Browse Articles

Pre-incision versus pre-closure intravenous tegileridine for analgesia after laparoscopic cholecystectomy: a randomized, double-blind, three-arm trial

Minute-scale red phosphorescence in carbon nanodots

SpikeMicroNet: neuromorphic visual sensing for energy-efficient optical microrobot pose and depth estimation under microscopy

Abstract Optical microrobots actuated by optical tweezers (OT) are an emerging tool for cell-level manipulation, micro-assembly, and targeted biomedical interventions, but their closed-loop control depends on perception subsystems that must run in real time within tight power budgets. Existing perception pipelines on optical-microscopy data rely on dense artificial neural networks that consume several to tens of millijoules per inference, which is incompatible with embedded controllers driving the optical hardware. This paper proposes SpikeMicroNet , a directly trained, defocus-aware spiking neural network for single-frame optical microrobot perception. The proposed model integrates a Phase-Coded Defocus Encoder (PCDE) that converts a static microscopy frame into a temporally structured spike train, an Adaptive-Threshold Leaky Integrate-and-Fire (AT-LIF) neuron that maintains stable firing rates across heterogeneous microrobot geometries, and a Defocus-Aware Spiking Self-Attention (DASSA) block whose attention map is conditioned on the temporal phase of the encoder. The performance of the proposed method is benchmarked on the OpTical MicroRobot dataset against seven ANN and SNN baselines under a subject independent evaluation protocol. SpikeMicroNet attains $$95.1\%$$ top-1 accuracy on pose classification and a depth mean absolute error of $$1.78\,\mu$$ m while reducing the estimated model-side compute energy by up to $$28.4\times$$ relative to the strongest dense vision transformer baseline. To the best of our knowledge, this is the first spiking neural network designed and benchmarked for optical microrobot perception.

Multicellular architectures for high-rate solar evaporation with spatial salt crystallization under high-salinity

Abstract Solar-driven evaporation offers decentralized freshwater production and brine management, yet remains limited by inefficient water transport, thermal losses and salt fouling arising from insufficient understanding of geometry–transport–performance relationships. Here, 3D-printed multicellular solar evaporators with systematically varied lattice unit cells are developed to clarify these relationships, identifying liquid–solid contact perimeter, porosity and thermal interface area as key geometric parameters governing capillary water delivery and heat transfer. Guided by these, an optimized FBCC-+_5 evaporator achieves a high evaporation rate of 6.90 kg m −2 h −1 and sustains zero-liquid-discharge operation. A hybrid multicellular architecture combining high- and low-evaporation-rate unit cells further generates controlled evaporation gradients, thereby localizing salt crystallization, enabling stable operation for 5.5 days with 97.49% salt recovery under 20 wt% NaCl. Outdoor desalination yields up to 47.7 kg m −2 day −1 of freshwater. This work establishes unit-cell and macro-scale geometry as programmable design parameters for scalable and durable solar desalination.

Random Forest Detection of charcoal driven vegetation loss in Ghana’s Afram Plains

Docking of virtual libraries identifies small-molecule agonists of neurotensin receptors with analgesic activity

Abstract Peptide-activated G protein-coupled receptors (GPCRs) play crucial roles in numerous diseases, but remain difficult therapeutic targets due to the challenges in developing small-molecule drugs. Here, we explore structure-based strategies to identify small-molecule agonists of neurotensin (NTS) receptors, which hold promise for developing non-opioid analgesics. Chemical libraries of drug-like molecules are first designed based on a receptor-peptide complex, and then 14.5 million compounds are computationally docked to the orthosteric binding site of the NTS 1 receptor. A set of 39 top-ranked compounds is synthesized, and seven of these are experimentally confirmed to activate the NTS 1 receptor. Structure-guided optimization yields NTS 1 ligands with signaling signatures distinct from the endogenous peptide, and these compounds also exhibit high affinity for the NTS 2 receptor. High-resolution crystal structures of two agonists bound to the NTS 1 receptor confirm predicted binding modes and reveal key determinants of activation. In vivo, the compounds produce robust antinociception in rodents without inducing hypotension, consistent with a contribution of NTS 2 receptor activity. To facilitate broader application of our virtual screening approach to peptide-binding GPCRs, we provide access to tailored chemical libraries containing billions of readily synthesizable compounds.

