cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19579951.v1
title: Additional file 3 of Influence of the geometric and material properties of lumbar endplate on lumbar interbody fusion failure: a systematic review

description: Additional file 3. Results of quality assessment on each included study.
DOI: 10.6084/m9.figshare.9630953
title: Additional file 1: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: Basic genetic parameter statistics for 100-seed weight in the tested soybean population (nâ =â 185). (XLS 16 kb)
DOI: 10.6084/m9.figshare.9630953.v1
title: Additional file 1: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: Basic genetic parameter statistics for 100-seed weight in the tested soybean population (nâ =â 185). (XLS 16 kb)
DOI: 10.6084/m9.figshare.9630959
title: Additional file 2: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: Genes in 100 kbp flanking regions of peak SNP associated with 100-seed weight of soybean. (XLS 51 kb)
DOI: 10.6084/m9.figshare.9630959.v1
title: Additional file 2: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: Genes in 100 kbp flanking regions of peak SNP associated with 100-seed weight of soybean. (XLS 51 kb)
DOI: 10.6084/m9.figshare.9630962
title: Additional file 3: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: Gene-based association study on 100-seed weight of soybean with 281 candidate genes. (XLS 35 kb)
DOI: 10.6084/m9.figshare.9630962.v1
title: Additional file 3: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: Gene-based association study on 100-seed weight of soybean with 281 candidate genes. (XLS 35 kb)
DOI: 10.6084/m9.figshare.9630965
title: Additional file 4: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: The information of soybean association panel. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.9630965.v1
title: Additional file 4: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: The information of soybean association panel. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.9630971
title: Additional file 5: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: SNP data of 185 soybean accessions for GWAS. (XLSX 1490 kb)
DOI: 10.6084/m9.figshare.9630971.v1
title: Additional file 5: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: SNP data of 185 soybean accessions for GWAS. (XLSX 1490 kb)
DOI: 10.6084/m9.figshare.9630980
title: Additional file 6: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: SNP data of 20 soybean accessions generated from genome resequencing. (XLSX 299 kb)
DOI: 10.6084/m9.figshare.9630980.v1
title: Additional file 6: of Genome wide association mapping and candidate gene analysis for hundred seed weight in soybean [Glycine max (L.) Merrill]

description: SNP data of 20 soybean accessions generated from genome resequencing. (XLSX 299 kb)
DOI: 10.6084/m9.figshare.25211768
title: Supplementary Material for: Colonic diverticulosis at colonoscopy in Africa: a systematic review and meta-analysis of pooled estimates

description: Background: There is need to ascertain any epidemiologic shift of diverticulosis among Africans with traditionally high fiber diet consumption patterns and rare diverticulosis prevalence. 
Methods: We systematically searched PubMed, Scopus, Cochrane Library, African Journal Online (AJOL) and Google Scholar. Eligibility criteria included full text observational and experimental human colonoscopy studies on asymptomatic and symptomatic African population from 1985-2022. Case reports, conference abstracts, dissertations, systematic reviews, and studies lacking colonoscopy findings were excluded. NIH quality assessment tool for observational cohort and cross-sectional studies was used to assess risk of bias. Meta-analysis was performed using the random-effect model. Heterogeneity was assessed using inconsistency (I2) statistics. 
Results: Thirty studies were included. Pooled prevalence rate of colonic diverticulosis was 9.1% (95%CI 7.1-11.2; I2=96.3%) with highest regional prevalence rate in West African studies at 11.3% (95%CI 7.6-14.9; I2=96.2%). Proportion of individuals with diverticulosis ≥50 years and male sex were 86.9 % (95%CI 80.5-92.1) and 65.2% (95%CI 55.0-74.8), respectively. Left colon had the highest diverticulosis frequency [37% (148/400)]. 
Bleeding/inflammation complications were sparingly detected [OR 0.2 (95%CI 0.03-0.75;p&lt;0.0001)].
Conclusion: Colonic diverticulosis was most common in males aged &gt;50. Left was colon predominantly affected. Regional variation in detection of diverticulosis was reported across Africa.
DOI: 10.6084/m9.figshare.11203973
title: Draft Genome Assembly of Takifugu bimaculatus

