cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19029527.v1
title: Additional file 6 of Open chromatin interaction maps reveal functional regulatory elements and chromatin architecture variations during wheat evolution

description: Additional file 6: Table S8 The differentially interacted intrachromosomal loops between bread wheat and T. durum.
DOI: 10.6084/m9.figshare.12214838
title: Mapping the global potential transmission hotspots for severe fever with thrombocytopenia syndrome by machine learning methods

description: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing spread. Currently SFTS transmission has expanded beyond Asian countries, however, with definitive global extents and risk patterns remained obscure. Here we established an exhaustive database that included globally reported locations of human SFTS cases and the competent vector, <i>Haemaphysalis longicornis</i> (<i>H. longicornis</i>), as well as the explanatory environmental variables, based on which, the potential geographic range of <i>H. longicornis</i> and risk areas for SFTS were mapped by applying two machine learning methods. Ten predictors were identified contributing to global distribution for <i>H. longicornis</i> with relative contribution ≥1%. Outside contemporary known distribution, we predict high receptivity to <i>H. longicornis</i> across two continents, including northeastern USA, New Zealand, parts of Australia, and several Pacific islands. Eight key drivers of SFTS cases occurrence were identified, including elevation, predicted probability of <i>H. longicornis</i> presence, two temperature-related factors, two precipitation-related factors, the richness of mammals and percentage coverage of water bodies. The globally model-predicted risk map of human SFTS occurrence was created and validated effective for discriminating the actual affected and unaffected areas (median predictive probability 0.74 vs. 0.04, <i>P</i> &lt; 0.001) in three countries with reported cases outside China. The high-risk areas (probability ≥50%) were predicted mainly in east-central China, most parts of the Korean peninsula and southern Japan, and northern New Zealand. Our findings highlight areas where an intensive vigilance for potential SFTS spread or invasion events should be advocated, owing to their high receptibility to <i>H. longicornis</i> distribution.
DOI: 10.6084/m9.figshare.19029530
title: Additional file 7 of Open chromatin interaction maps reveal functional regulatory elements and chromatin architecture variations during wheat evolution

description: Additional file 7: Table S9 The differentially interacted intrachromosomal loops between bread wheat and Ae. tauschii.
DOI: 10.5281/zenodo.10085301
title: Spectral hardness of X- and gamma-ray emissions from lightning stepped and dart leaders

description: This repository has four folders dedicated to the 11 triggers outlined in the manuscript. Within each folder, the data is organized according to the four sensors:

Slow Antenna Folder: For every trigger, there is a corresponding .asc file paired with a complementary .readme file. Additionally, this folder includes a .txt file that lists the file names and UTC times.
LEFA: The *.txt files within this section consist of four columns representing seconds after midnight (UTC), instrument power voltage, sensitive channel, medium channel, and unsensitive channel. The file names adhere to the format lefa2-yymmdd-hhmm00.txt, each containing one minute of LEFA data.
DAS: Files in this category follow the format XRAY_yyyy.mm.dd_hh-mm-ss_milliseconds.channel[B,C, or D].csv, with UTC time. The file name corresponds to time zero in the data. The first column denotes seconds from/after zero, while the second column represents the measured data in Volts. The channels (B, C, D) correspond to Fast Antenna, LaBr detector, and NaI detector, respectively. The instrument has a sampling rate of 180 MHz.
Fieldmill:The file names in this section adhere to the format kv2022mmdd-hhmm.flt and are accompanied by a calibration file.
DOI: 10.5281/zenodo.10085302
title: Spectral hardness of X- and gamma-ray emissions from lightning stepped and dart leaders

description: This repository has four folders dedicated to the 11 triggers outlined in the manuscript. Within each folder, the data is organized according to the four sensors:

