cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/g6j4bc3m7v.2
title: QTNano - Single-atom catalysts on ceria substrates: Exploring cluster and surface effects on methane activation, Molecular Catalysis, 564, 114318, (2024)

description: Raw data of the published paper - https://www.sciencedirect.com/science/article/pii/S2468823124005017
DOI: 10.17632/g6j4bc3m7v.3
title: QTNano - Single-atom catalysts on ceria substrates: Exploring cluster and surface effects on methane activation, Molecular Catalysis, 564, 114318, (2024)

description: Raw data of the published paper - https://www.sciencedirect.com/science/article/pii/S2468823124005017
DOI: 10.17632/86n5bcpm46.1
title: Datasets used to train and test prediction model to predict scores in terms of SDG 7 realization for 2010-2020

description: The datasets used in this research work refer to the aims of Sustainable Development Goal 7. These datasets were used to train and test machine learning model based on artificial neural network and other machine learning regression models for solving the problem of prediction scores in terms of SDG 7 aims realization. Train dataset was created based on data from 2010 to 2019 and includes 300 samples. Test dataset includes 30 samples. Sources data from 2010 to 2020 are available in 11 XLSX and CSV files. Train and test datasets are available in XLSX and CSV files. Detailed description of data is available in PDF file.
DOI: 10.15468/dl.hysncv
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ghana",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Vigna speciosa (Kunth) Verdc."
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007306-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11245297
title: ExpertSegmentation: Sample datasets for segmentation of microscopy with domain-informed targets via custom loss

description: Sample datasets for submission to NeurIPS 2024 titled ExpertSegmentation: Segmentation for microscopy with domain-informed targets via custom loss. Hand-labels were generated using Ilastik. Files include:



NMC_3D: 3D, 2-phase, microCT image of a Lithium-ion battery LiNiMnCoO2 electrode

NMC_3D_Labels: Hand labels for NMC_3D volume.

NMC_2D: 2D, 4-phase, SEM image of a Lithium-ion battery LiNiMnCoO2 electrode cross-section

NMC_2D_Labels: Hand labels for NMC_2D image.

Graphite_3D: 3D, 3-phase, microCT image of a Laser-ablated lithium-ion battery graphite electrode

Graphite_3D_Labels: Hand labels for Graphite_3D volume.

PEMFC_3D: 3D, 5-phase, microCT image of a Polymer Electrolyte Membrane Fuel Cell (PEMFC)

PEMFC_3D_Labels: Hand labels for PEMFC_3D volume.


See references for dataset sources.
DOI: 10.5281/zenodo.11245298
title: ExpertSegmentation: Sample datasets for segmentation of microscopy with domain-informed targets via custom loss

description: Sample datasets for submission to NeurIPS 2024 titled ExpertSegmentation: Segmentation for microscopy with domain-informed targets via custom loss. Files include:



NMC_3D: 3D, 2-phase, microCT image of a Lithium-ion battery LiNiMnCoO2 electrode

NMC_2D: 2D, 4-phase, SEM image of a Lithium-ion battery LiNiMnCoO2 electrode cross-section

Graphite_3D: 3D, 3-phase, microCT image of a Laser-ablated lithium-ion battery graphite electrode

PEMFC_3D: 3D, 5-phase, microCT image of a Polymer Electrolyte Membrane Fuel Cell (PEMFC)


See references for dataset sources.
DOI: 10.5281/zenodo.14984135
title: ExpertSegmentation: Sample datasets for segmentation of microscopy with domain-informed targets via custom loss

description: Sample datasets for submission to NeurIPS 2024 titled ExpertSegmentation: Segmentation for microscopy with domain-informed targets via custom loss. Hand-labels were generated using Ilastik. Files include:



NMC_3D: 3D, 2-phase, microCT image of a Lithium-ion battery LiNiMnCoO2 electrode

NMC_3D_Labels: Hand labels for NMC_3D volume.

NMC_2D: 2D, 4-phase, SEM image of a Lithium-ion battery LiNiMnCoO2 electrode cross-section

NMC_2D_Labels: Hand labels for NMC_2D image.

Graphite_3D: 3D, 3-phase, microCT image of a Laser-ablated lithium-ion battery graphite electrode

Graphite_3D_Labels: Hand labels for Graphite_3D volume.

PEMFC_3D: 3D, 5-phase, microCT image of a Polymer Electrolyte Membrane Fuel Cell (PEMFC)

PEMFC_3D_Labels: Hand labels for PEMFC_3D volume.


