| 1. |
- Berner, Logan T., et al.
(author)
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The Arctic plant aboveground biomass synthesis dataset
- 2024
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 11:1
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Journal article (peer-reviewed)abstract
- Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.
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| 2. |
- Cai, Lina, et al.
(author)
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Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study
- 2020
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 7:1
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Journal article (peer-reviewed)abstract
- Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D.
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| 3. |
- Flannick, Jason, et al.
(author)
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Data Descriptor : Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
- 2017
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In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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Journal article (peer-reviewed)abstract
- To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (> 80% of low-frequency coding variants in similar to ~82 K Europeans via the exome chip, and similar to ~90% of low-frequency non-coding variants in similar to ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
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| 4. |
- Hahn, Max, et al.
(author)
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Quantitative 3D OPT and LSFM datasets of pancreata from mice with streptozotocin-induced diabetes
- 2022
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 9:1
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Journal article (peer-reviewed)abstract
- Mouse models for streptozotocin (STZ) induced diabetes probably represent the most widely used systems for preclinical diabetes research, owing to the compound's toxic effect on pancreatic beta-cells. However, a comprehensive view of pancreatic beta-cell mass distribution subject to STZ administration is lacking. Previous assessments have largely relied on the extrapolation of stereological sections, which provide limited 3D-spatial and quantitative information. This data descriptor presents multiple ex vivo tomographic optical image datasets of the full beta-cell mass distribution in mice subject to single high and multiple low doses of STZ administration, and in glycaemia recovered mice. The data further include information about structural features, such as individual islet beta-cell volumes, spatial coordinates, and shape as well as signal intensities for both insulin and GLUT2. Together, they provide the most comprehensive anatomical record of the effects of STZ administration on the islet of Langerhans in mice. As such, this data descriptor may serve as reference material to facilitate the planning, use and (re)interpretation of this widely used disease model.
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| 5. |
- Högfors-Rönnholm, Eva, et al.
(author)
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Metagenomes and metatranscriptomes from boreal potential and actual acid sulfate soil materials
- 2019
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 6, s. 1-6
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Journal article (peer-reviewed)abstract
- Natural sulfide rich deposits are common in coastal areas worldwide, including along the Baltic Sea coast. When artificial drainage exposes these deposits to atmospheric oxygen, iron sulfide minerals in the soils are rapidly oxidized. This process turns the potential acid sulfate soils into actual acid sulfate soils and mobilizes large quantities of acidity and leachable toxic metals that cause severe environmental problems. It is known that acidophilic microorganisms living in acid sulfate soils catalyze iron sulfide mineral oxidation. However, only a few studies regarding these communities have been published. In this study, we sampled the oxidized actual acid sulfate soil, the transition zone where oxidation is actively taking place, and the deepest un-oxidized potential acid sulfate soil. Nucleic acids were extracted and 16S rRNA gene amplicons, metagenomes, and metatranscriptomes generated to gain a detailed insight into the communities and their activities. The project will be of great use to microbiologists, environmental biologists, geochemists, and geologists as there is hydrological and geochemical monitoring from the site stretching back for many years.
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| 6. |
- Lagali, Neil, et al.
(author)
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Wide-field corneal subbasal nerve plexus mosaics in age-controlled healthy and type 2 diabetes populations
- 2018
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 5
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Journal article (peer-reviewed)abstract
- A dense nerve plexus in the clear outer window of the eye, the cornea, can be imaged in vivo to enable non-invasive monitoring of peripheral nerve degeneration in diabetes. However, a limited field of view of corneal nerves, operator-dependent image quality, and subjective image sampling methods have led to difficulty in establishing robust diagnostic measures relating to the progression of diabetes and its complications. Here, we use machine-based algorithms to provide wide-area mosaics of the corneas subbasal nerve plexus (SBP) also accounting for depth (axial) fluctuation of the plexus. Degradation of the SBP with age has been mitigated as a confounding factor by providing a dataset comprising healthy and type 2 diabetes subjects of the same age. To maximize reuse, the dataset includes bilateral eye data, associated clinical parameters, and machine-generated SBP nerve density values obtained through automatic segmentation and nerve tracing algorithms. The dataset can be used to examine nerve degradation patterns to develop tools to non-invasively monitor diabetes progression while avoiding narrow-field imaging and image selection biases.
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| 7. |
- Latz, Meike, et al.
