Biology subjects

Shi, B.

Publications and source records attributed to Shi, B..

At least 19 recordsLinked to original sources

bioRxiv2026

SpectroBird: Event-Level Vocalization Detection and Curation for Avian Ecology

Passive acoustic monitoring often summarizes long recordings as fixed-window presence predictions, but many ecological questions require records of individual vocal events: how many occurred, when they occurred, whether they overlapped, how long they lasted, what frequency band they occupied, and whether each event was complete enough for structural measurement. We address this event-level measurement problem with SpectroBird, a spectrogram-based method for localizing and curating avian vocalizations in noisy field recordings. SpectroBird first applies a detection-localization model to identify candidate vocalizations as time-frequency boxes. An event-consolidation step merges repeated detections from overlapping windows while preserving overlapping vocalizations as separate events. A completeness-curation model then classifies each consolidated event as complete or incomplete before downstream event-level analysis. We demonstrate SpectroBird on breeding-season Hume's Leaf Warbler buzz vocalizations recorded in the Himalaya across a 3,200-3,800 m elevational gradient. Under shared window-level scoring, the detection-localization model remained competitive with AST and YOLOv11-cls baselines while retaining event timing and frequency bounds; event-level evaluation achieved AP > 0.999 for complete buzzes. Applied to two field seasons, the resulting event records showed that duration of complete buzzes declined with elevation, complete-buzz occurrence showed no simple elevation trend, and relative day-of-year occurrence patterns were strongly correlated between years. These results show how event-level detection and curation can support ecological analyses that depend on individual vocalizations rather than fixed-window presence alone.

bioinformatics↗

bioRxiv2026

Targeted tumor desialylation by engineered probiotic reprograms the tumor microenvironment to potentiate immunotherapy

Tumor hypersialylation drives immunosuppression and limits immunotherapy efficacy by shielding tumor cells and engaging inhibitory immune receptors. Here, we engineered Escherichia coli Nissle 1917 (EcN{Delta}pgi-SAS) as a metabolically confined "desialylation catalyst" to remodel the tumor microenvironment. This strain combines HER2-directed adhesion, hypoxia-inducible surface sialidase display for targeted glycan cleavage, and sialic acid catabolism to prevent glycolytic recycling. Critically, disrupting glucose metabolism ({Delta}pgi) restricts bacterial proliferation to sialic acid-rich tumor microenvironment, significantly enhancing biosafety. In mice, EcN{Delta}pgi-SAS colonized tumors and effectively desialylated tumor cells, synergizing with anti-PD-L1 to suppress growth of immunologically "cold" tumors. Mechanistically, desialylation reversed immunosuppression by broadly enhancing antitumor immunity. Orally administered EcN{Delta}pgi-SAS substantially inhibited colorectal carcinogenesis, repaired epithelial barrier integrity by restoring tight junctions, and prevented adenoma formation. This integrated strategy establishes a clinically translatable platform for reversing immunosuppression in solid tumors.

synthetic biology↗

bioRxiv2026

Biology-guided machine learning for robust anatomical correspondence across biodiversity datasets

Three-dimensional imaging is rapidly increasing the scale of biological morphometric datasets, but establishing automated anatomical correspondence remains a major bottleneck. Conventional point-cloud registration methods transfer landmarks efficiently, yet poor initialization or high morphological variation can produce geometrically plausible but biologically implausible deformations. Here, we developed a statistical-shape-model (SSM)-regularized coherent point drift (CPD) estimator for automated morphometric landmark transfer. It replaces the unconstrained non-rigid CPD update with optimization in SSM coefficient space and regularizes coefficients by inverse population covariance, so deformations along low-variance biological modes are penalized more strongly. We compared pose-matched conventional CPD, SSM-CPD, and SSM-CPD with refinement in leave-one-out atlas experiments on laboratory mouse skulls (N=249), primate molars (N=115), and squamate vertebrae (N=254) under aligned, mildly perturbed, and severely perturbed initialization. We evaluated these formulations in terms of landmark accuracy, failure-tail behavior, runtime, and preservation of morphometric structure. Under severe perturbation, we also evaluated an integrated recovery procedure that optimizes the starting template, recovers global pose, and then applies SSM-CPD with refinement. Severe misalignment produced widespread failures in pose-matched conventional CPD, whereas SSM regularization reduced median error from 13 - 21% to approximately 1 - 3% of the target bounding-box diagonal. This improvement was highly consistent for skulls and molars. In the morphologically complex vertebral dataset, however, low median error concealed a substantial minority of catastrophic failures (28% of vertebrae above a 6% error threshold), which integrated recovery reduced to 4%. Across datasets, automated landmarks preserved the major axes and pairwise relationships of morphometric shape space, and local CPD refinement improved covariance preservation. Embedding learned biological variation directly into registration broadens the range of starting conditions and anatomies for which automated landmark transfer remains reliable. Our results also show that failure tails and downstream morphometric fidelity must be assessed alongside median accuracy when automated landmarking methods are evaluated.

