Find research datasets worth reusing

opencc-by-4.0Feb 2020View details →

Resilient farm demographics withstand, adapt, or transform in the face of competitive pressure, technological change, and the expected lifestyles of future generations

Farm demographics has been recognized as an important driver of structural change in European agriculture. Focus groups and computer simulations on farm demographic change were used to better understand its role for the case study regions of the Altmark in the eastern part of Germany and Flanders in the northern part of Belgium. According to these analyses, many potential agricultural entrants are deterred by what they view as a poor quality of life that farming offers. This applies to farm successors as well as hired workers. For higher attractiveness of agriculture, policy objectives should address the social image of farming as well as revitalize rural areas. Increasingly critical is the demand for skilled hired labour. However, policies dealing with farm demographic change ignore these needs and focus almost exclusively on farm succession. Particularly, the direct payment system, including additional support for small farms and young farmers, must be re-evaluated for its effectiveness. The analyses provide evidence that this system constrains European agricultural development more than assists it; ultimately preventing farms from adapting and transforming.

opencc-by-4.0Sep 2023View details →

Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus)

Supplemental datasets associated with publication: Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) Abstract <ul> <li>Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species.</li> <li>Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus constitutive QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum. We did not identify any loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen—hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR.</li> <li>This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight constitutively expressed candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. In conclusion, this study represents and advancement in our understanding if broad-spectrum QDR in B. napus and is a significant resource for the scientific community.  </li> </ul> Description of data files Full dataset for input into AT analysis  Full datasets (infection phenotypes for A. brassicicola, B. cinerea, or V.longisporum, ROS measurements for chitin, flg22, or elf18) and link to original P. brassicae dataset. These datasets were used for input into the Associative Transcriptomics pipeline (Nichols, 2022, <a href="https://github.com/bsnichols/GAGA. https://zenodo.org/badge/latestdoi/512807075">https://github.com/bsnichols/GAGA. https://zenodo.org/badge/latestdoi/512807075</a>).  Table S1 Mean, normalized phenotype data for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). These data were used for association transcriptomic analysis.  Table S2 Full list of single nucleotide polymorphism (SNP) markers and significance levels from genome-wide association (GWA) analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. The best fit model for GWA analysis is indicated in the tab title. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates SNP location along the chromosome; the y-axis indicates the -log10(p) (P value). Qqplots are included to demonstrate model fit. Table S3 Full list of gene expression markers (GEMs) and significance levels from GEM analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates GEM location along the chromosome; the y-axis indicates the -log10(p) (P value).  Table S4 184 gene expression markers (GEMs) associated with chitin-induced ROS compared with GEMs associated with resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by flg22, and elf18. Lists correspond to Venn diagrams in Fig. 2. The first tab includes all 184 GEMs associated with chitin-induced ROS. The subsequent tabs include lists of shared GEMs associated with chitin-induced ROS response and each additional trait (quantitative disease resistance (QDR) to each fungal pathogen or additional PAMP-induced ROS responses). The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S5 Enrichment analyses to determine if the number of gene expression markers (GEMs) shared between different lists is greater than the number of GEMs that would be expected by chance (e.g., lists of quantitative disease resistance (QDR) GEMs for two fungal pathogens). The representation factor is the number of overlapping GEMs divided by the expected number of overlapping GEMs drawn from two independent groups (traits), considering the total number of GEMs sequenced (53884). A representation factor > 1 indicates more overlap than expected of two groups, a representation factor < 1 indicates less overlap than expected, and a representation factor of 1 indicates that the two groups by the number of genes expected for independent groups of genes.  Table S6 Results from Weighted Co-expression Gene Network Analysis (WGCNA). The first tab indicates significant modules from WGCNA analysis. Black and magenta modules are associated with antagonistic effects on resistance/susceptibility to all four pathogens. The second tab includes a full list of the GEM markers (Table S3), which are in significant WGCNA modules. The third, fourth and, fifth tabs indicate all significant GEMs in the black module,  GO terms associated with GEMs in the black module, and all GO terms associated with the black module, respectively.  The sixth, seventh and, eighth tabs indicate all significant GEMs in the magenta module,  GO terms associated with GEMs in the magenta module, and all GO terms associated with the magenta module, respectively. Table S7 Shared gene expression markers (GEMs) associated with resistance to different pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum). Lists correspond to matrices and Venn diagrams in Fig. 3. The first tab includes all GEMs associated quantitative disease resistance (QDR) to the fungal pathogens. The subsequent tabs include lists of shared GEMs associated with QDR to two or more fungal pathogens. The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S8 List of genes in linkage disequilibrium with the top marker for Verticillium longisporum resistance from genome-wide association (GWA) analysis on chromosome A09 (107 genes)(Tab 1) and the homoeologous region on C08 (Tab 2). Their percentage identity and query coverage in Brassica napus reference genotypes Quinta, Tapidor, Westar and Zhongshuang 11 compared to the B. napus pantranscriptome is indicated. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.

