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An optical archival storage technology based on femtosecond laser direct writing in glass addresses the practical demands of archival storage.

The contribution of ether lipid species in cancer cell fate has not been fully understood yet. Here the authors show that malignant cancer cells employ ether lipids to modulate membrane biophysical properties, enhancing iron endocytosis and ferroptosis susceptibility.

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.

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.

Scanning nitrogen-vacancy microscopy unveils super-moiré spin textures emerging in twisted double-bilayer CrI₃ and provides real-space evidence of antiferromagnetic Néel-type skyrmions spanning multiple moiré cells.

A multiancestry phenome-wide analysis of copy number variants in the UK Biobank genomes increases power to detect genetic associations with complex traits across human populations.

Splice-site targeting antisense oligonucleotides can increase the expression of host gene intron-embedded microRNA and affect axonal development in zebrafish.

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

How the brain adapts its representations to prioritize task-relevant information remains unclear. Here, the authors show that both monkey brains and deep learning models stretch neural representations along goal-relevant dimensions, with spike timing playing a key role.

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

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.

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.

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.

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.

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.

Artificial intelligence has become popular as a cancer classification tool, but there is distrust of such systems due to their lack of transparency. Here, the authors develop an explainable AI system which produces text- and region-based explanations alongside its classifications which was assessed using clinicians’ diagnostic accuracy, diagnostic confidence, and their trust in the system.

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

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.

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.

A meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

Creative experiences such as dance, music, drawing, and strategy video games might preserve brain health. The authors show that regular practice or short training in these activities is linked to brains that look younger and work more efficiently.

HistoPlexer, a deep learning model, generates multiplexed protein expression maps from H&E images, capturing tumour–immune cell interactions. It outperforms baselines, enhances immune subtyping and survival prediction and offers a cost-effective tool for precision oncology.

Targeting FSP1 in lymph nodes has considerable potential for blocking melanoma progression.

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.

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 role of rare pathogenic/likely pathogenic (P/LP) germline variants in pediatric central nervous system (CNS) tumour development remains poorly understood. Here, the authors investigate the prevalence and clinical significance of germline P/LP variants in cancer predisposition genes across 830 CNS tumour patients.

Molecular biomarkers of recurrence in colorectal cancer (CRC) generally cannot capture spatial information about the tumour and its microenvironment. Here, the authors develop HIBRID, a deep learning model to predict disease-free survival in CRC from histopathology whole slide images, improving risk stratification in large cohorts.

Regrowth of lost enamel in tooth decay and sensitivity is a major obstacle to overcome. Here, the authors report on a protein-based material that mimics features of natural enamel formation, allowing for epitaxial growth of apatite nanocrystals to restore enamel structure and function.

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.

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.

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.

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.

Resonant dispersive wave (RDW) emission enables tunable few-femtosecond UV pulses which can be useful for ultrafast science. Here, the authors investigate ultrafast relaxation and structural evolution of morpholine with enhanced temporal resolution, following excitation via RDWs.

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.

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.

Insects are declining in many regions. Here the authors show that arthropod biomass losses in Jena Experiment and Biodiversity Exploratories time series are driven more by species loss than by species identity and abundance declines, and are mitigated by high plant diversity and low land-use intensity.

Chordoma is a rare often incurable malignant bone tumour. Here, the authors investigate driver mutations of sporadic chordoma in 104 cases, revealing duplications in notochordal transcription factor brachyury (T), PI3K signalling mutations, and mutations in LYST, a potential novel cancer gene in chordoma.

Literature produced inconsistent findings regarding the links between extreme weather events and climate policy support across regions, populations and events. This global study offers a holistic assessment of these relationships and highlights the role of subjective attribution.

Analyses of neuroimaging datasets from 5,306 participants across 15 countries found generally larger brain-age gaps in Latin American compared with non-Latin American populations, which were influenced by disparities in socioeconomic and health-related factors.

The transcription factor ATF6 causes an enrichment in long-chain fatty acids in the colonic epithelium, which leads to changes in the gut microbiota and contributes to the development of colorectal cancer in humans and mice, thereby linking endoplasmic reticulum stress responses to lipid metabolism and tumorigenesis.

Using X-ray photon correlation spectroscopy, this study reveals the rivalry between two distinct types of atomic motion in a metallic glass, offering insights into the complex dynamics and relaxation processes across the glass transition.

Yuan et al. present crossNN, an explainable machine learning tool to classify tumors based on DNA methylation data from several platforms with different epigenome coverage and sequencing depth, benchmark against other models and validate externally.

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.