Advanced Science

Cervical spinal cord injury (SCI) causes profound and persistent loss of hand function, and effective neuromodulation strategies remain limited. We report the first-in-human implantation of a 32-contact cervical epidural paddle array in two individuals with severe chronic SCI. Individualized motor pool recruitment maps, derived from systematic bipolar and multipolar configurations, enabled person-specific stimulation parameters. Optimized stimulation restored volitional hand opening, closing and coordinated upper-limb movements that were previously unattainable. This approach achieved a >91% success rate in complex reach-grasp-lift-release sequences, supported by substantial gains in range of motion, grip, and pinch strength. Electrophysiological and kinematic analyses demonstrated parameter-dependent, selective recruitment of flexor and extensor motor pools. Personalized stimulation programs integrated with goal-directed activities enabled functional hand use in home and community settings, sustained over several months of continued autonomous use. These findings establish a mechanistically grounded and translational framework for restoring upper-limb function after chronic severe SCI.

Glaucoma is characterized by progressive stiffening of the trabecular meshwork (TM), which elevates intraocular pressure and contributes to tissue dysfunction. Although substrate stiffness and mechanical stimulation both regulate TM homeostasis, their combined effects remain poorly understood. Here, a hydrogel-integrated microfluidic platform is presented that enables simultaneous control of substrate stiffness via tunable gelatin methacryloyl (GelMA) hydrogels and equi-biaxial quasi-static stretch via hydraulic actuation. Finite element analysis validates the applied strain field, and optimized crosslinking ensures structural stability. Primary normal TM (nTM) and glaucomatous TM (gTM) cells cultured under coupled conditions exhibit selective mechanotransduction dysregulation rather than global mechanosensory impairment. While nTM cells dynamically regulate -smooth muscle actin (-SMA), myocilin (MYOC), matrix metalloproteinase-2 (MMP2), and collagen type I (COL1), gTM cells display constitutively elevated -SMA, loss of mechanical regulation of MMP2, and impaired stretch-mediated COL1 suppression, while retaining stiffness-dependent focal adhesion kinase and MYOC sensitivity. Key differences between normal and glaucomatous cells emerge only under combined stiff and stretched conditions, underscoring the importance of coupled mechanical cues in revealing disease-relevant phenotypes. These findings implicate tissue stiffening in selective pathway dysregulation and highlight mechanotransduction-targeted therapeutic strategies.

Persistent hyperglycemia impairs wound healing in diabetic patients, and severe cases may even lead to disability or death. Glycemic control alone cannot effectively prevent the occurrence of diabetic foot ulcers, a serious complication of diabetes. However, safe, efficient, and cost-effective therapies remain unavailable and are urgently needed. Using a novel sports medicine paradigm, we predicted, based on reverse-transcriptomics, that exercise-induced sweat has the potential to promote would healing in diabetic foot ulcers. Subsequent animal experiments demonstrated that sweat can indeed promote re-epithelialization and collagen deposition, upregulate the expression of the proliferation marker Ki-67, the angiogenesis marker CD31, and -SMA, and significantly accelerate wound healing in a mouse model of diabetic foot ulcers. This study provides a new direction for sports medicine and offers a novel therapeutic strategy for patients with diabetic foot ulcers.

The thymus plays a pivotal role in the generation of immunocompetent T cells. Although its function is dependent on its complex extracellular matrix, its 3D architecture and mechanical properties remain poorly characterised This knowledge gap limits efforts to model and engineer the organ, which is a critical step towards the development of strategies for the treatment of many haematological and autoimmune diseases. Here, we provide the first comprehensive multiscale dataset of bovine thymic extracellular matrix architecture and viscoelastic behaviour, including quantitiative descriptors such as relaxation times, instantaneous and equilibrium elastic moduli, storage and loss moduli, and spatial mechanical heterogeneity. Taken together, our data define the thymus as a compliant, highly dissipative viscoelastic organ with a fibrillar architecture. They also represent a unique database, which, for the first time, paves the way for quantitative thymus tissue engineering.

