cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28088732.v1
title: Supplementary Material for: Novel Von Hippel-Lindau Germline Variants in Iranian Patients with Retinal Capillary Hemangioblastoma

description: Introduction: To determine the potential genetic cause of retinal capillary hemangioblastoma (RCH) with symptoms of VHL disease. 
Case Presentations: Three Iranian families (5 RCH patients) with novel variants are included in this study. The VHL variant analysis was performed by the Sanger sequencing technique. Molecular dynamic (MDs) simulations were conducted to analyze conformational changes resulting from variants in VHL protein structure and were compared with that of the native structure. Novel variant sites, including c.511A&gt;C, c.511A&gt;T and c.514C&gt;T in exon 3 of the VHL gene were identified. According to the American College of Medical Genetics (ACMG) classifications, c.514C&gt;T (p.P172S) and c.511A&gt;C (p.K171Q) are classified as variants of uncertain significance (VUS), and c.511A&gt;T (p.K171*) is classified as a likely pathogenic variant. MD simulations demonstrated overall fluctuations of the proteins structure and a significantly lower degree of flexibility in the α-domain for the variant-encoded VHL protein structure compared to that of the native form. 
Conclusion: The structural information and computational analysis of the identified variants are predicted to induce conformational changes that limit the flexibility of pVHL interaction interface with Elongin B/C, Elongin C/B, and Cullin-2, which are necessary for HIF1-α binding. The genetic variants identified in Iranian patients with RCH may aid in the molecular confirmation of other patients diagnosed with VHL and their at-risk family members. These pioneering results that include detailed structural and functional analysis of a variant’s effect on the VHL protein may serve as a model for future studies.
DOI: 10.6084/m9.figshare.24716832.v2
title: Voxelwise difference

description: <b>Voxelwise differences in GMV and ReHo between OC and non-OC measured by Cohen’s </b><b><i>d </i></b>
DOI: 10.6084/m9.figshare.28333727.v1
title: J_W_Datasets_Rickettsia_E_E.xlsx

description: Dataset for Ticks and Rickettsia prevalence in the great Tits in the city of Lodz central Poland.
DOI: 10.6084/m9.figshare.4542985.v1
title: Supplementary Material for: Generating Conditionally Immortalised Podocyte Cell Lines from Wild-Type Mice

description: <b><i>Background:</i></b> Understanding podocyte biology is key to deciphering the pathogenesis of numerous glomerular diseases. However, cultivation of primary podocytes results in de-differentiation with loss of specialised architecture. Human conditionally immortalised podocytes partly overcome this problem, utilising a temperature-sensitive transgene. Conditionally immortalised murine podocytes exist, but are derived from the Immortomouse. <b><i>Methods:</i></b> Using retroviral temperature-sensitive SV40 transfection, we created a conditionally immortalised podocyte cell line from wild-type mice. <b><i>Results:</i></b> These cells develop characteristic mature podocyte morphology and robustly express slit diaphragm proteins. Functionally, these cells demonstrate comparable responses in motility and glucose uptake to human conditionally immortalised podocytes. <b><i>Conclusion:</i></b> Podocyte-specific transgenic mice are extensively used to study glomerular disease and this technique could be used to make podocyte cell lines from any mouse, allowing study at the cellular level. This will help characterise these disease models and add to the laboratory resources used to study podocytopathies and glomerular disease.
DOI: 10.6084/m9.figshare.7200734.v1
title: Supplementary Material for: Comparison of Renal Function after Radical Surgery for Upper Tract Urothelial Carcinoma versus Renal Cell Carcinoma: Propensity Score Matching

description: <b><i>Objectives:</i></b> To compare renal function after radical nephrectomy for renal cell carcinoma (RCC) and for upper tract urothelial carcinoma (UTUC). <b><i>Method:</i></b> Data from 1,236 patients with RCC or UTUC treated surgically from 2000 to 2013 were enrolled. The estimated glomerular filtration rate (eGFR) was calculated preoperatively and postoperatively at 12, 24, 36, 48, and 60 months. A multivariate logistic regression was used to determine independent factors for a decrease in eGFR to &lt; 60 mL/min/1.73 m<sup>2</sup> and end-stage renal disease. <b><i>Result:</i></b> After propensity score matching, a total of 554 patients were included. During follow-up for 5 years, there was statistically significant difference in eGFR between 2 groups. And there was a statistically significant difference in the number of patients developing impaired renal function between the 2 groups (UTUC 73.3 vs. RCC 66.1%, <i>p</i> = 0.039). Multivariate analysis showed that old age (OR 3.957, <i>p</i> &lt; 0.001), UTUC (OR 1.838, <i>p</i> = 0.006), BMI (OR 2.463, <i>p</i> = 0.001) and a baseline eGFR (OR 0.976, <i>p</i> = 0.001) were independent risk factors for postoperative impaired renal function. <b><i>Conclusion:</i></b> Patients with UTUC had worse baseline eGFR, old age, comorbidities than RCC patients. Even after adjusting by PS matching, UTUC patients had lower postoperative eGFR and higher rates of CKD development than RCC patients.
DOI: 10.6084/m9.figshare.14485419.v1
title: LaBarge et al. Pumas (Puma concolor) as ecological brokers.xlsx

