cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23715522
title: Gender discrimination, power structure, marital quality

description: SPSS data
DOI: 10.6084/m9.figshare.23715522.v1
title: Gender discrimination, power structure, marital quality

description: SPSS data
DOI: 10.6084/m9.figshare.23211230
title: Gender discrimination, Power structure, Marital quality

description: Statistic Data for The Moderating Role of Power Structure in the Relationship between Gender discrimination and marital quality
DOI: 10.6084/m9.figshare.23211230.v2
title: Gender discrimination, Power structure, Marital quality

description: Statistic Data for The Moderating Role of Power Structure in the Relationship between Gender discrimination and marital quality
DOI: 10.6084/m9.figshare.23211230.v1
title: Power structure, Gender discrimination, Marital quality

description: Statistic Data for The Moderating Role of Power Structure in the Relationship between Gender discrimination and marital quality
DOI: 10.6084/m9.figshare.23715588
title: Supplementary Material for: Prioritization of monogenic CAKUT candidate genes with existing single-cell transcriptomics data of the human fetal kidney

description: Introduction: Congenital anomalies of the kidney and urinary tract (CAKUT) are the most common cause of chronic kidney disease in the first three decades of life. Over 40 genes have been identified as causative for isolated human CAKUT. However, many genes remain unknown and the prioritization of potential CAKUT candidate genes is challenging. To develop an independent approach to prioritize CAKUT candidate genes, we hypothesized that monogenic CAKUT genes are most likely co-expressed along a temporal axis during kidney development and that genes with coinciding high expression may represent strong novel CAKUT candidate genes. Methods: We analyzed single-cell-mRNA (sc-mRNA) transcriptomics data of human fetal kidney for temporal sc-mRNA co-expression of 40 known CAKUT genes. A maximum of high expression in consecutive timepoints of kidney development was found for four of the 40 genes (EYA1, SIX1, SIX2, and ITGA8) in nephron progenitor cells a, b, c, d (NPCa-d). We concluded that NPCa-d are relevant for CAKUT pathogenesis and intersected two lists of CAKUT candidate genes resulting from unbiased whole exome sequencing (WES) with the 100 highest expressed genes in NPCa-d. Results: Intersection of the 100 highest expressed genes in NPCa-d with WES-derived CAKUT candidate genes identified an overlap with the candidate genes KIF19, TRIM36, USP35, CHTF18, in each of which a biallelic variant was detected in different families with CAKUT. Conclusion: Sc-mRNA expression data of human fetal kidney can be utilized to prioritize WES-derived CAKUT candidate genes. KIF19, TRIM36, USP35, and CHTF18 may represent strong novel candidate genes for CAKUT.
DOI: 10.6084/m9.figshare.23715588.v1
title: Supplementary Material for: Prioritization of monogenic CAKUT candidate genes with existing single-cell transcriptomics data of the human fetal kidney

description: Introduction: Congenital anomalies of the kidney and urinary tract (CAKUT) are the most common cause of chronic kidney disease in the first three decades of life. Over 40 genes have been identified as causative for isolated human CAKUT. However, many genes remain unknown and the prioritization of potential CAKUT candidate genes is challenging. To develop an independent approach to prioritize CAKUT candidate genes, we hypothesized that monogenic CAKUT genes are most likely co-expressed along a temporal axis during kidney development and that genes with coinciding high expression may represent strong novel CAKUT candidate genes. Methods: We analyzed single-cell-mRNA (sc-mRNA) transcriptomics data of human fetal kidney for temporal sc-mRNA co-expression of 40 known CAKUT genes. A maximum of high expression in consecutive timepoints of kidney development was found for four of the 40 genes (EYA1, SIX1, SIX2, and ITGA8) in nephron progenitor cells a, b, c, d (NPCa-d). We concluded that NPCa-d are relevant for CAKUT pathogenesis and intersected two lists of CAKUT candidate genes resulting from unbiased whole exome sequencing (WES) with the 100 highest expressed genes in NPCa-d. Results: Intersection of the 100 highest expressed genes in NPCa-d with WES-derived CAKUT candidate genes identified an overlap with the candidate genes KIF19, TRIM36, USP35, CHTF18, in each of which a biallelic variant was detected in different families with CAKUT. Conclusion: Sc-mRNA expression data of human fetal kidney can be utilized to prioritize WES-derived CAKUT candidate genes. KIF19, TRIM36, USP35, and CHTF18 may represent strong novel candidate genes for CAKUT.
DOI: 10.6084/m9.figshare.23713818
title: <strong>Coexistence of drug-resistant genes in </strong><em><strong>Klebsiella pneumoniae</strong></em>

