cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14752440
title: Plasma Pyrolysis of C3 and C4-Product Gas Composition

description: Excell raw data set of gaseous products resulted from plasma pyrolysis of C3 and C4
DOI: 10.5281/zenodo.14752398
title: CFD Simulation of Stream Reforming of Pyrolysis Volatiles of Plastic in Fluidized Bed Reactor: Effect of Catalyst Loading and Temperature on Hydrogen Production
DOI: 10.5281/zenodo.14752399
title: CFD Simulation of Stream Reforming of Pyrolysis Volatiles of Plastic in Fluidized Bed Reactor: Effect of Catalyst Loading and Temperature on Hydrogen Production
DOI: 10.15468/dl.xwhpp9
title: Occurrence Download

description: A dataset containing 252 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scomber australasicus Cuvier, 1832",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 252 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001581-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t2a3px
title: Occurrence Download

description: A dataset containing 481 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Russian Federation",
 "GbifRegion is Europe and Central Asia",
 "TaxonKey is Potamogeton compressus L."
 ]
}

 The dataset includes 481 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001582-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.25343699
title: Biostimulatory effects of boar seminal gel, saliva and semen on sexual behavior of young boars, gilts and sows

description: The present study aimed to identify novel biostimulatory compounds in boar seminal gel (SG), saliva and semen using Gas chromatography-mass spectrometry (GC-MS). The bio-stimulatory effect of SG, SG + saliva and SG + semen on young boar for semen collection as well were employed to study bio-stimulatory effects on gilts and sows. Distilled water (DW) exposure was kept as control. SG, saliva and semen were screened for total 105, 96 and 89 compounds. The highest concentration was of alkanes followed by sugar alcohols, then hydrocarbons, amino acids and fatty acids. Elaidic acid was the novel compound identified in pigs. Significantly higher (<i>p</i> &lt; 0.05) number of males got trained in exposure to SG (80%), SG + saliva (75%) and SG + semen (75%) than control (0%). The time (hrs) taken by young boars to get trained on exposure to combination of SG + saliva (244 ± 22.19) and SG + semen (216 ± 13.14) was lesser (<i>p</i> &lt; 0.05) than SG (356 ± 61.85) alone. Interval (hrs) from initiation of exposure for exhibition of different sexual behaviour by males on exposure to SG, saliva and semen was lesser (<i>p</i> &lt; 0.05) than control. Significantly (<i>p</i> &lt; 0.05) higher number of females showed estrus response to exposure of SG (72.72%), SG + saliva (69.23%) and SG + semen (76.92%) than control (0). Interval (hrs) taken to exhibit estrus was shorter (<i>p</i> &lt; 0.05) in females exposed to SG + saliva (201.88 ± 12.66), SG + semen (198.20 ± 9.42) than SG (262.14 ± 20.06) alone. Interval (hrs) for exhibition of different sexual behaviour by females on exposure to SG + saliva and SG + semen was lesser (<i>p</i> &lt; 0.05) than control. In conclusion, novel compounds were identified in boar seminal gel, saliva and semen with biostimulatory properties have been identified in boar SG, saliva and semen. The combined exposure of SG with saliva and semen has more intense biostimulation effect than SG alone for training of young boars and estrus induction in gilts and sows. Such compounds biostimulatory effects can be exploited for augmenting reproductive efficiency in pigs.
DOI: 10.6084/m9.figshare.25343699.v1
title: Biostimulatory effects of boar seminal gel, saliva and semen on sexual behavior of young boars, gilts and sows