description: A draft genome assembly of <i>Takifugu bimaculatus</i>, generating using Pacbio sequencing technology, and assembled using Falcon.
DOI: 10.6084/m9.figshare.14210609
title: Data presented in "Addressing pediatric HIV pretreatment drug resistance and virologic failure in sub-Saharan Africa: A cost-effectiveness analysis of diagnostic-based strategies in children ≥ 3 years old"

description: Please see "Description of files" word document for overview of excel files included, which present data output from "Addressing pediatric HIV pretreatment drug resistance and virologic failure in sub-Saharan Africa: A cost-effectiveness analysis of diagnostic-based strategies in children ≥ 3 years old," published in Diagnostics.
DOI: 10.5281/zenodo.8328265
title: Fitness for Future: eLTER RI's Representation of Climate and Land Use Change

description: Data and code associated with the publication on the Fitness for Research Challenges of the eLTER Research Infrastructure. All data and code are provided within a .zip-folder.  
DataWithin the folder priority regions, all datasets relating to Figures 10 and 11 are stored and will be explained using Figure 11. From left to right in Figure 11, the shapefiles have the endings "RCP4.5_Category1 and 2 Sites_26_4param_weighted", "RCP8.5_Category1 and 2 Sites_26_4param_weighted", "RCP4.5_Category1 and 2 Sites_26" and "RCP8.5_Category1 and 2 Sites_26". 
Data directly depicting research challenges or their hotspots are found within the folder research_challenges. They are named as follows: RCP4.5 or RCP8.5 depicts the scenario, the T Pressure datasets underlie Figure 1, the P Pressure datasets Figure 2, SPEI Pressure Figure 4, Land Use Change Figure 6, and all z-transformed data Figure 7. 
Within the folder other_figures the data underlying Figure 3 ("T_P_ratio.tif") and underlying Figure 8 ("RepRasters_All.tif") are found.
 
CodeAll Code is found in the r_code folder. Scripts are numbered in order of processing. 01 - 03 regard the processing of climate scenario and historical climate data to produce and visualize baseline an scenario climate data. In 04 the model mean of nine individual simulations was produced. In 05 the PET was derived to allow for SPEI calculation and a model mean was derived in 06. Then, these data were transformed to pressures in 07 and 08. In 09 and 10 Robustness Measures were prepared and calculated. In 11, the Climatic Pressures derived were analysed (Fig. 1 - 5). In 12, they were transformed to allow for a Representativity Analysis to work, which was conducted in 13 for the Climatic Pressures only. Also, with 13 associated source scripts required for the Representativity Analysis are depicted.  In 14 - 16, Land Use Change data was processed, quantified (Fig. 6) and prepared for the Representativity Analysis. In 17, the Representativity Analysis was conducted for the Climatic Pressures and LUC combined, and in 17b Land Use Change was triple-weighted (Fig. 9). In 18, the outcomes of the different Representativity Analyses were compared (Fig. 10). In 19, Climate Hot Spots were derived from the Climatic Pressures (Fig. 7) and in 20 the Representedness Rasters were visualized (Fig. 8).
DOI: 10.5281/zenodo.8328266
title: Fitness for Future: eLTER RI's Representation of Climate and Land Use Change

description: Data and code associated with the publication on the Fitness for Research Challenges of the eLTER Research Infrastructure. All data and code are provided within a .zip-folder.  
DataWithin the folder priority regions, all datasets relating to Figures 10 and 11 are stored and will be explained using Figure 11. From left to right in Figure 11, the shapefiles have the endings "RCP4.5_Category1 and 2 Sites_26_4param_weighted", "RCP8.5_Category1 and 2 Sites_26_4param_weighted", "RCP4.5_Category1 and 2 Sites_26" and "RCP8.5_Category1 and 2 Sites_26". 
Data directly depicting research challenges or their hotspots are found within the folder research_challenges. They are named as follows: RCP4.5 or RCP8.5 depicts the scenario, the T Pressure datasets underlie Figure 1, the P Pressure datasets Figure 2, SPEI Pressure Figure 4, Land Use Change Figure 6, and all z-transformed data Figure 7. 
Within the folder other_figures the data underlying Figure 3 ("T_P_ratio.tif") and underlying Figure 8 ("RepRasters_All.tif") are found.
 
