Scientific Data最新文献

Recent studies have highlighted the potential association between common benign epilepsy syndromes in children and the development of partial cognitive impairment. We established a comprehensive database of cognitive, structural magnetic resonance imaging (sMRI), and resting-state functional magnetic resonance imaging (rsfMRI) data obtained from a cohort of 36 Chinese paediatric volunteers. The participants, aged 5-16 years, were specifically diagnosed with either benign epilepsy with centrotemporal spikes (BECTs) or childhood absence epilepsy by certified paediatric neurologists. All imaging data were collected by qualified clinicians, and cognitive data were collected within 1 year of magnetic resonance imaging data collection. This database allows researchers to perform more detailed analyses using multimodal data to explore the relationship between cognitive impairment and brain mechanisms in children with common epilepsy syndromes.

The Multidisciplinary Observatory for Study of the Arctic Climate (MOSAiC) expedition consisted of a year-long drifting survey of the Central Arctic Ocean. The ecosystems component of MOSAiC included the sampling of molecular data, with metagenomes collected from a diverse range of environments. The generation of metagenome-assembled-genomes (MAGs) from metagenomes are a starting point for genome-resolved analyses. This dataset presents a catalogue of MAGs recovered from a set of 73 samples from MOSAiC, including 2407 prokaryotic and 56 eukaryotic MAGs, as well as annotations of a near complete eukaryotic MAG using the Joint Genome Institute (JGI) annotation pipeline. The metagenomic samples are from the surface ocean, chlorophyll maximum, mesopelagic and bathypelagic, within leads and under-ice ocean, as well as melt ponds, ice ridges, and first- and second-year sea ice. This set of MAGs can be used to benchmark microbial biodiversity in the Central Arctic Ocean, compare individual strains across space and time, and to study changes in Arctic microbial communities from the winter to summer, at a genomic level.

The Oshima cherry (Cerasus speciosa), which is endemic to Japan, has significant cultural and horticultural value. In this study, we present a near complete telomere-to-telomere genome assembly for C. speciosa, derived from the old growth "Sakurakkabu" tree on Izu Oshima Island. Using Illumina short-read, PacBio long-read, and Hi-C sequencing, we constructed a 269.3 Mbp genome assembly with a contig N50 of 32.0 Mbp. We examined the distribution of repetitive sequences in the assembled genome and identified regions that appeared to be centromeric. Detailed structural analysis of these putative centromeric regions revealed that the centromeric regions of C. speciosa comprised repetitive sequences with monomer lengths of 166 or 167 bp. Comparative genomic analysis with Prunus sensu lato genome revealed structural variations and conserved syntenic regions. This high-quality reference genome provides a crucial tool for studying the genetic diversity and evolutionary history of Cerasus species, facilitating advancements in horticultural research and the preservation of this iconic species.

This study describes a monthly Atlas for the Northeast Asian Seas 2023 (ANAS23) with a 1/10° horizontal resolution and 73 vertical levels. For ANAS23, over 1.6 million hydrographic profiles were analyzed, utilizing a simple kriging interpolation technique, which considers data density and their covariance at each grid point, along with a profile stabilizing method to minimize damage to water-mass structures. Comparison of ANAS23 with previously published atlases, repeated sectional observations, and satellite-based geostrophic current fields reveals that the ANAS23 provides reliable descriptions of the spatial distribution of water masses, currents, thermohaline fronts, and mesoscale eddies while avoiding spike-shape noises, vertical instabilities, and artificial waters, particularly over large-topographic features. The ANAS23 could be utilized as a baseline to assess the dynamic state of climatological mean fields and their changes under evolving climates. The fact that uncertainty among atlases is still apparent, particularly in a region of scarce observations, calls for a collaborative international effort to collect qualified hydrographic observations for a better-performing regional atlas, thus improving predictive skills for future climate.

Crop production is among the most extensive human activities on the planet - with critical importance for global food security, land use, environmental burden, and climate. Yet despite the key role that croplands play in global land use and Earth systems, there remains little understanding of how spatial patterns of global crop cultivation have recently evolved and which crops have contributed most to these changes. Here we construct a new data library of subnational crop-specific irrigated and rainfed harvested area statistics and combine it with global gridded land cover products to develop a global gridded (5-arcminute) irrigated and rainfed cropped area (MIRCA-OS) dataset for the years 2000 to 2015 for 23 crop classes. These global data products support critical insights into the spatially detailed patterns of irrigated and rainfed cropland change since the start of the century and provide an improved foundation for a wide array of global assessments spanning agriculture, water resource management, land use change, climate impact, and sustainable development.