description: Resistance genes coexisted in Klebsiella pneumoniae on the chick farms in Anyang, Henan, China, which mainly included <em>bla</em><sub>NDM</sub>,<em> temxCD-toprJ,</em> and <em>mcr</em>. <em> temxCD</em>1<em>-topr</em>1<em>J</em>was found to coexist with <em>mcr</em>-1 and <em>bla</em><sub>NDM</sub><sub>-1 </sub>in a plasmid of type IncHI1B/IncFIB, respectively.
DOI: 10.6084/m9.figshare.23713818.v1
title: <strong>Coexistence of drug-resistant genes in </strong><em><strong>Klebsiella pneumoniae</strong></em>

description: Resistance genes coexisted in Klebsiella pneumoniae on the chick farms in Anyang, Henan, China, which mainly included <em>bla</em><sub>NDM</sub>,<em> temxCD-toprJ,</em> and <em>mcr</em>. <em> temxCD</em>1<em>-topr</em>1<em>J</em>was found to coexist with <em>mcr</em>-1 and <em>bla</em><sub>NDM</sub><sub>-1 </sub>in a plasmid of type IncHI1B/IncFIB, respectively.
DOI: 10.34740/kaggle/dsv/6165137
title: Cloud Computing Performance Metrics
DOI: 10.5281/zenodo.7993644
title: Single-copy orthologous genes used for Ricefish phylogeny

description: Ortholog set We generated a reference set consisting of 8390 single-copy protein-coding genes derived from OrthoDB v.9.1 (Waterhouse et al., 2013) available for the following species: <em>Austrofundulus limnaeus, Centrocoris variegatus, Fundulus heteroclitus, Kryptolebias marmoratus, Nothobranchius furzeri, Oryzias latipes, O. melastigma, Poecilia formosa, P. latipinna ,P. mexicana, P. reticulata</em> and <em>Xiphophorus maculatus </em>(NCBI Accession numbers in Table S7). The hierarchical split was set to Actinopterygii (ID 7898). We used the script “make-ogs-corresponding.pl” to check for inconsistencies between the amino acid sequences and the corresponding nucleotide sequences and removed 96 problematic genes (Tab. S7). Identification of orthologs for transcripts and genome and alignment of single-copy genes Ortholog identification among 16 ricefish species and four outgroups (DS1, supplementary tables Tab. S1a) was carried out with Orthograph v0.7.1 (Petersen et al., 2017). Forward search for candidate transcript was left at default. Best reciprocal hit: Ortholog candidate genes needed at least one hit in either <em>O. latipes</em> or <em>O. melastigma </em>and we allowed concatenation of hits if they met the criteria and did not overlap. Max-blast-searches were set to 50, blast-max-hits were also set to 50. “U” in the amino acid sequences was changed to “X” to avoid issues in downstream analysis. The results of the orthology prediction were summarized for all species using a custom perl script coming with the orthograph package. Sequences of only those orthologs with all species present were aligned using MAFFT v7.221 with the L-INS-I algorithm on amino acid level (Katoh & Standley, 2013). 915 orthologs with outliers were identified according to Misof et al. 2014 and were subsequently removed from further analysis. We used the amino-acid alignments as blue print to generate corresponding nucleotide alignments with a modified version of Pal2Nal v14 (Misof et al., 2014; Suyama et al., 2006). To check each amino acid alignment for ambiguously aligned regions, we ran ALISCORE v2.0 with the maximal number of possible sequence selected pairs to analyze (-r) (Kück et al., 2010; Misof et al., 2014; Misof & Misof, 2009). Sites which needed masking were cut out using ALICUT v2.3 (Kück, 2009) from the amino acid alignments and correspondingly also from the nucleotide alignments. For further analyses we only proceeded with the data set on nucleotide level.
description: This research was funded by an ERC starting grant to Arne W. Nolte ("Evolmapping") and a Leibniz-Gemeinschaft SAW grant to Julia Schwarzer (SAW-Ricefish P91/2016).
DOI: 10.5281/zenodo.7993643
title: Single-copy orthologous genes used for Ricefish phylogeny