CodeAll Code is found in the r_code folder. Scripts are numbered in order of processing. 01 - 03 regard the processing of climate scenario and historical climate data to produce and visualize baseline an scenario climate data. In 04 the model mean of nine individual simulations was produced. In 05 the PET was derived to allow for SPEI calculation and a model mean was derived in 06. Then, these data were transformed to pressures in 07 and 08. In 09 and 10 Robustness Measures were prepared and calculated. In 11, the Climatic Pressures derived were analysed (Fig. 1 - 5). In 12, they were transformed to allow for a Representativity Analysis to work, which was conducted in 13 for the Climatic Pressures only. Also, with 13 associated source scripts required for the Representativity Analysis are depicted.  In 14 - 16, Land Use Change data was processed, quantified (Fig. 6) and prepared for the Representativity Analysis. In 17, the Representativity Analysis was conducted for the Climatic Pressures and LUC combined, and in 17b Land Use Change was triple-weighted (Fig. 9). In 18, the outcomes of the different Representativity Analyses were compared (Fig. 10). In 19, Climate Hot Spots were derived from the Climatic Pressures (Fig. 7) and in 20 the Representedness Rasters were visualized (Fig. 8).
DOI: 10.6084/m9.figshare.23255483.v1
title: Additional file 2 of Chloroplast genome characteristics and phylogeny of the sinodielsia clade (apiaceae: apioideae)

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.12246212
title: A conjunctive lipidomic approach reveals plasma ethanolamine plasmalogens and fatty acids as early diagnostic biomarkers for colorectal cancer patients

description: <b>Background</b>: Colorectal cancer (CRC) represents a third leading cause of cancer-related death worldwide. The reliable diagnostic biomarkers for detecting CRC at early stage is critical for decreasing the mortality. <b>Method</b>: A conjunctive lipidomic approach was employed to investigate the differences in plasma lipid profiles of CRC patients (n = 101) and healthy volunteers (n = 52). Based on UHPLC-Q-TOF MS and UHPLC-QQQ MS platforms, a total of 236 lipids were structurally detected. Multivariate data analysis was conducted for biomarkers discovery. <b>Results</b>: A total of 11 lipid species, including 1 Glycerophosphoethanolamine (PE), 3 ethanolamine plasmalogens (PlsEtn), 1 plasmanyl glycerophosphatidylethanolamine (PE-O), 3 fatty acids (FFA), 1 Fatty acid ester of hydroxyl fatty acid (FAHFA) and 2 Diacylglycerophosphates (PA) were identified to distinguish the CRC patients at early stage from healthy controls. In addition, these potential lipid biomarkers achieved an estimated AUC=0.981 in a validation set for univariate ROC analysis. <b>Conclusion</b>: By combining Q-TOF MS and QQQ MS analysis, the 11 lipids exhibited good performance in differentiating early-stage CRC and healthy control. This study also demonstrated that lipidomics is a powerful tool in discovering new potential biomarkers for cancer diagnosis.
DOI: 10.6084/m9.figshare.12246212.v1
title: A conjunctive lipidomic approach reveals plasma ethanolamine plasmalogens and fatty acids as early diagnostic biomarkers for colorectal cancer patients

description: <b>Background</b>: Colorectal cancer (CRC) represents a third leading cause of cancer-related death worldwide. The reliable diagnostic biomarkers for detecting CRC at early stage is critical for decreasing the mortality. <b>Method</b>: A conjunctive lipidomic approach was employed to investigate the differences in plasma lipid profiles of CRC patients (n = 101) and healthy volunteers (n = 52). Based on UHPLC-Q-TOF MS and UHPLC-QQQ MS platforms, a total of 236 lipids were structurally detected. Multivariate data analysis was conducted for biomarkers discovery. <b>Results</b>: A total of 11 lipid species, including 1 Glycerophosphoethanolamine (PE), 3 ethanolamine plasmalogens (PlsEtn), 1 plasmanyl glycerophosphatidylethanolamine (PE-O), 3 fatty acids (FFA), 1 Fatty acid ester of hydroxyl fatty acid (FAHFA) and 2 Diacylglycerophosphates (PA) were identified to distinguish the CRC patients at early stage from healthy controls. In addition, these potential lipid biomarkers achieved an estimated AUC=0.981 in a validation set for univariate ROC analysis. <b>Conclusion</b>: By combining Q-TOF MS and QQQ MS analysis, the 11 lipids exhibited good performance in differentiating early-stage CRC and healthy control. This study also demonstrated that lipidomics is a powerful tool in discovering new potential biomarkers for cancer diagnosis.
DOI: 10.6084/m9.figshare.20110566.v1
title: Additional file 2 of Transcriptome study digs out BMP2 involved in adipogenesis in sheep tails

