cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7826505
title: The relationship between the clinical course of SARS-CoV-2 infection with ACE2 and TMPRSS2 expression and polymorphisms

description: Background<br> The viral S protein and host ACE2 and TMPRSS2 genetic variations may act as a barrier to viral<br> infection or determine susceptibility to COVID-19 infection.<br> Objectives<br> We investigated the relationship between the expression patterns and polymorphisms of the ACE2<br> and TMPRSS2 receptor genes associated with COVID-19 and the clinical course of COVID-19<br> infection.<br> Material and methods<br> We studied 147 COVID-19 patients (41 asymptomatic, 53 symptomatic and 53 treated in intensive<br> care unit (ICU) cases) and 33 healthy controls. ACE2 and TMPRSS2 expressions were determined<br> using the One-Run RT Q-PCR kit. Genotypic distributions of Single Nucleotide Polymorphisms (SNP)<br> of ACE2 and TMPRSS2 were obtained by RT-PCR.<br> Results<br> The expressions of ACE2 and TMPRSS2 were different between SARS-CoV-2 positive and negative<br> groups. ACE2 rs714205GG genotype and G-allele showed significant differences in the SARS-CoV-2<br> positive asymptomatic group. A significant correlation was found between TMPRSS2 rs8134378GA,<br> rs2070788GA, rs7364083GA and rs9974589AC genotypes and SARS-CoV-2 positivity. The<br> rs1978124 C-allele and rs8134378 A-allele were significant in the SARS-CoV-2 positive symptomatic<br> group. TMPRSS2 rs2070788GA was different in all patient groups from the control group. There was a<br> difference between SARS-CoV-2 positive and negative groups for the CTTA haplotype formed by<br> ACE2 variants. The AGCAG and AGAAG haplotypes formed by TMPRSS2 variants were more<br> common in the asymptomatic patient group than in other patient groups.<br> Conclusions<br> Identifying the relationship between host genetic variants and COVID-19 susceptibility will contribute to<br> further studies that will enable new vaccines and potential therapeutic approaches to be applicable.
DOI: 10.5281/zenodo.6339632
title: SARS-CoV-2 RNA levels in Scotland's wastewater

description: Nationwide, wastewater-based monitoring was newly established in Scotland to track the levels of SARS-CoV-2 viral RNA shed into the sewage network, during the COVID-19 pandemic. We present a curated, reference data set produced by this national programme, from May 2020 to February 2022. Viral levels were analysed by RT-qPCR assays of the N1 gene, on RNA extracted from wastewater sampled at 122 locations. Locations were sampled up to four times per week, typically once or twice per week, and in response to local needs. These wastewater data are contributing to estimates of disease prevalence and the viral reproduction number (R) in Scotland and in the UK. We report sampling site locations with geographical coordinates, the total population in the catchment for each site, and the information necessary for data normalisation, such as the incoming wastewater flow values and ammonia concentration, when these were available. The methodology for viral quantification and data analysis is briefly described, with links to detailed protocols online. Check the README for details and the project COVID-WW Website
description: This work was funded by Scotland's Centre of Expertise for Waters (CREW; Grant CD2019_06 Tracking SARS-CoV-2 via municipal wastewater) and by Scottish Environment Protection Agency (SEPA).
DOI: 10.5281/zenodo.6347803
title: SARS-CoV-2 RNA levels in Scotland's wastewater

description: Nationwide, wastewater-based monitoring was newly established in Scotland to track the levels of SARS-CoV-2 viral RNA shed into the sewage network, during the COVID-19 pandemic. We present a curated, reference data set produced by this national programme, from May 2020 to February 2022. Viral levels were analysed by RT-qPCR assays of the N1 gene, on RNA extracted from wastewater sampled at 122 locations. Locations were sampled up to four times per week, typically once or twice per week, and in response to local needs. These wastewater data are contributing to estimates of disease prevalence and the viral reproduction number (R) in Scotland and in the UK. We report sampling site locations with geographical coordinates, the total population in the catchment for each site, and the information necessary for data normalisation, such as the incoming wastewater flow values and ammonia concentration, when these were available. The methodology for viral quantification and data analysis is briefly described, with links to detailed protocols online. Check the README for details and the project COVID-WW Website
description: This work was funded by Scotland's Centre of Expertise for Waters (CREW; Grant CD2019_06 Tracking SARS-CoV-2 via municipal wastewater) and by Scottish Environment Protection Agency (SEPA).
DOI: 10.5281/zenodo.6339631
title: SARS-CoV-2 RNA levels in Scotland's wastewater