description: Ortholog set We generated a reference set consisting of 8390 single-copy protein-coding genes derived from OrthoDB v.9.1 (Waterhouse et al., 2013) available for the following species: <em>Austrofundulus limnaeus, Centrocoris variegatus, Fundulus heteroclitus, Kryptolebias marmoratus, Nothobranchius furzeri, Oryzias latipes, O. melastigma, Poecilia formosa, P. latipinna ,P. mexicana, P. reticulata</em> and <em>Xiphophorus maculatus </em>(NCBI Accession numbers in Table S7). The hierarchical split was set to Actinopterygii (ID 7898). We used the script “make-ogs-corresponding.pl” to check for inconsistencies between the amino acid sequences and the corresponding nucleotide sequences and removed 96 problematic genes (Tab. S7). Identification of orthologs for transcripts and genome and alignment of single-copy genes Ortholog identification among 16 ricefish species and four outgroups (DS1, supplementary tables Tab. S1a) was carried out with Orthograph v0.7.1 (Petersen et al., 2017). Forward search for candidate transcript was left at default. Best reciprocal hit: Ortholog candidate genes needed at least one hit in either <em>O. latipes</em> or <em>O. melastigma </em>and we allowed concatenation of hits if they met the criteria and did not overlap. Max-blast-searches were set to 50, blast-max-hits were also set to 50. “U” in the amino acid sequences was changed to “X” to avoid issues in downstream analysis. The results of the orthology prediction were summarized for all species using a custom perl script coming with the orthograph package. Sequences of only those orthologs with all species present were aligned using MAFFT v7.221 with the L-INS-I algorithm on amino acid level (Katoh & Standley, 2013). 915 orthologs with outliers were identified according to Misof et al. 2014 and were subsequently removed from further analysis. We used the amino-acid alignments as blue print to generate corresponding nucleotide alignments with a modified version of Pal2Nal v14 (Misof et al., 2014; Suyama et al., 2006). To check each amino acid alignment for ambiguously aligned regions, we ran ALISCORE v2.0 with the maximal number of possible sequence selected pairs to analyze (-r) (Kück et al., 2010; Misof et al., 2014; Misof & Misof, 2009). Sites which needed masking were cut out using ALICUT v2.3 (Kück, 2009) from the amino acid alignments and correspondingly also from the nucleotide alignments. For further analyses we only proceeded with the data set on nucleotide level.
description: This research was funded by an ERC starting grant to Arne W. Nolte ("Evolmapping") and a Leibniz-Gemeinschaft SAW grant to Julia Schwarzer (SAW-Ricefish P91/2016).
DOI: 10.5281/zenodo.8167063
title: Orthorexia, Compulsive Exercise, and Positive Body Experiences

description: spss datat for manuscript
DOI: 10.5281/zenodo.8167062
title: Orthorexia, Compulsive Exercise, and Positive Body Experiences

description: spss datat for manuscript
DOI: 10.5281/zenodo.8064517
title: Assembly data files Oryzias dopingdopingensis

