and protein abundance in single cells.

description: Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with <i>in situ</i> hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in <i>Escherichia coli</i> motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.
DOI: 10.6084/m9.figshare.3593046.v1
title: Direct correlation between motile behavior and protein abundance in single cells.

description: Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with <i>in situ</i> hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in <i>Escherichia coli</i> motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage.
DOI: 10.6084/m9.figshare.3593034
title: Exercício da Medicina e Direito Penal

description: Esta aula da disciplina de Bioética, Medicina e Direito, do Programa de Pós-Graduação em Medicina: Ciências Médicas da Universidade Federal do Rio Grande do Sul, tem como objetivo discutir as interações entre o Direito Penal e a Medicina. Inúmeras questões podem ser discutidas a respeito do exercício da Medicina, e, por extensão, das demais profissões da área da Saúde, e suas eventuais repercussões penais. A Bioética participa desta temática como um elemento de fundo, que busca dar justificativas de adequação ou não para as ações praticadas pelo profissional.
DOI: 10.6084/m9.figshare.3593034.v1
title: Exercício da Medicina e Direito Penal

description: Esta aula da disciplina de Bioética, Medicina e Direito, do Programa de Pós-Graduação em Medicina: Ciências Médicas da Universidade Federal do Rio Grande do Sul, tem como objetivo discutir as interações entre o Direito Penal e a Medicina. Inúmeras questões podem ser discutidas a respeito do exercício da Medicina, e, por extensão, das demais profissões da área da Saúde, e suas eventuais repercussões penais. A Bioética participa desta temática como um elemento de fundo, que busca dar justificativas de adequação ou não para as ações praticadas pelo profissional.
DOI: 10.6084/m9.figshare.3592863
title: Training set of clinical meta-data for Local Control Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (138 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 150 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the local recurrence status blinded.
DOI: 10.6084/m9.figshare.3592863.v1
title: Training set of clinical meta-data

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (138 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 150 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the local recurrence status blinded.
DOI: 10.6084/m9.figshare.3592863.v2
title: Training set of clinical meta-data for Local Control Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (138 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 150 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the local recurrence status blinded.
DOI: 10.6084/m9.figshare.3592860
title: Supplementary Material to RepurposeDB

description: Systematic analyses of drugs, diseases and drug targets in RepurpodeDBSupplementary Data files in Excel format <br>RepurposeDB_BinChe.xlsxRepurposeDB_CGEA.xlsxRepurposeDB_ChemicalProperties.xlsxRepurposeDB_CPDB.xlsxRepurposeDB_DAVID.xlsxRepurposeDB_DiseaseSimilarity.xlsxRepurposeDB_Drug_Food_Target_Networks.xlsxRepurposeDB_EHR_SGA.xlsxRepurposeDB_Enrichr.xlsxRepurposeDB_EvidenceTypes.xlsxRepurposeDB_PanOntology_Mapping.xlsxRepurposeDB_Pharmacoeconomics.xlsxRepurposeDB_PubMed_Articles.xlsxRepurposeDB_SFN_EFN_NA.xlsx<br>Compiled on Aug 16 2016 Compiled by Khader Shameer, Benjamin Glicksberg, Marcus A Badgeley, Tim O’ Connor & Max S Tomlinson<br>Contact us at repurposedb@dudleylab.org | skhadar@gmail.com <br>Dataset accompnying the following manuscript: Systematic analyses of 253 drugs and 1125 disease indications in RepurposeDB reveal chemical, biological and epidemiological factors influencing drug repositioning <br>Khader Shameer<sup>1,</sup> Benjamin S. Glicksberg<sup>1</sup>, Rachel Hodos<sup>1</sup>, Marcus A. Badgeley<sup>1</sup>, Kipp W Johnson<sup>1</sup>, Ben Readhead<sup>1</sup> , Max S. Tomlinson<sup>1</sup>, Timothy O’Connor<sup>1,2</sup>, Riccardo Miotto<sup>1</sup>, Brian A. Kidd<sup>1</sup>, Rong Chen<sup>1</sup>, Avi Ma’ayan<sup>3</sup> and Joel T. Dudley<sup>1,2*</sup> <br><sup>1</sup> Department of Genetics and Genomic Sciences, Harris Center for Precision Wellness, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York, USA. <br><sup>2</sup> Boston College, Morrissey College of Arts and Sciences, Chestnut Hill, MA<br><sup>3</sup> Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, Systems Biology Center New York (SBCNY), Mount Sinai Health System, New York, New York, USA. <br><sup>4</sup> Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, New York, USA.<br><b><sup>*</sup>Corresponding author:</b> joel.dudley@mssm.edu <br>
DOI: 10.6084/m9.figshare.3592857
title: Test set of clinical meta-data for Local Control Challenge

description: This MD Anderson Cancer Center set of anonymized high-quality computed tomography (CT) scans with contrast represent a comparatively homogeneous, uniform cohort of 288 oropharynx cancer patients with detailed clinical history, consistent follow-up of &gt; 2 years, known etiological/biological correlates (specifically, human papilloma virus status). Our major target is to assess/validate the radiomics workflow and predictive capacity of radiomics signatures from challenge participants.We imported the CT scans from the patients’ electronic medical records, that were performed before the initiation of the radiation treatment course. All the patients were treated using the IMRT modality. Some patients were simultaneously prescribed chemotherapy. We intended that the CT films would be as much representative of the original simulation CT scans that were used for treatment planning, in which no contrast was injected according to our institutional policy.Specifically, we posted around one-half of the CT scans from the dataset (138 patients), in DICOM-RT format, on the Kaggle in Class server system, as a “training set”. DICOM-RT files were fully anonymized, with expert physician segmenting primary tumor and lymph node as regions of interest, to eliminate segmentation-related uncertainty for challengers. The primary oropharyngeal tumor was segmented in red. Whereas, the metastatic cervical lymph nodes were segmented individually, rather than on the basis of the nodal level classification system. Both training and test sets include the following data for each DICOM-RT case:agegenderracetumor side and subsiteT-categoryN-categoryAJCC stagePathologic gradesmoking status (in pack-years)Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected 150 patients' DICOM files and relevant clinical meta-data, with local control status blinded.Challenge participants will also be able to download a “test" dataset, which includes the remaining randomly selected half of the dataset, with local control status blinded.Challenge participants will also be able to download a “test" dataset, with the remaining random selected half of the dataset, which will have the local recurrence status blinded.