Search

There is a growing interest in the role of timing of physical activity (PA) in improving health. Here, using a large-scale cohort study, the authors show that moderate-to-vigorous PA at the optimal time of day robustly predicts lower mortality risk and may maximize the beneficial effect of PA.

Here the authors reveal how an incoherent feedforward C/EBPα–Notch circuit times lung cell fate, guiding alveolar development, repair after injury, and shifts between protective and reparative states.

Allele-preferential transcription factor binding can influence pancreatic ductal adenocarcinoma risk loci function. Here, the authors show allele-specific JunB and JunD binding at chr1p36.33 and propose a role for KLHL17 in protein homeostasis by mitigating inflammation.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

KCNQ1 (Kv7.1) channels are critical for heart rhythm homeostasis. Here, the authors report the KCNQ1 structure in an intermediate state, revealing unique S1–S2 conformations that illuminate channel gating and may aid targeted drug development.

Distinguishing glioblastoma and primary central nervous system lymphoma (PCNSL) remains challenging due to their overlapping pathology features. Here, the authors develop a computational tool, PICTURE, for differentiating similar pathological features enabling improved diagnosis of CNS tumours.

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.

Analysis of HbA1c and FPG levels across 117 population-based studies demonstrates regional variation in prevalence of previously undiagnosed screen-detected diabetes using one or both measures and suggests that use of elevated FPG alone could underestimate diabetes prevalence in low- and middle-income countries.

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.

Excessive complement C3 causes synaptic stripping and neurodegeneration. Here, the authors used the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis and single-cell RNA sequencing to show that C3 expression defines disease-associated reactive glia. C3 deletion abrogated these pro-inflammatory glia and protected neurons.

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.

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.

CRISPR activators are powerful tools for controlling gene expression, but they suffer from inconsistent efficacy and high toxicity. Here, authors develop a high-throughput method to test thousands of CRISPR activators, revealing distinct principles of activator biology and delivering improved tools.

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.

Structural variations (SV) contribute to inter-individual variability. Here, the authors describe a first-generation multi-ancestry Asian SV catalogue containing 73,035 SVs from 8392 Singaporeans to provide insights into Asian SV diversity.

Generative artificial intelligence (AI) systems can be optimized using TextGrad, a framework that performs optimization by backpropagating large-language-model-generated feedback; TextGrad enables optimization across diverse tasks, including radiotherapy treatment plans and molecule generation.

It is uncertain how much life expectancy of the Chinese population would improve under current and greater policy targets on lifestyle-based risk factors for chronic diseases and mortality behaviours. Here we report a simulation of how improvements in four risk factors, namely smoking, alcohol use, physical activity and diet, could affect mortality. We show that in the ideal scenario, that is, all people who currently smokers quit smoking, excessive alcohol userswas reduced to moderate intake, people under 65 increased moderate physical activity by one hour and those aged 65 and older increased by half an hour per day, and all participants ate 200 g more fresh fruits and 50 g more fish/seafood per day, life expectancy at age 30 would increase by 4.83 and 5.39 years for men and women, respectively. In a more moderate risk reduction scenario referred to as the practical scenario, where improvements in each lifestyle factor were approximately halved, the gains in life expectancy at age 30 could be half those of the ideal scenario. However, the validity of these estimates in practise may be influenced by population-wide adherence to lifestyle recommendations. Our findings suggest that the current policy targets set by the Healthy China Initiative could be adjusted dynamically, and a greater increase in life expectancy would be achieved.

Studies using human pluripotent stem cells and a mouse model of Down syndrome identify HMGN1 as a key contributor to congenital heart defects in individuals with Down syndrome.

iSCALE leverages histology and spatial transcriptomics to infer gene expression at super resolution in large tissues.

Basal cells, rather than neuroendocrine cells, have been identified as the probable origin of small cell lung cancer and other neuroendocrine–tuft cancers, explaining neuroendocrine–tuft heterogeneity and offering new perspectives for targeting lineage plasticity.

Here the authors identify hundreds of genetic loci linked to 36 traits in East Asians, revealing population-specific associations and emphasizing the importance of diverse ancestry groups in genome-wide association studies.

High contiguity human genomes can be assembled de novo in 6 h using nanopore long-read sequences and the Shasta toolkit.

Monkeypox virus genomic data from Nigeria and Cameroon, sampled between 2018 and 2023, indicate that the virus spread through repeated zoonoses in Cameroon, whereas in Nigeria, it spread mainly through human–human transmission, predominantly originating in Rivers State.