bioinformatics↗

bioRxiv2026

Direct electrochemical cortisol detection via transition-resolved interrogation at a defect-engineered graphene interface

Continuous tracking of cortisol is central to understanding human stress physiology, yet direct electrochemical detection without biological receptors remains challenging despite its promise for stable and dynamic sensing. Electrochemical reduction of cortisol typically occurs at highly negative potentials, where parasitic interfacial currents, hydrogen evolution, and substantial capacitive background overlap with the cortisol reduction signal, preventing accurate quantification. We overcome this barrier through an integrated material-measurement strategy combining a defect-engineered graphene interface with a transition-resolved interrogation (TRI) measurement strategy. First, we engineered polybenzimidazole-derived laser-induced graphene containing nitrogen-rich defects while suppressing oxygen-derived functionalities which reduced parasitic background currents within the same cathodic potential regime. Next, we designed TRI to leverage differences in the time-dependent evolution of overlapping cathodic processes to isolate a localized cortisol-associated electrochemical reduction transition. Derivative-domain projection coupled with background estimation enables its reliable quantification. This integrated sensing architecture enables sensitive, selective, and dynamic cortisol detection in both artificial and biological interstitial fluids at low nanomolar concentrations. The response remains reproducible across physiologically relevant variations in pH, ionic strength, temperature, and repeated cycling. Together, these capabilities provide a basis for continuous electrochemical cortisol monitoring for future study of stress physiology.

bioengineering↗

bioRxiv2026

Apoptotic bodies from patients with Sjogren's disease drive atypical memory B cell and macrophage activation and autoantibody production

The impaired clearance of apoptotic cells has long been associated with systemic autoimmune diseases like Sjogrens disease (SjD), which is characterised by autoantibodies targeting antigens on apoptotic cells. However, most studies analysing human samples have used patient-derived phagocytes and in vitro generated apoptotic cells, which do not reflect the heterogeneity of patient-derived apoptotic bodies (ApoBDs). Here, we molecularly and functionally compare ApoBDs derived from patients with SjD and healthy donors. ApoBDs were increased in the circulation in SjD and induced atypical memory B cell expansion, which was attenuated by blocking B cell receptor (BCR) and Toll-like receptors (TLR) 7-9 signalling. Co-cultures of ApoBDs and B cells drove autoantibody production. Macrophages engulfing SjD ApoBDs had a distinct inflammatory profile compared to macrophages engulfing healthy control ApoBDs. These findings define patient-derived ApoBDs as immunostimulatory substrates capable of driving innate and adaptive immune responses consistent with the pathogenic features observed in SjD, hence opening a new avenue of diagnostic and therapeutic development.

immunology↗

bioRxiv2026

SparseSeg: Target-Conditioned Discovery Segmentation of Cryo-Volume Electron Microscopy Under Sparse Annotation

Cryo-volume electron microscopy (cryo-vEM) enables near-native visualization of cellular ultrastructure, but its broad use is limited by low image contrast and the high cost of dense voxel-level annotation. Existing automated segmentation methods often generalize poorly across cell types, organelles, and imaging conditions. Here, we introduce SparseSeg, a target-conditioned, sparsity-driven segmentation framework that treats organelle segmentation as a discovery process rather than a closed-set classification task. SparseSeg uses a small number of context-specific exemplars to iteratively propagate reliable supervision through the volume. It combines sparse patch-based sampling, a multi-kernel U-Net, and geometry-consistent refinement to expand accurate segmentation while suppressing context-dependent false positives. Across serial cryo-FIB-SEM and conventional vEM datasets, SparseSeg achieves robust segmentation under extreme sparse annotation, including settings with less than 1% labeled slices. This framework reduces annotation burden while preserving morphological fidelity for quantitative cryo-vEM analysis.