opencc-by-4.0Nov 2021View details →

Neolithic Settlements in Central Europe: Data from the Project 'Lifestyle as an Unintentional Identity in the Neolithic'

This repository contains data set submitted to Journal of Open Archaeology Data. The data set originated in course of the Czech Science Foundation project n. 19-16304S entitled Lifestyle as an unintentional identity in the Neolithic. The data set comprises of over 2100 Neolithic settlement sites from Central Europe (mainly Czech Republic with small parts of Slovakia and Austria). Each site is is defined by spatial coordinates and information about relative chronology phase. The time span is 4900 BCE to 3300 BCE. The data set consists of the following files: <ul> <li> sites.csv – is a main list of sites with unique identifiers in the id field, id starting with B means the site is from the eastern part of the Bohemia section of the study area and in case of id starting with M the site is from the Morava river catchment. Field orig_id contains identifier by which the site is referenced in cited works and field site contains the site name; </li> <li> pot_traditions.csv – contains site ids, field chrono giving the general pottery tradition and field period listing occurence of the site in one of the nine time slices; </li> <li> pot_groups.csv – has same fields as the previous file with the difference in chrono field that contains information on detailed pottery groups; </li> <li> references.csv – list of references, where possible, the excavation reports are linked to their source in the Digital Archive of the Archaeological Map of the Czech Republic (<a href="https://digiarchiv.aiscr.cz/">https://digiarchiv.aiscr.cz/</a>). Column ref_id is linked through file references_sites.csv to the database of sites in sites.csv file. </li> <li> references_sites.csv – connects files references.csv and sites.csv </li> </ul> Geodata (in S-JTSK / Krovak East North coordinate reference system): <ul> <li> site_locations.gml and site_locations.xsd – settlement sites locations. The id field gives a unique identifier for each site, column accuracy gives how accurately the site location is defined, value 1 meaning accurate location (instrumentally measured), value 2 is precision in hundreds of meters, i.e. the site location is known by the local name, street name or so and value 3 means the location is not very accurate, in approx. 1 km range. The field surface is TRUE if the site is defined based on surface survey only and field altitude gives altitude in meters; </li> <li> study_area.gml and study_area.xsd – polygon giving the borders of the area where data was initially collected; </li> <li> regions.gml and regions.xsd – polygons giving the extent of the two studied regions, (1) eastern part of Bohemia and (2) Morava river drainage basin; </li> <li> raw_material_sources.gml and raw_material_sources.xsd – locations of raw material sources as points or lines. Points are based on places where prehistoric procurement activities are known or the outcrops of the given raw materials are present.  Lines give the border of the raw material occurrence in case of erratic flint or river courses, in which the raw materials can be procured. The rm column gives an abbreviated name of the raw material and type field is either l for chipped stone tools or p for polished stone tools. </li> </ul> Vocabularies: <ul> <li> voc_periods.csv – contains period labels; </li> <li> voc_pot_traditions.csv – contains pottery traditions labels, where possible, field periodo_link maps the period to AMCR Periods Vocabulary at Periodo (<a href="http://n2t.net/ark:/99152/p0wctqt">http://n2t.net/ark:/99152/p0wctqt</a>); </li> <li> voc_pot_groups.csv – contains pottery groups labels, same fields as previous file; </li> <li> voc_pot_groups_facets.csv – general labels for pottery groups; </li> <li>voc_raw_materials.csv – list of raw material abbreviations in the rm column of raw_material_sources.gml file with full names.</li> </ul>

opencc-by-4.0Sep 2024View details →

Supplemental data for: Mapping lifestyle factors in blood glucose variability in adolescents with Type 1 Diabetes Mellitus- A pilot study

