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The International Brain Laboratory presents a brain-wide electrophysiological map obtained from pooling data from 12 laboratories that performed the same standardized perceptual decision-making task in mice.

Polygenic risk scores can help identify individuals at higher risk of type 2 diabetes. Here, the authors characterise a multi-ancestry score across nearly 900,000 people, showing that its predictive value depends on demographic and clinical context and extends to related traits and complications.

Brain-wide recordings in mice reveal that prior expectations are distributed through recurrent loops across all levels of cortical and subcortical processing.

Chronic care manages long-term, progressive conditions, while acute care handles short-term ones. Here, authors show chronic conditions account for most of the global health burden, with 68% of DALYs and 93% of YLDs attributed to chronic care needs.

This study reports on a closed-loop approach combining multiscale simulations, interpretable machine learning, experiments and techno-economic analysis for systematic plasma catalyst design, showing that alloys from noncritical minerals can potentially replace costly noble metals such as ruthenium for hydrogen production from ammonia decomposition under plasma conditions.

GHIST is a deep learning-based method that can predict spatial gene expression at high resolution using histology data.

The quark structure of the f₀(980) hadron is still unknown after 50 years of its discovery. Here, the CMS Collaboration reports a measurement of the elliptic flow of the f₀(980) state in proton-lead collisions at a nucleon-nucleon centre-of-mass energy of 8.16 TeV, providing strong evidence that the state is an ordinary meson.

An analysis of data from the Sherlock-Lung study provides insight into the mutational processes that contribute to lung cancer in never smokers, and looks at the possible role of factors such as air pollution and passive smoking.

Compiling data on floral introductions and European colonial history of regions worldwide, the authors find that compositional similarity of floras is higher than expected among regions once occupied by the same empire and similarity increases with the length of time the region was occupied by that empire.

An analysis of 18 metagenomic datasets of individuals with colorectal cancer, adenomas and healthy controls yields improved cancer prediction accuracy based solely on gut metagenomics, as well as the identification of new species associated with the development of cancer.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

In this Stage 2 Registered Report, Buchanan et al. show evidence confirming the phenomenon of semantic priming across speakers of 19 diverse languages.

This Registered Report compares computational methods for single-cell multimodal omics integration and provides recommendations for different tasks and scenarios.

Federated learning (FL) algorithms have emerged as a promising solution to train models for healthcare imaging across institutions while preserving privacy. Here, the authors describe the Federated Tumor Segmentation (FeTS) challenge for the decentralised benchmarking of FL algorithms and evaluation of Healthcare AI algorithm generalizability in real-world cancer imaging datasets.

The advantage of living in cities compared with rural areas with respect to height and BMI in children and adolescents has generally become smaller globally from 1990 to 2020, except in sub-Saharan Africa.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

Together with a companion paper, the generation of a transcriptomic atlas for the mouse lemur and analyses of example cell types establish this animal as a molecularly tractable primate model organism.

The LHCb experiment at CERN has observed significant asymmetries between the decay rates of the beauty baryon and its CP-conjugated antibaryon, thus demonstrating CP violation in baryon decays.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

Analysis of whole-genome sequences of 25,465 individuals of European ancestry shows that rare variants contribute substantially to the heritability of height and body mass index.

Systematic analysis from the Global Burden of Disease study reported that, despite global improvements from 1990 to 2021, dietary iron deficiency-associated disease burden remains high in women, children and residents in low socio-demographic index countries.

An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Replacing animal feathers and wool with synthetic materials can ameliorate the ethical and environmental issues associated with the production of clothing designed to retain warmth. Here the authors present synthetic nanofibre textiles that combine wearability, comfort, lightness and thermal insulation.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

Timothy Frayling, Joel Hirschhorn, Peter Visscher and colleagues report a meta-analysis of genome-wide association studies for adult height in 253,288 individuals. They identify 697 variants in 423 loci significantly associated with adult height and find that these variants cluster in pathways involved in growth and together explain one-fifth of the heritability for this trait.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

This study integrated proteomics, metabolomics, and genetics in EUR and AFR populations to map QTLs and identify ancestry-specific proteins/metabolites linked to T2D risk, highlighting molecular differences in disease mechanisms across ancestries.

How tree diversity effects on ecosystem functioning vary along climatic gradients is unclear. Here, analysing data from 15 experimental forest sites, the authors show that tree growth responses to neighbourhood species diversity are stronger in wetter climates but are unaffected by interannual climatic variation within sites.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.