Slow Antenna Folder: For every trigger, there is a corresponding .asc file paired with a complementary .readme file. Additionally, this folder includes a .txt file that lists the file names and UTC times.
LEFA: The *.txt files within this section consist of four columns representing seconds after midnight (UTC), instrument power voltage, sensitive channel, medium channel, and unsensitive channel. The file names adhere to the format lefa2-yymmdd-hhmm00.txt, each containing one minute of LEFA data.
DAS: Files in this category follow the format XRAY_yyyy.mm.dd_hh-mm-ss_milliseconds.channel[B,C, or D].csv, with UTC time. The file name corresponds to time zero in the data. The first column denotes seconds from/after zero, while the second column represents the measured data in Volts. The channels (B, C, D) correspond to Fast Antenna, LaBr detector, and NaI detector, respectively. The instrument has a sampling rate of 180 MHz.
Fieldmill:The file names in this section adhere to the format kv2022mmdd-hhmm.flt and are accompanied by a calibration file.
DOI: 10.1285/i20705948v9n4p675
title: Job crafting and job satisfaction in a sample of Italian teachers: the mediating role of Perceived Organizational Support

description: We aimed to explore the mediating role of perceived organizational support(POS) on the relationship between job crafting and job satisfaction, which is considered as an important outcome for the development of well-being at work.   Participants  were  263  teachers  from  public  schools  in  the  South  of Italy.  Results indicated that POS fully mediated the relationship between job crafting and job satisfaction.  Implications for management educational practice and limitations of the study are discussed.
DOI: 10.6084/m9.figshare.20078696
title: Additional file 1 of Job crafting and employees’ general health: the role of work–nonwork facilitation and perceived boundary control

description: Additional file 1.
DOI: 10.6084/m9.figshare.20078696.v1
title: Additional file 1 of Job crafting and employees’ general health: the role of work–nonwork facilitation and perceived boundary control

description: Additional file 1.
DOI: 10.5517/ccdc.csd.cc22gckh
title: CCDC 1920436: Experimental Crystal Structure Determination

description: Related Article: Steven P. Kelley, Volodymyr Smetana, Hatem M. Titi, Si-Fu Tang, Guillaume Bousrez, Olivier Renier, Brando Adranno, Elnaz Tahavori, Anja-Verena Mudring, and Robin D. Rogers|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc22gclj
title: CCDC 1920437: Experimental Crystal Structure Determination

description: Related Article: Steven P. Kelley, Volodymyr Smetana, Hatem M. Titi, Si-Fu Tang, Guillaume Bousrez, Olivier Renier, Brando Adranno, Elnaz Tahavori, Anja-Verena Mudring, and Robin D. Rogers|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc22gcmk
title: CCDC 1920438: Experimental Crystal Structure Determination

description: Related Article: Steven P. Kelley, Volodymyr Smetana, Hatem M. Titi, Si-Fu Tang, Guillaume Bousrez, Olivier Renier, Brando Adranno, Elnaz Tahavori, Anja-Verena Mudring, and Robin D. Rogers|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.13264121
title: Processed gene counts matrices from scRNA-seq datasets

description: Gene counts matrices extracted from scRNA-seq datasets processed with different pipelines.
DOI: 10.25386/genetics.16934209
title: Supplementary information for Cridland et al., 2021

description: Supplementary tables for "Population biology of accessory gland-expressed de novo genes in Drosophila melanogaster".
DOI: 10.25386/genetics.16934209.v2
title: Supplementary information for Cridland et al., 2021

description: Supplementary tables for "Population biology of accessory gland-expressed de novo genes in Drosophila melanogaster".
DOI: 10.25386/genetics.16934209.v1
title: Supplementary information for Cridland et al 2021

description: Supplementary tables for "Population biology of accessory gland-expressed de novo genes in Drosophila melanogaster".
DOI: 10.6084/m9.figshare.17982016.v1
title: Additional file 1 of Genome-wide association study identifies SNPs for growth performance and serum indicators in Valgus-varus deformity broilers (Gallus gallus) using ddGBS sequencing

