cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14345365
title: DNA methylation signatures in cord blood associated with birthweight are enriched for dmCpGs previously associated with maternal hypertension or pre-eclampsia, smoking and folic acid intake

description: Many epidemiological studies have linked low birthweight to an increased risk of non-communicable diseases (NCDs) in later life, with epigenetic proceseses suggested as an underlying mechanism. Here, we sought to identify neonatal methylation changes associated with birthweight, at the individual CpG and genomic regional level, and whether the birthweight-associated methylation signatures were associated with specific maternal factors. Using the Illumina Human Methylation EPIC array, we assessed DNA methylation in the cord blood of 557 and 483 infants from the UK Pregnancies Better Eating and Activity Trial and Southampton Women’s Survey, respectively. Adjusting for gestational age and other covariates, an epigenome-wide association study identified 2911 (FDR≤0.05) and 236 (Bonferroni corrected p ≤ 6.45×10−8) differentially methylated CpGs (dmCpGs), and 1230 differentially methylated regions (DMRs) (Stouffer ≤0.05) associated with birthweight. The top birthweight-associated dmCpG was located within the Homeobox Telomere-Binding Protein 1 (HMBOX1) gene with a 195 g (95%CI: −241, −149 g) decrease in birthweight per 10% increase in methylation, while the top DMR was located within the promoter of corticotropin-releasing hormone-binding protein (CRHBP). Furthermore, the birthweight-related dmCpGs were enriched for dmCpGs previously associated with gestational hypertension/pre-eclampsia (14.51%, p = 1.37×10−255), maternal smoking (7.71%, p = 1.50 x 10−57) and maternal plasma folate levels during pregnancy (0.33%, p = 0.029). The identification of birthweight-associated methylation markers, particularly those connected to specific pregnancy complications and exposures, may provide insights into the developmental pathways that affect birthweight and suggest surrogate markers to identify adverse prenatal exposures for stratifying for individuals at risk of later NCDs.
DOI: 10.6084/m9.figshare.9637403
title: Additional file 12: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S4. Mitochondrial volumes, ATP content and VSL across 10 species. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9637403.v1
title: Additional file 12: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S4. Mitochondrial volumes, ATP content and VSL across 10 species. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9637406
title: Additional file 13: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S5. Regression correlation analysis data of the sperm ultrastuctures across 10 species. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.10675148.v2
title: Table S1 from The unity and diversity of the ciliary central apparatus.

description: Sources of genomic data used in this study
DOI: 10.6084/m9.figshare.9637406.v1
title: Additional file 13: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S5. Regression correlation analysis data of the sperm ultrastuctures across 10 species. (XLSX 20 kb)
DOI: 10.6084/m9.figshare.9637409
title: Additional file 14: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S6. The parameters of asthenozoospermic and normozoospermic semen samples. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.9637409.v1
title: Additional file 14: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S6. The parameters of asthenozoospermic and normozoospermic semen samples. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.10675160.v1
title: Table S2 from The unity and diversity of the ciliary central apparatus

description: Orthologs identified for C. reinhardtii CA-specific proteins
DOI: 10.6084/m9.figshare.10675160.v2
title: Table S2 from The unity and diversity of the ciliary central apparatus.

description: Orthologs identified for C. reinhardtii CA-specific proteins
DOI: 10.6084/m9.figshare.20105445
title: Additional file 5 of Identification, characterization and functional analysis of gonadal long noncoding RNAs in a protogynous hermaphroditic teleost fish, the ricefield eel (Monopterus albus)

description: Additional file 5: Dataset S2. GO terms with significant differences among different developmental stages.
DOI: 10.6084/m9.figshare.9637430
title: Additional file 4: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Figure S4. Relationships between areas of odfs 1–9 and outer areas across 10 species. A-J. The scatter plots show the distribution of the odfs 1–9 areas along flagella across 10 species. The dash lines, green lines, blue lines, pink lines, dot lines, solid lines, light blue lines, grey lines and red lines are regression lines of odfs 1–9 in species, respectively. (ZIP 2159 kb)
DOI: 10.6084/m9.figshare.9637430.v1
title: Additional file 4: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Figure S4. Relationships between areas of odfs 1–9 and outer areas across 10 species. A-J. The scatter plots show the distribution of the odfs 1–9 areas along flagella across 10 species. The dash lines, green lines, blue lines, pink lines, dot lines, solid lines, light blue lines, grey lines and red lines are regression lines of odfs 1–9 in species, respectively. (ZIP 2159 kb)
DOI: 10.6084/m9.figshare.14345365.v1
title: DNA methylation signatures in cord blood associated with birthweight are enriched for dmCpGs previously associated with maternal hypertension or pre-eclampsia, smoking and folic acid intake