See references for dataset sources.
DOI: 10.6084/m9.figshare.28550579
title: Data

description: Role of Sirtuin 6 in mesenchymal stem cell-mediated regeneration in diabetic ischemic. Background: Mesenchymal Stem Cells (MSCs) offer tremendous regenerative and therapeutic potential in an injured tissue in diabetic conditions. But the functional efficiency of MSCs has been shown to decrease with diabetes and aging. This reduces the potential of cell-based therapy in diabetic patients. Recent studies have established the role of sirtuin family proteins in metabolic disease, inflammation, longevity, and DNA repair. However, their potential to be used as a therapeutic target in cardiomyopathy and heart failure remain unexplored. Objective: To investigate the role of Sirtuin 6 (SIRT6) in mesenchymal stem cells senescence and cardiac regeneration. Methods and Results: We performed genomics and proteomics in the human control and diabetic heart tissues collected from the heart transplant. Human MSCs were treated with high glucose and mouse MSCs were derived from the bone marrow of diabetic db/db mice for this study. We found that SIRT6 expression is reduced in the myocardium of diabetic patients compared to non-diabetic controls. The SIRT6 expression decreased in high glucose-treated human MSCs compared to mannitol-treated control MSCs as well as in db/db mice MSCs compared to control mice MSCs. These high glucose-treated human MSCs and db/db mice MSCs showed increased expression of senescence and inflammation-related markers like that in diabetic human myocardium. Furthermore, we used small interfering RNA (SIRT6-siRNA) in human MSCs to knock down the SIRT6 gene and validated our findings. Indeed, the knockdown of SIRT6 promoted senescence and inflammation in those MSCs. Finally, we used adeno-associated viruses (AAV-SIRT6) to overexpress SIRT6 in MSCs treated with high glucose and performed proteomic analysis. SIRT6 overexpression in high glucose-treated MSCs reduced the expression of senescence and inflammation related genes and proteins. Conclusion: Our results highlight the importance of SIRT6 in diabetic myocardium and its role in balancing senescence and inflammation in MSCs. The validation of such in vitro studies in a diabetic mouse model (db/db) along with transplantation of SIRT6 overexpressed db/db MSCs into the myocardium of diabetic mice could open doors to successfully use MSC therapy in diabetic patients in the future.
DOI: 10.6084/m9.figshare.28550579.v1
title: Data

description: Role of Sirtuin 6 in mesenchymal stem cell-mediated regeneration in diabetic ischemic. Background: Mesenchymal Stem Cells (MSCs) offer tremendous regenerative and therapeutic potential in an injured tissue in diabetic conditions. But the functional efficiency of MSCs has been shown to decrease with diabetes and aging. This reduces the potential of cell-based therapy in diabetic patients. Recent studies have established the role of sirtuin family proteins in metabolic disease, inflammation, longevity, and DNA repair. However, their potential to be used as a therapeutic target in cardiomyopathy and heart failure remain unexplored. Objective: To investigate the role of Sirtuin 6 (SIRT6) in mesenchymal stem cells senescence and cardiac regeneration. Methods and Results: We performed genomics and proteomics in the human control and diabetic heart tissues collected from the heart transplant. Human MSCs were treated with high glucose and mouse MSCs were derived from the bone marrow of diabetic db/db mice for this study. We found that SIRT6 expression is reduced in the myocardium of diabetic patients compared to non-diabetic controls. The SIRT6 expression decreased in high glucose-treated human MSCs compared to mannitol-treated control MSCs as well as in db/db mice MSCs compared to control mice MSCs. These high glucose-treated human MSCs and db/db mice MSCs showed increased expression of senescence and inflammation-related markers like that in diabetic human myocardium. Furthermore, we used small interfering RNA (SIRT6-siRNA) in human MSCs to knock down the SIRT6 gene and validated our findings. Indeed, the knockdown of SIRT6 promoted senescence and inflammation in those MSCs. Finally, we used adeno-associated viruses (AAV-SIRT6) to overexpress SIRT6 in MSCs treated with high glucose and performed proteomic analysis. SIRT6 overexpression in high glucose-treated MSCs reduced the expression of senescence and inflammation related genes and proteins. Conclusion: Our results highlight the importance of SIRT6 in diabetic myocardium and its role in balancing senescence and inflammation in MSCs. The validation of such in vitro studies in a diabetic mouse model (db/db) along with transplantation of SIRT6 overexpressed db/db MSCs into the myocardium of diabetic mice could open doors to successfully use MSC therapy in diabetic patients in the future.
DOI: 10.15468/dl.zdhq9w
title: Occurrence Download

description: A dataset containing 107006371 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is iNaturalist Research-grade Observations"
 ]
}

