cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14938649
title: 4DHydro_Results_Tetis_Tugela_30sec_daily_exp34_20070101_20221231

description: Modeling results with TETIS software, for Tugela River with a spatial resolution of 30 seconds, and temporal resolution daily. Experiment 34. Forcing "mergedera5gpmsm2a". Calibrating methodology MOSCEM, calibrated variable SM+ET

Includes results for the following variables:



Total evapotranspiration flux in kg m-2 s-1

Discharge flux in m-3 s-1

Volumetric soil moisture content in percentage

Total water storage content in kg m-2
DOI: 10.5281/zenodo.14926156
title: Retonic acid based wound healing in Monopterus Cuchia

description: This dataset contain images of wound healing pattern of a fish known as Monopterus Albus commonly known as Swamp Eel. Wound healing in this dataset is analysed with the use of medicine(Retonic Acid).
DOI: 10.5281/zenodo.14926157
title: Retonic acid based wound healing in Monopterus Cuchia

description: This dataset contain images of wound healing pattern of a fish known as Monopterus Albus commonly known as Swamp Eel. Wound healing in this dataset is analysed with the use of medicine(Retonic Acid).
DOI: 10.58132/xrinlf
title: Advancing dynamic quantum crystallography: enhanced models for accurate structures and thermodynamic properties - cif files

description: CIF files for 5 molecules: alanine, xylitol, naphthalene and glycine polymorphs are stored here. In which file different models can be found. All of them were used to present the effectiveness of AAM_NoMoRe model and highlighting its the influence on the H-atom positions and shape of their ADPs, which are com­parable with neutron data and described in manuscript Advancing dynamic quantum crystallography: enhanced models for accurate structures and thermodynamic properties. IUCrJ. 2025, 12, 123-136.Cif files can be opened by any text editor and/or by any version of crystallographic software, e.g. Mercury, Vesta.
DOI: 10.6084/m9.figshare.28506518
title: Supplementary Material for: Genetical predicted causal relationship between gut microbiota and different types of kidney diseases

description: Introduction: Although recent research suggests that alterations in gut microbiota play a critical role in the pathophysiology of kidney diseases, the causal relationship between specific intestinal flora and the risk of kidney diseases remains unclear. Here, we investigated the causal relationship between gut microbiota and different kidney diseases through Mendelian randomization analysis.
Methods: Gut microbiota and three types of kidney diseases, including diabetic nephropathy, IgA nephropathy, and membranous nephropathy, were identified from large-scale genome-wide association studies summary data. Inverse variance weighted method was employed to estimate causal relationships. Cochran’s Q test was utilized to uncover any heterogeneity. The Mendelian randomization Egger intercept test was employed to detect horizontal pleiotropy, and the leave-one-out method was used for testing the stability. In addition, the reverse, multivariable, and two step Mendelian randomization analysis was conducted to assess the causation possibilities. Furthermore, the associations between three types of kidney diseases and immune infiltration were determined.
Results: We identified 1,531 single nucleotide polymorphisms. There were 6 positive and 9 negative causal effects between gut microbiota and three types of kidney diseases. Specifically, Dialister was a protective factor for diabetic nephropathy while LachnospiraceaeUCG008 was a risk factor. Clostridiuminnocuum was a protective factor for IgA nephropathy, while ChristensenellaceaeR.7, Clostridiumsensustricto1, LachnospiraceaeUCG004, LachnospiraceaeUCG010, Oscillospira, RuminococcaceaeUCG010, and Terrisporobacter were risk factors for IgA nephropathy. Butyricicoccus, Catenibacterium, Flavonifractor, and Lachnospira were associated with an increased risk of membranous nephropathy, while RuminococcaceaeUCG011 was associated with a decreased risk of membranous nephropathy. Sensitivity analysis indicated the results were robust. No significant pleiotropy or heterogeneity was identified. Notably, the reverse Mendelian randomization analysis did not reveal any causal relationship. After adjusting for environmental confounders, including CO, PM 2.5, PM10, and exposure to tobacco smoke at home, these causal relationships still exist. Additionally, immune infiltration analysis indicated unique immune cell distribution in each type of kidney disease, which are largely consistent with later two step approach.
Conclusion: This study uncovered the causal relationship between gut microbiota and three types of kidney diseases. This discovery provides fresh perspectives on how microbes contribute to kidney diseases, paving the way for more in-depth clinical studies.
DOI: 10.6084/m9.figshare.28506518.v1
title: Supplementary Material for: Genetical predicted causal relationship between gut microbiota and different types of kidney diseases