Study on structural design and stress simulation of carbon fiber composite Type IV hydrogen storage cylinder

Spinal nociceptive denervation impedes subsequent chronic autonomic remodeling after myocardial infarction in male swine

Abstract After chronic myocardial infarction (MI), pathological autonomic remodeling, including vagal dysfunction and sympathoexcitation, predisposes to ventricular arrhythmias (VT/VF). However, what underlies this functional and structural remodeling remains unknown. We hypothesized that spinal nociceptive afferent signaling initiates and perpetuates these pathological autonomic changes. We employed cervicothoracic epidural resiniferatoxin (RTX) to ablate spinal nociceptive neurons in male pigs before MI, and assessed autonomic and electrophysiological function four-to-six weeks post-infarction. Compared to vehicle-treated infarcted animals, epidural RTX attenuated the loss of vagal tone and baroreflex sensitivity, reduced spinal cord inflammation, glial activation, and circulating stress and inflammatory markers, and stabilized electrophysiological parameters, lowering VT/VF inducibility. In a separate cohort, acute C7–T1 nociceptive afferent ablation after chronic MI acutely restored vagal function and decreased VT/VF inducibility. This study demonstrates that cervicothoracic spinal nociceptive afferents significantly contribute to MI-induced autonomic remodeling and VT/VF, providing novel insight into the mechanisms underlying sympathovagal imbalance after MI.

A modified asperity model for bolted joint interfaces based on cubic polynomial interpolation

A global molecular code for birth order and neuronal identity in Drosophila

Abstract The assembly of functional neural circuits relies on the generation of diverse neural types with precise molecular identity and connectivity. Unlocking general principles of neuronal specification and wiring across the nervous system requires a systematic and high-resolution characterization of its diversity, recently enabled by advances in single-cell transcriptomics and connectomics. However, linking the molecular identity of neurons to circuit architecture remains a key challenge. Here we present a high-resolution developmental transcriptional atlas for the Drosophila melanogaster nerve cord, the central hub for sensory–motor circuits. With a considerable 38× aggregate coverage relative to its reference connectome 1,2 , our atlas captures extensive molecular diversity and enables robust alignment to the adult connectome. We identified three developmental principles underlying neuronal diversity in the nerve cord. First, the timing of neurogenesis shapes diversification of molecular identity: embryonic-born neurons diverge faster than larval-born neurons, as also observed in the adult connectome. Second, 17 transcription factors common to neurons from all lineages provide a global molecular identity code for birth order. Lastly, by mapping sex-specific transcriptional profiles to the connectome, we identified female-specific apoptosis and transcriptional divergence as key global drivers of sex specification. By revealing key organizational axes of molecular identity, this atlas opens avenues to dissect the molecular mechanisms underpinning the development and evolution of neural circuits.

Supramolecular nanofiber stabilization of microdroplets enables ultra-sensitive virus infection analysis

Tree extraction in open-pit mine restoration areas using unmanned aerial vehicle LiDAR and you only look once-based deep learning

Regional drivers and contributors to changes in life expectancy across Asia

Multispectral image fusion via heterogeneous integration of broadband image sensor and sub‑Boltzmann Transistors on CMOS

Histidine-functionalized mixed-linker ZIF-8 for enhanced copper immobilization and efficient 1,2,3-triazole synthesis

Precise DNA base editing using AlphaFold3-based contact modelling

Lengthened autumn growing season contributes substantially to Earth’s greening

Advantages and challenges of training of inhalation technique with the Vitalograph AIM device

AI identifies interactions in CRISPR complexes to improve specificity of DNA editing

High-power hybrid commutated converter for carbon-neutral power transmission

Abstract To achieve carbon neutrality, we must overcome the challenges associated with the long-distance and large-capacity transmission of renewable energy. Direct-current transmission system has advantages in terms of high voltage and high controllability over the alternating-current transmission system. First-generation line-commutated-converter-based high-voltage direct-current systems risk commutation failures that threaten the safety of power grid, whereas second-generation voltage-source-converter systems entail higher carbon emissions, lower robustness, and higher power loss. We propose a next-generation high-power hybrid commutated converter that accesses renewable power, eliminating commutation failures through its hybrid operation modes of forced and recovery-enhanced commutation, with a hybrid device connection topology. We investigate the commutation principles and present the system design. Experimental results from a 120 kV/360 MW prototype demonstrate the efficacy of this high-power converter, which has been deployed in the Lingbao super-high-voltage direct-current project in Henan, China, and Mengxi ultra-high-voltage direct-current project in Inner Mongolia, China.