cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6078/d1v10c
title: Chronic Arsenic Exposure Impairs Adaptive Thermogenesis in Male C57BL/6J Mice

description: The global prevalence of type 2 diabetes (T2D) has doubled since 1980.
 Human epidemiological studies support arsenic exposure as a risk factor
 for T2D, although the precise mechanism is unclear. We hypothesized that
 chronic arsenic ingestion alters glucose homeostasis by impairing adaptive
 thermogenesis, i.e. body heat production in cold environments. Arsenic is
 a pervasive environmental contaminant, with more than 200 million people
 worldwide currently exposed to arsenic-contaminated drinking water. Male
 C57BL/6J mice exposed to sodium arsenite in drinking water at 300 parts
 per billion (ppb) for 9 weeks experienced significantly decreased
 metabolic heat production when acclimated to chronic cold tolerance
 testing, as evidenced by indirect calorimetry, despite no change in
 physical activity. Arsenic exposure increased total fat mass, and
 unilocular lipid droplet size in both subcutaneous inguinal white adipose
 tissue (iWAT) and brown adipose tissue (BAT). This hypertrophy appeared to
 be specific to BAT and WAT, as no lipidosis was observed in liver. RNA
 sequencing analysis of iWAT indicated that arsenic dysregulated
 mitochondrial processes, including fatty acid metabolism. Western blotting
 confirmed that arsenic significantly decreased TOMM20 in both BAT and WAT,
 a correlate of mitochondrial abundance; PGC1A, a master regulator of
 mitochondrial biogenesis; and, CPT1B,the rate limiting step of fatty acid
 oxidation (FAO).  Our findings show that chronic arsenic
 exposure impacts the mitochondria of thermogenic tissues involved in
 energy expenditure and glucose regulation, providing novel mechanistic
 evidence for arsenic’s role in T2D development.
DOI: 10.5061/dryad.0828sr3
title: Data from: Conodont faunas across the Kasimovian–Gzhelian boundary (Late Pennsylvanian) in South China and implications for the selection of the stratotype for the base of the global Gzhelian Stage

description: The upper Pennsylvanian Naqing and Narao carbonate successions were
 deposited in intra-platform slope to basinal settings across the
 Kasimovian-Gzhelian boundary in Guizhou, South China. Conodont faunas
 comprise a mixture of the endemic taxa of the Idiognathodus luodianensis
 group and cosmopolitan species of the I. simulator group. The I.
 luodianensis group includes the new species I. fengtingensis, I.
 luodianensis, I. naqingensis and I. naraoensis. Platform landmark analysis
 demonstrates that the species of the I. luodianensis group differ in
 morphological features from co-occurring species of the I. simulator
 group. Both groups display similar increasing asymmetry in P1 element
 pairs across the Kasimovian-Gzhelian boundary, as recognized on the basis
 of the first occurrence of I. simulator. Many Kasimovian Idiognathodus
 species disappear and several Gzhelian species first appear with I.
 simulator, including two new species of Streptognathodus, S. nemyrovskae
 and S. zhihaoi. Just below the base of the Gzhelian, carbonate δ13C falls
 from 4‰ to 2‰ in both sections. The combination of an abrupt faunal
 turnover immediately above the prominent negative δ13C excursion might
 represent an oceanic event in South China, maybe recognizable on a global
 scale. One of these two South China sections may be the best location to
 place the GSSP for the base of the Gzhelian Stage.
description: Idiognathodus
 morphometric dataMorphometric data and
 analysis of the Idiognathodus P1 elements from the Naqing and Narao
 sectionsAppendix1.xlsx
DOI: 10.7291/d1cm1m
title: Fractional crystallization of a Martian magma ocean and formation of a thermochemical boundary layer at the base of the mantle

description: BurnMan and pMELTS outputs for simulations of fractionally crystallizing
 magma oceans on Mars.
DOI: 10.25338/b8ck5n
title: Measurements from the Fire Influence on Regional and Global Environments Experiment (FIREX) Fire Lab Mini Chamber Experiment

