cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16028875
title: Serine synthesis and catabolism in starved lung cancer and primary bronchial epithelial cells_dataset1

description: Gas chromatogpahy - mass spectrometry data and metadata - dataset1
description: Abstract:

Serine and glycine give rise to important building blocks in proliferating cells. Both amino acids are either synthesized de novo or taken up from the extracellular space. In lung cancer, serine synthesis gene expression is variable, yet, expression of the initial enzyme, phosphoglycerate dehydrogenase (PHGDH), was found to be associated with poor prognosis. While the contribution of de novo synthesis to serine pools has been shown to be enhanced by serine starvation, the impact of glucose deprivation, a commonly found condition in solid cancers is poorly understood. Here, we utilized a stable isotopic tracing approach to assess serine and glycine de novo synthesis and uptake in different lung cancer cell lines and normal bronchial epithelial cells in variable serine, glycine, and glucose conditions. Under low glucose supplementation (0.2 mM, 3-5% of normal plasma levels), serine de novo synthesis was maintained or even activated. As previously reported, also gluconeogenesis supplied carbons from glutamine to serine and glycine under these conditions. Unexpectedly, low glucose treatment consistently enhanced serine to glycine conversion, along with an up-regulation of the mitochondrial one-carbon metabolism enzymes, serine hydroxymethyltransferase (SHMT2) and methylenetetrahydrofolate dehydrogenase (MTHFD2). The relative contribution of de novo synthesis greatly increased in low serine/glycine conditions. In bronchial epithelial cells, adaptations occurred in a similar fashion as in cancer cells, but serine synthesis and serine to glycine conversion, as assessed by label enrichments and gene expression levels, were generally lower than in (PHGDH positive) cancer cells. In summary, we found a variable contribution of glucose or non-glucose carbon sources to serine and glycine and a high adaptability of the downstream one-carbon metabolism pathway to variable glucose supply.
DOI: 10.5281/zenodo.16028874
title: Serine synthesis and catabolism in starved lung cancer and primary bronchial epithelial cells_dataset1

description: Gas chromatogpahy - mass spectrometry data and metadata - dataset1
description: Abstract:

Serine and glycine give rise to important building blocks in proliferating cells. Both amino acids are either synthesized de novo or taken up from the extracellular space. In lung cancer, serine synthesis gene expression is variable, yet, expression of the initial enzyme, phosphoglycerate dehydrogenase (PHGDH), was found to be associated with poor prognosis. While the contribution of de novo synthesis to serine pools has been shown to be enhanced by serine starvation, the impact of glucose deprivation, a commonly found condition in solid cancers is poorly understood. Here, we utilized a stable isotopic tracing approach to assess serine and glycine de novo synthesis and uptake in different lung cancer cell lines and normal bronchial epithelial cells in variable serine, glycine, and glucose conditions. Under low glucose supplementation (0.2 mM, 3-5% of normal plasma levels), serine de novo synthesis was maintained or even activated. As previously reported, also gluconeogenesis supplied carbons from glutamine to serine and glycine under these conditions. Unexpectedly, low glucose treatment consistently enhanced serine to glycine conversion, along with an up-regulation of the mitochondrial one-carbon metabolism enzymes, serine hydroxymethyltransferase (SHMT2) and methylenetetrahydrofolate dehydrogenase (MTHFD2). The relative contribution of de novo synthesis greatly increased in low serine/glycine conditions. In bronchial epithelial cells, adaptations occurred in a similar fashion as in cancer cells, but serine synthesis and serine to glycine conversion, as assessed by label enrichments and gene expression levels, were generally lower than in (PHGDH positive) cancer cells. In summary, we found a variable contribution of glucose or non-glucose carbon sources to serine and glycine and a high adaptability of the downstream one-carbon metabolism pathway to variable glucose supply.
DOI: 10.15468/dl.s4ggja
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Echinochloa colonum",
 "Country is Guyana",
 "HasCoordinate is true"
 ]
}

 The dataset includes 25 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000778-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rwsznj
title: Occurrence Download

description: A dataset containing 5198 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lycopus europaeus glabrescens, Lycopus europaeus lanuginosus, Lycopus europaeus pusillus, Lycopus europaeus velutina, Lycopus europaeus menthifolius, Lycopus europaeus mollis, Lycopus europaeus mollis, Lycopus europaeus elatior, Lycopus europaeus europaeus, Lycopus europaeus glabrescens)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 5198 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000777-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bkbt7f
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Setaria italica",
 "Country is Madagascar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000781-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6qng6d
title: Occurrence Download

description: A dataset containing 285 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cakile geniculata"
 ]
}

 The dataset includes 285 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000779-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7mzugy
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arabis nordmanniana"
 ]
}

 The dataset includes 180 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000782-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fqtwjd
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oxalis corniculata",
 "Country is Lithuania",
 "HasCoordinate is true"
 ]
}

