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Machine learning is used to understand emissions of the potent greenhouse gas nitrous oxide from the Southern Ocean. Low-pressure storms are found to drive emissions, leading to a revised picture of marine greenhouse gas cycling

Humanity’s Last Exam, a multi-modal benchmark at the frontier of human knowledge, is designed to be an expert-level closed-ended academic benchmark with broad subject coverage.

Rising CO₂ levels reduced drought stress on plants on the Qinghai–Tibetan Plateau over the past four decades, but this benefit is largely cancelled out by warming that increases plant water demand, as revealed by ecological modelling and multi-source observations from 1979 to 2018.

cellSTAAR advances noncoding rare variant association analysis by integrating single-cell genomics data.

Global Burden of Disease estimates show that between 1990 and 2023, the prevalence and burden of drug use disorders, inclusive of amphetamine, cannabis, cocaine and opioid use, have been increasing in high-income countries, particularly in the USA.

Large-effect variants in autism remain elusive. Here, the authors use long-read sequencing to assemble phased genomes for 189 individuals, identifying pathogenic variants in TBL1XR1, MECP2, and SYNGAP1, plus nine candidate structural variants missed by short-read methods.

The wastewater sector is a major source of non-CO₂ emissions, but accurate emissions accounting remains challenging, despite guidelines for basic inventories provided by the IPCC. This research reveals that national inventories widely omit key sources and apply inconsistent methods, which lead to greatly under-reported emissions.

Enfortumab vedotin (EV) is the current standard treatment for advanced bladder cancer, but resistance typically develops within a year, highlighting the need for new therapies. This study demonstrates that NECTIN4-targeting CAR T cells are effective against bladder cancer, including EV-resistant cells, and their potency can be further enhanced by using rosiglitazone to boost NECTIN4 expression.

Neural crest cells have been implicated in heart development, yet the mechanisms by which they act have remained elusive. Here, the authors show neural crest cells modulate Wnt signalling in cardiac progenitors, providing new insight into the mechanisms underpinning congenital heart defects.

The xylosyltransferase isoenzymes XT1 and XT2 catalyze the first glycosylation step in the biosynthesis of proteoglycans. Now, bump-and-hole engineering of XT1 and XT2 enables substrate profiling and modification of proteins as designer proteoglycans to modulate cellular behavior.

An algorithm that combines deep learning, Bayesian optimization and computer vision techniques can be used to autonomously tune a semiconductor spin qubit from a grounded device to Rabi oscillations.

The authors conduct a national inventory on individual tree carbon stocks in Rwanda using aerial imagery and deep learning. Most mapped trees are located in farmlands; new methods allow partitioning to any landscape categories, effective planning and optimization of carbon sequestration and the economic benefits of trees.

Single iron atoms on nitrogen-doped carbon catalysts are a promising alternative to platinum for the oxygen reduction reaction on fuel cell cathodes, but commonly suffer from low stability. Here an in situ chemical vapour deposition synthetic approach is presented, enabling high iron active site dispersion and reducing surface porosity, which mitigates demetallation and carbon corrosion, ensuring high activity and stability.

McGrail and colleagues report that high intratumoral bacteria abundance is associated with an immunosuppressive microenvironment and resistance to immune checkpoint blockade in head and neck squamous cell carcinoma.

A specialized, open-source, retrieval-augmented language model is introduced for answering scientific queries and synthesizing literature, the responses of which are shown to be preferred by human evaluations over expert-written answers.

High-depth sequencing of non-cancerous tissue from patients with metastatic cancer reveals single-base mutational signatures of alcohol, smoking and cancer treatments, and reveals how exogenous factors, including cancer therapies, affect somatic cell evolution.

National greenhouse gas inventories systematically undercount methane and nitrous oxide emissions from wastewater due to outdated methods and incomplete coverage. Addressing these discrepancies is essential to strengthen transparency in global climate efforts and improving the effectiveness of national mitigation strategies.

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.

Mapping of the neutrophil compartment using single-cell transcriptional data from multiple physiological and patological states reveals its organizational architecture and how cell state dynamics and trajectories vary during health, inflammation and cancer.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

EchoPrime, a video-based foundation artificial intelligence model for echocardiography, is presented.

As immune checkpoint therapy is more frequently used for cancer, side effects such as Stevens-Johson syndrome / toxic epidermal necrolysis (SJS/TEN) are becoming more common. Here the authors use single cell transcriptomics to implicate TNF and CXCL10 in recruitment of CXCR3⁺ cytotoxic T cell in SJS/TEN skin lesions.

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.

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.

Here the authors provide an explanation for 95% of examined predicted loss of function variants found in disease-associated haploinsufficient genes in the Genome Aggregation Database (gnomAD), underscoring the power of the presented analysis to minimize false assignments of disease risk.

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.

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.

The authors analyze 162 primary mismatch-repair-deficient gliomas and identify three subgroups underpinned by distinct somatic mutations in replicative DNA polymerases and IDH1.

Combination of epidemiology, preclinical models and ultradeep DNA profiling of clinical cohorts unpicks the inflammatory mechanism by which air pollution promotes lung cancer

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.

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.

The endoplasmic-reticulum (ER) transmembrane protein IRE1 mitigates ER stress through kinase-ribonuclease and scaffolding activities. However, a significant nonenzymatic IRE1 dependency has been shown in cancer. Here, the authors design a proteolysis-targeting chimera (PROTAC) to fully disrupt cellular IRE1 protein, selectively blocking growth of IRE1-dependent cancer cells.

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.

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.

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.

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.

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.

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

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.

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.

Spread of bloodborne infections, such as HCV and HIV, is a problem, particularly amongst people who inject drugs (PWID). Here, the authors describe and then confirm in observational PWID cohorts that those with more non-pathogenic viruses in plasma were more likely later to acquire HCV than PWID who had fewer of these non-pathogenic viruses.