description: Introduction: Although recent research suggests that alterations in gut microbiota play a critical role in the pathophysiology of kidney diseases, the causal relationship between specific intestinal flora and the risk of kidney diseases remains unclear. Here, we investigated the causal relationship between gut microbiota and different kidney diseases through Mendelian randomization analysis.
Methods: Gut microbiota and three types of kidney diseases, including diabetic nephropathy, IgA nephropathy, and membranous nephropathy, were identified from large-scale genome-wide association studies summary data. Inverse variance weighted method was employed to estimate causal relationships. Cochran’s Q test was utilized to uncover any heterogeneity. The Mendelian randomization Egger intercept test was employed to detect horizontal pleiotropy, and the leave-one-out method was used for testing the stability. In addition, the reverse, multivariable, and two step Mendelian randomization analysis was conducted to assess the causation possibilities. Furthermore, the associations between three types of kidney diseases and immune infiltration were determined.
Results: We identified 1,531 single nucleotide polymorphisms. There were 6 positive and 9 negative causal effects between gut microbiota and three types of kidney diseases. Specifically, Dialister was a protective factor for diabetic nephropathy while LachnospiraceaeUCG008 was a risk factor. Clostridiuminnocuum was a protective factor for IgA nephropathy, while ChristensenellaceaeR.7, Clostridiumsensustricto1, LachnospiraceaeUCG004, LachnospiraceaeUCG010, Oscillospira, RuminococcaceaeUCG010, and Terrisporobacter were risk factors for IgA nephropathy. Butyricicoccus, Catenibacterium, Flavonifractor, and Lachnospira were associated with an increased risk of membranous nephropathy, while RuminococcaceaeUCG011 was associated with a decreased risk of membranous nephropathy. Sensitivity analysis indicated the results were robust. No significant pleiotropy or heterogeneity was identified. Notably, the reverse Mendelian randomization analysis did not reveal any causal relationship. After adjusting for environmental confounders, including CO, PM 2.5, PM10, and exposure to tobacco smoke at home, these causal relationships still exist. Additionally, immune infiltration analysis indicated unique immune cell distribution in each type of kidney disease, which are largely consistent with later two step approach.
Conclusion: This study uncovered the causal relationship between gut microbiota and three types of kidney diseases. This discovery provides fresh perspectives on how microbes contribute to kidney diseases, paving the way for more in-depth clinical studies.
DOI: 10.6084/m9.figshare.28506521
title: Supplementary Material for: Depth and Duration of Response Are Associated With Survival in Patients With Unresectable Hepatocellular Carcinoma: Exploratory Analyses of IMbrave150

description: Introduction IMbrave150 established first-line atezolizumab plus bevacizumab as a global standard of care for unresectable hepatocellular carcinoma (HCC). We report exploratory analyses of associations between overall survival (OS) and depth of response (DpR) or duration of response (DoR).
Methods IMbrave150 was a phase III randomized study of atezolizumab plus bevacizumab vs sorafenib in patients with unresectable HCC. DpR was defined as maximum tumor shrinkage from baseline based on the sum of longest diameters per independent review facility (IRF)–assessed RECIST 1.1. DoR was defined as time from first complete/partial response by IRF-assessed RECIST 1.1 until progression or death. Associations between OS and DpR or DoR were evaluated by scatterplot in both arms; OS and PFS were evaluated by DpR in atezolizumab plus bevacizumab-treated patients. To minimize immortal time bias, the DpR analysis included patients who survived ≥6 months.
Results Of 312 and 140 patients with baseline measurable disease in the atezolizumab plus bevacizumab and sorafenib arms, respectively, 264 and 99 surviving ≥6 months were included in the DpR analysis, and 97 and 18 in the DoR analysis. Tumor shrinkage occurred in 230/312 (74%) patients in the atezolizumab plus bevacizumab arm and 76/140 (54%) in the sorafenib arm; their mean (SD) DpR was −42.5% (32.4%) and −25.0% (21.9%), respectively. Atezolizumab plus bevacizumab-treated ≥6-month survivors with DpR &lt;0% had improved OS vs those with DpR ≥0% (HR, 0.29; 95% CI, 0.19-0.44). Those with deeper responses (DpR −100% to −60%) had longer OS than those with DpR ≥20% (unstratified HR 0.08; 95% CI, 0.03-0.21). In scatterplots, DpR and DoR were generally associated with OS in both arms; interpretation was limited by censored patients.
Conclusions Depth and duration of response to atezolizumab plus bevacizumab and sorafenib were associated with OS in patients with unresectable HCC. More longer, deeper responses occurred with atezolizumab plus bevacizumab.
DOI: 10.6084/m9.figshare.28506521.v1
title: Supplementary Material for: Depth and Duration of Response Are Associated With Survival in Patients With Unresectable Hepatocellular Carcinoma: Exploratory Analyses of IMbrave150