description: We reviewed the published literature to address the question of what role puma (Puma concolor) plays within the diverse set of ecosystems it inhabits across the western hemisphere. We searched the ISI Web of Science databases and Google Scholar for keywords (page 1) associated with puma species interactions and their ecological roles and found 162 studies published between 1950-2020. These studies reported evidence of 542 distinct ecological interactions between pumas and other biota, across 484 distinct species.
DOI: 10.6084/m9.figshare.18665686.v1
title: Genomics of Salmonella Typhi from Samoa

description: This item contains the draft and complete assemblies used in the manuscript, "Persistence of rare <em>Salmonella</em> Typhi genotypes susceptible to first-line antibiotics in the remote islands of Samoa," by Sikorski et al., 2022, mBio.
DOI: 10.6084/m9.figshare.2068851.v1
title: A psychometric evaluation of the Gender Bias in Medical Education Scale

description: <em><b>Background: </b></em><em>Gender </em>bias in medical education is an increasing area of research and policy concern. However, to adequately address and monitor this issue, valid and reliable measures are needed. This research aimed to develop and test a short multidimensional measure of gender bias in medical education to assess student awareness of gender bias, beliefs about the degree to which gender bias should be addressed, and experience of gender bias. <em><b>Methods: </b></em>Using students from the School of Medicine at the University of Wollongong, one pilot study and two empirical studies were conducted. The pilot study was used to scope the domain space (n = 28). This initial measure was extended to develop the Gender Bias in Medical Education Scale (GBMES). For study 1 (n = 172), confirmatory factor analysis assessed the construct validity of the three-factor structure (awareness, beliefs, experience) and enabled deletion of redundant items. Study 2 (n = 457) tested the generalizability of the refined scale to a new sample. Combining study 1 and 2, invariance testing for program of study and gender was explored. The relationship of the GBMES to demographic and gender politics variables was tested. The results were analyzed using confirmatory factor analysis and Multiple-Indicator-Multiple-Indicator-Cause models in order to determine construct validity and whether the scale generalized to other samples. <em><b>Results:</b></em><i> </i>After analysis of the responses from the original 16-item GBMES (Study 1), a shortened measure of 10 items fitted the data well and was found to generalize to a new sample in Study 2. The GBMES was found to be invariant across studies, gender, and program of study. Female students and those who reported greater agreement with gender equality responded with greater agreement for each of the factors in relation to gender bias. Likewise, postgraduate students reported higher scores on experience of gender bias than undergraduate students. <b></b> <b><i>Conclusion:</i></b><i> </i>The GBMES provides a validated short multidimensional measure for use in research and policy. The factors are distinct and are related to background variables and covariates in expected patterns.<b></b>
DOI: 10.6084/m9.figshare.6983246.v2
title: A Model Predicting Unscheduled Caesarean Section.sav

description: Prospective cohort study consisted of nulliparae giving birth between the 37th and 42nd weeks of singleton low-risk pregnancy, with the fetus in vertex position and without primary indication for CS. Selected prenatal and intranatal factors were analyzed in relation to acute CS due to a failure to progress in labor and/or fetal distress. Using logistic regression analysis (LR1-3) and the classification tree method (chi-square automatic interaction detector 1-2), five prediction models were tested.
DOI: 10.6084/m9.figshare.24115149.v1
title: data and code

description: data and code
DOI: 10.6084/m9.figshare.26325319.v1
title: Response data for LLMs left, right, and center: Assessing GPT's capabilities to label political bias from web domains

