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Bark decomposition could significantly affect global carbon and nutrient cycling. Here, the authors report the global trend of bark decomposition rates, identify the key drivers in different climate regions, and predict the response of bark decomposition to future climate change.

Melting from the Greenland Ice Sheet triggers land uplift beneath the ice sheet and changes to Earth’s gravitational field and rotation axis, a process called Glacial Isostatic Adjustment. Lewright et al. find that this process will lead to a local sea level fall along Greenland’s coast over this century.

Nicholas and Mattar found that people use episodic memory to make decisions when it is unclear what will be needed in the future. These findings reveal how the rich representational capacity of episodic memory enables flexible decision-making.

META-SiM brings foundation model power to single-molecule time traces, excelling across diverse analysis tasks. Paired with the web-based META-SiM Projector and entropy mapping, it rapidly reveals hidden molecular behaviors inaccessible by other means.

Omnivores like bears can switch between plant and animal diets, potentially helping them respond to changing conditions. By combining modern and fossil data, this study shows that bears shift toward carnivory in harsher climates and toward herbivory in more productive environments.

Recent developments in trapped-ion platforms are opening towards quantum simulation of chemical dynamics. Here, the authors demonstrate independent control of spin-phonon coupling and reservoir engineering in a two-mode trapped-ion system to simulate excitation transfer dynamics.

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

Floquet engineering is often limited by weak light–matter coupling and heating. Now it is shown that exciton-driven fields in monolayer semiconductors produce stronger, longer-lived Floquet effects and reveal hybridization linked to excitonic phases.

The authors present MorphoGenie, an unsupervised model that profiles cell shapes to predict cellular heterogeneity without manual labels. It provides a scalable, interpretable, and generalizable approach for data-driven exploration of cellular heterogeneity across diverse imaging modalities.

Vortex dynamics and mutual friction in quantum fluids are intimately connected to the fundamental properties of superfluids. Here, the authors reveal previously unexplored mechanisms underlying the mutual friction coefficients in ultracold Fermi superfluids in the unitary limit, suggesting bound quasiparticles within the vortex core play a significant role.

Aadvanced computer simulations of three-dimensional turbulence reveal that the ab initio generation of large-scale magnetic fields is driven by shear-flow-induced jets; an analytical model is derived which reproduces the essential features of the flow- and field-generation mechanisms.

Respiration enhances cerebrospinal fluid flow through mechanical and autonomic pathways. Inhale length and diaphragm motion influence its displacement and net flow, identifying a modifiable, noninvasive mechanism relevant to brain homeostasis.

This study introduces a sediment-based method to reconstruct Antarctic fast-ice change during the late Holocene, revealing cyclic patterns linked to solar variability and offering insight into long-term cryosphere climate dynamics.

Vertical transmission is thought to favour beneficial host–microbe interactions, but these may also be context dependent. Here Bruijning et al. show with a model that variable environments can select for bet-hedging by hosts via imperfect vertical transmission of microbes.

Hole spin qubits in germanium have seen significant advancements, though improving control and noise resilience remains a key challenge. Here, the authors realize a dressed singlet-triplet qubit in germanium, achieving frequency-modulated high-fidelity control and a tenfold increase in coherence time.

Approaches combining genetic association and Perturb-seq data that link genetic variants to functional programs to traits are described.

The extent to which in-vitro cellular experiments are effective models for complex biology underlying human phenotypes is often unclear. Here the authors propose and implement a framework using gene perturbation data to evaluate in-vitro models.

Chromosomes interact with the cell environment through their interface. Here, the authors use Atomic Force Microscopy to probe the interface and local micromechanics of the chromatin network of native human mitotic chromosomes.

Inherited mitochondrial DNA mutations can result in diverse clinical phenotypes. Here, the authors characterise a heteroplasmic tRNA^Ala mutation (m.5019A>G) in mice and demonstrate that macrophages carrying this mutation display altered function and metabolism in vitro, along with increased type I IFN release following LPS challenge in vivo.

Simultaneous recordings were made of hundreds of neurons in the rat frontal cortex and striatum, showing that decision commitment involves a rapid, coordinated transition in dynamical regime and neural mode.

Here the authors develop a novel statistical method for quantifying mutation burden from whole genome sequencing data and use it to discover the genetic, genomic, and phenotypic correlates of clonal hematopoiesis without known driver genetic lesions.

Edge localised modes (ELMs) in highly confined plasmas are notoriously difficult to regulate. Here, the authors analyse multiscale modes and interactions by combining experimental measurements from DIII-D and modeling, showing promising results in ELM control.

Three-component Fermi gases represent a versatile platform for quantum simulation, including quantum chromodynamics-like physics, pairing and few-body effects. Here the authors demonstrate control of spin imbalances and an unexpected asymmetric decay due to different three-body losses for each component, and whose microscopic mechanism remains to be understood.

The CMS Collaboration reports the measurement of the spin, parity, and charge conjugation properties of all-charm tetraquarks, exotic fleeting particles formed in proton–proton collisions at the Large Hadron Collider.

By using superconducting quantum interference device arrays as microwave impedance transformers, piezoelectric microwave–acoustic transduction operating close to the maximal efficiency–bandwidth product of lithium niobate can be achieved.

