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.