description: This research investigates whether OpenAI's GPT-4, a state-of-the-art large language model, can accurately classify the political bias of news sources based solely on their URLs. This dataset contains GPT-4 classifications for sources listed on Media Bias/Fact Check (MBFC), rated on a seven-degree scale ("far-left" to "far-right").
DOI: 10.6084/m9.figshare.28903058.v1
title: Supplementary material, data, and figure scripts for Benavides & Barkley "Model for transitional turbulence in aplanar shear flow" (2025)

description: The zip file contains the following:<br><br>1) Electronic_supplementary_material_Benavides_Barkley_2025.pdf, which is the electronic supplementary material accompanying the main paper. This contains information regarding details of the stability analysis, details of the bound on the critical angle, and a description of supplementary movies.<br>2) Directory 'Movies', which includes the supplementary movie files (described in the supplementary material).3) Figures.ipynb (Jupyter notebook) and Figures.py (script version of the Jupyter notebook), which are the scripts used to make the figures in the study.4) Directory 'DNS', which includes both running scripts and data from fully-resolved, 3D simulation of Waleffe flow. Ran using Dedalus (https://dedalus-project.org/). 5) Directory '2D_MWF' which includes both running scripts and data from simulations of the paper's model of Waleffe flow. The code is preserved at https://doi.org/10.5281/zenodo.15261063, available via the Creative Commons Attribution 4.0 International (CC-BY) license. Ran using Dedalus.<br><br>6) Directory '1D_MWF' which includes both running scripts and data from simulations of the paper's model of Waleffe flow in the 1D, tilted geometry configuration. Ran using Dedalus.
DOI: 10.17632/jnmsdxz93c
title: Government Expenditure Composition and Long-Run Economic Growth in the Aging Democracy

description: This dataset supports the research article entitled “Government Expenditure Composition and Long-Run Economic Growth in the Aging Democracy.” It includes a Mathematica code file to illustrate the figures in the article.
DOI: 10.6084/m9.figshare.21440592.v1
title: Data files for github omz_stoichiometry repository

description: Data for https://github.com/dmuratore/omz_stoichiometry. Once a preprint is available for methods and details it will be posted here.
DOI: 10.6084/m9.figshare.7013003.v1
title: hcp_tractogram.zip

description: Testing tractogram of one of the HCP dataset subjects to be used in DIPY's tutorials.<br><br><br>
DOI: 10.6084/m9.figshare.19719310.v4
title: Seed-mediated AuNR Synthesis Extraction with GPT-3

description: The files were used as follows: <br> Empty synthesis template: clean_template_formatted.json Training sets for fine-tuning GPT-3 to extract structured seed-mediated AuNR growth procedures from unstructured text: aunr_synth_v6_ucfx_static_0_240_0_corrected_publishable.json Predictions and corrected predictions for evaluating the performance of GPT-3 recipe extraction completions: aunr_synth_v6_ucfx_static_0_40_6_predict_publishable.json aunr_synth_v6_ucfx_static_0_40_6_corrected_publishable.json GPT-3 recipe extraction completion prediction over the complete dataset: aunr_synth_v6_ucfx_static_0_1137_0_predict_publishable.json GPT-3 recipe extraction completion prediction over the complete dataset merged by paper with empty fields removed: aunr_synth_v6_ucfx_static_dynamic_0_1137_0_predict_paperwise_merged_publishable.json GPT-3 recipe extraction completion prediction over the complete dataset merged by paper with empty fields removed and post-processing applied: aunr_synth_v6_ucfx_static_dynamic_0_1137_0_predict_paperwise_merged_postprocessed_n_recipes_publishable.json Performance evaluation scripts: prediction_statistics_complete.py paperwise_prediction_statistics_complete.py paragraphwise_prediction_statistics_complete.py
DOI: 10.6084/m9.figshare.28248524.v2
title: Decentralised study using the Alethios Platform to assess the impact of OmeGo / Cardio salmon oil on Sleep, Cough and Inflammation in Urban dwelling participants troubled by Particulate Matter Pollution

description: An 8 week study to assess the inflammation-resolving effects of a whole salmon oil Cardio / OmeGo in urban dwelling participants with disruption of sleep and coughing likely arising from particulate matter pollution. Objective sleep metrics measured by wearable device and subjectively by VAS rating. Cough severity measured by VAS rating. Nasal swabs taken to measure the change in expression of genes encoding inflammatory cytokines.
DOI: 10.17632/86xkkncmw3
title: Research data supporting "A tale of two tails: Do Power Law and Lognormal models fit firm-size distributions in the mid-Victorian era?"