description: Nationwide, wastewater-based monitoring was newly established in Scotland to track the levels of SARS-CoV-2 viral RNA shed into the sewage network, during the COVID-19 pandemic. We present a curated, reference data set produced by this national programme, from May 2020 to February 2022. Viral levels were analysed by RT-qPCR assays of the N1 gene, on RNA extracted from wastewater sampled at 122 locations. Locations were sampled up to four times per week, typically once or twice per week, and in response to local needs. These wastewater data are contributing to estimates of disease prevalence and the viral reproduction number (R) in Scotland and in the UK. We report sampling site locations with geographical coordinates, the total population in the catchment for each site, and the information necessary for data normalisation, such as the incoming wastewater flow values and ammonia concentration, when these were available. The methodology for viral quantification and data analysis is briefly described, with links to detailed protocols online. Check the README for details and the project COVID-WW Website
description: This work was funded by Scotland's Centre of Expertise for Waters (CREW; Grant CD2019_06 Tracking SARS-CoV-2 via municipal wastewater) and by Scottish Environment Protection Agency (SEPA).
DOI: 10.5281/zenodo.6349579
title: SARS-CoV-2 RNA levels in Scotland's wastewater

description: Nationwide, wastewater-based monitoring was newly established in Scotland to track the levels of SARS-CoV-2 viral RNA shed into the sewage network, during the COVID-19 pandemic. We present a curated, reference data set produced by this national programme, from May 2020 to February 2022. Viral levels were analysed by RT-qPCR assays of the N1 gene, on RNA extracted from wastewater sampled at 122 locations. Locations were sampled up to four times per week, typically once or twice per week, and in response to local needs. These wastewater data are contributing to estimates of disease prevalence and the viral reproduction number (R) in Scotland and in the UK. We report sampling site locations with geographical coordinates, the total population in the catchment for each site, and the information necessary for data normalisation, such as the incoming wastewater flow values and ammonia concentration, when these were available. The methodology for viral quantification and data analysis is briefly described, with links to detailed protocols online. Check the README for details and the project COVID-WW Website
description: This work was funded by Scotland's Centre of Expertise for Waters (CREW; Grant CD2019_06 Tracking SARS-CoV-2 via municipal wastewater) and by Scottish Environment Protection Agency (SEPA).
DOI: 10.5281/zenodo.7455006
title: Nitrogen fixation in the Indian Ocean

description: Dinitrogen (N2) fixation rates measured in the Indian Ocean, collected from previously published papers. The dataset contains 241 volumetric rates (units nmol N l-1 d-1), 89 depth-integrated rates (units µmol N l-1 d-1) and metadata (including temperature, salinity, inorganic nutrient and chlorophyll concentrations) when available in the original publications. Basin-scale N<sub>2</sub> fixation rates calculations were done as follows: Depth-integrated rates from the literature are listed and classified according to sub-basin and season The arithmetic mean, geometric mean and median are calculated for each sub-basin and season Means and median are extrapolated to the area of each sub-basin considering the duration (days) of each season Sub-basin seasonal rates are summed for each sub-basin to obtain sub-basin yearly rates Sub-basin yearly rates are summed to obtain basin-scale (i.e., all the Indian Ocean) rates
DOI: 10.5281/zenodo.7455007
title: Nitrogen fixation in the Indian Ocean