description: Many epidemiological studies have linked low birthweight to an increased risk of non-communicable diseases (NCDs) in later life, with epigenetic proceseses suggested as an underlying mechanism. Here, we sought to identify neonatal methylation changes associated with birthweight, at both the individual CpG and genomic regional level, and whether the birthweight-associated methylation signatures were associated with specific maternal factors. Using the Illumina Human MethylationEPIC array we assessed DNA methylation in the cord blood of 557 and 483 infants from the UK Pregnancies Better Eating and Activity Trial and Southampton Women’s Survey, respectively. Adjusting for gestational age and other covariates, an epigenome-wide association study identified 2911 (FDR≤0.05) and 236 (Bonferroni corrected p≤6.45x10<sup>−8</sup>) differentially methylated CpGs (dmCpGs), and 1230 differentially methylated regions (DMRs) (Stouffer ≤0.05) associated with birthweight. The top birthweight-associated dmCpG was located within the Homeobox Telomere-Binding Protein 1 (<i>HMBOX1</i>) gene with a 195g (95%CI: -241, -149g) decrease in birthweight per 10% increase in methylation, while the top DMR was located within the promoter of corticotropin releasing hormone binding protein (<i>CRHBP</i>).. Furthermore, the birthweight-related dmCpGs were enriched for dmCpGs previously associated with gestational hypertension/pre-eclampsia (14.51%, p=1.37x10<sup>−255</sup>), maternal smoking (7.71%, p=1.50x10<sup>−57</sup>) and maternal plasma folate levels during pregnancy (0.33%, p=0.029). The identification of birthweight-associated methylation markers, particularly those connected to specific pregnancy complications and exposures, may provide insights into the developmental pathways that affect birthweight and/or suggest surrogate markers to identify adverse prenatal exposures for stratifying for individuals at risk of later NCDs.
DOI: 10.6084/m9.figshare.14345365.v2
title: DNA methylation signatures in cord blood associated with birthweight are enriched for dmCpGs previously associated with maternal hypertension or pre-eclampsia, smoking and folic acid intake

description: Many epidemiological studies have linked low birthweight to an increased risk of non-communicable diseases (NCDs) in later life, with epigenetic proceseses suggested as an underlying mechanism. Here, we sought to identify neonatal methylation changes associated with birthweight, at the individual CpG and genomic regional level, and whether the birthweight-associated methylation signatures were associated with specific maternal factors. Using the Illumina Human Methylation EPIC array, we assessed DNA methylation in the cord blood of 557 and 483 infants from the UK Pregnancies Better Eating and Activity Trial and Southampton Women’s Survey, respectively. Adjusting for gestational age and other covariates, an epigenome-wide association study identified 2911 (FDR≤0.05) and 236 (Bonferroni corrected p ≤ 6.45×10−8) differentially methylated CpGs (dmCpGs), and 1230 differentially methylated regions (DMRs) (Stouffer ≤0.05) associated with birthweight. The top birthweight-associated dmCpG was located within the Homeobox Telomere-Binding Protein 1 (HMBOX1) gene with a 195 g (95%CI: −241, −149 g) decrease in birthweight per 10% increase in methylation, while the top DMR was located within the promoter of corticotropin-releasing hormone-binding protein (CRHBP). Furthermore, the birthweight-related dmCpGs were enriched for dmCpGs previously associated with gestational hypertension/pre-eclampsia (14.51%, p = 1.37×10−255), maternal smoking (7.71%, p = 1.50 x 10−57) and maternal plasma folate levels during pregnancy (0.33%, p = 0.029). The identification of birthweight-associated methylation markers, particularly those connected to specific pregnancy complications and exposures, may provide insights into the developmental pathways that affect birthweight and suggest surrogate markers to identify adverse prenatal exposures for stratifying for individuals at risk of later NCDs.
DOI: 10.6084/m9.figshare.9637463
title: Additional file 7: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Figure S7. Statistical results of areas of odfs 1â 9 along flagella across species. A-I. Scatter plots show the mean areas of odfs 1â 9 from position 1 to position 9. Open inverse triangles, open hexagons, solid squares, open triangles, solid circles, solid triangles, solid hexagons, open squares, solid rhombuses and open circles represent data from human, rabbit, dog, pig, guinea pig, goat, bull, mouse, golden hamster and rat, respectively. (ZIP 1014 kb)
DOI: 10.6084/m9.figshare.9637463.v1
title: Additional file 7: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Figure S7. Statistical results of areas of odfs 1â 9 along flagella across species. A-I. Scatter plots show the mean areas of odfs 1â 9 from position 1 to position 9. Open inverse triangles, open hexagons, solid squares, open triangles, solid circles, solid triangles, solid hexagons, open squares, solid rhombuses and open circles represent data from human, rabbit, dog, pig, guinea pig, goat, bull, mouse, golden hamster and rat, respectively. (ZIP 1014 kb)
DOI: 10.6084/m9.figshare.19588554
title: Additional file 2 of Increased COVID-19 mortality rate in rare disease patients: a retrospective cohort study in participants of the Genomics England 100,000 Genomes project