Meningeal lymphatic vessels (mLVs) are vital for brain waste clearance, making them a promising therapeutic target. However, effective modulation strategies for mLVs with translational potential remain underdeveloped. Here, we develop a low-intensity focused ultrasound (LIFU) strategy that precisely targets the vault cranial meninges to non-invasively facilitate mLVs drainage. Using models of Alzheimers disease (AD) and aging, we demonstrate that this approach promotes CSF drainage, prevents cognitive decline, and reduces pathological biomarkers. Mechanistically, RNA sequencing combined with calcium imaging in vitro reveals that LIFU activates the Piezo1 ion channel in lymphatic endothelial cells, whereas pharmacological inhibition of Piezo1 abolishes LIFUs therapeutic effects. Compliant with FDA safety guidelines, this LIFU protocol demonstrates strong clinical translatability. If its efficacy is clinically confirmed, LIFU offers a promising therapy for neurodegenerative diseases triggered by waste accumulation.

The development of neural probes has enabled a deeper understanding and improved treatment for neurological disorders. Microneurography is currently the gold standard for assessing the electrophysiological signature of pain mechanisms in the human peripheral nervous system. However, its clinical utility is limited by the low recording yield and signal-to-noise ratio of single-electrode probes. To overcome these limitations, we developed mechanically robust, multi-electrode probes designed for acute percutaneous insertion and recording in peripheral nerves. The electrical and mechanical stability of these probes was confirmed through repeated insertions in artificial human skin and rat peripheral nerves. In addition, ex vivo and in vivo experiments demonstrated enhanced functional performance, with multi-site recordings enabling the isolation of single-fiber activity. Importantly, our probes can be operated analogously to conventional microneurography needles while substantially increasing the information yield, providing enhanced capabilities for minimally invasive peripheral nerve assessment.

Human induced pluripotent stem cells (hiPSCs) offer a powerful platform to model chondrogenesis and enable regenerative strategies, yet regulation of cell-fate commitment remains elusive. Here, we systematically mapped cell-fate trajectories from 7 time points during a 49-day chondrogenic hiPSC differentiation protocol using single-nucleus multimodal transcriptomic and chromatin accessibility profiling (scRNA-seq and scATAC-seq). Integrative analysis of dynamics revealed branching differentiation trajectories with clear bifurcation points and distinct cell-fates. Notably, the chondrogenic trajectory originated at day 6 as a neurogenic development and branched off at day 21 to a chondrogenic cell-fate. Through transcription factor activity analysis (TFAA) and cis-co-accessibility networks, we found that NFIA and NFIB drove chondrogenic distinction, exhibited in both modalities as directly targeting chondrogenic genes such as COMP, FIBIN, VIM. This was then confirmed by experimental validation as modulation of NFIA expression at this point further enhanced chondrocyte formation. Together, our study provides a high-resolution multimodal atlas of chondrogenic differentiation and identified critical transcriptional regulators that can now be leveraged to implement regenerative cartilage therapies from hiPSCs.

The superior stealth properties and high information density make DNA a sought-after candidate in the field of molecular steganography. Here, we developed the InfinMark end-to-end DNA steganography framework for anti-counterfeiting applications by combining the characteristics of both the Internet of Things (IoT) and DNA-of-Things (DoT). InfinMark includes five modules: Information Transcoding, Fingerprint Writing, Nano-encapsulation, Invisible Marking, and Multi-level Rapid Authentication. It ensures precise anti-counterfeiting information reading and writing through a dynamic DNA-compatible transcoding algorithm, achieves seamless embedding by developing scalable nanoparticle manufacture methods, and supports cross-scenario on-site verification, ultimately granting it comprehensive anti-counterfeiting capabilities spanning from source labeling to terminal tracing. By addressing the bottlenecks in IoT and DoT integration, lifecycle tracking, as well on-site product authentication, this research constructs a full-chain bimodal anti-counterfeiting system, thereby showcasing the practical application of informational DNA nanoparticles in various aspects of production and daily life.