description: Introduction IMbrave150 established first-line atezolizumab plus bevacizumab as a global standard of care for unresectable hepatocellular carcinoma (HCC). We report exploratory analyses of associations between overall survival (OS) and depth of response (DpR) or duration of response (DoR).
Methods IMbrave150 was a phase III randomized study of atezolizumab plus bevacizumab vs sorafenib in patients with unresectable HCC. DpR was defined as maximum tumor shrinkage from baseline based on the sum of longest diameters per independent review facility (IRF)–assessed RECIST 1.1. DoR was defined as time from first complete/partial response by IRF-assessed RECIST 1.1 until progression or death. Associations between OS and DpR or DoR were evaluated by scatterplot in both arms; OS and PFS were evaluated by DpR in atezolizumab plus bevacizumab-treated patients. To minimize immortal time bias, the DpR analysis included patients who survived ≥6 months.
Results Of 312 and 140 patients with baseline measurable disease in the atezolizumab plus bevacizumab and sorafenib arms, respectively, 264 and 99 surviving ≥6 months were included in the DpR analysis, and 97 and 18 in the DoR analysis. Tumor shrinkage occurred in 230/312 (74%) patients in the atezolizumab plus bevacizumab arm and 76/140 (54%) in the sorafenib arm; their mean (SD) DpR was −42.5% (32.4%) and −25.0% (21.9%), respectively. Atezolizumab plus bevacizumab-treated ≥6-month survivors with DpR &lt;0% had improved OS vs those with DpR ≥0% (HR, 0.29; 95% CI, 0.19-0.44). Those with deeper responses (DpR −100% to −60%) had longer OS than those with DpR ≥20% (unstratified HR 0.08; 95% CI, 0.03-0.21). In scatterplots, DpR and DoR were generally associated with OS in both arms; interpretation was limited by censored patients.
Conclusions Depth and duration of response to atezolizumab plus bevacizumab and sorafenib were associated with OS in patients with unresectable HCC. More longer, deeper responses occurred with atezolizumab plus bevacizumab.
DOI: 10.6084/m9.figshare.28506524
title: Supplementary Material for: Doppler Assessment of the Uterine Arteries is a Valuable Adjunct Tool for the Evaluation of Efficacy of Gonadotropin-Releasing Hormone Agonist Therapy in Girls with Central Precocious Puberty

description: Introduction: Pelvic ultrasound has been studied for the follow-up of girls with precocious puberty during gonadotropin-releasing hormone agonists (GnRHa) therapy. The addition of Doppler evaluation of uterine arteries needs to be further investigated. We aimed to evaluate the accuracy of the uterine artery pulsatility index (PI) for monitoring GnRHa therapy in girls with precocious puberty.
Methods: This is a retrospective cohort study of girls with central precocious puberty (CPP) and early and fast puberty (EFP) treated with GnRHa. We included girls who underwent pelvic ultrasound and Doppler imaging of the uterine arteries before and during therapy. Analyses included uterine artery PI and uterine, endometrial, and ovarian measurements. Receiver operating characteristic (ROC) curves with cutoffs determined by the Youden index were used for data analysis.
Results: In total, 28 pairs of PI measurements (54% of girls with CPP, 46% with EFP) before and during GnRHa therapy were included in the paired-sample analysis. The median duration of treatment at the time of ultrasound was 11.5 (7; 19) months. The mean PI was significantly higher during GnRHa therapy than at baseline (6.5 ± 1.8 vs. 4.0 ± 1.6, respectively, P &lt; 0.001). A total of three girls met clinical and laboratory criteria for treatment failure. ROC curve analysis showed that the PI was able to identify an effective GnRHa therapy with a mean area under the curve (AUC) of 0.967 ± 0.04 (P &lt; 0.001), and the PI cutoff point of 5.4 held a sensitivity of 84%, specificity of 100%, and accuracy of 86%.
Conclusion: We found a significant increase in the PI during GnRHa therapy, which reflects higher resistance in the blood flow to the uterus, indicating effective pubertal hormone suppression.
DOI: 10.15468/dl.t8stgn
title: Occurrence Download

description: A dataset containing 9172 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Argyroneta Latreille, 1804"
 ]
}

 The dataset includes 9172 records from 201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000878-250226211518916/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v2ewqk
title: Occurrence Download

description: A dataset containing 50121 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bromus catharticus Vahl"
 ]
}

 The dataset includes 50121 records from 1130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000106-250227125302545/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0066185.10fu
title: SH0066185.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0066186.10fu
title: SH0066186.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0066187.10fu
title: SH0066187.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0066188.10fu
title: SH0066188.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0066189.10fu
title: SH0066189.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0066190.10fu
title: SH0066190.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0066191.10fu
title: SH0066191.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.