description: Identification and masking of repetitive elements in the genome sequence of <em>O. dopingdopingensis </em>was performed with the following bioinformatic tool case. Nucleotides were masked using the DUST algorithm with dustmasker (version 1.0.0, part of blast+ 2.9.0 (Altschul et al., 1990; Camacho et al., 2009) (Kuzio et al., unpublished but described in (Morgulis et al., 2006). Tandem Repeats were identified with Tandem Repeat Finder (trf version 4.09) (Benson, 1999). A species-specific <em>de novo</em> repeat library was built with RepeatModeler v1.0.11 (http://www.repeatmasker.org/RepeatModeler/). Repeat Elements were located in the genome sequence using RepeatMasker (version 4.1.0) (http://www.repeatmasker.org) with the <em>de </em><em>novo</em> and<em> Danio rerio </em>libraries. The information from all four repeat analyses was merged and the genome was softmasked with bedtools (2.29.2) (Quinlan & Hall, 2010) PMID: 20110278; PMCID: PMC2832824.]. All steps of masking repetitive regions were performed with scripts provided by the sigenae platform, following the workflow from (Feron et al., 2020). For the identification of genes the masked genome was annotated with funannotate (Palmer & Stajich, 2019). The sequences were sorted by length with the ‘funannotate sort’ function, followed by a gene prediction with ‘funannotate predict’. No training based on RNA-Seq data was performed since it was not available for this species. Additional external evidence from transcripts and proteins was added. As transcript evidence, gene predictions from <em>Oryzias latipes</em> (NCBI Bioproject:PRJNA183868; Assembly: GCF_002234675.1) (Kasahara et al., 2007) and <em>Oryzias melastigma</em> (NCBI Bioproject: PRJNA401159 ; Assembly: ASM292280v2) (Kim et al., 2018) were used. As protein evidence, a protein set from Oryzias javanicus (NCBI Bioprject : PRJNA505405 ; Assembly: GCA_003999625.1) (Lee et al., 2020), manually annotated reference sequences from UniProt Knowledgebase (UniProtKB) (Release 2020_02 (22-Apr-2020) UniProtKB/Swiss-Prot with 562,253 entries ) (Apweiler et al., 2004) and a set of orthologous sequences generated in this study. Furthermore, the <em>de novo</em> gene predictors were trained with the Busco dataset of actinopterygii_odb10. Gene prediction resulted in a total of 56658 genes.
DOI: 10.5281/zenodo.8064516
title: Assembly data files Oryzias dopingdopingensis

description: Identification and masking of repetitive elements in the genome sequence of <em>O. dopingdopingensis </em>was performed with the following bioinformatic tool case. Nucleotides were masked using the DUST algorithm with dustmasker (version 1.0.0, part of blast+ 2.9.0 (Altschul et al., 1990; Camacho et al., 2009) (Kuzio et al., unpublished but described in (Morgulis et al., 2006). Tandem Repeats were identified with Tandem Repeat Finder (trf version 4.09) (Benson, 1999). A species-specific <em>de novo</em> repeat library was built with RepeatModeler v1.0.11 (http://www.repeatmasker.org/RepeatModeler/). Repeat Elements were located in the genome sequence using RepeatMasker (version 4.1.0) (http://www.repeatmasker.org) with the <em>de </em><em>novo</em> and<em> Danio rerio </em>libraries. The information from all four repeat analyses was merged and the genome was softmasked with bedtools (2.29.2) (Quinlan & Hall, 2010) PMID: 20110278; PMCID: PMC2832824.]. All steps of masking repetitive regions were performed with scripts provided by the sigenae platform, following the workflow from (Feron et al., 2020). For the identification of genes the masked genome was annotated with funannotate (Palmer & Stajich, 2019). The sequences were sorted by length with the ‘funannotate sort’ function, followed by a gene prediction with ‘funannotate predict’. No training based on RNA-Seq data was performed since it was not available for this species. Additional external evidence from transcripts and proteins was added. As transcript evidence, gene predictions from <em>Oryzias latipes</em> (NCBI Bioproject:PRJNA183868; Assembly: GCF_002234675.1) (Kasahara et al., 2007) and <em>Oryzias melastigma</em> (NCBI Bioproject: PRJNA401159 ; Assembly: ASM292280v2) (Kim et al., 2018) were used. As protein evidence, a protein set from Oryzias javanicus (NCBI Bioprject : PRJNA505405 ; Assembly: GCA_003999625.1) (Lee et al., 2020), manually annotated reference sequences from UniProt Knowledgebase (UniProtKB) (Release 2020_02 (22-Apr-2020) UniProtKB/Swiss-Prot with 562,253 entries ) (Apweiler et al., 2004) and a set of orthologous sequences generated in this study. Furthermore, the <em>de novo</em> gene predictors were trained with the Busco dataset of actinopterygii_odb10. Gene prediction resulted in a total of 56658 genes.
DOI: 10.6084/m9.figshare.23715625.v1
title: CaFerrite_SofQ.dat from The structure of molten calcium ferrite under various redox conditions