description: Additional file 2: Table S1. The top 8 most significantly affected differentially expressed genes in Hu sheep and Tibetan sheep. Table S2. Primers used in this study for RT-qPCR.
DOI: 10.6084/m9.figshare.9631562
title: Additional file 10: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S7. Cis-acting elements in the RCA promoter region of C3 and C4 species. (XLSX 12 kb)
DOI: 10.6084/m9.figshare.9631571
title: Additional file 2: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S2. Polymorphic sites in the promoter region of ZmRCAÎ˛ and OsRCA. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.9631577
title: Additional file 3: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S3. Origin and haplotype of plant materials of maize and rice association populations in this study. (XLSX 11 kb)
DOI: 10.6084/m9.figshare.9631595
title: Additional file 5: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S4. SNP markers associated with the expression of OsRCA in association population. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.9631607
title: Additional file 1: of Genome-wide association analysis of egg production performance in chickens across the whole laying period

description: Table S1. The whole information of genome-wide significant and suggestively significant SNPs for AFE and ENs using genome-wide association studies. (XLSX 21 kb)
DOI: 10.6084/m9.figshare.9631610
title: Additional file 7: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S5. Polymorphisms in the OsRCA promoter region significantly associated with gene expression. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9631628
title: Additional file 9: of Genetic determinants controlling maize rubisco activase gene expression and a comparison with rice counterparts

description: Table S6. SNP markers associated with the maize grain yield in the association population. (XLSX 36 kb)
DOI: 10.6084/m9.figshare.9631634
title: Additional file 4: of Genome-wide association analysis of egg production performance in chickens across the whole laying period

description: Table S2. Basic information of SNP markers on a physical map after quality control. (XLSX 11 kb)
DOI: 10.21227/k1k8-jt58
title: removeOutliersFromCube.m

description: This MATLAB function efficiently detects and removes outliers from a specified time slice of a radar data cube, improving data quality for analysis. It utilizes statistical thresholds to identify outliers and offers the option to visualize and save the cleaning process as a GIF, facilitating a clearer understanding of data integrity enhancements. The functionality is crucial for preprocessing in meteorological studies, ensuring accurate representations in spatial and temporal data analyses.
DOI: 10.6084/m9.figshare.9631739
title: Additional file 10: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S10. Comparison of Tajimaâ s D values of all accession and subgroups. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.9631748
title: Additional file 11: of Signatures of differential selection in chloroplast genome between japonica and indica

description: The result of bayesian inference tree. (TRE 190 kb)
DOI: 10.6084/m9.figshare.9631769
title: Additional file 1: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S1. Summarize the information of the total samples. (XLSX 51 kb)
DOI: 10.6084/m9.figshare.9631778
title: Additional file 2: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S2. Summary of the total variant among the subgroups. (XLSX 15 kb)
DOI: 10.6084/m9.figshare.13294426.v1
title: Additional file 4 of Management of flying insects on expressways through an academic-industrial collaboration: evaluation of the effect of light wavelengths and meteorological factors on insect attraction

description: Additional file 4. Classification of insects captured by light traps in Yubari in 2017 and 2018.
DOI: 10.6084/m9.figshare.9631787
title: Additional file 3: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S3. Location of all the SNPs and InDels in their coding region in the reference detected in this study. (XLSX 114 kb)
DOI: 10.6084/m9.figshare.9631790
title: Additional file 9: of Genotyping, generation and proteomic profiling of the first human autosomal dominant osteopetrosis type II-specific induced pluripotent stem cells