description: The present study aimed to identify novel biostimulatory compounds in boar seminal gel (SG), saliva and semen using Gas chromatography-mass spectrometry (GC-MS). The bio-stimulatory effect of SG, SG + saliva and SG + semen on young boar for semen collection as well were employed to study bio-stimulatory effects on gilts and sows. Distilled water (DW) exposure was kept as control. SG, saliva and semen were screened for total 105, 96 and 89 compounds. The highest concentration was of alkanes followed by sugar alcohols, then hydrocarbons, amino acids and fatty acids. Elaidic acid was the novel compound identified in pigs. Significantly higher (<i>p</i> &lt; 0.05) number of males got trained in exposure to SG (80%), SG + saliva (75%) and SG + semen (75%) than control (0%). The time (hrs) taken by young boars to get trained on exposure to combination of SG + saliva (244 ± 22.19) and SG + semen (216 ± 13.14) was lesser (<i>p</i> &lt; 0.05) than SG (356 ± 61.85) alone. Interval (hrs) from initiation of exposure for exhibition of different sexual behaviour by males on exposure to SG, saliva and semen was lesser (<i>p</i> &lt; 0.05) than control. Significantly (<i>p</i> &lt; 0.05) higher number of females showed estrus response to exposure of SG (72.72%), SG + saliva (69.23%) and SG + semen (76.92%) than control (0). Interval (hrs) taken to exhibit estrus was shorter (<i>p</i> &lt; 0.05) in females exposed to SG + saliva (201.88 ± 12.66), SG + semen (198.20 ± 9.42) than SG (262.14 ± 20.06) alone. Interval (hrs) for exhibition of different sexual behaviour by females on exposure to SG + saliva and SG + semen was lesser (<i>p</i> &lt; 0.05) than control. In conclusion, novel compounds were identified in boar seminal gel, saliva and semen with biostimulatory properties have been identified in boar SG, saliva and semen. The combined exposure of SG with saliva and semen has more intense biostimulation effect than SG alone for training of young boars and estrus induction in gilts and sows. Such compounds biostimulatory effects can be exploited for augmenting reproductive efficiency in pigs.
DOI: 10.6084/m9.figshare.26085010
title: Novel bioinformatic analyses of somatic cell contamination in sperm samples

description: The assessment of epigenetic profiles in sperm is sensitive to somatic cell contamination, which can influence methylation signals at gene promoters. This contamination is particularly problematic in the assessment of DNA methylation in samples with low sperm counts, where fractional amounts of somatic cell DNA can lead to significant shifts in measured methylation state. In this study, a new method of detecting possible somatic cell contamination is proposed through two multi-region bioinformatic models: a traditional differential methylation analysis and a machine learning logistic regression model. These models were trained on publicly available sperm (<i>n</i> = 489) and blood (<i>n</i> = 1029) DNA methylation array data and tested on a contamination set, wherein the sperm of four donors with normal sperm counts were run on a 450k methylation array with four permutations each, including pure blood, half blood and half sperm by DNA concentration, half blood and half sperm by cell count, and pure sperm (<i>n</i> = 16). The DMR and logistic regression model classified the contamination testing set with 100% and 94% accuracy, respectively. These new methods of detecting the effects of somatic cell contamination allow for more accurate differentiation between epigenetic profiles that contain a biological somatic-like shift and those that have somatic-like signatures because of contamination.
DOI: 10.6084/m9.figshare.25461068
title: Insight into the complexity of male infertility: a multi-omics review

description: Male infertility is a reproductive disorder, accounting for 40–50% of infertility. Currently, in about 70% of infertile men, the cause remains unknown. With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging. The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, non-coding RNA, proteins, and metabolites worth further exploring. Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping. A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics. A GO enrichment analysis was performed using the Enrichr tool. We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies. Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent. With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.
DOI: 10.6084/m9.figshare.25461068.v1
title: Insight into the complexity of male infertility: a multi-omics review