description: All experiments were conducted during the Fire Influence on Regional to
 Global Environments Experiment (FIREX) lab study, which took place at the
 Missoula Fire Sciences Lab in Missoula, MT, USA during November,
 2016. Experiments focused on refining our understanding of
 emissions and short timescale processing. The focus was on measuring fuels
 or combustion conditions that are characteristic of the western U.S. that
 may be under-sampled by the fire research community. Numerous
 types of biomass were combusted in a large chamber (12 x 12 x 19 m) and
 the smoke sampled to provide information on the physical, chemical, and
 optical properties of the resulting smoke (i.e., particulate and gas
 emissions). The general fuels types combusted included (exclusively or in
 combination): duff, dung, excelsior, straw, litter, untreated lumber,
 rotten debris, woody debris, shrub, herbaceous, and canopy biomass. Smoke
 from these burns was sampled into a small photochemical reaction chamber
 (the "mini Chamber"). The smoke from the mini Chamber was
 characterized using a variety of instrumentation: an Aerodyne high
 resolution aerosol mass spectrometer (HR-AMS) for non-refractory submicron
 particulate matter (NR-PM); an Aerodyne soot photometer aerosol
 mass spectrometer (SP-AMS) in "laser-only" mode, for refractory
 black carbon and NR-PM components mixed with BC; a DMT single
 particle soot photometer (SP2) for refractory black carbon;
 a Brechtel scanning electrical mobility sizer (SEMS), for
 particle size distributions; the UC Davis cavity
 ringdown/photoacoustic spectrometer (CRD-PAS), for particle absorption and
 extinction at 405 nm and 532 nm; a DMT PASS-3, for absorption and
 extinction at 781 nm; a thermodenuder, for heating particles to 300 degC
 for ~ 5 seconds; a proton transfer reaction mass spectrometer (PTRMS); and
 an iodide reagent ion chemical ionization mass spectrometer (I-CIMS). Not
 all measurements from all of these instruments are archived here; full
 data sets can be downloded from the National Oceanic and Atmospheric
 Administration
 at https://www.esrl.noaa.gov/csd/projects/firex/firelab/.  Measurements were made of both unprocessed (fresh) and photochemically aged particles and gases.   
description: Please see Lim et al., ACP (2019) (link) and Coggon et al., ACPD (2019) (link). Further descriptions will be provided in subsequent publications. 
description: Please see the read-me file. You are asked to discuss uses of
 this data with Chris Cappa or Jesse Kroll and to cite the appropriate
 papers that describe this dataset.
DOI: 10.25338/b87s43
title: Initial application of the noise-sorted scanning clustering algorithm to the analysis of composition-dependent organic aerosol thermal desorption measurements

description: The FIGAERO-CIMS (Filter Inlet for Gases and AEROsols + chemical
 ionization mass spectrometer) measures thermal desorption profiles for
 individual ions evolved from evaporation of organic aerosol
 components. Often, hundreds of individual thermograms are obtained,
 reflecting the compositional complexity of organic aerosol. We
 have developed a novel clustering algorithm, Noise-Sorted
 Scanning Clustering (NSSC), that provides a robust, reproducible analysis
 of the FIGAERO temperature-dependent mass spectral data. The NSSC allows
 for determination of thermal profiles for compositionally distinct
 clusters, increasing the accessibility and enhancing the interpretation of
 FIGAERO data. The potential of NSSC for analysis of FIGAERO-CIMS data is
 demonstrated via application to a suite of distinct experiments. A static
 version of the NSSC algorithm is archived here, and an evolving version at
 GitHub (doi: 10.5281/zenodo.3361796). The data used to test and
 develop the NSSC, and reported on in Li et al. (submitted to Atmospheric
 Measurement Techniques) and in Ziyue Li's dissertation at UC Davis,
 are archived here. The experiments took place at the Pacific Northwest
 National Laboratory. 
description: Please see Read Me file for details, and associated publications.
 Details of data collection and processing can be found in D'Ambro et
 al. (ACP, 2019) (link), D'Ambro et al. (ACS Earth Space Chem, 2019) (link) and in Li et al. (AMT, submitted). 
description: Please see Read Me file for details. Please contact Chris Cappa
 or Joel Thornton prior to use of this data or the NSSC algorithm. Any
 publications that wish to make use of this data or the NSSC algorithm must
 offer co-authorship.
DOI: 10.7280/d1j38b
title: UCI Libraries chatbot Transcripts (ANTswers)

