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Mucosal influenza vaccines promise enhanced protection but lack defined immune correlates of protection. Here, the authors conduct a phase I trial of an intranasal recombinant influenza A/H5 vaccine with a nanoemulsion adjuvant, demonstrating successful mucosal priming and broad cross-clade immune responses, advancing the development of intranasal influenza vaccines.

Typical quantum error correcting codes assign fixed roles to the underlying physical qubits. Now the performance benefits of alternative, dynamic error correction schemes have been demonstrated on a superconducting quantum processor.

Experimental measurements of high-order out-of-time-order correlators on a superconducting quantum processor show that these correlators remain highly sensitive to the quantum many-body dynamics in quantum computers at long timescales.

Insights into the mechanism of methylthio-alkane reductase (MAR)—a nitrogenase-like enzyme essential for growth under sulfate-limited conditions—have remained scarce. Now a cryo-EM structure of MAR from Rhodospirillum rubrum, along with spectroscopic investigations, reveals how it uses complex metallocofactors for catalysis.

MrVI, based on deep generative modelling, is a unified framework for integrative, exploratory and comparative analyses of large-scale (multi-sample) single-cell RNA-seq datasets.

Cell type labelling in single-cell datasets remains a major bottleneck. Here, the authors present AnnDictionary, an open-source toolkit that enables atlas-scale analysis and provides the first benchmark of LLMs for de novo cell type annotation from marker genes, showing high accuracy at low cost.

Literature mining, such as systematic review and meta-analysis, is crucial for discovering, integrating, and interpreting emerging research. This study presents a specialized large language model for literature that outperforms six general LLMs and helps clinicians in study selection and data extraction tasks.

It remains unclear whether machine learning methods can accurately identify cancer driver alterations. Here, the authors compare machine learning-based approaches to other computational methods to determine their utility for annotating variants of unknown significance and identifying driver alterations in real-world cancer patient data, demonstrating superior performance.

This study combines AI and light-based brain stimulation to detect and treat Parkinson’s disease in mice, enabling early diagnosis and deeper insight into symptoms and treatment effects.

Pulmonary large cell neuroendocrine carcinoma is an aggressive subtype of lung cancer. Here, the authors identify distinct subtypes based on genomic alterations and transcriptomic alterations.

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

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.

The results from a state-of-the-art suite of hydrodynamical cosmological zoom-in simulations show how globular clusters naturally emerge in the Standard Cosmology and also reveal the existence of a new class of object called globular-cluster-like dwarfs.

A single-cell sequencing study using more than 30,000 tumour genomes from human ovarian cancers shows that whole-genome doubling is an ongoing mutational process that drives tumour evolution and disrupts immunity.

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.

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.

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 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 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.

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.

Clonal haematopoiesis (CH) has been associated with altered inflammatory profiles and increased risk of cardiovascular and malignant diseases. Here, the authors analyze patient data from two different cohorts and show that CH is associated with severe infections and severe Covid19.

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.

Resistance to first line treatment is a major hurdle in cancer treatment, that can be overcome with drug combinations. Here, the authors provide a large drug combination screen across cancer cell lines to benchmark crowdsourced methods and to computationally predict drug synergies.

We report full-colour, vertically stacked µLEDs that achieve exceptionally high array density (5,100 pixels per inch) and small size (4 µm) via a 2D material-based layer transfer technique, allowing the creation of full-colour µLED displays for augmented and virtual reality.

Using well-calibrated statistical methods the authors jointly analyze Undiagnosed Diseases Network genomes, identifying known and novel disease genes. Software is publicly available to support future cross-cohort rare disease discovery efforts.

The Mass Spectrometry Query Language (MassQL) is an open-source language that enables instrument-independent searching across mass spectrometry data for complex patterns of interest via concise and expressive queries without the need for programming skills.

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

Basal cell adenoma (BCA) and basal cell adenocarcinoma (BCAC) of the salivary gland are rare tumours. Here the authors report that BCA and BCAC patients possess distinct genomic profiles despite histopathological similarities, and identify a recurrent FBXW11 missense mutation (p.F517S) which leads to accumulation of β-catenin in BCA and higher expression of Wnt/β-catenin targets.

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.

Kwak et al. report that adherens junctions organize membrane microdomains, leading to lipid-dependent γ-secretase recruitment and size-dependent protein segregation, excluding full-length Notch receptor.

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.

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.

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.

Combined high-throughput protein engineering with machine learning to curate libraries of CRISPR genome-editing enzymes with distinct genome targeting properties is described.

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.

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.

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.

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.

The authors highlight inconsistencies and divergencies in the literature reporting data on indirect calorimetry for studies on whole-body energy homeostasis, and propose harmonization of standards to facilitate data comparison and interpretation across different 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.

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.

This study shows that cerebellar Bergmann glia process noxious stimuli by integrating signals from the locus coeruleus. This mechanism modulates pain-related behaviors. These findings provide insight into cerebellar involvement in pain processing.