Squeaking is a constant companion in various aspects of our daily lives, whether we slide rubber-soled shoes across hardwood floors1, scrape chalk on a blackboard2, engage the brakes on a bicycle3 or walk with a hip replacement4,5. When two rigid bodies slide over each other, squeaking is widely understood to result from self-excited stick-slip oscillations, triggered by a decrease in the friction coefficient with increasing slip velocity6-10. However, sliding of extended interfaces can involve crack or slip-pulse propagation11-21. This distinction is amplified when a soft body slides on a rigid one, in which large deformations and material mismatch can cause detachment by opening slip pulses22-27. Previous studies focused mainly on slow sliding17,26,28-34, in which pulses are slow and squeaking is absent. Although squeaking at soft-rigid interfaces has been linked to stick-slip oscillations35-37, the mechanisms remain unclear. Here we experimentally investigate soft-rigid interfaces sliding at velocities that produce squeaking. High-speed imaging and acoustic analysis show that opening pulses propagate at approximately the shear wave speed of the soft material, mediating local slip across diverse materials. In flat samples, these pulses are irregular and generate broadband acoustic emissions. Introducing thin surface ridges confines pulse propagation, yielding a consistent repetition frequency matching the first shear mode of the sliding block and squeaking at that frequency. These findings show a structure-driven mechanism that stabilizes rupture in bimaterial friction. Geometric confinement suppresses competing modes, transforming irregular two-dimensional dynamics into coherent one-dimensional pulse trains, offering new insights into frictional rupture from engineered surfaces to geological faults.

Is it feasible to alter the ground-state properties of a material by engineering its electromagnetic environment? Inspired by theoretical predictions1-12, experimental realizations of such cavity-controlled properties without optical excitation are beginning to emerge13-19. Here we devised and implemented a new platform to realize cavity-altered materials. Single crystals of hyperbolic van der Waals (vdW) compounds provide a resonant electromagnetic environment with enhanced density of photonic states and prominent mode confinement20-24. We interfaced hexagonal boron nitride (hBN) with the molecular superconductor κ-(BEDT-TTF)2Cu[N(CN)2]Br (κ-ET). The frequencies of infrared hyperbolic modes (HMs) of hBN (refs. 25,26) match the infrared-active carbon-carbon (C=C) stretching molecular resonance of κ-ET implicated in superconductivity27. Nano-optical data supported by first-principles molecular Langevin dynamics simulations confirm the presence of resonant coupling between the hBN hyperbolic cavity modes and the C=C stretching mode in κ-ET. Meissner-effect measurements using magnetic force microscopy (MFM) demonstrate a strong suppression of superfluid density near the hBN/κ-ET interface. Non-resonant control heterostructures, including RuCl3/κ-ET and hBN/Bi2Sr2CaCu2O8+x (BSCCO), do not show the pronounced superfluid suppression. These observations suggest that hBN/κ-ET realizes a cavity-altered superconducting ground state. Our work highlights the potential of dark cavities devoid of external photons for engineering electronic ground-state properties of complex quantum materials.

Oncogenes such as KRAS display marked tissue specificity in their oncogenic potential, genetic interactions and phenotypic effects, but the underlying determinants remain largely unresolved1-5. Here, to address these questions, we developed the Mouse Cancer Cell line Atlas, a broad-utility resource of 590 comprehensively characterized models across a wide range of entities ( www.mcca.tum.de ). Comparative and functional studies using this platform, human cohorts and mice identified core principles underlying tissue-specific evolution of KRAS-initiated cancers. First, we show that mutant KRAS dosage gain through allelic imbalance exerts cell-type-specific effects, defining its timing across entities, as exemplified by dosage-sensitive developmental reprogramming during pancreatic cancer initiation. Second, we highlight how tissue- and stage-specific evolutionary requirements, such as block of differentiation in the intestine, select for KRAS-collaborating alterations. Third, we identified context-dependent epistatic KRAS-tumour suppressor interactions and show that reciprocal dosage sensitivities dictate the entity-specific patterns of cancer gene alterations, explaining their frequency, zygosity and acquisition chronology. These findings highlight how intrinsic and acquired determinants instruct cancer evolution in different tissues, with predictable molecular patterns, temporal dynamics and phenotypic outcomes. Our study provides major advances towards a mechanistic understanding of cancer genomes.