Chronic periodontitis represents one of the most prevalent inflammatory tissue-destructive conditions in humans, yet the molecular thresholds separating reversible inflammation from permanent structural collapse remain undefined. Using single-cell RNA sequencing data from 12,104 cells (GSE152042) spanning three disease states -- healthy gingival tissue, mild periodontitis, and severe periodontitis -- we constructed a variational autoencoder (VAE)-derived 20-dimensional latent disease manifold and applied formal hysteresis quantification to measure transcriptional irreversibility. Chi-square analysis across 9,163 cells occupying transitional pseudotime bins yielded {chi}{superscript 2} = 11,971 (p < 10-300, df = 4), with Cramers V = 0.81, confirming strong state-memory effects inconsistent with freely reversible disease dynamics. Non-negative matrix factorisation (NMF; k = 15) identified biologically coherent gene programs whose co-activation topology was encoded as a hypergraph constraint network; in severe disease, 16 of 76 healthy constraints collapsed by more than 60%, and the Fibroblast-Epithelial coupling (Programs 1-4) was reduced by 84%. A six-agent agentic AI simulation faithfully recapitulated observed shifts in cellular composition and established a temporal threshold beyond which tissue damage trajectories diverge irreversibly. We introduce the Regenerative Permission Index (RPI), a composite single-cell metric (range: 0.060-0.644), whose mean in severe periodontitis (0.323) falls well below the 0.50 permissibility threshold, indicating that all tested biomaterial interventions will fail. Five-fold cross-validated classification achieved 88% accuracy (Random Forest, AUC = 0.992), and permutation testing confirmed that constraint network patterns are biologically specific rather than artefactual (p < 0.01). Together, these findings provide a quantitative basis for understanding periodontal irreversibility and position RPI-guided decision-making as a framework for precision regenerative medicine.

Brain-body interactions (BBIs) are fundamental to cognition and mental health, but their continuous multimodal dynamics remain difficult to extract. Previous approaches have been largely observational, and few frameworks enable these interacting processes to be modeled within an integrated generative system. Here, we applied a Predictive-Coding-Inspired Variational RNN (PV-RNN) to simultaneous EEG, ECG, and respiration recordings obtained from 33 participants during exteroceptive and interoceptive attention. The model learned a temporal hierarchy spanning modality-specific dynamics, multimodal associative integration, and sequence-level global states, and accurately reconstructed unseen physiological sequences. Specifically, the intermediate associative layer successfully captured the core complexities of BBI by extracting multiscale, nonlinear, and bidirectional coupling dynamics with variable temporal lags. Furthermore, the estimated precision (inverse variance) of latent variables representing BBI dynamics within this multimodal associative layer increased significantly during interoceptive attention. The magnitude of this condition-dependent precision enhancement correlated positively with subjective adaptive body controllability and negatively with psychiatric vulnerabilities, including rumination and trait anxiety. These findings identify a latent physiological signature of interoceptive attention and establish hierarchical generative modeling as an interpretable framework for extracting continuous BBI dynamics and linking multimodal physiology to cognitive and clinical characteristics.

In vitro models of the small intestine frequently neglect the role of physiological oxygen tension in drug absorption studies. To meet the throughput demands of preclinical drug development while maintaining compatibility with standard permeability assays, we engineered a new technology, termed Gradient-on-Platform. This system enables the establishment of physiologically relevant oxygen gradients across intestinal epithelium in vitro models by leveraging Caco-2 cells metabolic oxygen consumption. In this work, we demonstrated that exposure to physiomimetic oxygen conditions modulates epithelial barrier function, mitigating the excessively tight Caco-2 phenotype typically observed under conventional aerobic cultures, which leads to underestimation of drug bioavailability in vitro. Indeed, while complete hypoxia disrupts epithelial barriers, oxygen gradients drive Caco-2 TEER toward values more consistent with ex vivo measurements and result in a 3-fold increase in paracellular permeability compared to fully aerobic controls. The incorporation of physiologically relevant oxygen gradients into a scalable, assay-compatible platform could represent a pivotal step toward improving the predictive accuracy of in vitro preclinical drug absorption assays.

