cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18364077
title: PSCount: Dataset and Pre-trained Model for Polystyrene Particle Counting

description: This dataset accompanies the PSCount software for automated polystyrene particle counting in brightfield microscopy images.

Contents:- Training data: 19 labeled images with point annotations and generated masks- Test data: 24 images with ground truth (Set A: point annotations, Set B: CSV)- Pre-trained model: Fine-tuned Cellpose-SAM model- Output: Prediction results and probability maps

The fine-tuned model achieves MAE of 2.1 particles per image, representing a 97% reduction in counting error compared to the base Cellpose-SAM model.

Code available at: https://github.com/seoleuns/pscount
DOI: 10.6084/m9.figshare.31147348
title: Riboflavin intake and kidney health: population evidence and mechanistic insights from NHANES and molecular docking analyses

description: Chronic kidney disease (CKD) constitutes a significant global public health challenge, with emerging evidence suggesting that riboflavin may confer renoprotective effects. However, the association between dietary riboflavin intake and CKD risk remains inadequately elucidated. To investigate this, we analyzed National Health and Nutrition Examination Survey (NHANES) 2005–2018 datasets using weighted multivariate logistic regression, interaction testing, stratified subgroup analyses, and curve fitting. Additionally, network pharmacology and molecular docking simulations were employed to identify and validate potential therapeutic targets. Our results showed that patients with CKD exhibited significantly lower riboflavin intake than their non-CKD counterparts (1.98 vs. 2.21 mg/d, <i>p</i> &lt; 0.001). After full adjustment, each 1 mg/d increment in riboflavin intake was associated with an 18.8% reduced risk of CKD (adjusted OR = 0.812, 95% CI: 0.686–0.962). Individuals in the highest intake quartile had a 42.7% lower risk compared to the lowest quartile (adjusted OR = 0.573, 95% CI: 0.400–0.822). A non-linear dose-response relationship was observed, characterized by an inflection point at 1.66 mg/d, indicating a more pronounced protective effect at lower intake levels. Mechanistic investigations suggested that riboflavin’s benefits may be mediated through interactions with key targets like caspase-3 (CASP3), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and matrix metallopeptidase 9 (MMP9), implicating apoptotic and metabolic pathways. In conclusion, dietary riboflavin intake is inversely associated with CKD risk, particularly at lower concentrations, and strategic augmentation of intake represents a promising dietary intervention for CKD prevention and management.
DOI: 10.6084/m9.figshare.31147348.v1
title: Riboflavin intake and kidney health: population evidence and mechanistic insights from NHANES and molecular docking analyses

description: Chronic kidney disease (CKD) constitutes a significant global public health challenge, with emerging evidence suggesting that riboflavin may confer renoprotective effects. However, the association between dietary riboflavin intake and CKD risk remains inadequately elucidated. To investigate this, we analyzed National Health and Nutrition Examination Survey (NHANES) 2005–2018 datasets using weighted multivariate logistic regression, interaction testing, stratified subgroup analyses, and curve fitting. Additionally, network pharmacology and molecular docking simulations were employed to identify and validate potential therapeutic targets. Our results showed that patients with CKD exhibited significantly lower riboflavin intake than their non-CKD counterparts (1.98 vs. 2.21 mg/d, <i>p</i> &lt; 0.001). After full adjustment, each 1 mg/d increment in riboflavin intake was associated with an 18.8% reduced risk of CKD (adjusted OR = 0.812, 95% CI: 0.686–0.962). Individuals in the highest intake quartile had a 42.7% lower risk compared to the lowest quartile (adjusted OR = 0.573, 95% CI: 0.400–0.822). A non-linear dose-response relationship was observed, characterized by an inflection point at 1.66 mg/d, indicating a more pronounced protective effect at lower intake levels. Mechanistic investigations suggested that riboflavin’s benefits may be mediated through interactions with key targets like caspase-3 (CASP3), Erb-B2 receptor tyrosine kinase 2 (ERBB2), and matrix metallopeptidase 9 (MMP9), implicating apoptotic and metabolic pathways. In conclusion, dietary riboflavin intake is inversely associated with CKD risk, particularly at lower concentrations, and strategic augmentation of intake represents a promising dietary intervention for CKD prevention and management.
DOI: 10.15468/dl.uzjh7j
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Biswarea tonglensis"
 ]
}

 The dataset includes 48 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011766-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hj83a7
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kazakhstan",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus robur"
 ]
}