A powerful approach to understand the computations carried out by the visual cortex is to build models that predict neural responses to any arbitrary image. Deep neural networks (DNNs) have emerged as the leading predictive models1,2, yet their underlying computations remain buried beneath millions of parameters. Here we challenge the need for models at this scale by seeking predictive and parsimonious DNN models of the primate visual cortex. We first built a highly predictive DNN model of neural responses in macaque visual area V4 by alternating data collection and model training in adaptive closed-loop experiments. We then compressed this large, black-box DNN model, which comprised 60 million parameters, to identify compact models with 5,000 times fewer parameters yet comparable accuracy. This dramatic compression enabled us to investigate the inner workings of the compact models. We discovered a salient computational motif: compact models share similar filters in early processing, but individual models then specialize their feature selectivity by 'consolidating' this shared high-dimensional representation in distinct ways. We examined this consolidation step in a dot-detecting model neuron, revealing a computational mechanism that leads to a testable circuit hypothesis for dot-selective V4 neurons. Beyond V4, we found strong model compression for macaque visual areas V1 and IT (inferior temporal cortex), revealing a general computational principle of the visual cortex. Overall, our work challenges the notion that large DNNs are necessary to predict individual neurons and establishes a modelling framework that balances prediction and parsimony.

Achieving pancreatic-targeted delivery marks a breakthrough in treating pancreatic diseases, yet precise delivery remains challenging1. Here we identify an explicit and universal principle for pancreatic-selective delivery and propose a pancreatic-targeted lipid nanoparticle (AH-LNP) for mRNA delivery. AH-LNP exhibits size enlargement after assembly with proteins, facilitating capsule-filter-mediated pancreas-selective accumulation and receptor-mediated endocytosis, thereby boosting the pancreatic-targeted ability. Benefiting from this, AH-LNP enables precise and efficient genome editing in the pancreas through the delivery of Cas9 mRNA and single guide RNA (sgRNA), exhibiting promising potential in the treatment of autoimmune pancreatic diseases. Furthermore, pancreatic-targeted delivery of mRNA encoding therapeutic cytokines through AH-LNP demonstrates superior antitumour efficacy when combined with a cancer vaccine or chimeric antigen receptor T cell therapy in multiple pancreatic cancer models. The safety and pancreatic mRNA delivery of AH-LNP were verified in multiple animal models, including non-human primates, demonstrating great promise for clinical translation. Our findings highlight the transformative potential of this pancreatic-targeted mechanism and the derived LNP platform, opening avenues for developing precision therapeutics against diverse pancreatic diseases.

The family of nickelate superconductors have long been explored as analogues of the high-temperature cuprates1-6. Nonetheless, the recent discovery that certain stoichiometric nickelates superconduct up to high critical temperatures (Tc) under pressure came as a surprise7-13. The mechanisms underlying the superconducting state remain experimentally unclear. Apart from the practical challenges posed by working in a high-pressure environment, typical samples exhibit anomalously weak diamagnetic responses, which have been conjectured to reflect inhomogeneous 'filamentary' superconducting states7,9,14-17. Here we perform wide-field, high-pressure, optically detected magnetic resonance spectroscopy to image the local diamagnetic responses of as-grown La3Ni2O7 samples in situ, using nitrogen vacancy quantum sensors embedded in the diamond anvil cell18-23. These maps confirm marked inhomogeneity of the functional superconducting responses at the few μm scale. By spatially correlating the diamagnetic Meissner response with both the local tensorial stress environment, also imaged in situ, and stoichiometric composition, we show the dominant mechanisms suppressing and enhancing superconductivity. Our wide-field technique simultaneously provides a broad view of sample behaviour and excellent local sensitivity, enabling the rapid construction of multi-parameter phase diagrams from the local structure-function correlations observed at the sub-μm pixel scale.

