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Robustness checks and reproduction of analyses with existing and updated data based on 110 articles in economics and political science journals with data and code-sharing requirements found high levels of robustness and reproducibility and determined that robustness was not dependent on author characteristics or data availability.

Atmospheric river (AR) characteristics, particularly AR shape associated with large-scale circulation, as well as interactions with other weather systems, significantly influence surface warming over Antarctic ice shelves and their future stability.

When 100 social and behavioural science claims were examined, 34% of reanalyses closely matched the original results, with 74% reaching the same conclusion, revealing limited robustness of single-path analyses and the need to address analytical uncertainty.

Exposome analyses across 34 countries showed that social exposures were associated with faster functional brain aging and physical exposures with faster structural brain aging.

The cellular origin and developmental trajectory of DICER1 syndrome-associated tumors are currently unknown. Here, the authors employ a lineage-traceable genetically modified mouse model for DICER1 syndrome to identify universal fibroblasts as the likely cellular origin of mouse Dicer1 sarcoma and map their developmental trajectory, findings that are validated in human DICER1 mesenchymal tumors.

IMiD-based PROTACs may degrade IKZF1/3 with hematologic effects. This study profiles these liabilities using hematopoietic assays showing stem cell rewiring and interferon activation and introduces a CRBN ligand that reduces them.

Divergent white matter metabolic patterns reveal a mechanistic basis for cognitive resilience and enhance prediction of future cognitive decline beyond established aging and dementia biomarkers.

Bacteriophages are the most abundant life form on earth and can be applied to eliminate or engineer bacteria. Here, authors demonstrate RNA barcoding as a high throughput tool to measure bacteriophage host range in natural microbial communities and inform bacteriophage ecology and applications.

An analysis of whole-exome sequencing data linked to longitudinal electronic health records from 44,028 British South Asians finds new gene–phenotype associations and identifies 2,991 genes with rare biallelic predicted loss-of-function genotypes.

Atopic dermatitis is an immune disease driven by cytokines including IL-4/IL-13. This study shows that a topical ITK/TRK inhibitor blocks an array of T cell cytokines, inhibits NGF-induced basophil activation, and reduces inflammation in human skin explants and dermatitis models, indicating therapeutic potential.

A fully automated methodology based on rubrics capturing a broad range of cognitive and intellectual demands is illustrated using LLMs and tasks, demonstrating a new way to evaluate the capabilities of AI systems and anticipate their performance.

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.

Zhou, Ho and colleagues show that, in mice, a schizophrenia-associated mutation impairs belief updating by weakening mediodorsal (MD) thalamus activity. Boosting this activity restored flexible decision-making, suggesting MD thalamus as a potential therapeutic target.

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.

Heparan sulfate proteoglycans facilitate the assembly of clusters of glycoRNAs and cell surface RNA-binding proteins, which negatively modulate VEGF-A signalling and angiogenesis.

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

The response of soil carbon to warming is critical feedback that has been difficult to constrain. This study uses a long-term experiment to show that precipitation modulates microbial and therefore carbon dynamics; drought leads to carbon loss with warming, but wet conditions increase soil carbon.

Solid-state batteries remain promising but essential insights into electrode-electrolyte interface are required. Here, the authors report in situ infrared nanospectroscopy of the lithium-polymer-electrolyte interface to reveal its intrinsic molecular, structural, and chemical heterogeneities.

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 monolithically integrated photonic ski-jump enables scalable, diffraction-limited 2D beam scanning from photonic chips, achieving ultrahigh spot rates, compact footprints and applications spanning displays, sensing and quantum photonics.

The mediobasal hypothalamus plays a central role in integrating nutritional and sex-related signals to regulate energy homeostasis. Here, through snRNA-seq of the mediobasal hypothalamus in female and male mice across nutritional states, authors show that Agrp neurons are nutrition-sensitive, DA neurons exhibit transcriptional differences in a sex-dependent manner, and KNDy neurons are responsive to both sex and nutrition.

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.

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 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.

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.

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 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.

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.

Stable and cell-specific transgene expression can be achieved through in vivo site-specific integration of large DNA payloads using a two-vector system of enveloped delivery vehicles and adeno-associated viruses.

Evo 2 is an artificial intelligence-based biological foundation model trained on 9 trillion DNA base pairs spanning all domains of life that predicts functional properties from genomic sequences and provides a rich generative model for researchers in biology.

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

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.

Temporal profiling of central carbon metabolism during Kras^G12D-driven acinar-to-ductal metaplasia reveals that disruptions in NADPH-producing enzymes accelerate the formation of pancreatic precancerous lesions.

Understanding phase transitions in electrodes under realistic conditions is important for future battery design. Here, the authors use synchrotron micro-beam diffraction to reveal the phase transition mechanism within individual particles of LiFePO₄, revealing a cycling rate transformation mechanism.

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.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

Multiomic single-cell analyses of 15 Down syndrome fetal cortical samples identify widespread disruption of neurodevelopmental transcriptional programs, driven by three dosage-sensitive chromosome 21 transcription factors.

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.

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.

Leveraging pythons as an extreme model of feeding and fasting behaviour, this study uncovers para-tyramine-O-sulphate as a conserved postprandial metabolite that links nutrient intake to energy balance by activating hypothalamic neurons and suppressing food intake in pythons and mice.

New field measurements and modeling show meltwater refreezing in Greenland’s bare ice may reduce runoff to surrounding oceans, highlighting a process climate models can incorporate for improved predictions of future sea-level rise.

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.

The authors study epitaxial thin films of the pyrochlore-sublattice compound LiTi2O4 by RIXS and ARPES. They observe cooperation between strong electron correlations and strong electron-phonon coupling, giving rise to a mobile polaronic ground state in which charge motion and lattice distortions are coupled.

The authors identify key enzymes, including four cytochrome P450s, a dehydrogenase and a sulfotransferase, that together build the core chemical scaffold of withanolides, medicinal compounds from ashwagandha with neurological and anti-cancer activities.

Fast panoramic rotational ultrasound tomography and photoacoustic tomography are integrated for hybrid rotational ultrasound and photoacoustic tomography, for three-dimensional dual-contrast imaging of soft tissue and vasculature across the human body.

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.

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.

A model trained to generate spatial proteomics profiles and predict the expression of 40 biomarkers directly from histopathology slides is shown to improve survival and treatment response prediction in patients with lung cancer.