 The dataset includes 78 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011767-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h2yefj
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kazakhstan",
 "Geometry POLYGON((51.35277 35.74421,87.64723 35.74421,87.64723 50.25579,51.35277 50.25579,51.35277 35.74421))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhaphidophyton regelii"
 ]
}

 The dataset includes 29 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011768-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18372675
title: Threshold Analysis of Tobin's Q on Corporate Financial Transparency: Evidance form an Emerging Market
DOI: 10.5281/zenodo.18372676
title: Threshold Analysis of Tobin's Q on Corporate Financial Transparency: Evidance form an Emerging Market
DOI: 10.6084/m9.figshare.31147237
title: Code and data used in "Forest disturbances intensify land surface warming across Europe"

description: This is the code and data used in the study "Forest disturbances intensify land surface warming across Europe"<br><br>AuthorsYang Su a, b, c, Yidi Xu b, Xianglin Zhang c, David Makowski d, Agnes Pellissier-tanon b, Saverio Francini e, Tianqi Shi b, Ke Yu b, Siyu Liu f, Haotian Chen g, c, Haoruo Li h, Jinfeng Chang i, Songchao Chen i, Chaohui Yin j, Nikola Besic k, l, Martin Brandt f, Alba Viana-Soto m, Katja Kowalski n, Cornelius Senf m, Alexandre d'Aspremont a, Philippe Ciais bAffiliationsa CNRS & Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, Francec Université Paris-Saclay, AgroParisTech, INRAE, UMR ECOSYS, 91120 Palaiseau, Franced Université Paris-Saclay, AgroParisTech, INRAE, Unit Applied Mathematics and Computer Science (MIA 518), 91120 Palaiseau, Francee Department of Science and Technology of Agriculture and Environment (DISTAL), University of Bologna, 40126 Bologna, Italyf Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmarkg Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs of China, 100081 Beijing, Chinah State Key Laboratory of Efficient Utilization of Arable Land in China，the Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, 100081 Beijing, PR Chinai College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, Chinaj School of Resource and Environment, Henan Agricultural University, 450046 Zhengzhou, Chinak Université de Lorraine, Géodata Paris, IGN, LIF, F-54000, Nancy, Francel Université Gustave Eiffel, Géodata Paris, IGN, Laboratoire d’inventaire forestier, F-54000, Nancy, Francem School of Life Sciences, Earth Observation for Ecosystem Management, Technical University of Munich, Freising, Germanyn Geography Department, Humboldt-Universität zu Berlin, Berlin, GermanyCorresponding AuthorYang Su yang.su@ens.fr +33 1 89 10 07 67 École Normale Supérieure – PSLYidi Xu yidi.xu@lsce.fr +33 6 71 68 25 78 LSCE<br>
DOI: 10.6084/m9.figshare.31147237.v1
title: Code and data used in "Forest disturbances intensify land surface warming across Europe"