description: Additional file 2: Table S1. Univariable and multivariable ORs for association between rare disease groups/specific diseases and COVID-19
DOI: 10.6084/m9.figshare.21153748.v1
title: Additional file 2 of Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma

description: Additional file 2. Table S1. The list of immune signatures gene sets.
DOI: 10.6084/m9.figshare.21153754.v1
title: Additional file 4 of Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma

description: Additional file 4. Table S3. The overlapping differentially expressed genes (DEGs) among the three tumor molecular subtypes.
DOI: 10.6084/m9.figshare.19588554.v1
title: Additional file 2 of Increased COVID-19 mortality rate in rare disease patients: a retrospective cohort study in participants of the Genomics England 100,000 Genomes project

description: Additional file 2: Table S1. Univariable and multivariable ORs for association between rare disease groups/specific diseases and COVID-19
DOI: 10.6084/m9.figshare.13297069
title: Additional file 2 of Immunological classification of gliomas based on immunogenomic profiling

description: Additional file 2: Table S2. The gene sets representing immune cells or signatures, pathways, and biological processes.
DOI: 10.6084/m9.figshare.9637478
title: Additional file 9: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S1. The mean parameters of the sperm morphology. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.9637478.v1
title: Additional file 9: of Comparative analysis of mammalian sperm ultrastructure reveals relationships between sperm morphology, mitochondrial functions and motility

description: Table S1. The mean parameters of the sperm morphology. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.14345721.v1
title: Change in mortality rates of respiratory disease during the COVID-19 pandemic

description: This study explored the change in mortality rates of respiratory disease during the corona virus disease 2019 (COVID-19) pandemic. Death data of registered residents of Suzhou from 2014 to 2020 were collected and the weekly mortality rates due to respiratory disease and all deaths were analyzed. The differences in mortality rates during the pandemic and the same period in previous years were compared. Before the pandemic, the crude mortality rate (CMR) and standardized mortality rate (SMR) of Suzhou residents including respiratory disease, were not much different from those in previous years. During the emergency period, the CMR of Suzhou residents was 180.2/100,000 and the SMR was 85.5/100,000, decreasing by 9.1% and 14.6%, respectively; the CMR of respiratory disease was 16.4/100,000 and the SMR was 6.8/100,000, down 41.4% and 44.9%, respectively. Regardless of the mortality rates of all deaths or respiratory disease, the rates were higher in males than in females, although males had aslightly greater decrease in all deaths during the emergency period compared with females, and the opposite was true for respiratory disease. During the pandemic, the death rate of residents decreased, especially that due to respiratory disease.
DOI: 10.6084/m9.figshare.21153757
title: Additional file 5 of Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma

description: Additional file 5. Table S4. Multivariate Cox analysis (stepwise regression models) for the construction of an IRGS.
DOI: 10.6084/m9.figshare.21153763
title: Additional file 7 of Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma

description: Additional file 7. Table S6. Analysis of differential gene expression between high and low IRGS groups.
DOI: 10.6084/m9.figshare.9637562
title: Additional file 1: of Genome-wide identification of circular RNAs in peanut (Arachis hypogaea L.)

description: Table S1. Raw data of rRNA-depleted sequencing in peanut. Table S2. A detailed summary of RibominusSeq data after primary quality control for each sample. Table S3. Number of circRNAs derived from the same hosting gene. Table S4. Distribution of 347 circRNAs on 20 chromosomes of peanut. Table S5. Sequence of divergent primer pairs designed for 15 circRNAs. (XLS 44 kb)
DOI: 10.6084/m9.figshare.9637562.v1
title: Additional file 1: of Genome-wide identification of circular RNAs in peanut (Arachis hypogaea L.)

