cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28280149.v1
title: Unveiling the role of miRNAs in Diminished Ovarian Reserve: an in silico network approach

description: MicroRNAs (miRNAs) have acquired an increased recognition to unravel the complex molecular mechanisms underlying Diminished Ovarian Reserve (DOR), one of the main responsible for infertility. To investigate the impact of miRNA profiles in granulosa cells and follicular fluid, crucial players in follicle development, this study employed a computational network theory approach to reconstruct potential pathways regulated by miRNAs in granulosa cells and follicular fluid of women suffering from DOR. Available data from published research were collected to create the FGC_MiRNome_MC, a representation of miRNA target genes and their interactions. 365 hubs were identified within the network, representing potential key regulators, and 210 nodes that act as both hubs and bottlenecks (H&BN nodes), suggesting that they may control the information flow within the network. GO enrichment analysis of the 210 H&BN nodes revealed their involvement in fundamental cellular processes relevant to ovarian function. In particular, the cluster analysis identified several shared pathways between cluster 1 and cluster 2 involved in the RAS/MAPK pathway, which plays a critical role in cell proliferation, differentiation and survival. These findings suggest that miRNAs play a significant role in DOR and highlight the potential of the RAS/MAPK pathway as a target for further investigation. Additionally, the genes identified as both hubs and bottlenecks revealed interesting connections to reproductive health in KO mice models. This <i>in silico</i> approach provides valuable insights into potential biomarkers and therapeutic targets for age-related reproductive disorders.
DOI: 10.6084/m9.figshare.28599342
title: Whole exome sequencing uncovers rare variants associated with PCOS susceptibility in Indian women

description: Polycystic ovary syndrome (PCOS) is a complex polygenic endocrinopathy affecting 5–20% of reproductive-age women. Familial studies, candidate gene studies, and GWAS have identified multiple PCOS-associated genetic loci. This study aims to identify the functional variants associated with PCOS. We applied whole exome sequencing (WES) to identify functional variants among eighty-five well-characterized women with PCOS. The annotated variants were filtered based on minor allele frequency and <i>in-silico</i> pathogenicity prediction. We found a significant association of 234 rare pathogenic nonsynonymous variants in 201 genes with PCOS in our study group. These genes are linked to steroid hormone biosynthesis, ovarian steroidogenesis, insulin resistance, and PI3K-Akt signaling pathway which are influential in PCOS pathophysiology. Further, several rare variants were found to be unique to women with and without insulin resistance, and enrichment analysis revealed that carbohydrate and lipid metabolism was especially deranged in insulin-resistant PCOS women. Variants of the steroidogenesis pathway were validated by Sanger sequencing including rs368902124 (<i>CYP19A1</i>), rs143286842 (<i>IGF1R</i>), and rs555458296 (<i>BMP-6</i>). <i>In-silico</i> analysis by DUET showed that these variants destabilized the folding of their corresponding protein. Women carrying these rare variants presented with altered hormonal profiles and clinical signs of hyperandrogenism and hyperinsulinemia, emphasizing their impact on PCOS pathophysiology. Several functional rare variants have been revealed to be associated with increased PCOS risk in the present study thus, expanding the genetic susceptibility landscape of Indian women to PCOS.
DOI: 10.6084/m9.figshare.28599342.v1
title: Whole exome sequencing uncovers rare variants associated with PCOS susceptibility in Indian women