description: Dinitrogen (N2) fixation rates measured in the Indian Ocean, collected from previously published papers. The dataset contains 241 volumetric rates (units nmol N l-1 d-1), 89 depth-integrated rates (units µmol N l-1 d-1) and metadata (including temperature, salinity, inorganic nutrient and chlorophyll concentrations) when available in the original publications.
DOI: 10.5281/zenodo.7688074
title: Nitrogen fixation in the Indian Ocean

description: Dinitrogen (N2) fixation rates measured in the Indian Ocean, collected from previously published papers. The dataset contains 241 volumetric rates (units nmol N l-1 d-1), 89 depth-integrated rates (units µmol N l-1 d-1) and metadata (including temperature, salinity, inorganic nutrient and chlorophyll concentrations) when available in the original publications.
DOI: 10.5281/zenodo.7870536
title: Nitrogen fixation in the Indian Ocean

description: Dinitrogen (N2) fixation rates measured in the Indian Ocean, collected from previously published papers. The dataset contains 241 volumetric rates (units nmol N l-1 d-1), 89 depth-integrated rates (units µmol N l-1 d-1) and metadata (including temperature, salinity, inorganic nutrient and chlorophyll concentrations) when available in the original publications. Basin-scale N<sub>2</sub> fixation rates calculations were done as follows: Depth-integrated rates from the literature are listed and classified according to sub-basin and season The arithmetic mean, geometric mean and median are calculated for each sub-basin and season Means and median are extrapolated to the area of each sub-basin considering the duration (days) of each season Sub-basin seasonal rates are summed for each sub-basin to obtain sub-basin yearly rates Sub-basin yearly rates are summed to obtain basin-scale (i.e., all the Indian Ocean) rates
DOI: 10.35078/ezq5ra
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Diamantina | Município: Minas Novas

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.25345/c5st7f68h
title: MassIVE MSV000091808 - Complexome Profiling of the chloroplast proteome from Arabidopsis thaliana
title: Chloroplasts are the metabolically most active compartment of mature leaf cells. Their proteins are involved in essential cellular processes, such as photosynthesis, nitrogen fixation, and fatty acid synthesis. For this, chloroplast proteins have to associate with other fellow organellar proteins to form functional units, react to changing environmental conditions, or optimize efficiency of biochemical reactions. We here investigated chloroplast protein-protein interactions by a combination of complexome profiling and cross-linking mass spectrometry (CX-MS). Different detergents and MS settings were tested for developing a new workflow, which was found to produce data of improved quality when comparted to standard complexome profiling approaches. This procedure was applied to chloroplasts acclimated to increasing light intensities to investigate the role of protein-protein interactions in the adaption to these conditions.
DOI: 10.5281/zenodo.7182594
title: openENTRANCE - Case Study 1 - Residential Demand Response - Final Data

description: Three data files are provided for Case Study 1 in the openENTRANCE project: Full_potential.V9.csv, metaData.Full_Potential.csv, and acheivable_NUTS2_summary.csv. The data covers 10 residential devices on the NUTS2 level for the EU27 + UK +TR + NO + CH from 2020-2050. The devices included are storage heater, water heater with storage capabilitites, air conditiong, heat circulation pump, air-to-air heat pump, refreigeration (includes refrigerators and freezers), dish washer, washing machine, and tumble drier. Full_potential.V9.csv shows the NUTS2 level unadjusted loads for residential storage heater, water heater, air conditiong, circulation pump, air-to-air heat pump, refreigeration (includes refrigerators and freezers), dish washer, washing machine, and tumble drier using representative hours from 2020-2050. The loads provided here have not been adjusted with the direct load participation rates (see paper for more details). More details on the dataset can be found in the metaData.Full_Potential.csv file. The acheivable_NUTS2_summary.csv shows the NUTS2 level acheivable direct load control potentials for the average hour in the respective year (years - 2020, 2022,2030,2040, 2050).
DOI: 10.35078/upg6jp
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Caratinga | Município: Pocrane

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.6084/m9.figshare.8164034
title: Additional file 4: of Genome-wide characterization of a SRO gene family involved in response to biotic and abiotic stresses in banana (Musa spp.)