Here, the authors show that higher levels of the gut bacterial clade TANB77 associate with better response to cancer immunotherapy, and further demonstrate in mice that a conserved pilin from TANB77 plays a role in enhancing immunotherapy efficacy, suggesting a potential therapeutic avenue.

The posterolateral cortical amygdala and other connected brain regions have a key role in mediating the transition from investigative to aggressive behaviour in male mice.

Melinda Mills, Nicola Barban, Harold Snieder, Marcel den Hoed and colleagues perform a meta-analysis of data from over 300,000 individuals for age at first birth and number of children ever born. They identify 12 significant loci that associate with these traits, providing insights into the genetic basis of human reproductive behavior.

Mathieson et al. carried out a genome-wide association study of reproductive success (number of children born) in humans, revealing the importance of diverse neuro-endocrine and behavioural factors.

Human fMRI reveals distinct exploration codes: IPS tracks internal exploration, ACC tracks external exploration, and mPFC flexibly encodes the value guiding choices across exploration and acceptance.

Here, the authors study the effects of expression quantitative trait loci on enhancer activity and promoter contacts in primary monocytes isolated from male individuals, suggesting an inherent genetic link between the activity of enhancers, their contacts to target gene promoters and gene expression.

A cross-ancestry meta-analysis of genome-wide association studies identifies association signals for stroke and its subtypes at 89 (61 new) independent loci, reveals putative causal genes, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as potential drug targets, and provides cross-ancestry integrative risk prediction.

Genome-wide analyses identify 30 independent loci associated with obsessive–compulsive disorder, highlighting genetic overlap with other psychiatric disorders and implicating putative effector genes and cell types contributing to its etiology.

A genome wide association study of an African vector of schistosomiasis revealed two genomic regions associated with resistance to Schistosoma mansoni. These findings will inform novel control strategies to interrupt transmission to humans.

Traditional bulk sequencing data lack information about cell-type-specific gene expression. Here, the authors develop a Tissue-AdaPtive autoEncoder (TAPE), a deep learning method connecting bulk RNA-seq and single-cell RNA-seq, and apply it to analyze the cell type fractions and cell-type-specific gene expression in clinical data.

This study characterizes the three-dimensional (3D) genome architecture of 15 primary human cancer types from The Cancer Genome Atlas. The analyses identify different archetypes of enhancer usage and enhancer rewiring events due to different classes of mutations and structural variants.

Large-scale combination drug screens in cancer are extremely challenging because of the immense number of possible combinations. Here, the authors develop BATCHIE, a Bayesian active learning platform to design scalable and maximally informative drug combination screening assays; this is validated in retrospective and prospective cancer studies.

In vivo gene editing hinges on identifying an ideal delivery vehicle from numerous candidates. Here, authors establish the GFP-on mouse model capable of translating successful adenine base editing to a fluorescent readout thus enabling the rapid evaluation of genome editing delivery vehicles.

The associations between gut metabolites, brain activity, and behavior in youth with autism is unclear. Here authors show that some tryptophan metabolites are different in autism and are associated with autism symptoms and activity in interoceptive brain regions.

P. falciparum and vivax are responsible for most cases of malaria but are not genetically closely related and differ in their clinical and epidemiological impacts. In this study, the authors investigate the genomic and epidemiological characteristics of the two parasites in a co-endemic setting of Guyana.

Here, the authors unveiled a ‘super-silencer’ and its mechanisms of action. They revealed that a combined treatment of an enhancer of zeste homolog 2 inhibitor and a repressor element 1-silencing transcription factor inhibitor can disrupt super-silencers, potentially leading to cancer ablation.

Estimates from the Global Dietary Database indicated that 2.2 million new type 2 diabetes and 1.2 million new cardiovascular disease cases were attributable to sugar-sweetened beverages worldwide in 2020, with the highest burdens in sub-Saharan Africa, Latin America and the Caribbean.

CELLFIE, a CRISPR platform for optimizing cell-based immunotherapies, identifies gene knockouts that enhance CAR T cell efficacy using in vitro and in vivo screens.

Two bead-based approaches for CRISPR diagnostics increase sensitivity and deployability in resource-constrained settings.

Cell-cell fusion is fundamental to physiological processes such as muscle formation and viral infection. Here, the authors show that the proteins embedded on the plasma membrane present a biophysical barrier that can regulate cell-cell fusion.

Viral diagnostics with maximum sensitivity are designed using machine learning and combinatorial optimization.

DeepRETStroke is a deep learning system using retinal photographs to detect silent brain infarction and predict future stroke events.

Here, the authors computationally designed and produced small protein antagonists to target IL-6 and IL-1β signaling to develop modulators of CRS.

A general protein language model guides protein evolution with 20 or fewer variants needed for testing.

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