bioengineering↗

bioRxiv2026

Biogenesis and antigen presentation properties of dendritic cell-derived apoptotic bodies

Dendritic cells (DCs) are an important type of antigen presentation cell that regulate immunity by initiating antigen-specific immunity and tolerance through T cell activation. The interaction between DCs and T cells can be mediated through direct cell-cell contact or via the release of extracellular vesicles (EVs) from DCs that harbour antigen presentation machineries. Although small EVs (<200 nm in diameter) such as exosomes released by DCs have been shown to regulate immunity, whether other EV subtypes, in particular those that are released by dying DCs due to homeostatic turnover or following infection, can modulate immune responses is not defined. In this study, we demonstrated that DCs undergoing apoptosis can generate a subclass of large EVs ([~]1,000-5,000 nm in diameter) known as apoptotic bodies (ApoBDs) via distinct morphological steps. Mechanistically, ApoBD formation by apoptotic DCs is regulated by Rho-associated kinase 1 and T-type calcium channels. Functionally, DC-derived ApoBDs were found to mediate direct antigen presentation. These data demonstrate a novel function of ApoBDs and highlight the ability of apoptotic materials derived from dying DCs to continue mediating intercellular communication and regulating immune responses.

cell biology↗

bioRxiv2026

DesignMaster: A Multi-Conditional Diffusion Framework for Rational PROTAC Design

MotivationProteolysis-targeting chimeras (PROTACs) enable targeted protein degradation through ternary complex formation with E3 ubiquitin ligase. However, the rational design of PROTACs remains highly challenging due to limited structure-activity relationship data and the vast conformational diversity of linkers. Existing computational approaches can be broadly divided into structure-based ternary modelling methods and fragment-based linker generation models. Although these approaches have advanced PROTAC design, they typically neglect key physicochemical constraints and linker-length control during the generation process, causing the generated PROTACs to lack balanced structural properties required for effective ternary complex formation with drug-like characteristics. ResultsTo address these limitations, we propose DesignMaster, a diffusion-based generative framework that explicitly incorporates linker length and physicochemical properties as controllable conditioning signals. DesignMaster employs an E(3)-equivariant graph Transformer with a gated multi-condition fusion module to inject linker length and physicochemical constraints throughout the diffusion process, enabling fine-grained and constraint-aware molecular generation. Experiments on PROTAC-DB 2.0 and 3.0 demonstrate that DesignMaster outperforms state-of-the-art baselines, with a 3.2% improvement in validity and a 34.4% improvement in recovery. The Case study shows DesignMaster achieves a 51.78% reduction in RMSD when predicting the linker of PROTAC BCPyr targeting 6W7O, highlighting its potential for practical structure-guided PROTAC design. AvailabilityThe source code and datasets are available at https://github.com/ABILiLab/DesignMaster.

bioinformatics↗

bioRxiv2026

LizardLens: A Two-Stage Deep Learning Pipeline for Detecting and Classifying Similar Species in Visually Complex Environments

Community science platforms like iNaturalist generate unprecedented volumes of biodiversity data, but their scientific utility depends critically on accurate species identification--a persistent challenge when contributors often lack taxonomic expertise. We developed "LizardLens", a two-stage machine learning pipeline that decouples object detection from species classification to enable fine-grained identification of morphologically similar organisms in visually complex field photographs. Using 10,000 verified iNaturalist images of five Anolis lizard species in Florida, we trained specialized YOLO-based detection and Swin Transformer classification models and compared performance against state-of-the-art single-stage architectures. Our two-stage pipeline achieved 83.0% Top-1 accuracy and a macro-averaged F1-score of 89.0%, indicating strong precision-recall performance across species and outperforming single-stage YOLOv8 and YOLOv12 models across all evaluation metrics for all species, with relative improvements ranging from 10.5% to 13.2%. Gradient-weighted Class Activation Mapping (Grad-CAM) indicated that the models predictions were consistently associated with regions corresponding to diagnostic morphological (e.g., head shape, feet, and limb lengths) and pattern features (e.g., ocular rings and body patterning), providing evidence that LizardLens leverages biologically relevant visual cues consistent with those used by expert taxonomists. Error analysis identified partial occlusion and multiple proximate individuals as primary sources of missed detections, while spurious detections of lizard-like environmental features (e.g., sticks, bark) represented the dominant false positive error mode. We deployed LizardLens as an accessible web application featuring interactive bounding box correction, ranked species predictions with confidence scores, directly supporting the "Lizards on the Loose" middle school community science initiative. By combining technical advances in fine-grained visual classification with user-centered design, LizardLens demonstrates how machine learning can simultaneously enhance data quality for biodiversity monitoring and provide authentic scientific experiences for student participants. Our approach is generalizable to other small-bodied organisms in complex habitats and provides a framework for translating computer vision advances into practical tools for community science and conservation.