From mammals to bacteria, the direct recognition and cleavage of viral nucleic acids is a potent defence strategy against viral infection, but it requires mechanisms for distinguishing self from non-self1,2. In bacteria, CRISPR-Cas and restriction-modification systems achieve this discrimination by recognizing specific DNA sequences or DNA modifications, respectively. Alternative mechanisms probably remain to be discovered. Here, we characterize SNIPE, an anti-bacteriophage defence system that constitutively localizes to the bacterial cell membrane in Escherichia coli to block phage λ infection. Using radiolabelled phage DNA and time-lapse microscopy to track phage genomes, we demonstrate that SNIPE directly cleaves phage DNA during genome injection. Based on proximity labelling, we find that SNIPE associates with host proteins essential for λ genome entry and with the λ tape measure protein, which facilitates λ genome injection across the inner membrane. SNIPE also defends against diverse siphoviruses, probably through direct interactions with their tape measure proteins. Our findings establish SNIPE as a widespread bacterial defence system that exploits the spatial organization of phage genome injection to specifically target viral DNA, representing a previously unknown strategy for distinguishing self from non-self in prokaryotic immune systems.

The sensitivity of non-local optical measurements at low light intensities, such as those involved in long-baseline telescope arrays1,2, is limited by fundamental quantum noise and photon losses3. Distributed quantum entanglement has been proposed as a route towards overcoming these limitations and accessing new regimes of non-local optical sensing4-6. Here we demonstrate the use of entangled quantum memories in a quantum network of silicon-vacancy centres in diamond nanocavities7-9 to experimentally perform such non-local phase measurements. Specifically, we combine the generation of event-ready remote quantum entanglement, photon mode erasure that hides the 'which-path' information of temporally and spatially separated incoming optical modes and non-local, non-destructive photon heralding enabled by remote entanglement to perform a proof-of-concept entanglement-assisted differential phase measurement of weak incident light between two spatially separate stations. Demonstrating successful operation of the remote phase sensing protocol with a fibre link baseline up to 1.55 km, our results provide an opportunity for a new class of quantum-enhanced optical imaging methods with potential applications ranging from long-baseline interferometry and astronomy to microscopy10,11.

Biological machines use targeted deformations that can be actuated by Brownian fluctuations. However, although synthetic micromachines can similarly make use of targeted deformations, they are too stiff to be driven by thermal fluctuations and require strong forcing1-3. Furthermore, systems that are able to change their conformation by thermal fluctuations do so uncontrollably4,5 or require external control6. Here we use DNA-based sliding contacts7-9 to create colloidal pivots, rigid anisotropic objects that freely fluctuate around their pivot point and use a hierarchical strategy to assemble these into Brownian metamaterials with targeted deformation modes. We realize the archetypical rotating diamond and rotating triangle, or kagome, geometries and quantitatively show how thermal fluctuations drive their predicted auxetic deformations10-15. Finally, we implement magnetic particles into the colloidal pivots to achieve colloidal metamaterials that can be controlled externally as well as use Brownian fluctuations for precisely controlled shape changes. Together, our work introduces a strategy for creating Brownian mechanical metamaterials with easily actuatable deformation modes.

Vectorization of teaching signals is a key element of almost all modern machine learning algorithms, including backpropagation, target propagation and reinforcement learning. Vectorization allows a scalable and computationally efficient solution to the credit assignment problem by tailoring instructive signals to individual neurons. Recent theoretical models have suggested that neural circuits could implement single-phase vectorized learning at the cellular level by processing feedforward and feedback information streams in separate dendritic compartments1-5. This presents a compelling, but untested, hypothesis for how cortical circuits could solve credit assignment in the brain. Here we used a neurofeedback brain-computer interface task with an experimenter-defined reward function to test for vectorized instructive signals in dendrites. We trained mice to modulate the activity of two spatially intermingled populations (four or five neurons each) of layer 5 pyramidal neurons in the retrosplenial cortex to rotate a visual grating towards a target orientation while we recorded GCaMP activity from somas and corresponding distal apical dendrites. We observed that the relative magnitudes of somatic and dendritic signals could be predicted using the activity of the surrounding network and contained information about task-related variables that could serve as instructive signals, including reward and error. The signs of these putative teaching signals depended on the causal role of individual neurons in the task and predicted changes in overall activity over the course of learning. Furthermore, targeted optogenetic perturbation of these signals disrupted learning. These results demonstrate a vectorized instructive signal in the brain, implemented via semi-independent computation in cortical dendrites, unveiling a potential mechanism for solving credit assignment in the brain.