description: S(Q) experimental data from figure 2 of Shi et al. for CaO-Fe2O-x as a function of Fe+.
DOI: 10.6084/m9.figshare.23715625
title: CaFerrite_SofQ.dat from The structure of molten calcium ferrite under various redox conditions

description: S(Q) experimental data from figure 2 of Shi et al. for CaO-Fe2O-x as a function of Fe+.
DOI: 10.6084/m9.figshare.23715628
title: CaFerrite_DofR.dat from The structure of molten calcium ferrite under various redox conditions

description: D(r) experimental data from figure 2 of Shi et al. for CaO-Fe2O-x as a function of Fe+.
DOI: 10.6084/m9.figshare.23715628.v1
title: CaFerrite_DofR.dat from The structure of molten calcium ferrite under various redox conditions

description: D(r) experimental data from figure 2 of Shi et al. for CaO-Fe2O-x as a function of Fe+.
DOI: 10.6084/m9.figshare.23715633
title: <em>Klebsiella pneumoniae</em> carrying <em>tmexCD-toprJ</em>

description: Klebsiella pneumoniae carrying <em>tmexCD</em>1<em>-toprJ</em>1 and <em>mcr</em>-8
DOI: 10.6084/m9.figshare.23715633.v1
title: <em>Klebsiella pneumoniae</em> carrying <em>tmexCD-toprJ</em>

description: Klebsiella pneumoniae carrying <em>tmexCD</em>1<em>-toprJ</em>1 and <em>mcr</em>-8
DOI: 10.23728/b2share.52b03f8dfa754e17b265eebc795eea06
title: Gesäuse-Johnsbachtal - Austria, Total nitrogen concentration

description: Total nitrogen concentration data of the Gesäuse-Johnsbachtal site
DOI: 10.25442/hku.23621187
title: <em>Supporting data for</em> Transcutaneous Auricular Vagus Nerve Stimulation: Unveiling Its Underlying Neural Mechanisms and Potential for Alleviating Depression

description: Depression is a highly prevalent neuropsychiatric illness and one of the leading causes of health-related disease burden. The COVID-19 pandemic has exacerbated the detriment conditions, with an enormous upsurge in depression cases. The unsatisfactory response of depression episodes to the currently available treatments poses a major clinical and socioeconomic problem. The complex pathophysiology of depression may involve multiple central and peripheral nervous systems, resulting in challenges in effectively treating depression. Therefore, alternative therapeutic strategies are needed to target multiple depression-related mechanisms for improving treatment efficiency. Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel and promising non-invasive technique for treating depression. The current study investigated the antidepressant-like activities of chronic taVNS and its potential mechanisms in a model of depression. The current dataset contains all the data related to the antidepressant activity of taVNS and its underlying mechanisms of action.
DOI: 10.25442/hku.23621187.v1
title: <em>Supporting data for</em> Transcutaneous Auricular Vagus Nerve Stimulation: Unveiling Its Underlying Neural Mechanisms and Potential for Alleviating Depression