description: Table S1. Proteomic analysis revealed the similar expression of pluripotency markers in the ADO2-iPSCs and NC-iPSCs. Table S2 GO functional enrichment analysis of the DEPs of the ADO2-iPSCs. Table S3 KEGG functional enrichment analysis of the DEPs of the ADO2-iPSCs. Table S4 Protein domain functional enrichment analysis of the DEPs of the ADO2-iPSCs. Table S5 GO functional enrichment analysis of the differently Khib-modified proteins of the ADO2-iPSCs. Table S6 KEGG functional enrichment analysis of the differently Khib-modified proteins of the ADO2-iPSCs. Table S7 Protein domain functional enrichment analysis of the differently Khib-modified proteins of the ADO2-iPSCs. (XLSX 32 kb)
DOI: 10.6084/m9.figshare.9631793
title: Additional file 4: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S4. Comparison of nucleotide diversity among all samples, Asian rice and wild rice. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.13294432.v1
title: Additional file 6 of Management of flying insects on expressways through an academic-industrial collaboration: evaluation of the effect of light wavelengths and meteorological factors on insect attraction

description: Additional file 6. Raw data and bar graphs based on results of experiments in 2017 showing the preferences of aquatic insects including caddisflies and dobsonflies to broadband wavelengths compared to moths.
DOI: 10.6084/m9.figshare.9631796
title: Additional file 5: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S5. Comparison of nucleotide diversity of indica, O. rufipogon, O. nivara and japonica. (XLSX 18 kb)
DOI: 10.6084/m9.figshare.9631799
title: Additional file 6: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S6 Reduction of nucleotide diversity between indica and japonica in the cp genome. (XLSX 16 kb)
DOI: 10.6084/m9.figshare.9631808
title: Additional file 7: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S7. IAM, TPM and SMM hypothesis of selection events. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9631817
title: Additional file 8: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S8. Allele frequency information of indica, temperate japonica and tropical japonica. (XLSX 23 kb)
DOI: 10.6084/m9.figshare.9631823
title: Additional file 9: of Signatures of differential selection in chloroplast genome between japonica and indica

description: Table S9 Ka and Ks value among chloroplast genome. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.7010528
title: Wu et al., 2018

description: The weather, CTD and ADCP data used in Wu et al., 2018
DOI: 10.6084/m9.figshare.24312520
title: Whistler - Mode Wave Generation During Interplanetary Shock Events in the Earth’s Lunar Plasma Environment

description: Data Files for GRL Manuscript titled "Whistler - Mode Wave Generation During Interplanetary Shock Events in the Earth’s Lunar Plasma Environment"
DOI: 10.6084/m9.figshare.13294585
title: Additional file 1 of Paxillin mediates ATP-induced activation of P2X7 receptor and NLRP3 inflammasome

description: Additional file 1.
DOI: 10.4121/21166810
title: Data of Blood tests, imaging tests, and genetic testing results of probands

description: The genetic mutations and two-years follow-up situation in a twin family with heterozygous familial hypercholesterolemia (HeFH) .
DOI: 10.4121/21166810.v1
title: Data of Blood tests, imaging tests, and genetic testing results of probands

description: The genetic mutations and two-years follow-up situation in a twin family with heterozygous familial hypercholesterolemia (HeFH) .
DOI: 10.6084/m9.figshare.13294393.v1
title: Additional file 3 of Genomics and lipidomics analysis of the biotechnologically important oleaginous red yeast Rhodotorula glutinis ZHK provides new insights into its lipid and carotenoid metabolism

description: Additional file 3. SNP/InDel annotations resulted from RNA-seq data.
DOI: 10.6084/m9.figshare.13294378.v1
title: Additional file 10 of Genomics and lipidomics analysis of the biotechnologically important oleaginous red yeast Rhodotorula glutinis ZHK provides new insights into its lipid and carotenoid metabolism

description: Additional file 10. Genomic synteny analysis between the ZHK and its closely related species Rhodotorula graminis.
DOI: 10.6084/m9.figshare.13294393
title: Additional file 3 of Genomics and lipidomics analysis of the biotechnologically important oleaginous red yeast Rhodotorula glutinis ZHK provides new insights into its lipid and carotenoid metabolism

description: Additional file 3. SNP/InDel annotations resulted from RNA-seq data.