cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28082603.v1
title: Impact of low-dose aspirin on the prevalence of anemia in elderly patients: a systematic review and meta-analysis

description: Aspirin is largely used for cardiovascular prevention. While its adverse effect on bleeding is well-documented, the prevalence of anemia remains uncertain. We conducted a meta-analysis on how low-dose aspirin affects hemoglobin and other hematologic parameters in the elderly. We systematically searched PubMed, Embase, and Cochrane for studies comparing the hematological parameters and the prevalence of anemia between low-dose aspirin (≤325 mg) and non-aspirin users in individuals aged older than 60 years. We pooled mean differences (MD) for continuous outcomes and odds ratio (OR) for binary outcomes, with 95% confidence intervals (CI), under a random-effects model for both. Seven studies were included, including three randomized controlled trials (RCTs), totaling 19,792 participants. Among them, 9,771 (49.3%) were treated with aspirin; 55.4% were women and 44% had a history of smoking. There was no significant difference in anemia prevalence (OR 0.85; 95% CI 0.52–1.38; <i>p</i> = 0.50). Mean Corpuscular Hemoglobin (MD 0.06 pg; 95% CI −0.37 to 0.49; <i>p</i> = 0.79), Mean Corpuscular Volume (MD −0.31 fl; 95% CI −1.17 to 0.56; <i>p</i> = 0.49), and hemoglobin concentration (MD −0.02 g/dL; 95% CI −0.26 to 0.21; <i>p</i> = 0.85) between the two groups. However, hemoglobin decline from baseline was higher in aspirin users (MD −0.11 g/dL; 95% CI −0.17 to −0.05; <i>p</i> = 0.0002; I<sup>2</sup> = 0%). Our study employs rigorous methodology and a substantial patient cohort, marking the first quantitative meta-analysis in the past decade. Limitations include diverse study designs, short follow-up durations, gender-specific anemia criteria, and insufficient ferritin and iron levels data. Nonetheless, our findings suggest that while low-dose aspirin does not increase anemia prevalence, it is associated with declining hemoglobin levels over time.
DOI: 10.6084/m9.figshare.28195996
title: Quality of guidelines for hyperthyroidism: systematic quality assessment using the AGREE II tool

description: The aim of this study was to systematically assess the quality of different guidelines for the management of patients with hyperthyroidism and to explore and analyze the recommendations and key evidence in different guidelines. A systematic search of databases and websites was conducted to identify treatment guidelines for hyperthyroidism. The quality of the included guidelines was assessed using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. To evaluate the level of agreement among the guidelines, we employed the Measurement Scale of Rate of Agreement (MSRA), extracting and analyzing the evidence supporting these recommendations. Eleven guidelines for the management of patients with hyperthyroidism were identified. The guidelines from the American Thyroid Association (ATA), the Japanese Thyroid Association (JTA), the European Thyroid Association (ETA, 2022) and the Chinese Medical Association (CMA) had overall quality scores greater than 60% and warranted clinical recommendation. Recommendations vary widely across guidelines, and the main reasons included different emphases on the diagnosis of hyperthyroidism, different target populations, irrational selection of evidence and geographic variation. The quality of hyperthyroidism treatment guidelines is variable, and treatment recommendations vary greatly from guideline between guidelines. Analyzing and improving the causes of inconsistencies in recommendations for patients with hyperthyroidism could be a reasonable and effective way for developers to improve the quality of guidelines for the management of hyperthyroidism.
DOI: 10.6084/m9.figshare.28195996.v1
title: Quality of guidelines for hyperthyroidism: systematic quality assessment using the AGREE II tool

description: The aim of this study was to systematically assess the quality of different guidelines for the management of patients with hyperthyroidism and to explore and analyze the recommendations and key evidence in different guidelines. A systematic search of databases and websites was conducted to identify treatment guidelines for hyperthyroidism. The quality of the included guidelines was assessed using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. To evaluate the level of agreement among the guidelines, we employed the Measurement Scale of Rate of Agreement (MSRA), extracting and analyzing the evidence supporting these recommendations. Eleven guidelines for the management of patients with hyperthyroidism were identified. The guidelines from the American Thyroid Association (ATA), the Japanese Thyroid Association (JTA), the European Thyroid Association (ETA, 2022) and the Chinese Medical Association (CMA) had overall quality scores greater than 60% and warranted clinical recommendation. Recommendations vary widely across guidelines, and the main reasons included different emphases on the diagnosis of hyperthyroidism, different target populations, irrational selection of evidence and geographic variation. The quality of hyperthyroidism treatment guidelines is variable, and treatment recommendations vary greatly from guideline between guidelines. Analyzing and improving the causes of inconsistencies in recommendations for patients with hyperthyroidism could be a reasonable and effective way for developers to improve the quality of guidelines for the management of hyperthyroidism.
DOI: 10.6084/m9.figshare.28219765
title: Preoperative intravenous versus oral iron supplementation for elective surgery: evidence based on 12 randomized trials