Peptide ligands Urotensin II (hUII, human), hUII-related peptide (URP) and its cognate human receptor (hUT) are known for their implications in cardiovascular pathophysiology, yet the lack of experimentally resolved hUT structures has limited a deep mechanistic understanding of ligand binding and receptor activation. Here, we leverage recent breakthroughs in multistate AlphaFold predictions, long-timescale molecular dynamics (MD) simulations, and site identification by ligand competitive saturation (SILCS) based pocket mapping and solving ligand bound conformation to illuminate the dynamic interaction of hUII and URP with hUTR. By analyzing hUT dynamics in its intracellular transducer binding pocket, and residue-level interaction probabilities in each simulation, we capture subtle distinctions in the way hUII and URP anchor key pocket residues, modulate transmembrane (TM) domain tilts. Results indicate that hUII imposes stronger conformational constraints on TM5 and TM6 relative to URP, both potentially stabilizing different active-like receptor configurations. At the same time, interaction maps highlight unique aromatic and polar networks that each ligand exploits. These findings reinforce the concept that relatively small differences in GPCR peptide ligand structure may lead to large effects on receptor-state selection, signal specificity, ultimately reflecting different clinical outcomes. By integrating computational modeling with per-residue dynamics, this work not only reconciles prior mutagenesis and docking data but also provides validated 3D models and MD simulations of the endogenous ligands bound to hUT, offering new opportunities to selectively harness ligand-dependent signaling in the urotensinergic system.

Force-induced protein conformational changes govern many essential biological processes, yet their molecular mechanisms remain difficult to resolve. Von Willebrand factor (VWF), a central regulator of haemostasis, is activated by hydrodynamic forces in blood flow, but how mechanical signals propagate across its multidomain architecture is poorly understood. Here, we use flow molecular dynamics (FMD), a simulation framework that applies fluid forces via controlled solvent flow to interrogate mechanosensitive proteins. Using VWF as a model system, we reconstructed the complete mechanomodule (D'D3-A1-A2-A3; 1,109 residues) with native glycosylation by integrating crystallographic data and AlphaFold predictions. FMD simulations capture a force-driven transition from a compact, autoinhibited "birds-nest" ensemble to an extended, activated state, revealing asymmetric autoinhibitory strengths within the N'AIM and C'AIM modules of the A1 domain. By directly linking static structures to dynamic, force-regulated behaviour, this work establishes a generalizable platform for dissecting protein mechanosensitivity and enabling the rational design of force-responsive therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=48 SRC="FIGDIR/small/716521v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@edba50org.highwire.dtl.DTLVardef@1630df4org.highwire.dtl.DTLVardef@292887org.highwire.dtl.DTLVardef@23cdb7_HPS_FORMAT_FIGEXP M_FIG C_FIG Flow molecular dynamics simulations reveal that GPIb engages the A1 domain only after the disruption of key interdomain and intermodular interactions.