description: Additional file 1: Table S1. The phenotypic information of VVD and sound broile. Table S2. Annotated candidate genes to VVD trait. Table S3. Annotated candidate genes to ALP trait. Table S4. GO enrichment analysis of the candidate genes for VVD trait in Valgus-varus Deformity Broilers. Table S5. KEGG enrichment analysis of the candidate genes for VVD trait. Table S6. GO enrichment analysis of the candidate genes for ALP trait in Valgus-varus Deformity Broilers. Table S7. KEGG enrichment analysis of the candidate genes for ALP trait in Valgus-varus Deformity Broilers.
DOI: 10.6084/m9.figshare.20079153
title: Additional file 2 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 2: Table S2. One-to-one orthologous relationships between Medicago sativa L. and other plants.
DOI: 10.6084/m9.figshare.20079156
title: Additional file 3 of Genome-wide identification, phylogeny and expression analysis of the SPL gene family and its important role in salt stress in Medicago sativa L.

description: Additional file 3: Table S3. Cis_elements contained in the MsSPL genes promoter region.
DOI: 10.6084/m9.figshare.24798716
title: Efficacy analysis of three brain stimulation techniques for Alzheimer’s disease: a meta-analysis of repeated transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation

description: This systematic review and meta-analysis study investigates the efficacy of repeated transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and deep brain stimulation (DBS) using neuropsychological assessments as a potential treatment option for Alzheimer's disease (AD). PubMed, Embase, and the Cochrane Library were searched for studies on rTMS, tDCS, and DBS for the treatment of patients with AD between April 1970 and October 2022. The mini-Mental State Examination (MMSE) and AD Assessment Scale – Cognitive Subscale (ADAS-Cog) were adopted as the efficacy index. The analysis yielded 17 eligible studies. rTMS greatly improved the cognition of patients with AD (immediate post-treatment WMD of MMSE score: 2.06, <i>p</i> &lt; 0.00001; short-term follow-up WMD of MMSE score: 2.12, <i>p</i> = 0.006; WMD of ADAS-Cog score in single-arm studies: -4.97, <i>p</i> = 0.001). DBS did not reverse the progression of cognitive decline (WMD of ADAS-Cog score in single-arm studies: 7.40, <i>p</i> &lt; 0.00001). Furthermore, tDCS demonstrated no significant efficacy in improving cognition in random clinical trials or single-arm studies. rTMS is a promising non-medicinal alternative for cognitive improvement inpatients with AD.
DOI: 10.6084/m9.figshare.24798716.v1
title: Efficacy analysis of three brain stimulation techniques for Alzheimer’s disease: a meta-analysis of repeated transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation

description: This systematic review and meta-analysis study investigates the efficacy of repeated transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and deep brain stimulation (DBS) using neuropsychological assessments as a potential treatment option for Alzheimer's disease (AD). PubMed, Embase, and the Cochrane Library were searched for studies on rTMS, tDCS, and DBS for the treatment of patients with AD between April 1970 and October 2022. The mini-Mental State Examination (MMSE) and AD Assessment Scale – Cognitive Subscale (ADAS-Cog) were adopted as the efficacy index. The analysis yielded 17 eligible studies. rTMS greatly improved the cognition of patients with AD (immediate post-treatment WMD of MMSE score: 2.06, <i>p</i> &lt; 0.00001; short-term follow-up WMD of MMSE score: 2.12, <i>p</i> = 0.006; WMD of ADAS-Cog score in single-arm studies: -4.97, <i>p</i> = 0.001). DBS did not reverse the progression of cognitive decline (WMD of ADAS-Cog score in single-arm studies: 7.40, <i>p</i> &lt; 0.00001). Furthermore, tDCS demonstrated no significant efficacy in improving cognition in random clinical trials or single-arm studies. rTMS is a promising non-medicinal alternative for cognitive improvement inpatients with AD.
DOI: 10.6084/m9.figshare.7497218
title: Additional file 1: of Genome sequence of walking catfish (Clarias batrachus) provides insights into terrestrial adaptation