description: This study aims to clarify hematological parameters, transfusion requirements, and adverse events of preoperative intravenous (IVIS) versus oral iron supplementation (OIS) in elective surgery patients. We conducted a comprehensive literature search across multiple databases up to 10 December 2023. Twelve RCTs involving 930 participants met our eligibility criteria. Our analysis focused on post-treatment hemoglobin levels, changes in hemoglobin from baseline, ferritin levels, hemoglobin attainment rates, transfusion requirements, and adverse events. We employed the random-effects model for data synthesis, calculating pooled standard mean differences (SMD) or mean differences (MD) or risk ratios (RR) with 95% confidence intervals (CI). Methodological quality was assessed using the Cochrane ROB 2 tool. The GRADE approach evaluated the confidence in effect estimates. IVIS significantly improved post-treatment hemoglobin levels (MD = 0.77 g/dL, 95% CI [0.30 to 1.23]), hemoglobin increments (MD = 0.69 g/dL, 95% CI [0.01 to 1.37]), and ferritin levels (MD = 260.03 ng/mL, 95% CI [119.65 to 400.42]) compared to OIS. IVIS also led to a higher hemoglobin attainment rate (RR = 1.88, 95% CI [1.24 to 2.86]). No significant differences were noted in transfusion rates or volumes. IVIS was associated with fewer digestive (RR = 0.10, 95% CI [0.05 to 0.22]; I2 = 0%) but more pain-related adverse events (RR = 7.79, 95% CI [1.78 to 34.07]; I2 = 0%). Hospital stay durations and mortality rates were similar between the two groups. IVIS offers a superior improvement in hematological parameters for elective surgery patients but not reducing transfusion needs compared to OIS. While IVIS has fewer digestive adverse events, it increases pain-related complications. These findings highlight the importance of personalized approaches in selecting iron supplementation methods, carefully balancing time, efficacy, and adverse event profiles. PROSPERO CRD42023483284.
DOI: 10.6084/m9.figshare.28219765.v1
title: Preoperative intravenous versus oral iron supplementation for elective surgery: evidence based on 12 randomized trials

description: This study aims to clarify hematological parameters, transfusion requirements, and adverse events of preoperative intravenous (IVIS) versus oral iron supplementation (OIS) in elective surgery patients. We conducted a comprehensive literature search across multiple databases up to 10 December 2023. Twelve RCTs involving 930 participants met our eligibility criteria. Our analysis focused on post-treatment hemoglobin levels, changes in hemoglobin from baseline, ferritin levels, hemoglobin attainment rates, transfusion requirements, and adverse events. We employed the random-effects model for data synthesis, calculating pooled standard mean differences (SMD) or mean differences (MD) or risk ratios (RR) with 95% confidence intervals (CI). Methodological quality was assessed using the Cochrane ROB 2 tool. The GRADE approach evaluated the confidence in effect estimates. IVIS significantly improved post-treatment hemoglobin levels (MD = 0.77 g/dL, 95% CI [0.30 to 1.23]), hemoglobin increments (MD = 0.69 g/dL, 95% CI [0.01 to 1.37]), and ferritin levels (MD = 260.03 ng/mL, 95% CI [119.65 to 400.42]) compared to OIS. IVIS also led to a higher hemoglobin attainment rate (RR = 1.88, 95% CI [1.24 to 2.86]). No significant differences were noted in transfusion rates or volumes. IVIS was associated with fewer digestive (RR = 0.10, 95% CI [0.05 to 0.22]; I2 = 0%) but more pain-related adverse events (RR = 7.79, 95% CI [1.78 to 34.07]; I2 = 0%). Hospital stay durations and mortality rates were similar between the two groups. IVIS offers a superior improvement in hematological parameters for elective surgery patients but not reducing transfusion needs compared to OIS. While IVIS has fewer digestive adverse events, it increases pain-related complications. These findings highlight the importance of personalized approaches in selecting iron supplementation methods, carefully balancing time, efficacy, and adverse event profiles. PROSPERO CRD42023483284.
DOI: 10.15468/dl.ykeqqr
title: Occurrence Download

description: A dataset containing 220534 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.continent = 'ASIA'
 AND occurrence.countrycode = 'CN'
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence."year" &gt;= 2001 AND occurrence."year" &lt;= 2025)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 220534 records were derived from 2443 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017162-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5aa3m8
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Perissocarpa umbellifera",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 27 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004377-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uc4cs7
title: Occurrence Download

description: A dataset containing 922 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Herichthys pantostictus"
 ]
}

 The dataset includes 922 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004379-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hjhab6
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Philacra auriculata",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 22 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004380-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18444067
title: Uncertainty-Quantified QSAR Predictions: VEGA Models (98 Endpoints) with Conformal Intervals/Sets for Training, Test, and EPA CompTox Datasets (500K Compounds)

description: # Dataset Description

This repository contains training data, test data, and uncertainty-quantified predictions for 98 QSAR models from the VEGA platform, plus large-scale screening results for the EPA CompTox database.

