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The development of a universal protein coarse-grained model has been a long-standing challenge. A coarse-grained model with chemical transferability has now been developed by combining deep-learning methods with a large and diverse training set of all-atom protein simulations. The model can be used for extrapolative molecular dynamics on new sequences.

Cannabinoids potentiate responses of brain receptors, but their mechanism of action is unknown. Here, using coarse-grained MD simulations and electrophysiology of mutants, the authors elucidate the allosteric binding sites for two cannabinoids at the glycine receptor.

Estimates from the Global Burden of Disease study reveal declines in chronic respiratory disease mortality between 1990 and 2023—especially during the COVID-19 pandemic—but the burdens on people affected remain substantial.

Modern neutrino experiments require precise tuning of energy response parameters, a task complicated by the parameters’ nonlinear behavior and strong correlations. The authors present neural density estimators using normalizing flows and transformers integrating them with Bayesian nested sampling to achieve near-zero systematic biases and uncertainties limited only by statistics, offering a flexible framework for particle physics applications

In the proof-of-concept phase 2 ROME trial, comprehensive genomic profiling followed by molecular tumor board evaluation and randomization of patients with metastatic solid cancer to receive personalized therapy or standard of care led to a significantly higher objective response rate and longer progression-free survival in patients who received personalized therapy.

Defects and disordered local domains in soft, self-assembled aggregates determine their dynamic and adaptive properties, and enable communication between entities, but characterizing and classifying such intricate dynamic behaviors is highly complex. Here, the authors report on a data-driven workflow to identify objective criteria for the comparison of complex dynamic features in soft supramolecular materials, deriving a data-driven ’defectometer’ that allows to classify soft self-assembled materials based on the structural dynamics of the ordered/disordered molecular environments that statistically emerge within them.

Demonstration of biophysical determinants impacting Osh6-mediated lipid transport in a model membrane system, revealing the subtle orchestration between the transporter, cargo, and membrane properties.

Recent single-cell transcriptomes revealed spatiotemporal programmes of liver function on the sublobular scale. Here, Martini et al. show that VLDLR is more highly expressed in females and in the liver’s pericentral zone, while VLDL assembly occurs periportally.

Tissue fluidification in invasive breast carcinoma is accompanied by mechanical stresses that compromise nuclear integrity and liberate DNA, resulting in the activation of a pro-inflammatory response that shape tumour evolution and progression.

A complementary analysis of DESI DR2 distance measurements along with supernova and CMB data shows consistent, moderate evidence that dark energy changes over time rather than behaving as a simple cosmological constant.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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 respiratory complex I (NADH:ubiquinone oxidoreductase) is a large redox-driven proton pump that initiates respiration in mitochondria. Here, the authors present the 3.0 Å cryo-EM structure of complex I from mouse heart mitochondria with the ubiquinone-analogue inhibitor piericidin A bound in the active site and with kinetic measurements and MD simulations they further show that this inhibitor acts competitively against the native ubiquinone-10 substrate.

Anodic pulsing during electrocatalytic CO₂ reduction has been shown to enhance activity and selectivity towards hydrocarbons and alcohols on copper yet the nature of the active sites remains unclear. Here, correlated spectro-microscopy in a quasi in situ experimental set-up provides information on the formation of specific facets and oxidation states under reactive conditions.

Cryo-EM structures of human SERINC5 and its fly orthologue, along with extensive functional analyses, reveal the protein architecture and identify regions important for HIV-1 restriction.

The membrane-shaping protein ARL6IP1 is involved in the selective degradation of the endoplasmic reticulum, and this process depends on its ubiquitination and interaction with other membrane-shaping proteins such as FAM134B.

mRNA therapeutics delivered via lipid nanoparticles are being developed for the treatment of metabolic diseases caused by protein deficiency. Here, the authors use preclinical data to develop translational PK/PD models, which scaled allometrically to humans to predict starting doses for first-in-human clinical studies for in propionic acidemia, methylmalonic acidemia, and phenylketonuria.

In this Review the authors explore the emerging role of HER2 in urothelial carcinoma, highlighting its biological and clinical significance, the challenges of using HER2 as a biomarker, and the variability and complexity of HER2 assessment. Evidence supporting HER2-targeted therapies and future directions for research and clinical applications are also discussed.

Systemic administration of human PBGD mRNA encapsulated in lipid nanoparticles ameliorates disease phenotypes in mouse and rabbit models of acute hepatic porphyria and is safe in nonhuman primates.

Glycogen Storage Disease 1a (Gsd1a) is an inherited disorder caused by glucose 6-phosphatase (G6Pase-α) deficiency and characterized by hypoglycaemia and high risk of liver cancer. Here the authors develop a mRNA-based G6Pase-α delivery therapy that is efficacious and safe in a mouse model of GSD1a.

Propionic acidemia is a serious pediatric inherited disorder with no effective treatments. Here the authors demonstrate that delivering dual mRNAs as an enzyme replacement approach can be used as an effective therapy in a mouse model of propionic acidemia, with potential applicability to chronically administer multiple mRNAs in other genetic disorders.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Copper-nitrogen co-doped carbon catalysts reversibly transform into metal clusters, when employed for the electrocatalytic CO2 reduction. Here, by applying potential pulses, the authors show the size of the formed metal clusters can be finely tuned, allowing on-the-fly steering of the distribution of reaction products.