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Scientists who join protest movements often find themselves at the centre of a media and political firestorm, causing tensions with some employers.

The APOE-ε4 allele is the strongest genetic risk factor for late-onset Alzheimer’s disease, but it is not deterministic. Here, the authors show that common genetic variation changes how APOE-ε4 influences cognition.

The authors survey community palaeontological databases, documenting their contributions to science as well as their vulnerabilities, and provide recommendations for the future of open science databases.

The pressures faced by lab leaders to be excellent researchers, teachers, managers, accountants and mentors can exact a heavy toll.

A follow-up analysis of a clinical trial that evaluated anti-PD-1 therapy in patients with cancer who are living with HIV provides mechanistic insights into transcriptomic, cellular and cytokine changes related to immune checkpoint inhibitor treatment and identifies a signature associated with clinical response.

Scientists who don’t consistently publish great papers and attract bumper funding are often overlooked, say campaigners for healthier lab environments.

Projected impacts of climate change on malaria burden in Africa by 2050 highlight the urgent need for climate-resilient malaria control strategies and robust emergency response systems to safeguard progress towards malaria eradication.

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.

Identifying jets originating from heavy quarks plays a fundamental role in hadronic collider experiments. In this work, the ATLAS Collaboration describes and tests a transformer-based neural network architecture for jet flavour tagging based on low-level input and physics-inspired constraints.

Lampert et al. use a game theoretic approach to study conditions in which vaccine-rich countries might donate vaccines. They find that if the total amount of surplus vaccines is sufficiently large, coordination can lead to significant surplus donations even by strictly self-interested vaccine-rich countries.

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.

Land-use change, among other anthropogenic factors, has led to increased levels of zoonotic disease transmission. The authors assess how land-use change and restoration activities impact zoonotic disease transmission, providing an online tool useful for One Health-oriented restoration planning.

Kinematic measurements of the Perseus galaxy cluster reveal two drivers of gas motions: a small-scale driver in the inner core associated with black-hole feedback and a large-scale driver in the outer core powered by mergers.

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.

Kozai, Fernandez-Martinez et al. use high-speed atomic force microscopy to study the permeability barrier of yeast nuclear pore complexes. They show that karyopherins remodel a central plug that shapes barrier dynamics and disorder within the pore.

Two researchers with direct experience of online abuse describe its impact, coping strategies, and how it compares to other types of harassment.

Global warming is causing widespread coral mortality through bleaching. Here, simulations of coral eco-evolutionary dynamics forecast strong population declines in the 21st century. Coral reefs may collapse by 2100, unless global warming is limited to 2 °C, enabling corals to adapt and persist.

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.

A growth-coupled biosynthetic pathway enables xathommatin synthesis in the soil bacterium Pseudomonas putida.

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).

Fault tolerance is essential for reliable AI acceleration using novel memristive hardware. Yousuf et al. developed a training-free fault tolerance scheme and demonstrated on a 20,000-memristor prototyping platform that it outperforms other solutions.

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.

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.

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.

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.

What is the state of trust in scientists around the world? To answer this question, the authors surveyed 71,922 respondents in 68 countries and found that trust in scientists is moderately high.

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

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.

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.

Lipid particles loaded with RNA coding for tumour-unspecific antigens can enhance early responses of type-I interferons, mediating the success of immune checkpoint inhibitors as well as epitope spreading.

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.

A behavioral healthcare workforce — concordant in race, ethnicity, lived experience, language, and geography with the populations it serves — is urgently needed to end the US behavioral health crisis.

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.

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.

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.

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 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.

Scvi-hub is a versatile and efficient platform for model-based analysis of single-cell sequencing studies with access to a diverse array of datasets and downstream analysis.

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.

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.

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.

XRISM observations show the presence of odd-numbered elements chlorine and potassium in Cas A. These findings suggest that stellar activity plays an important role in cosmic chemical evolution, enriching space with elements vital for planets and life.

Engineering quantum states requires precise manipulations at the atomic level. Here, the authors use deep reinforcement learning to manipulate Ag adatoms on Ag surfaces, which combined with path planning algorithms enables autonomous atomic assembly.

Data collected from more than 2,000 taxa provide an unparalleled opportunity to quantify how extreme wildfires affect biodiversity, revealing that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas.

Shen et al. show that pre-existing neural similarity in strangers predicts future friendship and changes in social distance over time in an emerging social network of MBA students.