## Contents

### 1. VEGA Training and Test Sets- **51 regression endpoints** - **52 classification endpoints** - ~114,000 predictions across VEGA test sets- Molecular structures (SMILES), experimental values, model predictions- Applicability Domain Index (ADI) for each prediction

### 2. Conformal Prediction Results (VEGA)- **Prediction intervals** for regression (90% coverage)- **Prediction sets** for classification (90% coverage) - Auxiliary model confidence scores- Conformal prediction metrics 

3. VEGA point prediction and Conformal Prediction Results (EPA CompTox ) - **Prediction intervals** for regression (90% coverage)- **Prediction sets** for classification (90% coverage) - Auxiliary model confidence scores- Conformal prediction metrics - ADI values for all predictions

 

This is a supplementay information for a paper submitted to https://pubs.acs.org/doi/10.1021/acs.chemrestox.5c00293
DOI: 10.5281/zenodo.18444068
title: Uncertainty-Quantified QSAR Predictions: VEGA Models (98 Endpoints) with Conformal Intervals/Sets for Training, Test, and EPA CompTox Datasets (500K Compounds)

description: # Dataset Description

This repository contains training data, test data, and uncertainty-quantified predictions for 98 QSAR models from the VEGA platform, plus large-scale screening results for the EPA CompTox database.

## Contents

### 1. VEGA Training and Test Sets- **51 regression endpoints** - **52 classification endpoints** - ~114,000 predictions across VEGA test sets- Molecular structures (SMILES), experimental values, model predictions- Applicability Domain Index (ADI) for each prediction

### 2. Conformal Prediction Results (VEGA)- **Prediction intervals** for regression (90% coverage)- **Prediction sets** for classification (90% coverage) - Auxiliary model confidence scores- Conformal prediction metrics 

3. VEGA point prediction and Conformal Prediction Results (EPA CompTox ) - **Prediction intervals** for regression (90% coverage)- **Prediction sets** for classification (90% coverage) - Auxiliary model confidence scores- Conformal prediction metrics - ADI values for all predictions

 

This is a supplementay information for a paper submitted to https://pubs.acs.org/doi/10.1021/acs.chemrestox.5c00293
DOI: 10.5281/zenodo.18446952
title: TISHLARNI OQARTIRISH TEXNOLOGIYALARI: KIMYOVIY VA LAZERLI USULLAR TAQQOSLANISHI

description: Ushbu maqolada zamonaviy stomatologiyada qo'llaniladigan tishlarni oqartirish texnologiyalari - kimyoviy va lazerli usullar - taqqosiy tahlil qilingan. Tadqiqot xalqaro va mahalliy ilmiy manbalarga asoslanib, ikkala usulning ish mexanizmlari, samaradorligi, xavfsizligi va klinik amaliyotdagi qo'llanilishi tahlil qilinadi. Maqolada vodorod peroksidning oksidlanish jarayoni va lazer nurlanishining oqartirish samaradorligiga ta'siri batafsilolroq yoritilgan [1, 2, 3].
DOI: 10.5281/zenodo.18446953
title: TISHLARNI OQARTIRISH TEXNOLOGIYALARI: KIMYOVIY VA LAZERLI USULLAR TAQQOSLANISHI

description: Ushbu maqolada zamonaviy stomatologiyada qo'llaniladigan tishlarni oqartirish texnologiyalari - kimyoviy va lazerli usullar - taqqosiy tahlil qilingan. Tadqiqot xalqaro va mahalliy ilmiy manbalarga asoslanib, ikkala usulning ish mexanizmlari, samaradorligi, xavfsizligi va klinik amaliyotdagi qo'llanilishi tahlil qilinadi. Maqolada vodorod peroksidning oksidlanish jarayoni va lazer nurlanishining oqartirish samaradorligiga ta'siri batafsilolroq yoritilgan [1, 2, 3].
DOI: 10.15468/dl.bg7c8n
title: Occurrence Download

description: A dataset containing 453 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Incilius melanochlorus"
 ]
}

