Browse Articles

Analysis of gene co-expression connectivity dynamics implicates aberrant neuron-oligodendroglia interactions in schizophrenia

Shared latent representations of speech production for cross-patient speech decoding

Interactively addressable organic metadevices

Abstract Active, pixel-level addressability is central to the realization of metadevices with programmable wavefront control. However, two-dimensional operation at visible wavelengths remains challenging, as reducing metasurface pixel dimensions imposes increasing constraints on electrical interconnect design and local tunability. Here, we demonstrate interactively addressable organic metadevices, in which ultrathin polyaniline is conformally integrated with plasmonic nanoantennas to yield individually switchable metasurface pixels with localized electrochemical modulation. Using a planar fan-out architecture, we realize two-dimensional metasurface arrays, in which each pixel is electronically isolated and driven at sub-volt voltages, enabling millisecond-scale switching dynamics. Embedded within a user-driven electronic control loop, the platform converts user inputs into pixel-level voltage patterns to generate reconfigurable holographic projections, supporting functionalities ranging from alphanumeric character rendering to interactive gaming. Pixel-resolved measurements reveal uniform electrochemical behaviour, negligible electrical crosstalk, and stable operation across dynamically evolving holographic scenes. Our results establish organic metasurfaces as a promising route toward user-programmable and interactively addressable photonic systems.

Mixed triplet-singlet order parameter in decoupled superconducting 1H monolayers of transition-metal dichalcogenides

Abstract Understanding the emergence of unconventional superconductivity, where the order parameter deviates from simple isotropic s-wave pairing, is a central challenge in condensed matter physics. Some transition-metal dichalcogenides (TMDCs), though generally regarded as conventional superconductors, display signatures of unconventional pairing and thus provide a particularly intriguing platform to explore how exotic states arise. Here we investigate the misfit compound (SnS) 1.15 (TaS 2 ), a heterostructure composed of alternating SnS and 1H-TaS 2 layers. Using transport, photoemission, and scanning tunneling spectroscopy, we demonstrate that the SnS layers effectively decouple the TaS 2 into electronically isolated 1H sheets. In this limit, the tunneling density of states on the 1H layer reveals a clear two-gap superconducting spectrum with T c ≃ 3.1 K. A theoretical model based on lack of inversion symmetry of the system and finite-range attraction reproduces the observed multi-gap structure as a mixed singlet-triplet state. These results establish misfit compounds as a powerful platform for studying unconventional superconductivity in isolated 1H layers and for realizing multiple uncoupled superconductors within a single crystal.

Cooperative mechanism of neurotransmitter recognition and transport by the human vesicular polyamine transporter

From stars to molecules: AI guided device-agnostic super-resolution imaging

Abstract Super-resolution imaging has revolutionized the study of systems ranging from molecular structures to distant galaxies. However, existing super-resolution methods require extensive calibration and retraining for each imaging setup, limiting their practical deployment. We introduce a device-agnostic deep-learning framework for super-resolution imaging of point-like emitters that eliminates the need for calibration data or explicit knowledge of optical system parameters. Our device-agnostic modeling utilizes diverse, numerically simulated dataset encompassing a broad range of imaging conditions, enabling generalization across different optical setups. Once trained, the model reconstructs super-resolved images directly from a single resolution-limited camera frame with superior accuracy and computational efficiency compared to state-of-the-art methods. We experimentally validate our approach using a custom microscopy setup with controllable ground-truth emitter positions. We also demonstrate its versatility on stellar astronomy and single-molecule localization microscopy datasets of point-like sources, achieving high resolution without prior information. Our findings establish a pathway toward universal, calibration-free super-resolution imaging, expanding its applicability across scientific disciplines.

Chiral packings in cylinders are ultrasensitive to confinement deformation

Abstract Sphere packings in circular cylinders have attracted substantial research interest, among which the discovery of chiral helical structures is the most iconic. However, recent experimental results on zebrafish do not match the known packing structures in circular cylinders. To account for the inherent imperfections of biological tubes, we take elliptic cylinders as the canonical deformation of circular cylinders and investigate the densest packings of hard spheres in them using simulation, theory, and experiments. Starting from the chiral structures in circular cylinders, we demonstrate that even a weak cross-sectional deformation can trigger entirely new phases, including ones that either eliminate global chirality or significantly complicate the chiral structures. This reveals the significant effect of cylindrical anisotropy. The new helical phases under anisotropic confinement remain chiral and develop hierarchical periodic structures, which are difficult to obtain by simulations but are predicted by our newly developed theory for helical phases in elliptic cylinders. The theory also predicts double oscillated-chain phases without chirality, which perfectly match the simulations. Our work offers fresh insights into understanding packings in anisotropic cylinders, which will help researchers to design new materials and to understand many living systems.