<div> The dataset was used in the paper “Mapping lifestyle factors in blood glucose variability in adolescents with Type 1 Diabetes Mellitus- A pilot study”. The article is currently under review for publication. DOI to be inserted. </div> <div> A data-in-brief article is to be published to give in-depth information about the data collected to improve reproducibility "Dataset for: Lifestyle Factors and Blood Glucose Variability in Adolescents with Type 1 Diabetes Mellitus". DOI to be inserted.    The aim of the study was to assess whether adolescents with T1D in Ireland meet current nutrition and physical activity (PA) guidelines and to explore the impact of nutrition and PA on glycaemic variability (GV). The dataset includes continuous glucose monitoring (CGM) data, dietary intake records, and PA metrics, providing a comprehensive view of the participants' glucose levels and associated lifestyle behaviours. </div>

opencc-by-4.0Feb 2023View details →

Cessation of anti-diabetic medications by 'Daily 2-Only Meals-and- Exercise' lifestyle modification and remission of Type-2 Diabetes Mellitus

This is the dataset describing details of the patient's age, gender, weight, waist circumference, HBA1C levels and Fasting Insulin levels from the date of enrolment in the study and subsequent changes at monthly intervals.

opencc-by-4.0Nov 2023View details →

Lifestyle habits of adolescents before pandemic and one-year later

The database includes variables related to lifestyle habits (i.e. free-time activities, maladaptive behaviors, sleep quality, screen use) and anxiety of a sample of students (N=153, 16 years mean age, 72% female) who were assessed before pandemic (T0) and one year later (T1).

dryad40/100

Naked mole rats have distinctive cardiometabolic and genetic adaptations to their underground low-oxygen lifestyles (non-genetic data)

The naked mole-rat Heterocephalus glaber is a eusocial mammal exhibiting extreme longevity (37-year lifespan), extraordinary resistance to hypoxia and absence of cardiovascular disease. To identify the mechanisms behind these exceptional traits, metabolomics and RNAseq of cardiac tissue from naked mole-rats were compared to other African mole-rat genera. We identified metabolic and genetic adaptations unique to naked mole-rats including elevated glycogen, thus enabling glycolytic ATP generation during cardiac ischemia. Elevated normoxic expression of HIF-1α was observed while downstream hypoxia-responsive genes were down-regulated, suggesting adaptation to low-oxygen environments. Naked mole-rat hearts showed reduced succinate build-up during ischemia and negligible tissue damage following ischemia-reperfusion injury. These adaptive evolutionary traits reflect a unique hypoxic and eusocial lifestyle that collectively may contribute to their longevity and health span.

opencc-zeroJan 2024View details →

dryad40/100

Animal lifestyle affects acceptable mass limits for attached tags

Animal-attached devices have transformed our understanding of vertebrate ecology. To minimize any associated harm, researchers have long advocated that tag masses should not exceed 3% of carrier body mass. However, this ignores tag forces resulting from animal movement. Using data from collar-attached accelerometers on 10 diverse free-ranging terrestrial species from koalas to cheetahs, we detail a tag-based acceleration method to clarify acceptable tag mass limits. We quantify animal athleticism in terms of fractions of animal movement time devoted to different collar-recorded accelerations and convert those accelerations to forces (acceleration × tag mass) to allow derivation of any defined force limits for specified fractions of any animal's active time. Specifying that tags should exert forces that are less than 3% of the gravitational force exerted on the animal's body for 95% of the time led to corrected tag masses that should constitute between 1.6% and 2.98% of carrier mass, depending on athleticism. Strikingly, in four carnivore species encompassing two orders of magnitude in mass ( ca 2–200 kg), forces exerted by '3%' tags were equivalent to 4–19% of carrier body mass during moving, with a maximum of 54% in a hunting cheetah. This fundamentally changes how acceptable tag mass limits should be determined by ethics bodies, irrespective of the force and time limits specified.

opencc-zeroNov 2021View details →

opencc-by-4.0Jan 2022View details →

Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits

Full summary statistics for the publication "Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits".  The files, bmi.UKBBsummary.txt and height.UKBBsummary.txt, contain tissue specific associations with body mass index (BMI) and height respectively. The suffix UKBB450k indicates results from all ~450,000 European ancestry individuals in UK Biobank. The suffix UKBB50k corresponds to results from a subset of 50,000 Europeans in the UK Biobank. The suffix PAGE corresponds to results from ~50,000 individuals in the Population Architecture using Genomics and Epidemiology (PAGE) study.  The file PAGE_PrediXcan_associations.txt includes trait~tissue specific GReX associations for 25 traits. The first field specifies the tissue.trait.gene of the association results.

dryad40/100

Morphological adaptations linked to flight efficiency and aerial lifestyle determine natal dispersal distance in birds