 The dataset includes 453 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004383-260129131611470/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.31223478
title: Optimizing shear strength characterization of engineered emulsion-stabilized cold recycled materials for pavement design through predictive statistical modelling

description: Fundamental shear strength parameters, cohesion and frictional angle, offer significant insights into the shear characteristics of cold recycled materials and are good indices for mechanistic-empirical design models of cold recycled pavements. Material preparation, testing procedures and analysis are, however, often labor-intensive, costly, and time-consuming, necessitating efficient and practical alternatives for parameter estimation. This study employs a modeling framework to predict the shear strength characteristics of engineered emulsion-stabilized cold recycled materials. Data from monotonic triaxial shear tests were modeled using two machine learning approaches, namely, (1) self-validating ensemble modelling, which integrates multiple linear regression (forward selection, adaptive least absolute shrinkage and selection operator, elastic net) & neural network configurations, and (2) support vector regression. Based on model performance evaluations through a range of statistical error metrics, support vector regression demonstrated high accuracy and generalizability, identifying mixture coarseness and density as primary factors influencing cohesion, while stabilizer content and chemical additive presence were important for frictional angle. The predicted parameters were further validated within the deviator stress ratio framework, showing strong alignment with experimentally computed results. As an outcome of this study, a user-friendly Microsoft Excel-based predictive tool was developed to facilitate efficient shear parameter prediction and support pavement design and evaluation.
DOI: 10.6084/m9.figshare.31223478.v1
title: Optimizing shear strength characterization of engineered emulsion-stabilized cold recycled materials for pavement design through predictive statistical modelling

description: Fundamental shear strength parameters, cohesion and frictional angle, offer significant insights into the shear characteristics of cold recycled materials and are good indices for mechanistic-empirical design models of cold recycled pavements. Material preparation, testing procedures and analysis are, however, often labor-intensive, costly, and time-consuming, necessitating efficient and practical alternatives for parameter estimation. This study employs a modeling framework to predict the shear strength characteristics of engineered emulsion-stabilized cold recycled materials. Data from monotonic triaxial shear tests were modeled using two machine learning approaches, namely, (1) self-validating ensemble modelling, which integrates multiple linear regression (forward selection, adaptive least absolute shrinkage and selection operator, elastic net) & neural network configurations, and (2) support vector regression. Based on model performance evaluations through a range of statistical error metrics, support vector regression demonstrated high accuracy and generalizability, identifying mixture coarseness and density as primary factors influencing cohesion, while stabilizer content and chemical additive presence were important for frictional angle. The predicted parameters were further validated within the deviator stress ratio framework, showing strong alignment with experimentally computed results. As an outcome of this study, a user-friendly Microsoft Excel-based predictive tool was developed to facilitate efficient shear parameter prediction and support pavement design and evaluation.
DOI: 10.17909/8rct-8911
title: HST/WFPC2 Imaging of 51 Pegasi
DOI: 10.15468/dl.aaryvb
title: Occurrence Download

description: A dataset containing 2861 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (Moscow University Herbarium (MW), MHA Herbarium: collections of vascular plants)",
 "OccurrenceStatus is Present",
 "StateProvince is one of (Nenets Autonomous Okrug, Nenets Autonomous okrug, Nenets autonomous okrug)",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 2861 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004384-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18446971
title: TISH OQARTIRISHNING ZAMONAVIY VA XAVFSIZ USULLARI

description: Tish oqartirish dunyo bo‘ylab eng mashhur estetik stomatologik protseduralardan biridir. So‘nggi yillarda stomatologik materiallar va texnologiyalardagi yutuqlar zamonaviy va xavfsiz tish oqartirish usullarini yaratishga imkon berdi. Bunga stomatologiyada ofisda oqartirish, uyda maxsus plastinka bilan oqartirish, oqartiruvchi tish pastalari va lentalardan foydalanish kiradi. Zamonaviy usullar tish sezgirligini va emalga zarar yetkazishni minimallashtirish bilan birga samarali natijalarni ta’minlaydi. Ushbu maqola tish oqartirishning zamonaviy usullarini ko‘rib chiqadi, ularning xavfsizligi va samaradorligini baholaydi hamda klinik tavsiyalarni muhokama qiladi [1, 2, 4].
DOI: 10.5281/zenodo.18446972
title: TISH OQARTIRISHNING ZAMONAVIY VA XAVFSIZ USULLARI

description: Tish oqartirish dunyo bo‘ylab eng mashhur estetik stomatologik protseduralardan biridir. So‘nggi yillarda stomatologik materiallar va texnologiyalardagi yutuqlar zamonaviy va xavfsiz tish oqartirish usullarini yaratishga imkon berdi. Bunga stomatologiyada ofisda oqartirish, uyda maxsus plastinka bilan oqartirish, oqartiruvchi tish pastalari va lentalardan foydalanish kiradi. Zamonaviy usullar tish sezgirligini va emalga zarar yetkazishni minimallashtirish bilan birga samarali natijalarni ta’minlaydi. Ushbu maqola tish oqartirishning zamonaviy usullarini ko‘rib chiqadi, ularning xavfsizligi va samaradorligini baholaydi hamda klinik tavsiyalarni muhokama qiladi [1, 2, 4].