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Exposure to air pollution poses a substantial risk to health, contributing to high rates of cardiovascular and respiratory mortality. A study now evaluates the health impacts of different PM_2.5 reduction strategies, providing evidence of their effectiveness across different regions and timeframes.

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.

Our understanding of chromosome organization and dynamics in spherical bacteria, such as Staphylococcus aureus, remains limited. Here, the authors show that chromosome replication and cell division cycles are not synchronized in S. aureus, with cells exhibiting two segregated origins of replication at the start of the cell cycle.

Methods for developing machine learning models in medical imaging across multi-centre collaborations face important challenges, including technical burdens and privacy issues. Here, the authors introduce CATegorical and PHenotypic Image SyntHetic learnING - CATphishing - as an alternative to Federated Learning to generate synthetic multi-contrast 3D MRI data for downstream tasks.

Global climate mitigation and clean cooking fuel use improves air quality and cardiopulmonary health for the majority of the world’s population. Co-implementation of strategies addressing both outdoor and household air pollution offers greater and sustained long-term health benefits.

Single-molecule imaging reveals that peptidoglycan synthesis and synthase activity, rather than FtsZ treadmilling, are rate limiting and drive septum constriction in Staphylococcus aureus.

Haematopoietic stem cell numbers are restricted at both systemic and local levels.

Tropical forest landscapes are increasingly being modified by human activities. Here the authors apply a causal inference approach to Neotropical forest data to disentangle the role of landscape-level and local drivers and reveal replacement of ‘loser’ by ‘winner’ tree species with distinct functional profiles.

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).

Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.

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

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.

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.

Here, the authors present the Network Correspondence Toolbox, which enables researchers to examine and report spatial correspondence between their neuroimaging results and widely used brain atlases.

Analysing camera-trap data of 163 mammal species before and after the onset of COVID-19 lockdowns, the authors show that responses to human activity are dependent on the degree to which the landscape is modified by humans, with carnivores being especially sensitive.

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.

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.

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.

Infection studies on highly pathogenic avian influenza virus clade 2.3.4.4b H5N1 on calves and lactating cows indicate that transmission occurs primarily via milk and milking procedures rather than respiratory routes.

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.

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.

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.

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.

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.

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.

By combining bioorthogonal metabolic labelling and resolution enhancement through sequential imaging of DNA barcodes, the molecular organization of individual sugars in the native glycocalyx has been resolved at a spatial resolution of 9 ångström.

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.

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.

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.

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 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.

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.

The Human Microglia Atlas includes 91,716 brain immune cells covering six neurologic pathologies. It characterizes the signatures of nine populations and describes the expansion of GPNMB-high microglia in Multiple Sclerosis and Alzheimer’s Disease.

Influenza infection during pregnancy can affect health of offspring but it is not clear how this affects immune responses. Here the authors use a mouse model to show that influenza infection during pregnancy can increase susceptibility to secondary infection and alter immune cell function in offspring.

Species that hibernate generally have longer lifespans than expected based on their body size. The authors show epigenetic ageing patterns from a natural population of hibernating yellow-bellied marmots consistent with the hypothesis that ageing is suspended during hibernation.

The search for antivirals against SARS-CoV-2 continue due to the emergence of variants of concerns, able to escape the vaccinal humoral response. In this work, authors pre-clinically explore the potential of kinetin against SARS-CoV-2, which could be used alone or in combination with other antivirals.

Inflammatory monocytes in the brain meninges promote stress-induced fear behaviour, and the pathways involved can be modulated using psychedelic compounds.

Here the authors show that there are alterations in the glycome profile of serum IgG Fc regions that precede the diagnosis of Crohn’s disease by many years and are associated with complications during disease. This altered glycome triggers innate immune cell activation at a preclinical phase, which is the basis for the transition from healthy tissue to intestinal inflammation.

Exome sequencing and copy number analysis are used to define genomic aberrations in early sporadic pancreatic ductal adenocarcinoma; among the findings are mutations in genes involved in chromatin modification and DNA damage repair, and frequent and diverse somatic aberrations in genes known as embryonic regulators of axon guidance.

Streptococcus dysgalactiae subsp. equisimilis (SDSE) is an emerging cause of human infection closely related to Streptococcus pyogenes. Here the authors investigate the degree of genomic similarity between the two species and assess implications for development of vaccines.

Islands can provide insights into the evolution of diverse adaptations. The genomes of 34 major lineages of Mediterranean wall lizards reveal a highly reticulated pattern of evolution across the group, characterised by mosaic genomes and showing that hybrid lineages gave rise to several extant endemics.

Recent studies have provided mechanistic insight into the cell cycle of coccoid bacteria. In this Review, Pinho, Kjos and Veening discuss our current understanding of the molecular mechanisms orchestrating peptidoglycan synthesis, cell division and chromosome segregation inStaphylococcus aureus and Streptococcus pneumoniae.

Understanding patterns in woody plant trait relationships and trade-offs is challenging. Here, by applying machine learning and data imputation methods to a global database of georeferenced trait measurements, the authors unravel key relationships in tree functional traits at the global scale.