description: Figure S1. Multiple sequence alignment of myoglobin genes in the genomes of Clarias batrachus, Danio rerio, Ictalurus punctatus and Astyanax mexicanus. Figure S2. Detailed phylogenetic tree of olfactory receptor related to class A G protein-coupled receptor (ora) with species names and sequence names for Figure 3b. Figure S3. Multiple sequence alignment of olfactory receptor related to class A G protein-coupled receptor 1 (ora1) in the genomes of Clarias batrachus, Danio rerio, Ictalurus punctatus and Astyanax mexicanus. Figure S4. Syntenic analysis of myoglobin gene (mb) using genomic information of Danio rerio, Ictalurus punctatus and Clarias batrachus. Figure S5. Comparison of relative fold changes between air-breathing organ and gill in Clarias batrachus after normalization to 28S rRNA using RNA-Seq datasets and qRT-PCR. Table S1. Completeness of genome assembly assessed by CEGMA and BUSCO. Table S2. Mapping of five longest ABySS scaffolds to genome assembly. Table S3. Repetitive elements in the Clarias batrachus genome. Table S4. Orthogroups shared between species by OrthoFinder. Table S5. Specific genes in the Clarias batrachus genome compared with that of channel catfish (Ictalurus punctatus). Table S6. GO terms significantly enriched in the specific genes in the Clarias batrachus genome compared with that of channel catfish (Ictalurus punctatus). Table S7. Positively selected genes in the Clarias batrachus genome compared with those of 11 non-air-breathing teleost fish. Table S8. GO terms significantly enriched in the positively selected genes in the Clarias batrachus genome. Table S9. Expanded genes in the Clarias batrachus genome. Table S10. Summary of transcriptome sequencing data. Table S11. Expression values (RPKM) of all the genes in the transcriptomes of the gill and the air-breathing organ. Table S12. Differentially expressed genes in the transcriptome of the air-breathing organ compared with that of the gill. Table S13. GO terms significantly enriched in the differentially expressed genes comparing the transcriptome of the air-breathing organ with that of the gill. Table S14. Pathways significantly enriched in the differentially expressed genes comparing the transcriptome of the air-breathing organs with that of the gill. Table S15. Accession numbers of protein sequences and models used in the construction of phylogenetic trees of expanded genes. Table S16. Primer sequences used for qRT-PCR. (ZIP 5238 kb)
DOI: 10.6084/m9.figshare.16934418
title: Exhaustive Goodness of Fit Via Smoothed Inference and Graphics

description: Classical tests of goodness of fit aim to validate the conformity of a postulated model to the data under study. Given their inferential nature, they can be considered a crucial step in confirmatory data analysis. In their standard formulation, however, they do not allow exploring how the hypothesized model deviates from the truth nor do they provide any insight into how the rejected model could be improved to better fit the data. The main goal of this work is to establish a comprehensive framework for goodness of fit which naturally integrates modeling, estimation, inference and graphics. Modeling and estimation focus on a novel formulation of smooth tests that easily extends to arbitrary distributions, either continuous or discrete. Inference and adequate post-selection adjustments are performed via a specially designed smoothed bootstrap and the results are summarized via an exhaustive graphical tool called <i>CD-plot</i>. Technical proofs, codes and data are provided in the supplementary material.
DOI: 10.6084/m9.figshare.9594392
title: Target Population Statistical Inference With Data Integration Across Multiple Sources—An Approach to Mitigate Information Shortage in Rare Disease Clinical Trials

description: A major challenge for rare disease clinical trials is the limited amount of available information for making robust statistical inference. While external data present information integration opportunities to enhance statistical inference, conventional data combining methods, for example, meta-analysis, usually do not adequately address study population differences. Matching methods, on the other hand, directly account for population characteristics but often lead to inefficient use of data by underutilizing unmatched data points. Aiming at a better bias-variance tradeoff, we propose an intuitive integrated inference framework to borrow information from all relevant data sources and make inference on the response of interest over a target population precisely characterized by the joint distribution of baseline covariates. The method is easily implemented and can be complemented by modern statistical learning or machine learning tools. Statistical inference is facilitated by the bootstrap. We argue that the integrated inference framework not only provides an intuitive and coherent perspective for a variety of clinical trial inference problems but also has broad application areas in clinical trial settings and beyond, as a quantitative data integration tool for making robust inference in a target population precise manner for policy and decision makers.
DOI: 10.6084/m9.figshare.9594392.v1
title: Target population statistical inference with data integration across multiple sources – an approach to mitigate information shortage in rare disease clinical trials