description: This is the code and data used in the study "Forest disturbances intensify land surface warming across Europe"<br><br>AuthorsYang Su a, b, c, Yidi Xu b, Xianglin Zhang c, David Makowski d, Agnes Pellissier-tanon b, Saverio Francini e, Tianqi Shi b, Ke Yu b, Siyu Liu f, Haotian Chen g, c, Haoruo Li h, Jinfeng Chang i, Songchao Chen i, Chaohui Yin j, Nikola Besic k, l, Martin Brandt f, Alba Viana-Soto m, Katja Kowalski n, Cornelius Senf m, Alexandre d'Aspremont a, Philippe Ciais bAffiliationsa CNRS & Département d'Informatique, École Normale Supérieure – PSL, 45 Rue d'Ulm, 75005 Paris, France b Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, 91190 Gif-sur-Yvette, Francec Université Paris-Saclay, AgroParisTech, INRAE, UMR ECOSYS, 91120 Palaiseau, Franced Université Paris-Saclay, AgroParisTech, INRAE, Unit Applied Mathematics and Computer Science (MIA 518), 91120 Palaiseau, Francee Department of Science and Technology of Agriculture and Environment (DISTAL), University of Bologna, 40126 Bologna, Italyf Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmarkg Institute of Crop Sciences, Chinese Academy of Agricultural Sciences / Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs of China, 100081 Beijing, Chinah State Key Laboratory of Efficient Utilization of Arable Land in China，the Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, 100081 Beijing, PR Chinai College of Environmental and Resource Sciences, Zhejiang University, 310058 Hangzhou, Chinaj School of Resource and Environment, Henan Agricultural University, 450046 Zhengzhou, Chinak Université de Lorraine, Géodata Paris, IGN, LIF, F-54000, Nancy, Francel Université Gustave Eiffel, Géodata Paris, IGN, Laboratoire d’inventaire forestier, F-54000, Nancy, Francem School of Life Sciences, Earth Observation for Ecosystem Management, Technical University of Munich, Freising, Germanyn Geography Department, Humboldt-Universität zu Berlin, Berlin, GermanyCorresponding AuthorYang Su yang.su@ens.fr +33 1 89 10 07 67 École Normale Supérieure – PSLYidi Xu yidi.xu@lsce.fr +33 6 71 68 25 78 LSCE<br>
DOI: 10.15468/dl.z4auac
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kazakhstan",
 "Geometry POLYGON((52.35277 35.74421,88.64723 35.74421,88.64723 50.25579,52.35277 50.25579,52.35277 35.74421))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rhaponticum aulieatense"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011769-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26730892
title: Additional file 3 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 3: Supplementary Table 1. NCA PK parameter estimates for capmatinib and crizotinib in mouse plasma and brain. See Methods – Pharmacokinetics section for a description of abbreviations. Terminal phase parameters for crizotinib in brain could not be estimated and were not reported.
DOI: 10.6084/m9.figshare.26730892.v2
title: Additional file 3 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 3: Supplementary Table 1. NCA PK parameter estimates for capmatinib and crizotinib in mouse plasma and brain. See Methods – Pharmacokinetics section for a description of abbreviations. Terminal phase parameters for crizotinib in brain could not be estimated and were not reported.
DOI: 10.6084/m9.figshare.26730895
title: Additional file 4 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 4: Supplementary Table 2. EC50 and EC90 values of capmatinib (cap) and crizotinib (cri) following 3-day dose response assays. To calculate unbound EC50 and EC90 values, total values were multiplied with unbound drug fractions in culture media (Table 1).
DOI: 10.6084/m9.figshare.26730895.v2
title: Additional file 4 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 4: Supplementary Table 2. EC50 and EC90 values of capmatinib (cap) and crizotinib (cri) following 3-day dose response assays. To calculate unbound EC50 and EC90 values, total values were multiplied with unbound drug fractions in culture media (Table 1).
DOI: 10.6084/m9.figshare.26730895.v1
title: Additional file 4 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 4: Supplementary Table 2. EC50 and EC90 values of capmatinib (cap) and crizotinib (cri) following 3-day dose response assays. To calculate unbound EC50 and EC90 values, total values were multiplied with unbound drug fractions in culture media (Table 1).
DOI: 10.6084/m9.figshare.26730904
title: Additional file 7 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 7: Supplementary Table 3. Bioluminescence signals of in vivo trials.
DOI: 10.6084/m9.figshare.26730904.v2
title: Additional file 7 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 7: Supplementary Table 3. Bioluminescence signals of in vivo trials.
DOI: 10.6084/m9.figshare.26730904.v1
title: Additional file 7 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 7: Supplementary Table 3. Bioluminescence signals of in vivo trials.
DOI: 10.6084/m9.figshare.26730922
title: Additional file 13 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 13: Supplementary Table 4. Genesets from heatmap in Fig. 7b.  List of genes within the geneset “DNA REPAIR_7” as part of “baderlab pathways 2019”, which form the heatmap in Fig. 7b ordered from top to bottom.
DOI: 10.6084/m9.figshare.26730922.v2
title: Additional file 13 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 13: Supplementary Table 4. Genesets from heatmap in Fig. 7b.  List of genes within the geneset “DNA REPAIR_7” as part of “baderlab pathways 2019”, which form the heatmap in Fig. 7b ordered from top to bottom.
DOI: 10.6084/m9.figshare.26730925
title: Additional file 14 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 14: Supplementary Table 5. EC50 and EC90 values of capmatinib (cap), crizotinib (cri) and cabozantinib (cabo) following 3-day dose response assays. To calculate unbound EC50 and EC90 values, total values were multiplied with unbound drug fractions in culture media (Table 1).
DOI: 10.6084/m9.figshare.26730925.v2
title: Additional file 14 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 14: Supplementary Table 5. EC50 and EC90 values of capmatinib (cap), crizotinib (cri) and cabozantinib (cabo) following 3-day dose response assays. To calculate unbound EC50 and EC90 values, total values were multiplied with unbound drug fractions in culture media (Table 1).
DOI: 10.6084/m9.figshare.26730931.v2
title: Additional file 16 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 16: Supplementary Table 6.Differential expression analysis results for TRIM24-MET-i and TRIM24-MET-r drug treatments and TFG-MET capmatinib treatment.
DOI: 10.6084/m9.figshare.26730925.v1
title: Additional file 14 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 14: Supplementary Table 5. EC50 and EC90 values of capmatinib (cap), crizotinib (cri) and cabozantinib (cabo) following 3-day dose response assays. To calculate unbound EC50 and EC90 values, total values were multiplied with unbound drug fractions in culture media (Table 1).
DOI: 10.6084/m9.figshare.26730931
title: Additional file 16 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 16: Supplementary Table 6.Differential expression analysis results for TRIM24-MET-i and TRIM24-MET-r drug treatments and TFG-MET capmatinib treatment.
DOI: 10.6084/m9.figshare.26730934
title: Additional file 17 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 17: Supplementary Table 7. Full GSEA results with select categories of MSigDB genesets for TFG-MET PD cohort treated with capmatinib.
DOI: 10.6084/m9.figshare.26730934.v2
title: Additional file 17 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 17: Supplementary Table 7. Full GSEA results with select categories of MSigDB genesets for TFG-MET PD cohort treated with capmatinib.
DOI: 10.6084/m9.figshare.26730937
title: Additional file 18 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 18: Supplementary Table 8. Full GSEA results with select categories of MSigDB genesets for TRIM24-MET-i drug treatments.
DOI: 10.6084/m9.figshare.26730937.v2
title: Additional file 18 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 18: Supplementary Table 8. Full GSEA results with select categories of MSigDB genesets for TRIM24-MET-i drug treatments.
DOI: 10.6084/m9.figshare.26730940
title: Additional file 19 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 19: Supplementary Table 9. Full GSEA results with select categories of MSigDB genesets for TRIM24-MET-r drug treatments.
DOI: 10.6084/m9.figshare.26730937.v1
title: Additional file 18 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 18: Supplementary Table 8. Full GSEA results with select categories of MSigDB genesets for TRIM24-MET-i drug treatments.
DOI: 10.6084/m9.figshare.26730940.v2
title: Additional file 19 of Capmatinib is an effective treatment for MET-fusion driven pediatric high-grade glioma and synergizes with radiotherapy