Liquid-liquid phase separation (LLPS) underlies the formation of biomolecular liquid condensates (also referred to membraneless organelles, MLOs), which are essential for spatially organizing various biochemical processes within cells. Proteins that play a key role in driving condensates formation are termed phase-separating proteins (PSPs). Given experimental identification of PSPs remains labor-intensive and time-consuming, multiple computational tools have been developed based on empirical features or deep learning. In this study, we propose SSPSPredictor, a novel multimodal predictive model for PSPs with folded or intrinsically disordered structures, leveraging the fusion of sequence information from a protein language model ESM-2 and structural insights from a graph neural network GVP. Compared with existing tools, SSPSPredictor achieves balanced performance in identifying endogenous PSPs, predicting relative LLPS propensities, and recognizing key regions that drive LLPS. Moreover, SSPSPredictor exhibits good interpretability in identifying driving regions along protein sequences, although no relevant supervision was provided during training. Further predictive analysis of the human proteome using SSPSPredictor reveals that the proportion of intrinsically disordered proteins (IDPs) undergoing LLPS is significantly higher than that of folded proteins. In addition, pathogenic variants, especially those located in disordered regions, exhibit higher LLPS propensity than other mutations, uncovering a link between LLPS and diseases at the amino acid level.

Dermal bone, which forms a variety of skeletal structures and persists in a wide range of extant vertebrates, evolved prior to endochondral bone which forms all mammalian load-bearing bones. Sturgeons are a family of fish which diverged soon after the lobe-finned/ray-finned split. Sturgeon retain a long robust spine at the leading edge of the pectoral fin, called the pectoral fin spine (PFS). Pectoral fin spines are bone elements that are present in many extinct and extant species of non-tetrapod jawed fish. In this study, we characterize the structure (light, polarized, micro-computed tomography and scanning electron microscopy), composition (FTIR, TGA, BMD), and mechanical properties (3-point bending and microindentation) of the pectoral fin spine (PFS) of the Russian sturgeon (Huso gueldenstaedtii). The microstructure of the PFS is highly organized as it is formed by dermal osteonal bone and parallel fibered bone. Its microarchitecture, along with high material toughness, anisotropy, and substantial ash content, enables the PFS to bear loads and function in both locomotion and protection. In addition, we show an interconnected network of neurovascular canals and ornamentations, features also found in pectoral fin spines of other non-tetrapod jawed fish. Collectively, these findings demonstrate that dermal bone can form structurally organized, mechanically competent load-bearing elements and provide new insight into pectoral fin spines in ray-finned fish.

Epidermal development and homeostasis require precise coordination between keratinocyte differentiation and mechanics. Still, the mechanisms integrating these processes remain poorly understood in part due to limitations of existing experimental systems. Here, we introduce StrataChip, a tractable microphysiological system that enables dynamic, multimodal interrogation of human epidermal morphogenesis. The platform integrates a media perfused dermal tissue with human epidermal keratinocytes within a microfluidic device and supports rapid epidermal stratification following establishment of an air-liquid interface. High-resolution confocal imaging and single-cell RNA-sequencing demonstrate that the StrataChip recapitulates key architectural and molecular features of human epidermis, including distinct basal, spinous, and granular layers defined by canonical differentiation markers and adhesion molecule organization. Single-cell profiling reveals transcriptionally distinct basal and spinous subpopulations, including transitional states associated with suprabasal commitment. Live 3D imaging in situ captures keratinocyte morphodynamics including basal cell delamination and asymmetric division, linking dynamic cellular behaviors to defined differentiation fates and stratification. Altogether, StrataChip provides a robust platform for a dynamic and mechanistic interrogation of how gene regulation and cell mechanics are coupled during epidermal morphogenesis.

Prosthetic devices balance functionality and usability to support activities of daily living (ADLs). However, many designs rely on rigid end effectors that, while anthropomorphic in form, lack biomimetic design principles. This mismatch increases cognitive and physical burden, reducing adoption rates. We developed the Human-inspired Actuator Modeling and Reconstruction (HAMR) process, a user-centered framework informed by individual morphology and functional needs, to generate customized agonist/antagonist tendon-actuated end effectors. Using HAMR, we created the Tendon Actuated Prosthetic Hand (TAPH), which integrates human-derived geometry with adaptive force distribution to promote natural object interaction. In a study with 12 participants without limb difference, TAPH was compared to a structurally similar tendon-actuated hand with generalized anthropomorphic geometry across three ADL tasks of varying complexity. TAPH significantly improved task performance and reduced physical effort, mental workload, and frustration, particularly during gross motor tasks. For fine motor tasks, performance improved under stable conditions but not during tasks requiring dynamic precision and continuous coordination. These findings highlight the functional benefits of biologically informed prosthesis design and support biomimetic principles in enhancing performance and user experience.