description: Polycystic ovary syndrome (PCOS) is a complex polygenic endocrinopathy affecting 5–20% of reproductive-age women. Familial studies, candidate gene studies, and GWAS have identified multiple PCOS-associated genetic loci. This study aims to identify the functional variants associated with PCOS. We applied whole exome sequencing (WES) to identify functional variants among eighty-five well-characterized women with PCOS. The annotated variants were filtered based on minor allele frequency and <i>in-silico</i> pathogenicity prediction. We found a significant association of 234 rare pathogenic nonsynonymous variants in 201 genes with PCOS in our study group. These genes are linked to steroid hormone biosynthesis, ovarian steroidogenesis, insulin resistance, and PI3K-Akt signaling pathway which are influential in PCOS pathophysiology. Further, several rare variants were found to be unique to women with and without insulin resistance, and enrichment analysis revealed that carbohydrate and lipid metabolism was especially deranged in insulin-resistant PCOS women. Variants of the steroidogenesis pathway were validated by Sanger sequencing including rs368902124 (<i>CYP19A1</i>), rs143286842 (<i>IGF1R</i>), and rs555458296 (<i>BMP-6</i>). <i>In-silico</i> analysis by DUET showed that these variants destabilized the folding of their corresponding protein. Women carrying these rare variants presented with altered hormonal profiles and clinical signs of hyperandrogenism and hyperinsulinemia, emphasizing their impact on PCOS pathophysiology. Several functional rare variants have been revealed to be associated with increased PCOS risk in the present study thus, expanding the genetic susceptibility landscape of Indian women to PCOS.
DOI: 10.6084/m9.figshare.28555848
title: Diagnostic accuracy of plasma microRNA as a potential biomarker for detection of endometriosis

description: Endometriosis is a complex condition with a wide range of clinical manifestations, presenting significant challenges, particularly for young women. Its diverse and often perplexing presentations pose difficulties within the medical community. Laparoscopy remains the gold-standard diagnostic tool for endometriosis. However, alternative diagnostic methods are valuable for monitoring disease progression, assessing the likelihood of recurrence, reducing the need for surgical procedures, and facilitating timely decisions regarding fertility concerns. Recent research highlights the potential of microRNAs (miRNAs) as an alternative diagnostic test for endometriosis. A case-control study was conducted at the infertility unit of Arash Women’s Hospital, involving 50 female participants, 25 with endometriosis and 25 without it. Plasma samples were collected and analyzed for the expression levels of 16 miRNAs using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Diagnostic accuracy measures were evaluated to establish a reliable and comparable diagnostic framework. Compared to the control group, downregulation of 11 miRNAs and upregulation of 5 miRNAs were observed in the case group. Regarding expression patterns, evidence from this study indicates that half of the evaluated miRNAs fall into the high-agreement category with similar studies. Sensitivity (SN) of the evaluated miRNAs ranged from 64.0% to 88.0%, while specificity (SP) ranged from 56.0% to 88.0%. The area under the curve (AUC) was reported between 0.619 (miR-135a) and 0.846 (miR-340). These findings suggest that the evaluated miRNAs demonstrate moderate to acceptable diagnostic accuracy for endometriosis.
DOI: 10.6084/m9.figshare.28555848.v1
title: Diagnostic accuracy of plasma microRNA as a potential biomarker for detection of endometriosis

description: Endometriosis is a complex condition with a wide range of clinical manifestations, presenting significant challenges, particularly for young women. Its diverse and often perplexing presentations pose difficulties within the medical community. Laparoscopy remains the gold-standard diagnostic tool for endometriosis. However, alternative diagnostic methods are valuable for monitoring disease progression, assessing the likelihood of recurrence, reducing the need for surgical procedures, and facilitating timely decisions regarding fertility concerns. Recent research highlights the potential of microRNAs (miRNAs) as an alternative diagnostic test for endometriosis. A case-control study was conducted at the infertility unit of Arash Women’s Hospital, involving 50 female participants, 25 with endometriosis and 25 without it. Plasma samples were collected and analyzed for the expression levels of 16 miRNAs using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Diagnostic accuracy measures were evaluated to establish a reliable and comparable diagnostic framework. Compared to the control group, downregulation of 11 miRNAs and upregulation of 5 miRNAs were observed in the case group. Regarding expression patterns, evidence from this study indicates that half of the evaluated miRNAs fall into the high-agreement category with similar studies. Sensitivity (SN) of the evaluated miRNAs ranged from 64.0% to 88.0%, while specificity (SP) ranged from 56.0% to 88.0%. The area under the curve (AUC) was reported between 0.619 (miR-135a) and 0.846 (miR-340). These findings suggest that the evaluated miRNAs demonstrate moderate to acceptable diagnostic accuracy for endometriosis.
DOI: 10.6084/m9.figshare.30174247
title: Prediction of polycystic ovary syndrome using machine learning with SFS and Boruta feature selection: an explainable AI approach