description: Additional file 19: Supplementary Table 9. Full GSEA results with select categories of MSigDB genesets for TRIM24-MET-r drug treatments.
DOI: 10.5281/zenodo.18362320
title: Dataset: Divergent drivers of the spatial variation in greenhouse gas concentrations and fluxes along the Rhine River and the Mittelland Canal in Germany

description: This dataset comprises measured concentrations of greenhouse gases (GHGs) and N₂, along with their corresponding fluxes. Fluxes were estimated using gas transfer velocities derived from wind speed data. Measurements were collected at 23 sites along the Rhine River and the Mittelland Canal during the summer season of 2023.
DOI: 10.5281/zenodo.18372710
title: Dataset: Divergent drivers of the spatial variation in greenhouse gas concentrations and fluxes along the Rhine River and the Mittelland Canal in Germany

description: This dataset comprises measured concentrations of greenhouse gases (GHGs) and N₂, along with their corresponding fluxes. Fluxes were estimated using gas transfer velocities derived from wind speed data. Measurements were collected at 23 sites along the Rhine River and the Mittelland Canal during the summer season of 2023.
DOI: 10.15468/dl.y5gyf3
title: Occurrence Download

description: A dataset containing 3248 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "Geometry POLYGON((-58 -15,-53 -15,-53 -10,-58 -10,-58 -15))",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Noctuidae, Apis, Molossidae, Phyllostomidae, Pitangus sulphuratus, Falco sparverius, Caracara plancus, Tyrannus melancholicus, Collembola, Agaricomycetes)",
 "Year 1970-2026"
 ]
}

 The dataset includes 3248 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011771-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t426nu
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation, Specimen)",
 "Geometry POLYGON((-115.74 48.47,-95.63 48.47,-95.63 60.39,-115.74 60.39,-115.74 48.47))",
 "HasCoordinate is true",
 "License is one of (CC-BY-NC 4.0, CC-BY 4.0, CC0 1.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Ochrophyta"
 ]
}

 The dataset includes 144 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011773-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18338076
title: Beyond the Training Domain: Robust Generative Transition State Models for Unseen Chemistry

description: Pretrained models as well as the curated datasets.



AEFM: configs and database to train and run inference using adaptive equilibrium flow matching.

OAReactDiff: codebase and training script to finetune the published OAReactDiff checkpoint with the new embedding layer, as well as with the newly developed self-supervised scheme.

ReactOT: codebase and training/inference script to train and sample with ReactOT

checkpoint_: Checkpoints for all models used in the work