description: A major challenge for rare disease clinical trials is the limited amount of available information for making robust statistical inference. While external data presents information integration opportunities to enhance statistical inference, conventional data combining methods, e.g. meta-analysis, usually do not adequately address study population differences. Matching methods, on the other hand, directly account for population characteristics but often lead to inefficient use of data by underutilizing unmatched data points. Aiming at a better bias-variance tradeoff, we propose an intuitive integrated inference framework to borrow information from all relevant data sources and make inference on the response of interest over a target population precisely characterized by the joint distribution of baseline covariates. The method is easily implemented and can be complemented by modern statistical learning or machine learning tools. Statistical inference is facilitated by the bootstrap. We argue that the integrated inference framework not only provides an intuitive and coherent perspective for a variety of clinical trial inference problems but also has broad application areas in clinical trial settings and beyond, as a quantitative data integration tool for making robust inference in a target population precise manner for policy and decision makers.
DOI: 10.6084/m9.figshare.9594392.v2
title: Target Population Statistical Inference With Data Integration Across Multiple Sources—An Approach to Mitigate Information Shortage in Rare Disease Clinical Trials

description: A major challenge for rare disease clinical trials is the limited amount of available information for making robust statistical inference. While external data present information integration opportunities to enhance statistical inference, conventional data combining methods, for example, meta-analysis, usually do not adequately address study population differences. Matching methods, on the other hand, directly account for population characteristics but often lead to inefficient use of data by underutilizing unmatched data points. Aiming at a better bias-variance tradeoff, we propose an intuitive integrated inference framework to borrow information from all relevant data sources and make inference on the response of interest over a target population precisely characterized by the joint distribution of baseline covariates. The method is easily implemented and can be complemented by modern statistical learning or machine learning tools. Statistical inference is facilitated by the bootstrap. We argue that the integrated inference framework not only provides an intuitive and coherent perspective for a variety of clinical trial inference problems but also has broad application areas in clinical trial settings and beyond, as a quantitative data integration tool for making robust inference in a target population precise manner for policy and decision makers.
DOI: 10.6084/m9.figshare.17981941
title: Additional file 5 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 5: Clusters detected by SweepCluster for chromosome 2 variants between EUR-EAS selected at a series of Fst cutoff (0.4, 0.43, 0.45, 0.5, 0.55, 0.6, 0.65, and 0.7).
DOI: 10.6084/m9.figshare.17981944
title: Additional file 6 of SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes

description: Additional file 6: Clusters detected by SweepCluster for chromosome 10 variants between EUR-EAS selected at a series of Fst cutoff (0.4, 0.43, 0.45, 0.5, 0.55, 0.6, 0.65, and 0.7).
DOI: 10.6084/m9.figshare.7497257
title: MOESM1 of A novel deletion in KRT75L4 mediates the frizzle trait in a Chinese indigenous chicken

description: Additional file 1: Table S1. Pedigree and phenotypes of the GWAS population. Description: Columns A and B = sire and dam IDs, respectively; column C = sample IDs; column D = phenotype of the samples.
DOI: 10.6084/m9.figshare.19029515
title: Additional file 3 of Open chromatin interaction maps reveal functional regulatory elements and chromatin architecture variations during wheat evolution

description: Additional file 3: Table S4 The intrachromosomal open chromatin loops.
DOI: 10.6084/m9.figshare.19029521.v1
title: Additional file 4 of Open chromatin interaction maps reveal functional regulatory elements and chromatin architecture variations during wheat evolution

description: Additional file 4: Table S5 The triads with chromatin interaction bias.