 The dataset includes 107006371 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007361-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ykbmtb
title: Occurrence Download

description: A dataset containing 925494 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aechmophorus occidentalis (Lawrence, 1858)"
 ]
}

 The dataset includes 925494 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007293-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3zdybw
title: Occurrence Download

description: A dataset containing 59274 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is one of (Brazil, Argentina, Paraguay)",
 "TaxonKey is Chloroceryle amazona (Latham, 1790)",
 "Year 1000-2024"
 ]
}

 The dataset includes 59274 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007301-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h4ena4
title: Occurrence Download

description: A dataset containing 94282 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is one of (Brazil, Argentina, Paraguay)",
 "TaxonKey is Megaceryle torquata (Linnaeus, 1766)",
 "Year 1000-2024"
 ]
}

 The dataset includes 94282 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007360-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bnhpd3
title: Occurrence Download

description: A dataset containing 349407 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-01-09",
 "EventDate is less than or equal to 2025-02-08",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 349407 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007368-250227182430271/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.19426775
title: scz2022

description: GWAS summary statistics from the Psychiatric Genomics Consortium (PGC)
DOI: 10.15468/dl.9t4smp
title: Occurrence Download

description: A dataset containing 22254 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-02-09",
 "EventDate is less than or equal to 2025-03-11",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 22254 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007371-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.39qv4v
title: Occurrence Download

description: A dataset listing the 28407 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Geometry POLYGON((-80.88098 -1.98755,-75.41325 -1.98755,-75.41325 10.95885,-80.88098 10.95885,-80.88098 -1.98755))",
 "HasGeospatialIssue is false",
 "TaxonKey is Magnoliopsida"
 ]
}

 The dataset's 28407 records were derived from 513 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007307-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vncj8cn6xs.1
title: Dataset for "Engineering the cyanobacterial ATP-driven BCT1 bicarbonate transporter for functional targeting to C3 plant chloroplasts"

description: The ATP-driven bicarbonate transporter BCT1, a four-component complex in the cyanobacteria CO2 concentrating mechanism (CCM), could enhance photosynthetic CO2 assimilation in plant chloroplasts. However, directing its subunits (CmpA, CmpB, CmpC and CmpD) to three chloroplast sub-compartments is highly complex. Investigating BCT1 integration into Nicotiana benthamiana chloroplasts revealed promising targeting strategies using transit peptides from the intermembrane space (IMS) protein Tic22 for correct CmpA targeting, while the transit peptide of the chloroplastic ABCD2 transporter effectively targeted CmpB to the inner envelope membrane (IEM). CmpC and CmpD were targeted to the stroma by RecA and recruited to the IEM by CmpB. Despite successful targeting, expression of this complex in CO2-dependent E. coli provided no bicarbonate uptake. We then used rational design and directed evolution to generate new BCT1 forms which were always active. Several mutants were recovered, including a CmpCD fusion. Selected mutants were further characterized and stably expressed in Arabidopsis but the transformed plants did not have higher carbon assimilation rates or decreased CO2 compensation points in mature leaves. While further analysis is required, this directed evolution and heterologous testing approach presents potential for iterative modification and assessment of CCM components to improve plant photosynthesis.
DOI: 10.15468/dl.35px5e
title: Occurrence Download

description: A dataset containing 145310 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Carcharhinus leucas (Müller & Henle, 1839)"
 ]
}

 The dataset includes 145310 records from 180 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007368-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vncj8cn6xs.2
title: Dataset for "Engineering the cyanobacterial ATP-driven BCT1 bicarbonate transporter for functional targeting to C3 plant chloroplasts"

description: The ATP-driven bicarbonate transporter BCT1, a four-component complex in the cyanobacteria CO2 concentrating mechanism (CCM), could enhance photosynthetic CO2 assimilation in plant chloroplasts. However, directing its subunits (CmpA, CmpB, CmpC and CmpD) to three chloroplast sub-compartments is highly complex. Investigating BCT1 integration into Nicotiana benthamiana chloroplasts revealed promising targeting strategies using transit peptides from the intermembrane space (IMS) protein Tic22 for correct CmpA targeting, while the transit peptide of the chloroplastic ABCD2 transporter effectively targeted CmpB to the inner envelope membrane (IEM). CmpC and CmpD were targeted to the stroma by RecA and recruited to the IEM by CmpB. Despite successful targeting, expression of this complex in CO2-dependent E. coli provided no bicarbonate uptake. We then used rational design and directed evolution to generate new BCT1 forms which were always active. Several mutants were recovered, including a CmpCD fusion. Selected mutants were further characterized and stably expressed in Arabidopsis but the transformed plants did not have higher carbon assimilation rates or decreased CO2 compensation points in mature leaves. While further analysis is required, this directed evolution and heterologous testing approach presents potential for iterative modification and assessment of CCM components to improve plant photosynthesis.
DOI: 10.17632/2fmj3kz8b9.1
title: Risk of Alopecia Areata Induced by Biologic Therapy in Psoriasis and Psoriatic Arthritis: A 20-Year Real-World Pharmacovigilance Analysis Using the FAERS Database