description: Male infertility is a reproductive disorder, accounting for 40–50% of infertility. Currently, in about 70% of infertile men, the cause remains unknown. With the introduction of novel omics and advancement in high-throughput technology, potential biomarkers are emerging. The main purpose of our work was to overview different aspects of omics approaches in association with idiopathic male infertility and highlight potential genes, transcripts, non-coding RNA, proteins, and metabolites worth further exploring. Using the Gene Ontology (GO) analysis, we aimed to compare enriched GO terms from each omics approach and determine their overlapping. A PubMed database screening for the literature published between February 2014 and June 2022 was performed using the keywords: male infertility in association with different omics approaches: genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics. A GO enrichment analysis was performed using the Enrichr tool. We retrieved 281 global studies: 171 genomics (DNA level), 21 epigenomics (19 of methylation and two histone residue modifications), 15 transcriptomics, 31 non-coding RNA, 29 proteomics, two protein posttranslational modification, and 19 metabolomics studies. Gene ontology comparison showed that different omics approaches lead to the identification of different molecular factors and that the corresponding GO terms, obtained from different omics approaches, do not overlap to a larger extent. With the integration of novel omics levels into the research of idiopathic causes of male infertility, using multi-omic systems biology approaches, we will be closer to finding the potential biomarkers and consequently becoming aware of the entire spectrum of male infertility, their cause, prognosis, and potential treatment.
DOI: 10.6084/m9.figshare.26085010.v1
title: Novel bioinformatic analyses of somatic cell contamination in sperm samples

description: The assessment of epigenetic profiles in sperm is sensitive to somatic cell contamination, which can influence methylation signals at gene promoters. This contamination is particularly problematic in the assessment of DNA methylation in samples with low sperm counts, where fractional amounts of somatic cell DNA can lead to significant shifts in measured methylation state. In this study, a new method of detecting possible somatic cell contamination is proposed through two multi-region bioinformatic models: a traditional differential methylation analysis and a machine learning logistic regression model. These models were trained on publicly available sperm (<i>n</i> = 489) and blood (<i>n</i> = 1029) DNA methylation array data and tested on a contamination set, wherein the sperm of four donors with normal sperm counts were run on a 450k methylation array with four permutations each, including pure blood, half blood and half sperm by DNA concentration, half blood and half sperm by cell count, and pure sperm (<i>n</i> = 16). The DMR and logistic regression model classified the contamination testing set with 100% and 94% accuracy, respectively. These new methods of detecting the effects of somatic cell contamination allow for more accurate differentiation between epigenetic profiles that contain a biological somatic-like shift and those that have somatic-like signatures because of contamination.
DOI: 10.6084/m9.figshare.27227005
title: Identification of candidate genes for endometrial cancer in multi-omics: a Mendelian randomization analysis

description: Endometrial cancer is the most common malignant tumor of the uterus, but the underlying genetic mechanisms of EC remain unclear. To identify candidate genes and investigate genetic mechanisms for endometrial cancer, we utilized the summary-data-based Mendelian randomization (SMR) method to investigate causal associations between genetic variants, gene expression, DNA methylation, and endometrial cancer. Three main analyses were conducted utilizing cis-expression and methylation quantitative trait loci (eQTLs and mQTLs) as instrumental variables to examine causal relationships with endometrial cancer, and assessing the causal relationship between DNA methylation and gene expression. Data sources included genetic association data from O'Mara et al. eQTL data from the GTEx database, and mQTL data from McRae et al. Analysis involved the HEIDI test to distinguish pleiotropy, SMR analysis with multiple testing correction, and colocalization analysis to assess associations driven by linkage disequilibrium. Functional enrichment analysis was performed by the Metascape tool. Our study showed that three genes, SNX11, LINC00243, and EVI2A, were identified as causally related to endometrial cancer. SNX11 exhibited a positive causal relationship, while LINC00243 and EVI2A showed negative ones. Furthermore, 24 CpG sites were identified as causally related to endometrial cancer, with cg14424631 (CYP19A1) being the most significant. The study revealed common genes implicated in endometrial cancer, gene expression, and methylation sites, with LINC00243 playing a key role. Colocalization analysis confirmed significant causal relationships between LINC00243, SNX11, and endometrial cancer. Enrichment analysis uncovered pathways like interferon gamma signaling enriched in both endometrial cancer GWAS and e/mQTL. These findings shed light on the molecular mechanisms underlying endometrial cancer development. The study identified candidate genes and DNA methylation loci causally associated with endometrial cancer, which are expected to serve as potential targets for treatment. <b>Flowcharts of SMR and Mendelian randomization mechanism for eQTL, mQTL, and endometrial cancer GWAS datasets.</b> (A) Mendelian randomization analysis architecture for endometrial cancer. (B) Three parts of SMR analysis using eQTL and mQTL datasets for endometrial cancers were conducted in order to find significant causal correlations in gene expression levels.
DOI: 10.6084/m9.figshare.27227005.v1
title: Identification of candidate genes for endometrial cancer in multi-omics: a Mendelian randomization analysis