description: Protein sequences used for the construction of phylogenetic trees. (TXT 39 kb)
DOI: 10.6084/m9.figshare.8164115.v1
title: Additional file 2: of lncRNA profile of Apis mellifera and its possible role in behavioural transition from nurses to foragers

description: The distribution of reads mapped to reference annotation. (XLS 25 kb)
DOI: 10.6084/m9.figshare.8164019.v1
title: Additional file 2: of Genome-wide characterization of a SRO gene family involved in response to biotic and abiotic stresses in banana (Musa spp.)

description: Chromosomal location, subcellular localization and putatively physicochemical characters of banana MaSROs. (XLSX 10 kb)
DOI: 10.6084/m9.figshare.8164028
title: Additional file 3: of Genome-wide characterization of a SRO gene family involved in response to biotic and abiotic stresses in banana (Musa spp.)

description: Information of the SRO orthologs in representative sequenced 16 plant species. (XLSX 14 kb)
DOI: 10.6084/m9.figshare.8164040.v1
title: Additional file 5: of Genome-wide characterization of a SRO gene family involved in response to biotic and abiotic stresses in banana (Musa spp.)

description: A newick file of the phylogenetic tree. (TXT 2 kb)
DOI: 10.6084/m9.figshare.8164139.v1
title: Additional file 6: of lncRNA profile of Apis mellifera and its possible role in behavioural transition from nurses to foragers

description: The top 20 enriched pathways in the TC_F vs. TC_N (A), SCC_YF vs. SCC_YN (B) and SCC_OF vs. SCC_ ON (C) comparisons (cis). (XLSX 12 kb)
DOI: 10.6084/m9.figshare.19174126
title: Additional file 1 of Combination of gut microbiota and plasma amyloid-β as a potential index for identifying preclinical Alzheimer’s disease: a cross-sectional analysis from the SILCODE study

description: Additional file 1 : Supplementary Table S1. The items of the semi-structured interview for lifestyles. Supplementary Table S2. Demographic information and neuropsychological assessments for CI patients. Supplementary Table S3. Gut microbial differences between CN- and CN+ with correction for multiple comparisons. Supplementary Table S4. The interaction effect between APOE and diagnosis in the altered gut microbiota for CN- and CN+ participants. Supplementary Figure S1. The alpha diversity of gut microbiota among the CN-, CN+, and CI groups. Each bar graph represented the mean and standard deviation. The Chao1 and ACE indexes showed significantly decline in CI compared with CN-. There were no significant differences in Simpson and Shannon indexes among the three groups. *, p &lt; 0.05. CN-, amyloid-β negative cognitively normal participants; CN+, amyloid-β positive cognitively normal participants; CI, cognitive impairment participants. Supplementary Figure S2. The PCoA and NMDS based on the distribution of ASVs. (A) PCoA showed that the difference of gut taxonomic composition between CN- and CI was marginal in statistical significance (F = 1.383, p &lt; 0.052); (B) NMDS showed that the gut taxonomic composition was significantly different between CN- and CI (R = 0.097, p &lt; 0.009); (C) PCoA showed that the gut taxonomic composition between CN+ and CI was not significantly different (F = 0.850, p &lt; 0.712); (D) NMDS showed that the structure of gut microbiota in the CN+ group was not significantly different from that in the CI group (F = -0.020, p &lt; 0.698). CN-, amyloid-β negative cognitively normal participants; CN+, amyloid-β positive cognitively normal participants; CI, cognitive impairment participants; ASV, amplicon sequence variants; PCoA, principal coordinates analysis; PERMANOVA, permutational multivariate analysis of variance; NMDS, non-metric multidimensional scaling; ANOSIM, analysis of similarities. Supplementary Figure S3. The relative abundance of altered gut microbiota at different taxonomic levels among the CN-, CN+ and CI groups. Bar graphs indicated the relative abundance of phylum-level (A), class-level (B), order-level (C), family-level (D), and genus-level (E) taxa. The phylum Firmicutes and its corresponding class Clostridia, order Clostridiales, family Desulfovibrionaceae, family Ruminococcaceae, genus Lachnospiracea_incertae_sedis and genus Faecalibacterium taxa showed a progressive decline from CN- to CN+ and CI. CN-, amyloid-β negative cognitively normal participants; CN+, amyloid-β positive cognitively normal participants; CI, cognitive impairment participants.
DOI: 10.6084/m9.figshare.20222014.v1
title: Additional file 2 of OsPP65 Negatively Regulates Osmotic and Salt Stress Responses Through Regulating Phytohormone and Raffinose Family Oligosaccharide Metabolic Pathways in Rice