description: Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder affecting numerous women of reproductive age, characterized by a variety of clinical and biochemical features. Accurate classification and diagnosis of PCOS remains challenging due to the heterogeneous nature of its manifestations. This study introduces a robust machine learning framework that combines a voting ensemble model with two distinct feature selection techniques, Sequential Forward Selection (SFS) and Boruta, to enhance the accuracy in classifying PCOS. We also utilized Explainable Artificial Intelligence (XAI) techniques, such as Shapley Additive Explanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), Partial Dependence Plot (PDP), AnchorTabular, and Permutation Importance, to interpret the ensemble model. These methods provide essential insights into the significance of key features for predicting PCOS patients. Results show that the proposed ensemble learning model achieved optimal performance with the feature selection technique used. Specifically, the proposed voting ensemble classifier and features picked by SFS had the highest accuracy among all models. This method can help in PCOS diagnosis and support early intervention.
DOI: 10.6084/m9.figshare.30174247.v1
title: Prediction of polycystic ovary syndrome using machine learning with SFS and Boruta feature selection: an explainable AI approach

description: Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder affecting numerous women of reproductive age, characterized by a variety of clinical and biochemical features. Accurate classification and diagnosis of PCOS remains challenging due to the heterogeneous nature of its manifestations. This study introduces a robust machine learning framework that combines a voting ensemble model with two distinct feature selection techniques, Sequential Forward Selection (SFS) and Boruta, to enhance the accuracy in classifying PCOS. We also utilized Explainable Artificial Intelligence (XAI) techniques, such as Shapley Additive Explanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), Partial Dependence Plot (PDP), AnchorTabular, and Permutation Importance, to interpret the ensemble model. These methods provide essential insights into the significance of key features for predicting PCOS patients. Results show that the proposed ensemble learning model achieved optimal performance with the feature selection technique used. Specifically, the proposed voting ensemble classifier and features picked by SFS had the highest accuracy among all models. This method can help in PCOS diagnosis and support early intervention.
DOI: 10.6084/m9.figshare.30774494
title: Cytogenetic alterations in infertile men seeking assisted reproduction: associations with semen quality

description: Male infertility accounts for approximately half of all infertility cases and is often linked to chromosomal abnormalities. While numerical and structural rearrangements are well recognized, the clinical significance of chromosomal polymorphisms remains unclear. To characterize the spectrum of cytogenetic alterations – including polymorphisms, structural rearrangements, and numerical changes – in men presenting with infertility and to assess their incidence on men with semen abnormalities. In this retrospective observational study, peripheral blood samples from 62 patients with detected cytogenetic alterations were collected at Genos Laboratory (Unimed Diagnostic Center) in Bauru, Brazil, between January 2015 and June 2020. Semen analysis reports for these patients were retrieved from the Fertility Clinic in Bauru, Brazil. Following specialist evaluation, a final cohort of 38 men diagnosed with infertility was analyzed. Results: Chromosomal polymorphisms were the most frequent alteration (77.4%), followed by structural rearrangements (17.7%) and numerical changes (4.8%). Among polymorphism carriers, 58% exhibited at least one abnormal semen parameter, most commonly asthenozoospermia (42%), teratozoospermia (38%), and oligozoospermia (33%). The 46,XYqh<sup>+</sup> variant predominated (50%), with half of these cases demonstrating semen abnormalities. Double polymorphisms (46,XY9qh<sup>+</sup> and 46,XY22ps<sup>+</sup>; <i>n</i> = 8) were uniformly associated with oligozoospermia and teratozoospermia. Structural alterations – pericentric inversion of chromosome 9 and Robertsonian translocation rob(13;14)(q10q10) – were found in 11 patients; 72% of these also had semen abnormalities. Numerical alterations were rare but associated with abnormal semen parameters in 66% of cases. Chromosomal polymorphisms, though traditionally viewed as benign, were frequently detected in compromised semen quality in this cohort. Structural and numerical rearrangements, while less common, were detected in a higher proportion of abnormal semen parameters. These findings underscore the value of comprehensive cytogenetic screening in the evaluation of male infertility.
DOI: 10.6084/m9.figshare.30774494.v1
title: Cytogenetic alterations in infertile men seeking assisted reproduction: associations with semen quality