 The dataset includes 15 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000780-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3csgjb
title: Occurrence Download

description: A dataset containing 609 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Maytenus",
 "HasCoordinate is true",
 "Geometry POLYGON ((-17.66889 -35.11691, 51.34702 -35.11691, 51.34702 37.62, -17.66889 37.62, -17.66889 -35.11691))"
 ]
}

 The dataset includes 609 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000784-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zkeg3n
title: Occurrence Download

description: A dataset containing 305 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Echinochloa colonum",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 305 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000785-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16030311
title: Raw data for the paper "Growth substrate limitation enhances anaerobic arsenic methylation by Paraclostridium bifermentans strain EML"

description: This repository contains all raw and processed data supporting Qiao et al. (2024) “Growth substrate limitation enhances anaerobic arsenic methylation by Paraclostridium bifermentans strain EML.” Experiments were carried out under strict anoxic conditions in reinforced clostridial broth (RCB) with 25 µM arsenite across a gradient of substrate dilutions and in anaerobic co-culture with wild-type or arsP-expressing E. coli.
DOI: 10.5281/zenodo.16030310
title: Raw data for the paper "Growth substrate limitation enhances anaerobic arsenic methylation by Paraclostridium bifermentans strain EML"

description: This repository contains all raw and processed data supporting Qiao et al. (2024) “Growth substrate limitation enhances anaerobic arsenic methylation by Paraclostridium bifermentans strain EML.” Experiments were carried out under strict anoxic conditions in reinforced clostridial broth (RCB) with 25 µM arsenite across a gradient of substrate dilutions and in anaerobic co-culture with wild-type or arsP-expressing E. coli.
DOI: 10.15468/dl.rn3yqk
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Echinochloa colonum",
 "Country is Lao People’s Democratic Republic",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000786-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15972430
title: Mental Health Sentiment Analysis Using Social Media Texts

description: This project aims to analyze public sentiment related to mental health and suicide by processing text data from social media and other open sources. It uses natural language processing (NLP) and machine learning techniques to classify user-generated content into positive, negative, and neutral sentiments. The goal is to identify emotional patterns that could help in early detection of mental distress and promote timely support.

The repository contains:





Cleaned and preprocessed dataset (.csv)




Python code for sentiment analysis




Model training scripts using scikit-learn and/or deep learning




Visualizations for data exploration and sentiment trends



This resource can be valuable for researchers, mental health professionals, and developers building mental health-aware AI systems.

Disclaimer: This dataset is for academic and research purposes only. It does not replace clinical advice or diagnosis.
DOI: 10.5281/zenodo.16032163
title: Mental Health Sentiment Analysis Using Social Media Texts

description: This project aims to analyze public sentiment related to mental health and suicide by processing text data from social media and other open sources. It uses natural language processing (NLP) and machine learning techniques to classify user-generated content into positive, negative, and neutral sentiments. The goal is to identify emotional patterns that could help in early detection of mental distress and promote timely support.

The repository contains:





Cleaned and preprocessed dataset (.csv)




Python code for sentiment analysis




Model training scripts using scikit-learn and/or deep learning




Visualizations for data exploration and sentiment trends



This resource can be valuable for researchers, mental health professionals, and developers building mental health-aware AI systems.

Disclaimer: This dataset is for academic and research purposes only. It does not replace clinical advice or diagnosis.
DOI: 10.5281/zenodo.15882098
title: Dados das análises de resíduos de agrotóxicos encontrado no monitoramento de água superficiais adjacentes as áreas de rizicultura em Santa Catarina, safras 2014_15, 2015_2016 e 2016_17.

description: Durante três safras consecutivas, de 2014 a 2016, foram monitoradas águas superficiais adjacentes às áreas de rizicultura, com foco na detecção de 33 compostos que poderiam estar presentes em função do manejo agrícola associado à produção de arroz. As campanhas de coleta ocorreram entre os meses de setembro e fevereiro, período que abrange as principais fases do ciclo produtivo, como o preparo do solo, a semeadura e a condução da lavoura, totalizando seis campanhas de amostragem por ciclo. A amostragem foi realizada em cinco grandes regiões hidrográficas do estado, distribuídas da seguinte forma: R1 – Bacias dos Rios Araranguá e Mampituba (21 pontos); R2 – Complexo Lagunar, incluindo as bacias do Rio D’Una e do Rio Tubarão (13 pontos); R3 – Bacia do Rio Camboriú (5 pontos); R4 – Bacia do Rio Itapocú (15 pontos); e R5 – Bacia do Rio Itajaí (8 pontos). No total, foram monitorados 62 pontos de coleta, permitindo uma avaliação abrangente da presença de resíduos de agrotóxicos nas principais áreas produtoras de arroz do estado.