The existence of human hippocampal neurogenesis has long been disputed1-12 and its relevance in cognition remains unknown. Recent studies have established the presence of proliferating progenitors and immature neurons and a reduction in the latter in Alzheimer's disease (AD)11,13. However, their origin and the molecular networks that regulate neurogenesis and function are poorly understood. Here we studied human post-mortem hippocampi obtained from different cohorts: young adults with intact memory, aged adults with no cognitive impairments, aged adults with extraordinary memory capacity (SuperAgers)14,15, adults with preclinical intermediate pathology or adults with AD. Using multiomic single-cell sequencing (single-nucleus RNA sequencing and single-nuclei assay for transposase-accessible chromatin with sequencing), we analysed the profiles of 355,997 nuclei isolated from the hippocampus samples and identified neural stem cells, neuroblasts and immature granule neurons. Dysregulated neurogenesis was largely associated with changes in chromatin accessibility. Analyses of transcription factors and target gene signatures that distinguished each of the groups revealed early alterations in chromatin accessibility of neurogenic cells from individuals with preclinical AD, and such changes were even more evident in samples from individuals with AD. We identified a distinct profile of neurogenesis in SuperAgers that may reflect a 'resilience signature'. Finally, alterations in the profile of astrocytes and CA1 neurons govern cognitive function in the ageing hippocampus. Together, our study points to a multiomic molecular signature of the hippocampus that distinguishes cognitive resilience and deterioration with ageing.

Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics1-5. Most of these variants individually have weak effects6 and lie in non-coding gene-regulatory elements7-10, for which we lack a complete understanding of how single-nucleotide alterations modulate transcriptional processes to affect human phenotypes5,11-15. To address this problem, we measured the activity of 221,412 fine-mapped trait-associated variants using a massively parallel reporter assay16-20 in 5 diverse cell types. We show that this assay effectively discriminates between likely causal variants and controls, and identified 13,121 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% of them can plausibly be explained by the disruption of a known transcription factor binding motif. We investigated the mechanisms of 136 variants using saturation mutagenesis and assigned affected transcription factors for 91% of variants without a clear canonical mechanism. Finally, we detected regulatory epistasis at 11% of tested regulatory variants in close proximity and identified multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants that underlie complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.

Atopic diseases associated with allergens, as well as allergic diseases, frequently arise early in life; however, the age-dependent mechanisms governing immune responses to allergens remain poorly understood1. Here we find that in early life, exposure to common allergens triggers a distinct bifurcated immune response, simultaneously triggering type 17 inflammation in the skin and initiating canonical T helper 2 sensitization in the lymph nodes. This early-life γδ type 17-mediated dermatitis primes the exaggerated allergic lung inflammation upon secondary allergen exposure. Mechanistically, we find dendritic cell (DC)-mediated type 17 activation directly in the skin without requiring migration to lymph nodes; we term this state 'peripheral immune inducer' (pii) DC. CD301b+ conventional type 2 DCs acquire allergen, adopt the pii-DC state, produce IL-23 and activate local γδ type 17 cells independently of lymph-node engagement. The pii-DC state is enabled by the immature hypothalamic-pituitary-adrenal axis and physiologically low systemic glucocorticoids characteristic of early life2,3; DC-specific deletion of the glucocorticoid receptor recapitulates the pii-DC phenotype. These findings define a developmental checkpoint, set by neuroendocrine maturation, that enables in situ DC activation and immune induction, thereby shaping age-dependent responses to allergens.