description: Endometrial cancer is the most common malignant tumor of the uterus, but the underlying genetic mechanisms of EC remain unclear. To identify candidate genes and investigate genetic mechanisms for endometrial cancer, we utilized the summary-data-based Mendelian randomization (SMR) method to investigate causal associations between genetic variants, gene expression, DNA methylation, and endometrial cancer. Three main analyses were conducted utilizing cis-expression and methylation quantitative trait loci (eQTLs and mQTLs) as instrumental variables to examine causal relationships with endometrial cancer, and assessing the causal relationship between DNA methylation and gene expression. Data sources included genetic association data from O'Mara et al. eQTL data from the GTEx database, and mQTL data from McRae et al. Analysis involved the HEIDI test to distinguish pleiotropy, SMR analysis with multiple testing correction, and colocalization analysis to assess associations driven by linkage disequilibrium. Functional enrichment analysis was performed by the Metascape tool. Our study showed that three genes, SNX11, LINC00243, and EVI2A, were identified as causally related to endometrial cancer. SNX11 exhibited a positive causal relationship, while LINC00243 and EVI2A showed negative ones. Furthermore, 24 CpG sites were identified as causally related to endometrial cancer, with cg14424631 (CYP19A1) being the most significant. The study revealed common genes implicated in endometrial cancer, gene expression, and methylation sites, with LINC00243 playing a key role. Colocalization analysis confirmed significant causal relationships between LINC00243, SNX11, and endometrial cancer. Enrichment analysis uncovered pathways like interferon gamma signaling enriched in both endometrial cancer GWAS and e/mQTL. These findings shed light on the molecular mechanisms underlying endometrial cancer development. The study identified candidate genes and DNA methylation loci causally associated with endometrial cancer, which are expected to serve as potential targets for treatment. <b>Flowcharts of SMR and Mendelian randomization mechanism for eQTL, mQTL, and endometrial cancer GWAS datasets.</b> (A) Mendelian randomization analysis architecture for endometrial cancer. (B) Three parts of SMR analysis using eQTL and mQTL datasets for endometrial cancers were conducted in order to find significant causal correlations in gene expression levels.
DOI: 10.6084/m9.figshare.25822724
title: FOXA1 co-activates circODC1 and ODC1 in HPV-positive cervical cancer cell growth