description: Male infertility accounts for approximately half of all infertility cases and is often linked to chromosomal abnormalities. While numerical and structural rearrangements are well recognized, the clinical significance of chromosomal polymorphisms remains unclear. To characterize the spectrum of cytogenetic alterations – including polymorphisms, structural rearrangements, and numerical changes – in men presenting with infertility and to assess their incidence on men with semen abnormalities. In this retrospective observational study, peripheral blood samples from 62 patients with detected cytogenetic alterations were collected at Genos Laboratory (Unimed Diagnostic Center) in Bauru, Brazil, between January 2015 and June 2020. Semen analysis reports for these patients were retrieved from the Fertility Clinic in Bauru, Brazil. Following specialist evaluation, a final cohort of 38 men diagnosed with infertility was analyzed. Results: Chromosomal polymorphisms were the most frequent alteration (77.4%), followed by structural rearrangements (17.7%) and numerical changes (4.8%). Among polymorphism carriers, 58% exhibited at least one abnormal semen parameter, most commonly asthenozoospermia (42%), teratozoospermia (38%), and oligozoospermia (33%). The 46,XYqh<sup>+</sup> variant predominated (50%), with half of these cases demonstrating semen abnormalities. Double polymorphisms (46,XY9qh<sup>+</sup> and 46,XY22ps<sup>+</sup>; <i>n</i> = 8) were uniformly associated with oligozoospermia and teratozoospermia. Structural alterations – pericentric inversion of chromosome 9 and Robertsonian translocation rob(13;14)(q10q10) – were found in 11 patients; 72% of these also had semen abnormalities. Numerical alterations were rare but associated with abnormal semen parameters in 66% of cases. Chromosomal polymorphisms, though traditionally viewed as benign, were frequently detected in compromised semen quality in this cohort. Structural and numerical rearrangements, while less common, were detected in a higher proportion of abnormal semen parameters. These findings underscore the value of comprehensive cytogenetic screening in the evaluation of male infertility.
DOI: 10.6084/m9.figshare.29206277
title: Investigation of testis proteome alterations associated with male infertility in <i>Dcaf17</i>-deficient mice

description: Disruption of <i>Dcaf17</i> in mice resulted in male infertility with severe spermatogenesis defects. To investigate the molecular basis of infertility phenotype, we examined testicular proteomes of wild-type (WT) and <i>Dcaf17<sup>-/-</sup></i> mice using a mass spectrometry-based approach. We identified 727 and 525 differentially expressed proteins (DEPs) in 3- and 8-week old testes of <i>Dcaf17<sup>-/-</sup></i> mice, respectively, with an adjusted p-value cut-off of ≤ 0.05. Among these, 299 and 298 DEPs had fold change of ≥ 1.5 between WT and <i>Dcaf17<sup>-/-</sup></i> testes at ­3- and 8-week old, respectively. In the 3-week old <i>Dcaf17<sup>-/-</sup></i> testes, 59.5% of the DEPs were up-regulated, while 40.5% were down-regulated. Similarly, in the 8-week old <i>Dcaf17<sup>-/-</sup></i> testes, 83.9% and 16.1% DEPs were up-regulated and down-regulated, respectively. Functional annotation and network analyses highlighted that many DEPs were associated with key biological processes, including ubiquitination, RNA processing, translation, protein folding, protein stabilization, metabolic processes, oxidation-reduction processes and sper­matogenesis. Subsequent immunohistochemistry and immunoblotting analyses showed higher ubiquitin levels in <i>Dcaf17<sup>-/-</sup></i> testes compared to WT, suggesting potential impairment in ubiquitin proteasome system (UPS) due to DCAF17 loss of function. Our data provide a basis for further work to elucidate the molecular function(s) of DCAF17 in spermatogenesis and male fertility.
DOI: 10.6084/m9.figshare.29206277.v1
title: Investigation of testis proteome alterations associated with male infertility in <i>Dcaf17</i>-deficient mice