description: This dataset contains firm-size distributions for mid-Victorian era from the 1851-1881 England and Wales censuses and corresponds to research data supporting "A tale of two tails: Do Power Law and Lognormal models fit firm-size distributions in the mid-Victorian era?" by Montebruno, P., Bennett, R, van Lieshout, C., and Smith, H. as an outcome of the ESRC project ES/M010953: Drivers of Entrepreneurship and Small Businesses lead by PI Prof. Robert J. Bennett. The material consists of one raw text file with eight variables: 1. Frequency distribution of 1851 2. Frequency distribution of 1861 3. Frequency distribution of 1871 4. Frequency distribution of 1881 5. Size distribution of 1851 6. Size distribution of 1861 7. Size distribution of 1871 8. Size distribution of 1881 A detailed explanation of how these distributions were obtained and how to use them in the context of firm-size distribution analysis including the distinction between Power Law and Lognormal behaviour in the tails can be found in the paper "A tale of two tails: Do Power Law and Lognormal models fit firm-size distributions in the mid-Victorian era?" by Montebruno, P., Bennett, R, van Lieshout, C., and Smith, H. published in the journal Physica A: Statistical Mechanics and its Applications. The file can be opened in any text editor, database management system (Access) or statistical package (Stata, SPSS). This dataset should be cited as Montebruno, P., Bennett, R., van Lieshout, C., and Smith, H. “Research data supporting "A tale of two tails: Do Power Law and Lognormal models fit firm-size distributions in the mid-Victorian era?"” Mendeley Data. http://dx.doi.org/10.17632/86xkkncmw3.1
DOI: 10.17632/9dnrc6s3ck
title: Real-time truck scheduling model for multiple-door cross-dock

description: This dataset is in regard to Chapter 5 of the PhD thesis titled "Real-time Truck Scheduling in Cross-Docking: A Hybrid Multi-Agent Simulation Framework". It is organised in 5 folders, each representing a door set as follows: - DootSet_1: 2-inbound and 2-outbound doors. H: high traffic, 280 pallets per hour. M: medium traffic, 140 pallets per hour. L: low traffic, 70 pallets per hour. - DootSet_2: 5-inbound and 5-outbound doors. H: high traffic, 680 pallets per hour. M: medium traffic, 340 pallets per hour. L: low traffic, 170 pallets per hour. - DootSet_3: 10-inbound and 10-outbound doors. H: high traffic, 1300 pallets per hour. - DootSet_4: 15-inbound and 15-outbound doors. H: high traffic, 1900 pallets per hour. - DootSet_5: 20-inbound and 20-outbound doors. H: high traffic, 2500 pallets per hour. The input data for each door set is defined in Excel files, each file containing the inbound trucks, outbound trucks and pallets data for one or more simulation instances. Excel files are named with the following convention: "<i>_" Where: - <i> represents the inbound traffic level (H for high, M for medium, L for low) as defined for each door set above - represents the outbound traffic level (H for high, M for medium, L for low) as defined for each door set above - represents the simulation instance(s). It may represent a single instance (for example "4") or a range of instances (for example 1-10 representing instances 1 to 10). For example, the file "LM_51-60" in the folder "DoorSet_1" represents the input data for instances 51 to 60, with low (70 pallets per hour) inbound and medium (140 pallets per hour) outbound traffic, for door set 1. Each Excel file contains the following worksheets: - inboundTrucks: list of inbound trucks (one per row) with the instance ID they are associated with, a unique ID and their corresponding arrival times since the start of simulation in minutes. - outboundTrucks: list of outbound trucks (one per row) with the instance ID they are associated with, a unique ID, their corresponding arrival times since the start of simulation in minutes, their due date in minutes since the start of simulation and their destination identified by an integer ranging from 1 to 3 (included). - pallets: list of pallets (one per row) with the instance ID they are associated with, a unique ID, the ID of the inbound truck in which they start the simulation, their due date in minutes since the start of simulation, their destination identified by an integer ranging from 1 to 3 (included) and their type identified by a letter A, B or C.</i></i>
DOI: 10.25402/epi.25295710.v1
title: Neural tube defects and epigenetics: role of histone post-translational histone modifications

description: Supplementary Table 1
DOI: 10.6084/m9.figshare.29128958.v1
title: Visual encounter and eDNA surveys for amphibians in the southwestern USA

description: Visual encounter and eDNA surveys for amphibians in the southwestern USA
DOI: 10.17632/5tm6jgxhg2
title: Data for "Ice Sheet Speed-dating: Using expert judgement to identify "good" simulations of the Last Glacial Maximum North American Ice Sheets"

description: Data for Short Communication "Ice Sheet Speed-dating: Using expert judgement to identify "good" simulations of the Last Glacial Maximum North American Ice Sheets" in review at Quaternary Science Reviews.