Cellular metabolism is governed by the coordinated organization of macromolecules, including lipids and proteins, together with redox-active cofactors such as NADH and FAD. However, resolving these biochemical features quantitatively and spatially at subcellular resolution remains challenging because no single imaging modality can capture molecular composition, redox state, and tissue architecture simultaneously without labeling. Here, we present MANIFEST (Multi-modAl Nonlinear Imaging with Fluorescence Excitation and Statistical Temporal-resolved spectroscopy), a label-free imaging platform that integrates stimulated Raman scattering (SRS), second harmonic generation (SHG), multiphoton fluorescence (MPF), and fluorescence lifetime imaging microscopy (FLIM). The MANIFEST combines chemical imaging of lipids with autofluorescence- and lifetime-based quantification of NADH and FAD metabolism, enabling spatially resolved analysis of metabolic heterogeneity at organelle and tissue-compartment levels. We apply this framework to four distinct aging or disease models: amyloid-beta-treated tri-cultured brain cells, high-fat diet mouse liver, human non-ischemic cardiomyopathy tissue, and aging mouse retina. Across these systems, MANIFEST reveals disease-associated lipid remodeling, redox imbalance, disrupted metabolic zonation, collagen reorganization, and layer-specific metabolic changes. By integrating complementary nonlinear optical modalities into a single label-free platform, MANIFEST provides a generalizable approach for high-resolution metabolic phenotyping in complex biological systems and offers new opportunities for studying disease mechanisms, aging biology, and metabolism-driven tissue pathology.

Network pharmacology has become a widely used approach for deciphering multi-component, multi-target mechanisms of traditional Chinese medicine (TCM). Here we introduce TCMCard, a high-confidence digital infrastructure built on a Multi-Dimensional Evidence Integration (MDEI) framework. The framework integrates experimental activity data from authoritative chemical databases, literature-derived evidence, and structure-based similarity inference. Preprocessing steps include chemical structure normalization, species-specific filtering, and target quality scoring. Applied to conventional interaction datasets, this pipeline leads to the removal of over 60% of low-confidence noise. TCMCard supports network pharmacology exploration through an interactive visualization platform, and module analysis identifies functionally relevant communities that offer insights into the synergistic actions of TCM formulas. Overall, TCMCard may help move the field beyond simple data aggregation toward evidence-informed curation and quality-driven analysis. As an interactive and publicly accessible platform, it reveals an organized backbone within complex interaction networks, offering a more reliable basis for understanding multi-component synergy in TCM.

Chronic pain affects billions globally, yet safe, long-lasting, and non-addictive analgesics remain lacking. Nav1.7 is a genetically validated pain target, but traditional small molecules have repeatedly failed. Therapeutic oligonucleotides-antisense oligonucleotides (ASOs) and siRNAs-offer selective, durable silencing. We developed N02C0702, an ASO-siRNA conjugate (ASC), achieving robust Nav1.7 knockdown and sustained analgesia without additional delivery vehicles. N02C0702 outperformed individual ASO (N02A114) and siRNA (N02S154) moieties at mRNA and protein levels and in pain relief. In CFA-induced inflammatory pain, a single intrathecal dose exceeded naproxen and suzetrigine, while in SNL neuropathic pain, efficacy persisted up to 56 days, comparable to or surpassing pregabalin. Genome-wide RNA sequencing confirmed minimal off-target effects. N02C0702 highlights Nav1.7 as a key analgesic target and demonstrates the ASC platforms potential for chronic pain and other CNS-related pathologies, offering durable, selective, and safe therapeutic effects.