description: ANTswers is an experimental chatbot that can answer questions about the UC
 Irvine Libraries. ANTswers is a web-based application, run on a remote
 library server and is accessed through a web interface page. ANTswers’
 personality and persona is based on the UCI mascot, Peter the Anteater.
 ANTswers responds to simple and short questions. The first link in a
 response opens in a preview window, all other links open in a new window.
 Each transaction is reviewed and a data form is filled out to track usage;
 such as date, time, answer rate, etc. Using the UAMCorpusTool3 an analysis
 of ANTswers transcripts were conducted for a 2019 ACRL Contributed
 Paper.  Transcripts with the corresponding replies removed are
 available here.  Names (if provided) have been removed for
 privacy.
description: Qualitative data - observational. Transcripts exported from
 ANTswers back-end system.
description: Chatbot reponses, names, demo transcripts, and spam transcripts
 removed.
DOI: 10.5281/zenodo.18245669
title: The Big Ban Theory: A Pre- and Post-Intervention Dataset of Online Content Moderation

description: The Big Ban Theory (TBBT) is a large-scale dataset designed to support systematic research on the effects of online content moderation interventions. The dataset includes 25 moderation interventions of varying type, severity, and scope (e.g., community bans, community quarantines, community bans with migration, and post removals). TBBT comprises more than 38 million comments, collected from Reddit communities affected by moderation interventions. For each intervention, the dataset provides standardized metadata together with pseudonymized user activity data covering the three months preceding and following the enforcement of the intervention. This pre- and post-intervention design enables consistent, comparable, and reproducible analyses of behavioral changes associated with moderation interventions.

This Dataset is described in the paper:

Cerulli, A., Cima, L., Tessa, B., Tardelli, S., & Cresci, S. (2026). The Big Ban Theory: A Pre-and Post-Intervention Dataset of Online Content Moderation Actions. arXiv preprint arXiv:2601.11128.

 If you use this data, please cite the original paper.

For additional details on the dataset structure and organization, please refer to the README file and the paper.
DOI: 10.5281/zenodo.18393453
title: The Big Ban Theory: A Pre- and Post-Intervention Dataset of Online Content Moderation

description: The Big Ban Theory (TBBT) is a large-scale dataset designed to support systematic research on the effects of online content moderation interventions. The dataset includes 25 moderation interventions of varying type, severity, and scope (e.g., community bans, community quarantines, community bans with migration, and post removals). TBBT comprises more than 38 million comments, collected from Reddit communities affected by moderation interventions. For each intervention, the dataset provides standardized metadata together with pseudonymized user activity data covering the three months preceding and following the enforcement of the intervention. This pre- and post-intervention design enables consistent, comparable, and reproducible analyses of behavioral changes associated with moderation interventions.

This Dataset is described in the paper:

Cerulli, A., Cima, L., Tessa, B., Tardelli, S., & Cresci, S. (2026). The Big Ban Theory: A Pre-and Post-Intervention Dataset of Online Content Moderation Actions. arXiv preprint arXiv:2601.11128.

 If you use this data, please cite the original paper.

For additional details on the dataset structure and organization, please refer to the README file and the paper.
DOI: 10.25338/b8330f
title: Exposure to light changes soil chemical properties

description: Assessment of the effect of UV and visible light on the chemical
 properties of soils. Raw data of chemical properties measured in a
 laboratory study of a soils exposed to light.
DOI: 10.15468/dl.ukhspj
title: Occurrence Download

description: A dataset containing 1382201 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "StateProvince is one of (Indiana, Illinois, Michigan, Wisconsin, Ohio, Pennsylvania, Maryland, Delaware, New York, Maine, Rhode Island, Vermont, MAssachusetts, New Hampshire, New Jersey, Connecticut, New Brunswick, Ontario, Nova Scotia, Quebec)",
 "TaxonKey is Coleoptera"
 ]
}

 The dataset includes 1382201 records from 267 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001862-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.2hm3d5g
title: Data from: A 45-year-old man with progressive insomnia, psychiatric and motor symptoms

description: A 45-year-old right-handed hypertensive man presented with a 6-month
 history of worsening neuropsychiatric symptoms, abnormal movements, and
 weight loss. He was hallucinating, apathetic, and having severe insomnia
 (total sleep duration of 1–2 hours/night). During sleep, his wife noted
 labored and sonorous breathing. Six months before admission, he led a
 healthy and active lifestyle.
description: Neuroimaging
 