The circadian clock regulates various physiological processes in mammals. The core circadian clock gene Bmal1 is crucial for maintaining the oscillations of the circadian clock system by controlling the rhythmic expression of numerous circadian clock-controlled genes. To explore the transcriptional changes associated with Bmal1 deletion in liver tissues, we collected liver tissues from global and liver-specific Bmal1 knockout mice, along with their respective control groups, at two circadian time points (CT2 and CT14) and used them for transcriptome sequencing analysis. Genotyping, locomotor activity analysis, and comprehensive quality control analyses, including base quality scores, GC content, and mapping rates, confirmed the high quality of sequencing data. Differential expression analysis and RT-qPCR validation confirmed the reliability and validity of the dataset. These data offer a valuable resource for researchers investigating the role of BMAL1 in liver physiology, pathology, and the broader field of circadian biology.

Progress in both Machine Learning (ML) and Quantum Chemistry (QC) methods have resulted in high accuracy ML models for QC properties. Datasets such as MD17 and WS22 have been used to benchmark these models at a given level of QC method, or fidelity, which refers to the accuracy of the chosen QC method. Multifidelity ML (MFML) methods, where models are trained on data from more than one fidelity, have shown to be effective over single fidelity methods. Much research is progressing in this direction for diverse applications ranging from energy band gaps to excitation energies. One hurdle for effective research here is the lack of a diverse multifidelity dataset for benchmarking. We provide the Quantum chemistry MultiFidelity (QeMFi) dataset consisting of five fidelities calculated with the TD-DFT formalism. The fidelities differ in their basis set choice: STO-3G, 3-21G, 6-31G, def2-SVP, and def2-TZVP. QeMFi offers to the community a variety of QC properties such as vertical excitation properties and molecular dipole moments. Further QeMFi offers QC computation times allowing for a time benefit benchmark of multifidelity models for ML-QC.

Biogas production through the anaerobic digestion (AD) of organic waste plays a crucial role in promoting sustainability and closing the carbon cycle. Over the past decade, this has driven global research on biogas-producing microbiomes, leading to significant advances in our understanding of microbial diversity and metabolic pathways within AD plants. However, substantial knowledge gaps persist, particularly in understanding the specific microbial communities involved in biogas production in countries such as South Korea. The present dataset addresses one of these gaps by providing comprehensive information on the metagenomes of five full-scale mesophilic biogas reactors in South Korea. From 110 GB of raw DNA sequences, 401 metagenome-assembled genomes (MAGs) were created, which include 42,301 annotated genes. Of these, 187 MAGs (46.7%) were classified as high-quality based on Minimum Information about Metagenome-Assembled Genome (MIMAG) standards. The data presented here contribute to a broader understanding of biogas-specific microbial communities and offers a significant resource for future studies and advancements in sustainable biogas production.

The rare earth elements Sm and Nd significantly address fundamental questions about crustal growth, such as its spatiotemporal evolution and the interplay between orogenesis and crustal accretion. Their relative immobility during high-grade metamorphism makes the Sm-Nd isotopic system crucial for inferring crustal formation times. Historically, data have been disseminated sporadically in the scientific literature due to complicated and costly sampling procedures, resulting in a fragmented knowledge base. However, the scattering of critical geoscience data across multiple publications poses significant challenges regarding human capital and time. In response, we present an automated tabular extraction method for harvesting tabular geoscience data. We collect 10,624 Sm-Nd data entries from 9,138 tables in over 20,000 geoscience publications using this method. We manually selected 2,118 data points from it to supplement the previously constructed global Sm-Nd dataset, increasing its sample count by over 20%. Our automatic data collection methodology enhances the efficiency of data acquisition processes spanning various scientific domains.

Mytella strigata, a potentially invasive species native to South America, is rapidly spreading across various aquatic ecosystems around the globe, posing a threat to native mussels. This study presents the first comprehensive de novo transcriptome assembly of M. strigata. We generated 254 million reads, which were processed and assembled using the Trinity assembler, resulting in 60362 transcripts with an N50 of 1,578 bp and over 93-98% completeness, as confirmed by BUSCO analysis with multiple ortho-datasets. A number of databases were used for functional annotation, including UniProt, KEGG, Reactome, InterPro, and eggNOG. Gene Ontology and pathway analyses identified transcripts associated with key biological processes, including those associated with cell signalling, metabolism, stress responses, cancer pathways, and immune regulation. This dataset enriches the bivalve database by advancing the understanding of the adaptive success and evolutionary resilience of this invasive species. The present study provides a fundamental framework for future research on the ecological and evolutionary impacts of this invasive species.