In this study, the authors model the current mechanical properties of the seafloor of Jupiter’s icy moon Europa, and find those rocks to be too strong to allow the kind of fracturing that, on Earth, enables rock–water chemical reactions on which chemosynthetic life relies.

The study provides observational evidence of energy transfer in space plasmas, showing hydrogen and helium ions interact differently with ion-scale waves. Despite helium’s low abundance, they show their interaction can excite electrostatic waves, facilitating energy transfer across scales and challenging traditional models.

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.

Clock precision is thought to be fundamentally limited by entropy production in out-of-equilibrium systems. A theoretical work now introduces a quantum clock design where precision grows exponentially with dissipation.

We are currently short of methods that can extract objective parameters of dendritic spines useful for their categorization. Authors present in this study an automatic analytical pipeline for spine geometry using 3D-structured illumination microscopy, which can effectively extract many geometrical parameters of dendritic spines without bias and automatically categorize spine population based on their morphological features

ERK signaling involves complex spatiotemporal dynamics, making it difficult to quantify in many systems. In this study, live-cell activity measurements are combined with multiplexed immunofluorescence in a quantitative framework, allowing ERK dynamics to be quantified within fixed-cell samples.

The proportion of a population that has previously been infected by a pathogen is typically estimated using antibody thresholds adjusted for sensitivity and specificity. Here, the authors present a model-based alternative to threshold methods which accounts for antibody waning and other sources of spectrum bias.

The MICrONS mouse visual cortex dataset shows that neurons with similar response properties preferentially connect, a pattern that emerges within and across brain areas and layers, and independently emerges in artificial neural networks where these ‘like-to-like’ connections prove important for task performance.

Cancer evolutionary dynamics are quantitatively inferred using a method, EVOFLUx, applied to fluctuating DNA methylation.

Mussels produce a dynamic bio-interface between their living tissue and their non-living byssus attachment, relevant for design of implant devices. Here, authors discover a mechanoresponsive protein that may mediate mechanosensing at the interface.

Analysis of human Robertsonian chromosomes originating from 13, 14 and 21 reveal that they result from breaks at the SST1 macrosatellite DNA array and recombination between homologous sequences surrounding SST1.

In place of ‘season’ as the typical sun exposure proxy, this study uses ambient UVB linked to participants’ addresses. The results deepen our understanding of the link between vitamin D and health and highlight the utility of environmental data.

DNA damage can arise from natural cellular processes, but how cells prevent resulting mutations is unclear. Here, the authors show that the enzyme Polκ protects mouse tissues from mutations caused by endogenous guanine lesions, revealing how DNA repair and damage tolerance pathways cooperate to maintain genome integrity.

Yellow fluorescent proteins (YFPs) photobleach rapidly, restricting microscopy experiments. Here, the authors report mGold2s and mGold2t, YFPs that extend imaging durations up to 25 times longer than standard probes without sacrificing brightness.

Photonic processors are limited by the bulkiness of discrete components and wiring complexity. An experiment now demonstrates a reprogrammable two-dimensional waveguide that performs neural network inference through multimode wave propagation.

This research introduces a method for generating customizable spatiotemporal optical vortex (STOV) combs, enabling precise control of light’s spatial and temporal properties. It also demonstrates their application in high-capacity, efficient information transmission systems.

The advantage of living in cities compared with rural areas with respect to height and BMI in children and adolescents has generally become smaller globally from 1990 to 2020, except in sub-Saharan Africa.

The authors observe shot noise orders of magnitude greater than expected in superconductor/insulator/ferromagnet (V/MgO/Fe) junctions. They argue that the origin involves orbital-symmetry-controlled superconducting proximity effect and spin-triplet superconductivity in the Fe.

Multi-plane light converters (MPLCs) rely on complex nonlinear design optimisation and are challenging to physically realise with high fidelity. Here the authors develop a self-configuring free-space MPLC for linear optical information processing.

Superconducting transmon qubits are limited by a tradeoff between anharmonicity and charge-noise sensitivity. Here, the authors show how highly transparent Josephson junctions in hybrid superconducting-semiconducting heterostructures can remove this tradeoff and achieve both benefits.

Genetic association tests prioritize candidate genes based on different criteria.

The highest-quality JWST spectra reveal that little red dots are young supermassive black holes shrouded in dense cocoons of ionized gas, where electron scattering, not Doppler motions, broadens their spectral lines.

Identification of gene-by-environment interactions is crucial to understand the interplay of environmental effects on complex traits. Here, the authors present MonsterLM, a method for estimating the proportion of trait variance explained by gene-by-environment interactions in a fast, unbiased manner on biobank-scale datasets.

Extrachromosomal circular DNAs (ecDNAs) are prevalent in human cancers and are thought to drive tumor evolution and drug resistance by amplifying oncogenes. Here, authors develop ec3D to reconstruct three-dimensional ecDNA structures, revealing how their spatial organization rewires regulatory circuits.

MultiSTAAR provides a general and flexible statistical framework for functionally informed multi-trait rare variant analysis of biobank-scale sequencing studies by jointly analyzing multiple traits and incorporating annotation information.