description: Additional file 2: Table S1. Differentially expressed genes in ko6 plants by RNA-seq analysis before (0 h) and after (4 h) osmotic stress treatment. |log2 Ratio| ≥1 and FDR ≤ 0.05.
DOI: 10.6084/m9.figshare.20222020.v1
title: Additional file 4 of OsPP65 Negatively Regulates Osmotic and Salt Stress Responses Through Regulating Phytohormone and Raffinose Family Oligosaccharide Metabolic Pathways in Rice

description: Additional file 4: Table S3. 120 metabolites identified by GC-MS in WT and the OsPP65 knockout plants. Number after the metabolite represents the isomer.
DOI: 10.6084/m9.figshare.20222817
title: Autophagy loss impedes cancer-associated fibroblast activation via downregulating proline biosynthesis

description: Cancer-associated fibroblasts (CAFs) are considered one of the most critical stromal cells that interact with pancreatic ductal adenocarcinoma (PDAC) and promote tumor growth, metastasis, and treatment resistance. Previous studies illustrated macroautophagy/autophagy contributes to CAF activation during tumor progression. Here in our study, we found that autophagy deficiency in CAFs impedes CAF activation by inhibiting proline biosynthesis and collagen production. Furthermore, we uncovered that autophagy promotes proline biosynthesis through mitophagy-mediated regulation of NADK2 (NAD kinase 2, mitochondrial), an enzyme responsible for production of mitochondrial NADP(H). Using an orthotopic mouse model of PDAC, we found that inhibiting mitophagy by targeting PRKN (parkin RBR E3 ubiquitin protein ligase) in the stroma reduced tumor weight. Thus, inhibition of CAFs mitophagy might be an attractive strategy for stroma-focused anti-cancer intervention.
<b>Abbreviations:</b> ACTA2/α-SMA: actin alpha 2, smooth muscle, aorta; ACTB/β-actin: actin, beta; ALDH18A1/P5CS: aldehyde dehydrogenase 18 family, member A1; ATG3: autophagy related 3; ATG5: autophagy related 5; BNIP3L: BCL2/adenovirus E1B interacting protein 3-like; CAFs:cancer-associated fibroblasts; COL1A1: collagen, type I, alpha 1; DES: desmin; ECM: extracellular matrix; FABP4: fatty acid binding protein 4, adipocyte; FAP/FAPα: fibroblast activation protein; IHC: immunohistochemical staining; LAMP1: lysosomal-associated membrane protein 1; NADK2: NAD kinase 2, mitochondrial; PC1: pro-collagen 1; PDAC: pancreatic ductal adenocarcinoma; PDGFR: platelet derived growth factor receptor; PDPN: podoplanin; PRKN: parkin RBR E3 ubiquitin protein ligase; PSCs: pancreatic stellate cells; VIM: vimentin; WT: wild-type
DOI: 10.6084/m9.figshare.8164211.v1
title: MOESM4 of Effect of intestinal tapeworms on the gut microbiota of the common carp, Cyprinus carpio

description: Additional file 4: Table S2. Complete OTU table of gut microbiota at the genus level in the intestine of common carp (Cyprinus carpio).
DOI: 10.6084/m9.figshare.8164106.v1
title: Additional file 1: of lncRNA profile of Apis mellifera and its possible role in behavioural transition from nurses to foragers

description: Detailed information on six honey bee samples for RNA-seq. (XLS 25 kb)