Abstract: After generating a large ensemble of palaeo ice sheet model runs, it is common to either rank the simulations, or classify each simulation as an acceptable match to observations or not. Both tasks require implicit human judgement, usually left to the discretion of the research authors. For instance, even numerical comparisons to reconstructions require human input on values for match thresholds and allowances for model-mismatch. We embrace the subjectivity of human judgement and calibrate an ice-sheet model by explicitly asking experts to identify simulations that are good enough. Expert judgement is made based on a set of features of the model output that is of interest (for example, margin shapes and regional ice volumes); where possible we also record such knowledge. By seeking the input of many experts, we obtain a community consensus that can be used to develop guidance to determine the quality of future simulations. This short communication describes our exercise in seeking expert classifications of simulations of the Last Glacial Maximum (LGM) North American Ice Sheets, discusses the lessons learnt, and suggests future analysis of the responses.
DOI: 10.6084/m9.figshare.21394908.v1
title: WES data from 286 diffuse gliomas under the 2021 WHO Classification of Tumors of the Central Nervous System

description: The output table with called SNVs per sample
DOI: 10.6084/m9.figshare.28497596.v1
title: Lung Cancer Detection - Dataset.zip

description: This dataset comprises medical images categorized into four distinct classes: Adenocarcinoma, Large Cell Carcinoma, Squamous Cell Carcinoma, and Normal. The dataset includes a total of 1,000 images, with 338 images labeled as Adenocarcinoma, 187 as Large Cell Carcinoma, 260 as Squamous Cell Carcinoma, and 215 as Normal. The images are primarily in PNG format (988 images) with a small fraction in JPG format (12 images). The average image dimensions are 258 pixels in height and 356 pixels in width.The dataset is structured into three subsets: training, validation, and test sets, ensuring proper evaluation and model generalization. Additionally, a separate category, referred to as "bad images," stores non-readable or corrupted images that are unsuitable for processing. The dataset provides a valuable resource for developing and evaluating deep learning models for lung cancer detection and classification.
DOI: 10.6084/m9.figshare.13259657.v1
title: Lung Mucosal MAIT Cell Heterogeneity

description: MAIT cell single-cell RNA-seq matrixMAIT cell bulk RNA-seq DEGs (HIV-negative)
DOI: 10.6084/m9.figshare.1585839.v2
title: Modeling of Solar Intensity via Markov Chains with Applications in Solar Energy Harvesting

description: Here, we propose a solar intensity model based on Markov chain. This model provides more accurate results for instantaneous solar intensity vector. We show that by increasing the order of Markov chain, we can achieve finer results in terms of maximum likelihood of the model matching the instantaneous data. Applying this model on the data collected from Rochester in upstate New York shows the effectiveness of our approach.
DOI: 10.6084/m9.figshare.21521142.v2
title: Measuring Compound Eye Optics with Microscope and MicroCT Images (Supplement)

description: Here are all of the resources used in creating the statistics and figures in the paper . We also include the figures in vector form. Folder Contents: You should find 5 zip files: benchmark_2D.zip -- images and code for benchmarking the ODA-2D on 4 example datasets d_melanogaster_data.zip -- images and code for benchmarking the ODA-2D on one dataset of 29 vinegar flies for comparisons within a species benchmark_3D.zip -- images and code for bechmarking the ODA-3D on 4 CT stacks of the eyes of 4 different species ODA-main.zip -- the version of the ODA used in the above folders revised_figs.zip -- the final figures generated, including the original vector files After unzipping these folders, you can find a README.md file explaining the contents of the folder and how to run the code. ODA Installation The 3 zipped datasets require the included version of the ODA package written in Python. To run this, make sure you have Python3.6+ and pip (the package managing module) installed. Then, unzip ODA-main.zip and navigate to that folder in the terminal. Once there, run the following: <em>pip install .</em> <br> This should install all of the dependencies needed to run the code in those 3 datasets. For more information, see the README.md files within each folder. If all else fails, contact Pablo at johnpaulcurrea@gmail.com.