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Here the authors show the prefrontal cortex simultaneously predicts context, the thoughts of others and future changes, while the precuneus acts as a hub to fuse these into a coherent experience.

A method integrates perturbation mapping with 10X Visium spatial transcriptomics to map tumour genetic complexity and heterogeneity.

AMP-activated protein kinase AMPK senses and regulates cellular energy state. Here the authors engineer a synthetic sensor, AMPfret, that allows direct, real-time readout of the AMPK conformational state by fluorescence resonance energy transfer (FRET).

TopoVelo infers cell differentiation stages and rate parameters of gene expression using spatially coupled differential equations.

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

An understanding of the molecular mechanisms promoting the generation of immunoregulatory and tumour-promoting monocytes and macrophages is key to breaking the cycle of tumour myelopoiesis and developing more effective myeloid-targeting therapies.

Western Africa is one of the world’s largest cocoa-producing regions, with just two countries supplying up to 60% of global production, but at a high carbon cost. Incorporating shade trees into cocoa farms offsets the industry’s carbon cost, but existing coverage is low. Expanding coverage could substantially boost carbon stocks without reducing yield.

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.

Here they generate endogenous optogenetic RhoGEFs and use them to quantitatively direct and study epithelial furrowing via cell shortening, uncovering design principles for morphogenetic furrowing including a role for tissue mechanics in furrow asymmetry.

The quark structure of the f₀(980) hadron is still unknown after 50 years of its discovery. Here, the CMS Collaboration reports a measurement of the elliptic flow of the f₀(980) state in proton-lead collisions at a nucleon-nucleon centre-of-mass energy of 8.16 TeV, providing strong evidence that the state is an ordinary meson.

Integrated multi-omic analyses using samples from the TRACERx study highlight cross-talk between DNA hypermethylation and genomic lesions in non-small cell lung cancer.

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.

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.

Gene regulatory network architecture and complex dosage effects from paralogue diversification converge to shape phenotypic space, producing the potential for both strongly buffered phenotypes and sudden bursts of phenotypic change.

Current intracortical brain-computer interfaces are subject to recording interface instabilities that degrade decoding performance. Here, the authors present a platform for Nonlinear Manifold Alignment with Dynamics (NoMAD), which stabilizes decoding using models of dynamics for at least 3 months.

The XRISM Resolve spectrum of the galactic neutron star X-ray binary, GX 13+1, reveals one of the densest winds ever seen in absorption lines.

Parametric matrix models (PMMs) are a new class of machine learning methods using parametrized matrices to find implicit governing equations describing data. PMMs excel at making accurate predictions for scientific computing applications.

We developed PRINT, a computational method that identifies footprints of DNA–protein interactions from bulk and single-cell chromatin accessibility data across multiple scales of protein size.

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.

A reinforcement learning-based virtual reality system, implementing a series of sport sessions with coaching, was as effective as standard physical activity in reducing fat mass in adolescents, with positive effects on cognition.

Meta-learning-empowered reflective lattice light-sheet virtual structured illumination microscopy (Meta-rLLS-VSIM) offers near-isotropic resolution for fast and versatile super-resolution imaging of subcellular dynamics

The majority of human genes can produce multiple isoforms, but studying their functional relevance requires tools to target specific isoforms. Here, the authors develop a CRISPR-based exon-exon junction-targeting strategy to achieve isoform-specific RNA knockdown.

This study presents a programming strategy for the two-dimensional folding of a robotic sheet into an unbounded set of hinge configurations post-deployment, enabling in situ multi-purpose tasks with applications in dexterous grasping and adaptive locomotion.

AMP activated protein kinase (AMPK) is a master regulator of cellular metabolism, but how AMPK activity is spatiotemporally regulated remains unclear. Here, Schmitt et al develop a sensitive biosensor for AMPK, which they use to uncover mechanisms for AMPK activity in the lysosome and nucleus.

As the energy consumption of neural networks continues to grow, different approaches to deep learning are needed. A neuromorphic method offering nonlinear computation based on linear wave scattering can be implemented using integrated photonics.

Leslie Kurumundayil and colleagues present a deep learning-based surrogate model that computes ground-level irradiation maps for complex agrivoltaic systems. This model speeds up calculations, enabling efficient optimization of photovoltaic systems.

Oxidative DNA damage is linked to cancer and aging, but its genomic effects remain hard to map. Here, authors develop a nanopore-based method using synthetic DNA and deep learning to detect 8- oxo-dG, revealing its distribution and interplay with DNA methylation.

In the brain of fruit flies, the mushroom body achieves flexible learning by using interconnected short- and long-term memory units for dopamine-mediated integration of innate valences with learnt valences obtained through experience.

An ‘intracrine’ signaling mechanism is proposed whereby a G-protein-coupled receptor (free fatty acid receptor 4) senses locally released fatty acids on intracellular membranes associated with lipid droplets to efficiently regulate lipolysis in adipocytes.

This pilot trial showed that perioperative treatment with the isocitrate dehydrogenase (IDH) inhibitor safusidenib of patients with low-grade IDH-mutant glioma, with craniotomy and lumbar puncture before and after treatment, is feasible and safe and enabled in-depth translational investigation of safusidenib treatment-induced changes in the tumor, including electrophysiological effects.

Flores et al. show that brain-penetrant eIF2B agonists suppress ISR activation in cellular and mouse models of ALS and reduce ISR biomarkers in humans, enabling further clinical studies of ISR inhibition in individuals with neurological diseases

Mathematical models of V1 seek to explain the response properties of V1 neurons, often with more complex models providing more accurate predictions. Here, the authors show that deep neural network models of mouse and monkey V1 can be dramatically simplified to a two-layer “minimodel" while retaining high accuracy.

People try to infer how others feel, with varying success. Here, the authors show that others’ feelings and our inferences can both be predicted from our brain activity, and that we are more accurate when these brain patterns align.