Natal dispersal—the movement from birthplace to breeding location—is often considered the most significant dispersal event in an animal's lifetime. Natal dispersal distances may be shaped by a variety of intrinsic and extrinsic factors, and remain poorly quantified in most groups, highlighting the need for indices that capture variation in dispersal among species. In birds, it is hypothesized that dispersal distance can be predicted by flight efficiency, which can be estimated using wing morphology. However, the use of morphological indices to predict dispersal remains contentious and the mechanistic links between flight efficiency and natal dispersal are unclear. Here, we use phylogenetic comparative models to test whether hand-wing index (HWI, a morphological proxy for wing aspect ratio) predicts natal dispersal distance across a global sample of 114 bird species. In addition, we assess whether HWI is correlated with flight usage in foraging and daily routines. We find that HWI is a strong predictor of both natal dispersal distance and a more aerial lifestyle. Our results support the use of HWI as a valid proxy for relative natal dispersal distance, and also suggest that evolutionary adaptation to aerial lifestyles is a major factor connecting flight efficiency with patterns of natal dispersal.

opencc-zeroApr 2022View details →

opencc-zeroJun 2024View details →

Dataset: Atour Lifestyle Holdings Limited (ATAT) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →

Dataset: Nova LifeStyle, Inc. (NVFY) Stock Performance

Fig. 7 in Gill dimensions in near-term embryos of Amazonian freshwater stingrays (Elasmobranchii: Potamotrygonidae) and their relationship to the lifestyle and habitat of neonatal pups

Fig. 7. (A) The relationship between total gill area (cm2) and Relative Opening of the spiracle. (B) Linear regression of the mass-specific gill area (cm2 g-1) and body surface area (cm2) of different potamotrygonid embryos: upsidedown triangle - Plesiotrygon iwamae; star - Paratrygon aiereba; diamond - Potamotrygon motoro (from Negro River); dot - Potamotrygon motoro (from Solimões River); triangle - Potamotrygon orbignyi; square - cururu ray Potamotrygon sp.

Fig. 6 in Gill dimensions in near-term embryos of Amazonian freshwater stingrays (Elasmobranchii: Potamotrygonidae) and their relationship to the lifestyle and habitat of neonatal pups

Fig. 6. The two main axes of a principal component analysis based on total gill area, mass-specific gill area, body mass, total length, Anatomical Diffusion Factor and Relative Opening of Spiracule (ROSp) in the different potamotrygonid embryos: black triangle - Plesiotrygon iwamae; open diamond - Paratrygon aiereba; circle - Potamotrygon motoro (from Negro River); open triangle - Potamotrygon motoro (from Solimões River); black square - Potamotrygon orbignyi; open square - Potamotrygon sp. (cururu ray).

Fig. 5 in Gill dimensions in near-term embryos of Amazonian freshwater stingrays (Elasmobranchii: Potamotrygonidae) and their relationship to the lifestyle and habitat of neonatal pups

Fig. 5. Triplot of log (Anatomic Diffusion Factor) versus log(water/blood barrier thickness) versus log(mass-specific gill area) of the potamotrygonid embryos.

Fig. 3 in Gill dimensions in near-term embryos of Amazonian freshwater stingrays (Elasmobranchii: Potamotrygonidae) and their relationship to the lifestyle and habitat of neonatal pups

Fig. 3. Mass-specific gill area of the anterior and posterior hemibranchs of the gill arches in different potamotrygonid embryos: (A) Potamotrygon orbignyi; (B) Potamotrygon sp.; (C) Potamotrygon motoro (from Negro River); (D) Potamotrygon motoro (from Solimões River); (E) Plesiotrygon iwamae; (F) Paratrygon aiereba.

Fig. 2 in Gill dimensions in near-term embryos of Amazonian freshwater stingrays (Elasmobranchii: Potamotrygonidae) and their relationship to the lifestyle and habitat of neonatal pups

Fig. 2. Total superficial gill area of the anterior and posterior hemibranchs of the gill arches in different potamotrygonid embryos: (A) Potamotrygon orbignyi; (B) Potamotrygon sp.; (C) Potamotrygon motoro (from Negro River); (D) Potamotrygon motoro (from Solimões River); (E) Plesiotrygon iwamae; (F) Paratrygon aiereba.

Fig. 1 in Gill dimensions in near-term embryos of Amazonian freshwater stingrays (Elasmobranchii: Potamotrygonidae) and their relationship to the lifestyle and habitat of neonatal pups

Fig. 1. The potamotrygonid embryos: (A) Potamotrygon orbignyi; (B) cururu ray Potamotrygon sp.; (C) Potamotrygon motoro (from Negro River); (D) Potamotrygon motoro (from Solimões River); (E) Plesiotrygon iwamae; (F) Paratrygon aiereba. Scale bars= 1 cm.