description: Disruption of <i>Dcaf17</i> in mice resulted in male infertility with severe spermatogenesis defects. To investigate the molecular basis of infertility phenotype, we examined testicular proteomes of wild-type (WT) and <i>Dcaf17<sup>-/-</sup></i> mice using a mass spectrometry-based approach. We identified 727 and 525 differentially expressed proteins (DEPs) in 3- and 8-week old testes of <i>Dcaf17<sup>-/-</sup></i> mice, respectively, with an adjusted p-value cut-off of ≤ 0.05. Among these, 299 and 298 DEPs had fold change of ≥ 1.5 between WT and <i>Dcaf17<sup>-/-</sup></i> testes at ­3- and 8-week old, respectively. In the 3-week old <i>Dcaf17<sup>-/-</sup></i> testes, 59.5% of the DEPs were up-regulated, while 40.5% were down-regulated. Similarly, in the 8-week old <i>Dcaf17<sup>-/-</sup></i> testes, 83.9% and 16.1% DEPs were up-regulated and down-regulated, respectively. Functional annotation and network analyses highlighted that many DEPs were associated with key biological processes, including ubiquitination, RNA processing, translation, protein folding, protein stabilization, metabolic processes, oxidation-reduction processes and sper­matogenesis. Subsequent immunohistochemistry and immunoblotting analyses showed higher ubiquitin levels in <i>Dcaf17<sup>-/-</sup></i> testes compared to WT, suggesting potential impairment in ubiquitin proteasome system (UPS) due to DCAF17 loss of function. Our data provide a basis for further work to elucidate the molecular function(s) of DCAF17 in spermatogenesis and male fertility.
DOI: 10.15468/dl.teufn7
title: Occurrence Download

description: A dataset containing 15896 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence)",
 "Country is one of (South Africa, Kenya, Tanzania, United Republic of, Namibia, Zimbabwe, Zambia, Botswana, Uganda)",
 "Month is one of (January, February, March, April, May, June, July, August, September, October, November, December)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aepyceros"
 ]
}

 The dataset includes 15896 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053667-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26008/1912/bco-dmo.986862.1
title: Concentrations of dissolved iron and manganese determined in water-column and near-surface seawater samples collected on the US GEOTRACES GP17-OCE cruise on R/V Roger Revelle (RR2214) in the South Pacific and Southern Oceans from Dec 2022 to Jan 2023

description: These data comprise the concentrations of dissolved iron and manganese determined in water-column and near-surface seawater samples, collected using a trace-metal clean CTD rosette or underway towfish sampler, respectively, during U.S. GEOTRACES cruise GP17-OCE (R/V Roger Revelle cruise RR2214). The dissolved iron data include shipboard measurements made using flow-injection analysis, and post-cruise measurements made using inductively-coupled plasma mass spectrometry, whereas the dissolved manganese data include only post-cruise measurements made using inductively-coupled plasma mass spectrometry.
DOI: 10.5286/ukerc.edc.000263
title: Refining Estimates of Land for Biomass - Data on the job implications of establishing a bioenergy market - data supporting charts in main report

description: Refining Estimates of Land for Biomass (RELB) was a project commissioned and funded by the ETI. This workbook includes the data for the charts displayed in the main body of the report, Job implications of establishing a bioenergy market.
DOI: 10.15468/dl.wbagb4
title: Occurrence Download

description: A dataset containing 29203 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Netherlands",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Castoridae",
 "Year 2020-2025"
 ]
}

 The dataset includes 29203 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053668-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.