description: Depression is a highly prevalent neuropsychiatric illness and one of the leading causes of health-related disease burden. The COVID-19 pandemic has exacerbated the detriment conditions, with an enormous upsurge in depression cases. The unsatisfactory response of depression episodes to the currently available treatments poses a major clinical and socioeconomic problem. The complex pathophysiology of depression may involve multiple central and peripheral nervous systems, resulting in challenges in effectively treating depression. Therefore, alternative therapeutic strategies are needed to target multiple depression-related mechanisms for improving treatment efficiency. Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel and promising non-invasive technique for treating depression. The current study investigated the antidepressant-like activities of chronic taVNS and its potential mechanisms in a model of depression. The current dataset contains all the data related to the antidepressant activity of taVNS and its underlying mechanisms of action.
DOI: 10.6084/m9.figshare.22493944
title: Illegal online trade of invasive plants in Australia

description: The project contains data and code used in our project investigating the illegal online trade of invasive plants in Australia. The dataset titled 'plant_trade_dataset.csv' contains cleaned and consolidated detection records from online advertisements for plants. The dataset titled 'weed_trade_dataset.csv' is a subset of the 'plant_trade_dataset.csv' dataset containing records of plants advertised which are prohibited to trade in at least one Australian jurisdiction. The advertisements were collected from an Australian online classifieds website which we have purposefully kept confidential in accordance with the ethics approval of this project. As such all information that could identify a user of the website has also been removed. However, this dataset still provides all necessary information needed to replicate the analysis of this study. We have provided R scripts which can be used to replicate the results of the study. ‘string_matching.R’ provides an example of how string matching was used to detect desired advertisements. This code uses ‘faux_web_scraped_data.csv’, ‘faux_plant_terms.csv’ and ‘incoreect_term_matches.csv’ to demonstrate how it functions. ‘quantity_price_permutation_code.R’ is the code used for analysing the effect of trade prohibition on quantity and price, along with the formatted datasets ‘qty_law_comp.csv’ for quantity and ‘price_law_comp’ for price. The remaining analysis (i.e., species accumulation, trade quantity, and use of traded taxa) was performed with code from the ‘analysis_code.R’ script.
DOI: 10.6084/m9.figshare.22493944.v4
title: Illegal online trade of invasive plants in Australia

description: The project contains data and code used in our project investigating the illegal online trade of invasive plants in Australia. The dataset titled 'plant_trade_dataset.csv' contains cleaned and consolidated detection records from online advertisements for plants. The dataset titled 'weed_trade_dataset.csv' is a subset of the 'plant_trade_dataset.csv' dataset containing records of plants advertised which are prohibited to trade in at least one Australian jurisdiction. The advertisements were collected from an Australian online classifieds website which we have purposefully kept confidential in accordance with the ethics approval of this project. As such all information that could identify a user of the website has also been removed. However, this dataset still provides all necessary information needed to replicate the analysis of this study. We have provided R scripts which can be used to replicate the results of the study. ‘string_matching.R’ provides an example of how string matching was used to detect desired advertisements. This code uses ‘faux_web_scraped_data.csv’, ‘faux_plant_terms.csv’ and ‘incoreect_term_matches.csv’ to demonstrate how it functions. ‘quantity_price_permutation_code.R’ is the code used for analysing the effect of trade prohibition on quantity and price, along with the formatted datasets ‘qty_law_comp.csv’ for quantity and ‘price_law_comp’ for price. The remaining analysis (i.e., species accumulation, trade quantity, and use of traded taxa) was performed with code from the ‘analysis_code.R’ script.