description: Table S1. Raw data of rRNA-depleted sequencing in peanut. Table S2. A detailed summary of RibominusSeq data after primary quality control for each sample. Table S3. Number of circRNAs derived from the same hosting gene. Table S4. Distribution of 347 circRNAs on 20 chromosomes of peanut. Table S5. Sequence of divergent primer pairs designed for 15 circRNAs. (XLS 44 kb)
DOI: 10.5517/ccdc.csd.cc2bj669
title: CCDC 2160520: Experimental Crystal Structure Determination

description: Related Article: Thach N. Tu, Manfred Scheer|2023|Chem (Cell Press)|9|227|doi:10.1016/j.chempr.2022.10.016
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.cc2bj68c
title: CCDC 2160522: Experimental Crystal Structure Determination

description: Related Article: Thach N. Tu, Manfred Scheer|2023|Chem (Cell Press)|9|227|doi:10.1016/j.chempr.2022.10.016
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.cc2gkz12
title: CCDC 2281384: Experimental Crystal Structure Determination

description: Related Article: Fang Guo, Chun-sheng Wei, Wen-sheng Guo|2002|Liaoning Daxue Xuebao,Ziran Kexueban|29|103|
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.cc2g5684
title: CCDC 2269115: Experimental Crystal Structure Determination

description: Related Article: Shu-Ling Sie, Surabhi Kamal, Zong-Zhan Lu, Ling-Fang Wei, Tzuoo-Tsair Luo, Yen-Hsiang Liu, Chao-Wan Chang, Kai-Ming Chi, Kuang-Lieh Lu|2023|CrystEngComm|25|6635|doi:10.1039/D3CE01001E
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.11917251.v1
title: Additional file 4 of Transcriptome differences in adipose stromal cells derived from pre- and postmenopausal women

description: Additional file 4. Complete pathway analysis results.
DOI: 10.6084/m9.figshare.13297069.v1
title: Additional file 2 of Immunological classification of gliomas based on immunogenomic profiling

description: Additional file 2: Table S2. The gene sets representing immune cells or signatures, pathways, and biological processes.
DOI: 10.6084/m9.figshare.20105448
title: Additional file 6 of Identification, characterization and functional analysis of gonadal long noncoding RNAs in a protogynous hermaphroditic teleost fish, the ricefield eel (Monopterus albus)

description: Additional file 6: Dataset S3. DE-lncRNAs and their targets in the significantly enriched GO terms and KEGG pathways.
DOI: 10.6084/m9.figshare.16435801.v1
title: Additional file 2 of Formation mechanisms of ringwoodite: clues from the Martian meteorite Northwest Africa 8705

description: Additional file 2. Additional tables of NWA 8705.
DOI: 10.6084/m9.figshare.16435843
title: Additional file 8 of Acute depletion of CTCF rewires genome-wide chromatin accessibility

description: Additional file 8: Supplementary Tables -Tables S7. Summary of RNA-seq data.
DOI: 10.6084/m9.figshare.11917251
title: Additional file 4 of Transcriptome differences in adipose stromal cells derived from pre- and postmenopausal women

description: Additional file 4. Complete pathway analysis results.
DOI: 10.6084/m9.figshare.23258564
title: Supplementary Material for: Relationship between dialysate bicarbonate concentration and all-cause mortality in hemodialysis patients

description: Introduction: The optimal dialysate bicarbonate concentration (DBIC) for hemodialysis (HD) remains controversial. Herein, we analyzed the effect of dialysate bicarbonate levels on mortality in hemodialysis patients. 
Methods: Patients undergoing maintenance hemodialysis were recruited from the hemodialysis unit of the Daping Hospital. Patients were categorized into quartiles according to their DBIC level (quartile 1: &lt;31.25 mmol/L, n=77; quartile 2: 31.25–32.31 mmol/L, n=76; quartile 3: 32.31–33.6 mmol/L; n=81; quartile 4: ≥33.6 mmol/L, n=79). Demographic and clinical data were collected. Survival curves were estimated using the Kaplan–Meier method. A Cox proportional hazards regression model was used to estimate the association between DBIC and all-cause mortality. 
Results: We included 313 patients undergoing maintenance HD with a mean DBIC of 32.16±1.59 mmol/L (range, 27.20–34.72 mmol/L). The patients in quartile 4 were more likely to have higher pre- and post-hemodialysis serum bicarbonate concentrations than those in other quartiles. The mortality rate was lowest in quartile 2 (10.53%). The survival time was significantly lower in the quartile 4 group than in the other quartiles (p=0. 008, log-rank test). After full adjustment, the hazard ratio (per 3 mmol/L higher DBIC) for all-cause mortality was 4.29 (95% confidence interval, 2.11–8.47) in all patients, whereas no significant association was observed between DBIC and initial hospitalization.
Conclusions: Our data indicate that DBIC is positively associated with all-cause mortality. A DBIC concentration of 31–32 mmol/L may benefit patient outcomes. This study provides an evidence-based medical basis for optimal dialysis prescription in the future.
DOI: 10.6084/m9.figshare.20105439.v1
title: Additional file 3 of Identification, characterization and functional analysis of gonadal long noncoding RNAs in a protogynous hermaphroditic teleost fish, the ricefield eel (Monopterus albus)

description: Additional file 3: Dataset S1. DE-lncRNA annotation.