description: The study investigates the potential adverse effect of alopecia areata (AA) in patients with psoriasis and psoriatic arthritis (PsA) undergoing biologic therapy. The research aims to evaluate the association and risk of AA with biologics using real-world data from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database from Q1 2004 to Q3 2024. The study conducted a disproportionality analysis, calculating the reporting odds ratio (ROR) to identify unusually high reporting frequencies of AA among patients treated with biologics. 

Key findings include:
- A total of 108 reports of AA in the context of psoriasis or PsA treatment were retrieved, with 92 attributed to biologics.
- The overall ROR of biologics was 2.12 (95% CI: 1.33–3.38), indicating a significant association.
- Certain biologics showed significant associations with AA, including TNF-α inhibitors adalimumab (ROR = 1.65) and infliximab (ROR = 2.64), IL-23 inhibitor risankizumab (ROR = 2.30), and IL-12/23 inhibitor ustekinumab (ROR = 2.88).
- Other biologics such as etanercept, ixekizumab, and secukinumab did not show significant RORs.

The study emphasizes the need for clinicians to recognize AA as a potential adverse event associated with specific biologics and the importance of personalized treatment strategies to minimize the impact of paradoxical reactions. However, the study acknowledges several limitations, including the exclusion of some biologics due to low AA report numbers, potential biases in voluntary reporting to FAERS, and the inherent limitations of the ROR method, such as dependency on reported data and potential confounding factors.
DOI: 10.17632/f94xs4hrtb.1
title: Forecast of Daily Reference Crop Evapotranspiration Using Universal Deep Learning Models in China

description: Evapotranspiration is a key process in ecosystems, and accurate prediction of short-term daily reference crop evapotranspiration (ETo) is crucial for real-time irrigation decision-making and regional water resource allocation. Due to the complex nonlinear relationship between meteorological factors and ETo, deep learning models are often trained using meteorological observation data from several to dozens of stations to estimate ETo at the station scale. These ETo estimation models are then driven by weather forecast data to achieve ETo prediction.
In this study, we collected a massive amount of public weather forecast data across the country over a four-year period using an automated program. Leveraging this data, along with location and seasonal information, we trained a high-precision ETo forecasting model applicable to the entire country.we forecasted national-scale ETo for a 15-day lead time using five deep learning (DL) models: LSTM, Bi-LSTM, GRU, CNN-BiLSTM, and CNN-BiLSTM-Attention. Five training sets were employed containing diverse input information, including historical climate data, weather forecast data, location, and seasonal information. Public weather forecast data were collected from 2,381 stations across China, spanning from January 2020 to April 2024, which included daily maximum (Tmax) and minimum temperatures (Tmin). 
The results revealed that the differences in ETo forecasting performance between the DL models were significantly smaller than the variations between training sets. By integrating location and seasonal information into the training set, we found a notable decrease in the RMSE of ETo forecasts for lead times of 1, 4, 7, and 15 days, shifting from 0.70, 0.84, 0.97, and 1.27 mm/day to 0.63, 0.79, 0.92, and 1.22 mm/day, respectively. Furthermore, when we directly use massive weather forecast data to train the model, the RMSE of ETo forecasts for the same lead times demonstrated a significant reduction, with the decrease percentages of 30.4%, 34.7%, 38.5%, and 47.2%, respectively.
We have provided a portion of weather forecast data and historical meteorological data for your reference and use. These data cover multiple key meteorological indicators such as temperature, humidity, wind speed, and precipitation, with high accuracy and reliability. Additionally, we offer a pre-trained model based on deep learning algorithms, specifically designed for predicting short-term daily reference crop evapotranspiration (ETo). You can utilize this model free of charge to enhance your real-time irrigation decision-making and regional water resource allocation efforts. By providing these data and the model, we aim to facilitate and assist your related research and practices.