As amostras foram processadas na Unidade de Ensaios Químicos (UENQ) da Epagri/Estação Experimental de Itajaí (EEI), passando por filtração e pré-concentração via extração em fase sólida, com o uso de cartuchos C18 (500 mg/6 mL). A quantificação dos resíduos foi realizada por cromatografia líquida de alta eficiência (HPLC), utilizando coluna C18 (150 x 4,6 mm, 3 µm) e detecção por arranjo de diodos (DAD) em três comprimentos de onda: 222,4; 245,4; e 278,4 nm. O método foi desenvolvido e validado para a detecção e quantificação de 33 agrotóxicos, sendo eles: herbicidas (atrazina, bentazona, bispiribaque-sódico, carfentrazona-etílica, cialofop-butílico, ciclossulfamurom, clomazona, imazapique, imazetapir, metsulfuron-metílico, molinato, penoxsulam, picloram, pirazossulfuro-etílico, fenoxaprop-P-etílico, oxadiazona, oxifluorfen, propanil, quincloraque, tiobencarbe, simazina, trifluralina e 2,4-D); inseticidas (carbofurano, ciflutrina, fipronil, malationa, pirimifós-metílico e parationa-metílica); e fungicidas (triciclazol, tiofanato-metílico e trifloxistrobina).

A relevância deste monitoramento está na identificação precoce de possíveis impactos ambientais decorrentes do uso de agrotóxicos na rizicultura. Os dados gerados contribuem para a gestão sustentável dos recursos hídricos, oferecendo suporte técnico e científico às políticas públicas voltadas ao controle da poluição difusa em bacias hidrográficas. Além disso, servem como ferramenta de apoio à extensão rural, à fiscalização ambiental e ao aprimoramento das boas práticas agrícolas.
DOI: 10.5281/zenodo.15882099
title: Dados das análises de resíduos de agrotóxicos encontrado no monitoramento de água superficiais adjacentes as áreas de rizicultura em Santa Catarina, safras 2014_15, 2015_2016 e 2016_17.

description: Durante três safras consecutivas, de 2014 a 2016, foram monitoradas águas superficiais adjacentes às áreas de rizicultura, com foco na detecção de 33 compostos que poderiam estar presentes em função do manejo agrícola associado à produção de arroz. As campanhas de coleta ocorreram entre os meses de setembro e fevereiro, período que abrange as principais fases do ciclo produtivo, como o preparo do solo, a semeadura e a condução da lavoura, totalizando seis campanhas de amostragem por ciclo. A amostragem foi realizada em cinco grandes regiões hidrográficas do estado, distribuídas da seguinte forma: R1 – Bacias dos Rios Araranguá e Mampituba (21 pontos); R2 – Complexo Lagunar, incluindo as bacias do Rio D’Una e do Rio Tubarão (13 pontos); R3 – Bacia do Rio Camboriú (5 pontos); R4 – Bacia do Rio Itapocú (15 pontos); e R5 – Bacia do Rio Itajaí (8 pontos). No total, foram monitorados 62 pontos de coleta, permitindo uma avaliação abrangente da presença de resíduos de agrotóxicos nas principais áreas produtoras de arroz do estado.

As amostras foram processadas na Unidade de Ensaios Químicos (UENQ) da Epagri/Estação Experimental de Itajaí (EEI), passando por filtração e pré-concentração via extração em fase sólida, com o uso de cartuchos C18 (500 mg/6 mL). A quantificação dos resíduos foi realizada por cromatografia líquida de alta eficiência (HPLC), utilizando coluna C18 (150 x 4,6 mm, 3 µm) e detecção por arranjo de diodos (DAD) em três comprimentos de onda: 222,4; 245,4; e 278,4 nm. O método foi desenvolvido e validado para a detecção e quantificação de 33 agrotóxicos, sendo eles: herbicidas (atrazina, bentazona, bispiribaque-sódico, carfentrazona-etílica, cialofop-butílico, ciclossulfamurom, clomazona, imazapique, imazetapir, metsulfuron-metílico, molinato, penoxsulam, picloram, pirazossulfuro-etílico, fenoxaprop-P-etílico, oxadiazona, oxifluorfen, propanil, quincloraque, tiobencarbe, simazina, trifluralina e 2,4-D); inseticidas (carbofurano, ciflutrina, fipronil, malationa, pirimifós-metílico e parationa-metílica); e fungicidas (triciclazol, tiofanato-metílico e trifloxistrobina).

A relevância deste monitoramento está na identificação precoce de possíveis impactos ambientais decorrentes do uso de agrotóxicos na rizicultura. Os dados gerados contribuem para a gestão sustentável dos recursos hídricos, oferecendo suporte técnico e científico às políticas públicas voltadas ao controle da poluição difusa em bacias hidrográficas. Além disso, servem como ferramenta de apoio à extensão rural, à fiscalização ambiental e ao aprimoramento das boas práticas agrícolas.
DOI: 10.15468/dl.assvs6
title: Occurrence Download

description: A dataset containing 1084566 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Thymus"
 ]
}

 The dataset includes 1084566 records from 2328 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000745-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1392259.10fu
title: SH1392259.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1392260.10fu
title: SH1392260.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1392262.10fu
title: SH1392262.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1392264.10fu
title: SH1392264.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.