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Heart failure can be caused by cardiac fibroblasts replacing myocytes. Here, the authors use functional genomic data from fibroblasts, genetic signals enriched in people with heart disease, and gene perturbation analyses to link disease-associated regulatory elements to protein-coding genes.

An electrostatic-repulsion-enabled advanced transfer technique based on ammonia solution is introduced for separating van der Waals thin-film materials from their substrates, demonstrating suitability for its use in the complementary metal–oxide–semiconductor (CMOS) industry.

The interplay between superconductivity, electron correlation and atomic ordering is at the heart of condensed-matter physics. Here, the authors demonstrate a link between superconductivity in the layered chalcogenide TaS_2−xSe_xand the ordering of the sulphur and selenium atoms

While Bell inequalities have been violated several times—mostly in photonic systems—their violations within particle physics experiments are less explored. Here, the BESIII Collaboration showcases Bell-violating nonlocal correlations between entangled hyperon pairs.

Circuit and cell type prioritization for complex disorders is crucial to direct future efforts. Here the authors integrate GWAS, human single-cell RNA-seq and fMRI analysis suggesting multi-modality convergence on amygdalar and hippocampal circuits.

In the final report of a phase 1/2 trial evaluating allogeneic CD19-specific CAR-NK cells armored with IL-15 in patients with CD19⁺ hematologic malignancies, the therapy was shown to be safe and efficacious with distinct cord blood features associated with response.

Increasing the metal loading of single-atom catalysts (SACs) typically results in aggregation, which can have a detrimental effect on catalytic performance. Now, a nitrogen-doping-assisted atomization approach is reported that transforms metal-sulfide nanoparticles into ultrahigh-density metal–nitrogen–carbon SACs.

Tracing cellular changes in complex biological systems is challenging. Here, authors present a flexible framework that integrates multi-sample data with in-house algorithms to infer comparative and spatiotemporal cell-gene patterns, advancing understanding of cellular dynamics.

The semileptonic decay channels of the Λc baryon can give important insights into weak interaction, but decay into a neutron, positron and electron neutrino has not been reported so far, due to difficulties in the final products’ identification. Here, the BESIII Collaboration reports its observation in e+e- collision data, exploiting machine-learning-based identification techniques.

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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

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.

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.

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.

Previous studies have proposed conflicting models of visual perceptual learning. Leveraging deep neural network modelling, human functional MRI imaging and multiunit recordings in macaques, Cheng et al. introduce a neural geometry approach to reconcile past findings. They propose a unified theory of visual perceptual learning.

A new dual-chimeric antigen receptor (CAR) system enhances the antitumor activity of CAR natural killer cells and makes them less susceptible to therapeutic resistance in preclinical models.

Polymer gels have potential in both flexible electronics and impact protections materials, but the balance between stiffness and toughness can be hard to achieve. Here, the authors report a gel with high-density crystalline domains linked by soft chelation crosslinking domains.

Early intermittent feeding of mice with a high-cholesterol Western-type diet accelerates atherosclerosis compared with late continuous exposure to the Western-type diet, despite similar cumulative circulating LDL-C levels.

A ketogenic diet and the ketone body β-hydroxybutyrate are shown to confer resistance to malaria in mice by inducing metabolic reprogramming in Plasmodium parasites, suggesting a dietary strategy for malaria prevention.

A transfer technique that embeds a van der Waals interface of interest in a high-adhesion matrix can decouple the properties of the functional interface from the forces required for its fabrication, providing single-step material-to-device integration.

The response of organic molecules to climate change is linked to warming, nutrient loading, and greenhouse gas emissions, according to an indicator developed to quantify the aggregated thermal response of individual organic molecules.

The efficacy of antiangiogenic therapy in the clinic is often limited by the emergence of resistance. Here, the authors show that in ovarian cancer anti-VEGF inhibitors induce the overexpression of CD5L in endothelial cells through hypoxia-driven PPARy activation and that blocking CD5L can overcome resistance.

Electric contacts of semimetallic bismuth on monolayer semiconductors are shown to suppress metal-induced gap states and thus have very low contact resistance and a zero Schottky barrier height.

A benchmarking competition improves tools that predict how regulatory regions control gene expression.

Binning is an essential step in genome-resolved metagenomic analysis in which assembled contigs originating from the same source population are clustered. However it is challenging, especially for low abundance microbial species. Here the authors introduce a toolkit that integrates multiple prominent binning tools and AI for efficient and high-resolution recovery of non-redundant bins from short- and long-read metagenomic sequencing datasets.

Mid-infrared photonic integrated circuits (PICs) are important for sensing and optical communications, but their operational wavelengths are usually limited below 4 μm. Here, the authors report the realization of photothermoelectric graphene photodetectors incorporated in a chalcogenide glass-on-CaF2 PIC operating at 5.2 μm, showing promising results for gas sensing applications.

Applications of van der Waals magnetic systems are typically hampered by the low Curie temperature of van der Waals magnets. Here, Wang et al use molecular beam epitaxy to grow large films of Fe₄GeTe₂ with Curie temperatures over 500 K, and the film’s magnetic anisotropy can be tuned arbitrarily by controlling stoichiometry.

Favoured cathodes for batteries should include abundant and redox-active elements, such as manganese. Here the authors report a Na_0.6Li_0.2Mn_0.8O₂ cathode design featuring a unique layer stacking sequence that provides topological protection to oxygen redox to overcome the performance fading.

ezSingleCell is an interactive and user-friendly application for the analysis of single-cell and spatial omics data, without the need for programming expertise. Here, authors integrated top-performing publicly available methods to enable comprehensive data analysis and interactive visualisation.

Hydrostatic pressure is an underexplored tuning knob to study moiré systems. Here a MoS₂/WSe₂ heterostructure is compressed and the enhancement in the moiré potential strength is quantified via moiré-activated Raman modes.

Using an integrated analysis on three independent large human datasets, Wang et al. map macroscale dysconnectivity in schizophrenia onto layer- and cell-type-specific microscale alterations. The authors identify different alterations of corticocortical and corticostriatal connectivity in schizophrenia and their relationship to different symptom dimensions and functional domains.