description: As demonstrated in previous research, hsa_circ_0052602 (circODC1) is dynamically expressed in HPV-positive cervical cancer (CC). CircODC1 expression was quantified using qRT-PCR, and its role in CC cell growth was assessed <i>via</i> loss-of-function assays. Interactions between miR-607 and circODC1 or ODC1 were confirmed using bioinformatics and mechanistic assays. The association of FOXA1 with the circODC1 promoter was validated through ChIP and luciferase reporter assays. CircODC1 was highly expressed in HPV-positive CC cell lines, and its depletion significantly impeded malignant processes such as proliferation, migration, and invasion. We found that ODC1 also played an oncogenic role in HPV-positive CC cells. CircODC1 was shown to positively regulate ODC1 as a ceRNA, competitively binding to miR-607 to counteract its suppression of ODC1. HPV-associated FOXA1 was identified as a potential transcription factor of circODC1. Restoration experiments showed that overexpression of circODC1 could counterbalance the inhibitory effect of FOXA1 knockdown. These findings offer new insights into therapeutic strategies for HPV-positive CC patients. Transcription factor FOXA1 binds to circODC1 promoter and activates circODC1 transcription. Activated circODC1 up-regulates ODC1 expression by sponging miR-607, thereby promoting HPV-positive CC cell invasion, proliferation and migration, while inhibiting apoptosis. Therefore, FOXA1 promotes HPV-positive CC progression by co-activating circODC1 and ODC1.
DOI: 10.6084/m9.figshare.25822724.v1
title: FOXA1 co-activates circODC1 and ODC1 in HPV-positive cervical cancer cell growth

description: As demonstrated in previous research, hsa_circ_0052602 (circODC1) is dynamically expressed in HPV-positive cervical cancer (CC). CircODC1 expression was quantified using qRT-PCR, and its role in CC cell growth was assessed <i>via</i> loss-of-function assays. Interactions between miR-607 and circODC1 or ODC1 were confirmed using bioinformatics and mechanistic assays. The association of FOXA1 with the circODC1 promoter was validated through ChIP and luciferase reporter assays. CircODC1 was highly expressed in HPV-positive CC cell lines, and its depletion significantly impeded malignant processes such as proliferation, migration, and invasion. We found that ODC1 also played an oncogenic role in HPV-positive CC cells. CircODC1 was shown to positively regulate ODC1 as a ceRNA, competitively binding to miR-607 to counteract its suppression of ODC1. HPV-associated FOXA1 was identified as a potential transcription factor of circODC1. Restoration experiments showed that overexpression of circODC1 could counterbalance the inhibitory effect of FOXA1 knockdown. These findings offer new insights into therapeutic strategies for HPV-positive CC patients. Transcription factor FOXA1 binds to circODC1 promoter and activates circODC1 transcription. Activated circODC1 up-regulates ODC1 expression by sponging miR-607, thereby promoting HPV-positive CC cell invasion, proliferation and migration, while inhibiting apoptosis. Therefore, FOXA1 promotes HPV-positive CC progression by co-activating circODC1 and ODC1.
DOI: 10.6084/m9.figshare.26799135
title: Transcriptome analyses reveal key features of mouse seminal vesicle during aging

description: Despite the significant morphological changes that occur in the seminal vesicles with aging, the transcriptomic characteristics remain largely unexplored. To address this, we performed bulk RNA sequencing on seminal vesicle samples from mice aged 3, 13, and 21 months to uncover transcriptomic alterations. Our findings reveal that aged seminal vesicles display cystic dilatation, epithelial hypoplasia, disordered muscle layers, fibrosis, and reduced proliferation capability. A comparison between 3-month-old and 21-month-old mice indicated that leukocyte-mediated immunity and leukocyte migration were the most significantly upregulated biological processes among differentially expressed genes (DEGs). Notably, several DEGs associated with "leukocyte migration," such as <i>Vcam1</i>, <i>Cxcl13</i>, and <i>Ccl8</i>, exhibited an increasing trend in transcriptomic and protein expression at three different time points in the seminal vesicles of mice. Additionally, we identified multiple aging-associated DEGs, including <i>P21</i> and <i>Tnfrsf1b</i>. Two genes (<i>Cd209f</i> and <i>Ccl8</i>) were consistently upregulated across all six regions of the male reproductive glands (testis, epididymis, and seminal vesicle) in the comparison of bulk RNA datasets from 3-month-old and 21-month-old mice. These analyses highlight an enhanced state of immune and inflammatory response in aged seminal vesicles. This study represents the first exploration of the overall transcriptome landscape of seminal vesicles in a murine model of natural aging, offering new insights into the mechanisms underlying aging-related seminal vesicle dysfunction.