(author)
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A comprehensive dataset on spatiotemporal variation of microbial plankton communities in the Baltic Sea
- 2024
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 11:1
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Journal article (peer-reviewed)abstract
- The Baltic Sea is one of the largest brackish water environments on earth and is characterised by pronounced physicochemical gradients and seasonal dynamics. Although the Baltic Sea has a long history of microscopy-based plankton monitoring, DNA-based metabarcoding has so far mainly been limited to individual transect cruises or time-series of single stations. Here we report a dataset covering spatiotemporal variation in prokaryotic and eukaryotic microbial communities and physicochemical parameters. Within 13-months between January 2019 and February 2020, 341 water samples were collected at 22 stations during monthly cruises along the salinity gradient. Both salinity and seasonality are strongly reflected in the data. Since the dataset was generated with both metabarcoding and microscopy-based methods, it provides unique opportunities for both technical and ecological analyses, and is a valuable biodiversity reference for future studies, in the prospect of climate change.
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| 8. |
- Luciw, Matthew D., et al.
(author)
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Multi-channel EEG recordings during 3,936 grasp and lift trials with varying weight and friction
- 2014
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In: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 1
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Journal article (peer-reviewed)abstract
- WAY-EEG-GAL is a dataset designed to allow critical tests of techniques to decode sensation, intention, and action from scalp EEG recordings in humans who perform a grasp-and-lift task. Twelve participants performed lifting series in which the object's weight (165, 330, or 660 g), surface friction (sandpaper, suede, or silk surface), or both, were changed unpredictably between trials, thus enforcing changes in fingertip force coordination. In each of a total of 3,936 trials, the participant was cued to reach for the object, grasp it with the thumb and index finger, lift it and hold it for a couple of seconds, put it back on the support surface, release it, and, lastly, to return the hand to a designated rest position. We recorded EEG (32 channels), EMG (five arm and hand muscles), the 3D position of both the hand and object, and force/torque at both contact plates. For each trial we provide 16 event times (e.g., 'object lift-off') and 18 measures that characterize the behaviour (e. g., 'peak grip force').
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| 9. |
- Maxwell, Tania L., et al.
(author)
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Global dataset of soil organic carbon in tidal marshes
- 2023
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In: Scientific Data. - : Springer Nature. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Tidal marshes store large amounts of organic carbon in their soils. Field data quantifying soil organic carbon (SOC) stocks provide an important resource for researchers, natural resource managers, and policy-makers working towards the protection, restoration, and valuation of these ecosystems. We collated a global dataset of tidal marsh soil organic carbon (MarSOC) from 99 studies that includes location, soil depth, site name, dry bulk density, SOC, and/or soil organic matter (SOM). The MarSOC dataset includes 17,454 data points from 2,329 unique locations, and 29 countries. We generated a general transfer function for the conversion of SOM to SOC. Using this data we estimated a median (± median absolute deviation) value of 79.2 ± 38.1 Mg SOC ha−1 in the top 30 cm and 231 ± 134 Mg SOC ha−1 in the top 1 m of tidal marsh soils globally. This data can serve as a basis for future work, and may contribute to incorporation of tidal marsh ecosystems into climate change mitigation and adaptation strategies and policies.
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| 10. |
- Parween, Saba, et al.
(author)
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Spatial and quantitative datasets of the pancreatic beta-cell mass distribution in lean and obese mice
- 2017
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In: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 4
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Journal article (peer-reviewed)abstract
- A detailed understanding of pancreatic β-cell mass distribution is a key element to fully appreciate the pathophysiology of models of diabetes and metabolic stress. Commonly, such assessments have been performed by stereological approaches that rely on the extrapolation of two-dimensional data and provide very limited topological information. We present ex vivo optical tomographic data sets of the full β-cell mass distribution in cohorts of obese ob/ob mice and their lean controls, together with information about individual islet β-cell volumes, their three-dimensional coordinates and shape throughout the volume of the pancreas between 4 and 52 weeks of age. These data sets offer the currently most comprehensive public record of the β-cell mass distribution in the mouse. As such, they may serve as a quantitative and topological reference for the planning of a variety of in vivo or ex vivo experiments including computational modelling and statistical analyses. By shedding light on intra- and inter-lobular variations in β-cell mass distribution, they further provide a powerful tool for the planning of stereological sampling assessments.
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