Advancing science by designing for surprise

The coupled reanalysis global meridional overturning circulation imprinted by historic volcanic eruptions

Abstract The global ocean meridional overturning circulation (GMOC) is central for ocean transport and climate variations. However, a comprehensive picture of its historical mean state and variability remains vague due to limitations in modelling and observing systems. Incorporating observations into models offers a viable approach to reconstructing climate history, yet achieving coherent estimates of GMOC has proven challenging due to difficulties in harmonizing ocean stratification. Here, we demonstrate that multiscale data assimilation that integrates atmospheric and oceanic observations into two coupled models in a dynamically consistent way robustly retrieves the past 80-year GMOC. By diagnosing volcanic eruption-induced North Atlantic cooling and surface buoyancy loss, we show historic volcanic eruption events are imprinted in variability of the rebuilt GMOC. The Mt. Pinatubo (1991) volcanic eruption produces a multidecadal characteristic of the overturning evolution by the chain of enhancing diapycnal mixing - strengthening deep convection - mediated by eddy activities.

Recovering lost origins

Integrated evidence helps triangulate the origins of African slaves buried on St Helena

AlphaGEM enables precise genome-scale metabolic modelling by integrating protein structure alignment with deep-learning-based dark metabolism mining

‘Humanizer’ tool can erase signs of AI-written text — alarming scientists

The rise and fall of the Amazon Soy Moratorium

Challenges to the voluntary zero-deforestation pact could impose costs for forests and the soy sector

Triple IFN pathway deficiency sensitizes mice to human respiratory virus infection independent of human viral receptor expression

AI in scientific publishing: Slower, worse, and more expensive

There’s a saying in the management world, popularized by NASA administrator Daniel Goldin in the 1990s, that the goal of technological improvements is to make products faster, better, and cheaper. Although this strategy had some success in the aerospace industry, the zealots of artificial intelligence (AI) have been making the same argument regarding how it will transform work, claiming that so little human effort will be required that humanity will enter an era of radical abundance, free from disease, drudgery, and danger, among other benefits, leaving society with more time for creative pursuits. But history tells a different story. When machines began to increase productivity during the second industrial revolution, American engineer Frederick Winslow Taylor’s The Principles of Scientific Management encouraged corporations to use surveillance to get employees to work harder and longer, an approach that exhausted and discouraged workers and led to the transfer of knowledge and any decision-making from workers to management, while enriching the profits for only those at the top. Yet, it remains foundational to the American economic enterprise. Indeed, scientific publishing is starting to experience some Taylorism with the insertion of AI. Rigorous human checking of AI-generated research papers is creating bottlenecks as publishers strive to maintain the integrity of the scientific record. The challenge is requiring even more human effort, making the whole endeavor slower and more expensive.

Diversity and distinctive characteristics of the global RNA virome in urban and peri-urban environments

Scandinavian radar array will probe mysteries of the aurora

EISCAT_3D will paint a new picture of the upper atmosphere as it is roiled by solar outbursts

Wavelength-dependent feedback behavior in light-gated polymersome nanoreactors

Tracing the origins of St Helena’s liberated Africans

In the mid-19th century, St Helena became a key receiving point for Africans “liberated” from illegal slave ships by the British Royal Navy. Of the ~27,000 landed, ~8000 died soon after arrival and were buried locally. In connection with a broader community-led commemorative effort, we analyzed tooth enamel strontium isotope ( 87 Sr/ 86 Sr) data for 152 individuals, including high-resolution intratooth profiles, to identify likely origins and infer forced movements before embarkation. Isoscape-based probabilistic assignment, integrated with historical evidence and published ancient DNA data, constrains homelands ranging from coastal Central Africa to far inland areas, revealing long-distance movements, sometimes beginning in childhood. By refining provenance, these data informed local decisions about care and potential repatriation, highlighting the complexities of return and ultimately supporting reburial on St Helena.

Topographically organized dorsal raphe activity modulates forebrain sensory-motor representations and contributes to defensive behaviors

Abstract The dorsal raphe nucleus (DRN) shapes behaviors including mood and motivation. The DRN contains molecularly distinct and topographically organized neurons that target specific forebrain regions. To understand how DRN neurons process sensory information, we investigated the spatiotemporal activity patterns of DRN neurons, DRN axons, and their forebrain targets in zebrafish. We found a remarkable topographic organization of ongoing activity and sensory-motor responses within the DRN. A subset of DRN neurons was driven by locomotion and sensory stimuli. Gad1-positive DRN neurons exhibited distinct activity during rest and sensory-motor stimulation. DRN axons in the forebrain showed topographically organized excitation and inhibition in response to sensory stimulation and locomotion. DRN axons covaried with forebrain neuronal activity. DRN ablation reduced the synchrony and sensory-motor responses of forebrain neurons and enhanced defensive behaviors. We revealed the functional diversity of DRN neurons and their role in transmitting sensory and locomotor signals via topographically organized forebrain projections.