 A – FDG-PET
 (Fluoro-2-deoxy-D-glucose Positron Emission Tomography) demonstrating
 asymmetric hypometabolism in thalami (left worse than right). B &
 C – Axial FLAIR (Fluid-Attenuated Inversion Recovery) sequences
 demonstrating an increased depth of sulci diffusely and ventricle size
 consistent with atrophy development over the course of 5
 months. Supplemental Figure
 1.pptx Neurohistopathology A – H&E (hematoxylin and eosin) staining from entorhinal cortex demonstrating mild spongiform changes (vacuolization – black arrows). There were no spongiform changes present in other slides. B – H&E staining from left thalamus demonstrating neuronal loss and lack of spongiform changes. C – Immunohistochemistry against PrP in left thalamus demonstrating typical weak and patchy staining pattern seen in FFI. D – Western Blot against Proteinase Resistant Prion Protein (PrPsc) using proteinase K digestion protocol in frontal lobe tissue. The first lane (patient) demonstrates high levels of PrPsc resistant to proteinase K digestion as typically seen in FFI. Second and third lanes represent controls (type 1 PrPsc and type 2 PrPsc, respectively). Supplemental Figure 2.pptx
DOI: 10.7280/d17m2f
title: Data from: Insensitivity of the cloud response to surface warming under radical changes to boundary layer turbulence and cloud microphysics: results from the ultraparameterized CAM

description: This data set contains the simulation outputs used in the study summarized
 below: We study the cloud response to a +4K surface warming in a new
 multiscale climate model that uses enough interior resolution to begin
 explicitly resolving boundary layer turbulence (i.e.,
 ultraparameterization or UP). UP's predictions are compared against
 those from standard superparameterization (SP). The mean cloud radiative
 effect feedback turns out to be remarkably neutral across all of our
 simulations, despite some radical changes in both cloud microphysical
 parameter settings and cloud‐resolving model grid resolution. The overall
 low cloud response to warming is a positive low cloud feedback over land,
 a negative feedback (driven by cloud optical depth increase) at high
 latitudes, and weak feedback over the low‐latitude oceans. The most
 distinct effects of UP result from tuning decisions impacting
 high‐latitude cloud feedback. UP's microphysics is tuned to optimize
 the model present‐day, top‐of‐atmosphere radiation fluxes against CERES
 observations, by lowering the cloud ice‐liquid phase shift temperature
 ramp, adjusting the ice/liquid autoconversion rate, and increasing the ice
 fall speed. This reduces high‐latitude low cloud amounts and damps the
 optical depth feedback at high latitudes, leading to a slightly more
 positive global cloud feedback compared to SP. A sensitivity test that
 isolates these microphysical impacts from UP's grid resolution
 confirms that the microphysical settings are mostly responsible for the
 differences between SP and UP cloud feedback.
description: This data set contains simulation data from "Insensitivity
 of the cloud response to surface warming under radical changes to boundary
 layer turbulence and cloud microphysics: results from the
 ultraparameterized CAM." All instructions and
 information are provided in the attached Readme.txt file. Please download
 the latest version for the full data set.
DOI: 10.5061/dryad.364vk23
title: Data from: Oncogene inference optimization using constraint-based modelling incorporated with protein expression in normal and tumour tissues

description: Cancer cells are known to exhibit unusual metabolic activity and yet, few
 metabolic cancer driver genes are known. Genetic alterations and
 epigenetic modi cations of cancer cells result in the abnormal regulation
 of cellular metabolic pathways that are different when compared to normal
 cells. Such a metabolic reprogramming can be simulated using
 constraint-based modelling approaches towards predicting oncogenes. We
 introduced the tri-level optimization problem to use the metabolic
 reprogramming towards inferring oncogenes. The algorithm incorporated
 Recon 2.2 network with the Human Protein Atlas to reconstruct genome-scale
 metabolic network models of the tissue-speci fic cells at normal and
 cancer states, respectively. Such reconstructed models were applied to
 build the templates of the metabolic reprogramming between normal and
 cancer cell metabolism. The inference optimization problem was formulated
 to use the templates as a measure towards predicting oncogenes. The nested
 hybrid differential evolution algorithm was applied to solve the problem
 to overcome solving difficulty for transferring the inner optimization
 problem into the single one. Head and neck squamous cells were applied as
 a case study to evaluate the algorithm. We detected 13 of the top ranked
 one-hit dysregulations and 17 of the top ranked two-hit oncogenes with
 high similarity ratios to the templates. According literature survey, most
 inferred oncogenes are consistent with the observation in various tissues.
 Furthermore, the inferred oncogenes were highly connected with the
 TP53/AKT/IGF/MTOR signalling pathway through PTEN, which is one of the
 most frequently detected tumour suppressor genes in human cancer.
description: TLOP
 codeThe oncoenzyme inference
 framework integrated the TLOP and the NHDE algorithm was implemented in
 the General Algebraic modelling System (GAMS)
 environment.TLOP.rar
DOI: 10.5061/dryad.sk6mr5v
title: Data from: Scrambler therapy improves pain in neuromyelitis optica: a randomized controlled trial