Electrolyte solvents for electrochemical devices have been dominated by oxygen (O)-based and nitrogen (N)-based ligands over the past decades1-5, for which the dipole-ion (Li+, Na+ and so on) interaction usually lays the foundations of ion dissociation and transport but frustrates the charge transfer process at the electrolyte-electrode interface6-9. Here, by synthesizing alkanes with monofluorinated structures, we show that fluorine (F)-based ligands with designed steric hindrance and Lewis basicity enable salt dissolution of more than 2 mol l-1. Among them, 1,3-difluoro-propane (DFP)-based Li-ion electrolyte is endowed with all merits for energy-dense and low-temperature batteries, including low viscosity (0.95 cp), high oxidation stability (>4.9 V) and ionic conductivity of 0.29 mS cm-1 at -70 °C. By incorporating F atoms in the first solvation shell, the weak F-Li+ coordination facilitates the Li plating/stripping process with Coulombic efficiency (CE) up to 99.7% and exchange current density one magnitude larger than O-Li+ coordination at -50 °C. The electrolytes further enable the operation of lithium-metal pouch cells under an electrolyte amount of less than 0.5 g Ah-1, achieving energy densities greater than 700 Wh kg-1 at room temperature and about 400 Wh kg-1 at -50 °C. The hydrofluorocarbon (HFC) electrolytes in this work provide a feasible approach to building electrochemical systems beyond traditional coordination chemistry.

Multicellularity evolved independently multiple times in eukaryotes1-4. Two distinct mechanisms underpin multicellularity5: clonality (serial cell division without sister-cell separation) and aggregation (whereby independent cells assemble into a multicellular entity). Clonal and aggregative multicellularity are traditionally considered to be mutually exclusive1,6-8, with rare exceptions9, and evolutionary hypotheses have addressed why multicellularity might diverge towards one or the other extreme3,4. Both animals and their sister group, the choanoflagellates, are currently known to acquire multicellularity only clonally4,10,11. Here we show that the choanoflagellate Choanoeca flexa12 forms motile and contractile cell monolayers (sheets) through multiple mechanisms-C. flexa sheets can form purely clonally, purely aggregatively or through a combination of both processes. We characterize the life history of C. flexa in its natural environment-ephemeral splash pools on the island of Curaçao-and show that C. flexa undergoes reversible transitions between unicellularity and multicellularity during evaporation-refilling cycles. Different splash pools house genetically distinct strains of C. flexa and kin recognition constrains aggregation between them. We show that clonal-aggregative multicellularity is a versatile strategy for the robust establishment of multicellularity in this variable and fast-fluctuating environment. Our findings challenge former generalizations about choanoflagellates and expand the option space of choanozoan multicellularity.

Coral reefs are marine biodiversity hotspots that provide a wide range of ecosystem services1. They are reservoirs of bioactive metabolites, many produced by microorganisms associated with reef invertebrate hosts2. However, for the keystone species of coral reefs-the reef-building corals-we still lack a systematic assessment of their microbially encoded biosynthetic potential and the molecular resources at stake due to the alarming decline in reef biodiversity. Here we analysed microbial genomes reconstructed from 820 reef-building coral samples of three representative coral genera collected at 99 reefs across 32 islands throughout the Pacific Ocean (Tara Pacific expedition)3. By contextualizing our analyses with the microbiomes of other reef species, we found that only 10% of the 4,224 microbial species and less than 1% of the 645 species exclusively identified in Tara Pacific samples had genomic information available. Furthermore, the biosynthetic potential of reef-building coral microbiomes rivalled or surpassed that of traditional natural product sources such as sponges. Among the biosynthetically rich bacteria in the reef microbiome, we identified new groups of Acidobacteriota that encode previously unknown enzymology, in turn opening promising avenues for functional protein engineering. Together, this study underscores the importance of conserving coral reefs as vital reservoirs of molecular diversity.