description: Objective: The primary objective aimed to determine if Scrambler therapy
 is an effective, acceptable and feasible treatment of persistent central
 neuropathic pain in patients with neuromyelitis optica spectrum disorder
 (NMOSD). The secondary objective explored the effect of Scrambler therapy
 on co-occurring symptoms. Methods: We conducted a randomized single blind,
 sham-controlled trial in patients with NMOSD who have central neuropathic
 pain using Scrambler therapy for 10 consecutive weekdays. Pain severity,
 pain interference, anxiety, depression and sleep disturbance were assessed
 at baseline, end of treatment, and at 30- and 60-day follow-up. Results:
 Twenty-two patients (11 per arm) were enrolled into and completed this
 trial. The median baseline NRS pain score decreased from 5.0 to 1.5
 following 10 days of treatment with Scrambler therapy, whereas the median
 NRS score did not significantly decrease in the sham arm. Depression was
 also reduced in the treatment arm, and anxiety was decreased in a subset
 of patients who responded to treatment. These symptoms were not impacted
 in the sham arm. The safety profiles were similar between groups.
 Conclusions: Scrambler therapy is an effective, feasible and safe
 intervention for central neuropathic pain in patients with NMOSD.
 Decreasing pain with Scrambler therapy may additionally improve depression
 and anxiety. Clinicaltrials.gov identifier NCT03452176 Classification of
 Evidence This study provides Class II evidence for patients with NMOSD and
 persistent central neuropathic pain that Scrambler therapy significantly
 reduces pain.
description: Table e-1: STROBE
 checklist Table e-2: Adverse
 Events
DOI: 10.5061/dryad.m1b1k35
title: Data from: Temperature and storage time strongly affect the germination success of perennial Euphorbia species in Mediterranean regions

description: This study aims to explore the effect of environmental factors
 (temperature,light, storage time) on germination response and dormancy
 patterns in eight Mediterranean native wildplants, belonging to the
 Euphorbia L. genus. In detail, we considered E. amygdaloides subsp.
 arbuscula, E. bivonae subsp. bivonae, E. ceratocarpa, E. characias, E.
 dendroides, E. melapetala, E. myrsinites, E. rigida. We collected seeds
 from natural plant populations and performed germination assays in
 climatic chambers at seven constant temperatures (from 5 to 35°C, with 5°C
 increments), and four fluctuating temperature regimes (8/15, 8/20, 8/25,
 8/30°C, with a 12/12 h thermoperiod). Germination assays were set up both
 in dark (D) and in light/dark conditions (L/D, 12/12 h photoperiod), after
 Short and Long seed Storage (SS around 30 days and LS around 150 days).
 For all these species, except E. amygdaloides subsp. arbuscula, results
 show that the final germinated proportions were improved by a long storage
 period (&gt; 150 days), which supports the existence of non-deep
 physiological dormancy. Optimal temperature levels ranged from 14.3 to
 21.3°C, base temperatures ranged from 5.6 to 12.1°C, while ceiling
 temperatures from 25.6 to 34.7°C. For none of these species, germinations
 were favoured by an alternating daily temperature regime, while in several
 instances, germinations were quicker and more complete in darkness, than
 in an alternating light/dark regime. In some instances, extreme
 temperature levels (5° and 30°C) induced dormancy and germinations did not
 resume when seeds where exposed at optimal temperature levels. Results are
 discussed in terms of the dynamics of emergences and how this might be
 affected by climate changes.
description: Temperature and storage
 time strongly affect the germination success of perennial Euphorbia
 species in Mediterranean regionsThe dataset contains the
 results of germination assays performed with eight species of the
 Euphorbia genus, after two storage times (1: short storage, less then 150
 days; 2: long storage: more than 1500 days), at several temperatures, wo
 temperature regimes (constant daily temperature: COST; alternating daily
 temperature: ALT) and two light conditions (1: continuous darkness; 2:
 light/dark 12h photoperiod).Euphorbia_s.csv