ecology↗

bioRxiv2026

LizardMorph: A generalizable machine learning framework for automated anatomical landmark detection in digital images

Morphological measurements underpin a wide range of ecological and evolutionary research, yet the manual landmarking workflows on which most morphometric studies depend remain a persistent bottleneck that limits both the pace and scale of biological research. Machine learning offers compelling solutions, but most automated landmarking tools require substantial computational expertise, creating a gap between technical capability and practical adoption by biologists. Here, we present LizardMorph, an integrated machine learning pipeline and web-based interface for semi-automated anatomical landmark detection on biological images. LizardMorph couples a fine-tuned ML-Morph shape predictor with an accessible, browser-based interface that enables researchers to upload images, review automated landmark predictions, interactively correct outliers through point-and-click editing, and export results in standard morphometric formats--all without programming expertise or local software installation. Using dorsal X-ray radiographs of Anolis lizards with 34 anatomical landmarks as a proof-of-concept, we show that the ML-Morph model achieves high predictive accuracy, with landmarks on well-defined skeletal structures predicted with 100% accuracy within a 1 mm tolerance threshold. A controlled user study comparing LizardMorph against traditional manual landmarking (TpsDig2) demonstrated significant efficiency gains: experienced annotators completed LizardMorph landmark verification 37.5% faster than manual annotation. Extrapolated to batch processing 1,000 lizards, LizardMorph saves experienced researchers approximately 6.5 hours of manual processing time. Critically, LizardMorph implements a human-in-the-loop design in which automated predictions serve as editable starting points, preserving researcher oversight and enabling correction of the occasional large-error outliers that would be unacceptable in fully automated workflows. LizardMorph is freely available as an open-source tool and provides a replicable framework for developing ML-assisted annotation tools that can democratize access to high-quality morphometric analysis across diverse biological research communities.

evolutionary biology↗

bioRxiv2026

EnzCast: Prediction of Patient-Specific Enzymatic Kinetics through Multi-Modal Deep Learning and Isoform-Resolved Bayesian Inference based on Single-Cell Transcriptomics

Enzyme kinetic parameters underpin mechanistic biology but remain sparse in physiological context. We present EnzCast, a multi-modal framework jointly predicting Km, kcat, kcat/Km, and Ki from protein sequence, 3D structure, substrate chemistry, and experimental conditions, paired with IsoKin, an isoform-resolved Bayesian framework converting EnzCast priors into patient-specific in vivo kinetics. Trained on KinBench, the largest curated kinetics database, task-adaptive EnzCast achieved R2 = 0.413, 0.455, 0.227, and 0.105 for Km, Ki, kcat, and kcat/Km, surpassing all baselines on catalytic tasks. Systematic condition scans recovered compartment-specific pH direction inversion and pathway-level temperature responses. In a 20-patient colorectal cancer single-cell cohort, IsoKin reduced posterior uncertainty by 73.3% and 77.3%, revealing cell-type-specific rewiring. Orthogonal validation--scFEA flux, DepMap essentiality (permutation P = 0.0008) and TCGA survival-- provided mixed but directionally consistent support. Together, EnzCast and IsoKin bridge in vitro prediction, condition-aware biochemical interrogation and patient-resolved in vivo inference.

bioinformatics↗

bioRxiv2026

A Haplotype-resolved Telomere-to-Telomere Pig Genome

Haplotype-resolved telomere-to-telomere (T2T) pig genomes have not been reported, but may be essential for xenotransplantation and interspecies chimerism. Here we describe fully phased paternal and maternal T2T assemblies of an Erhualian pig (Ssc_EHL), enabling chromosome-scale reconstruction at base resolution. We uncover 2,498 (paternal haplotype) and 2,577 (maternal haplotype) protein-coding loci previously unresolved in Sscrofa11.1, while maintaining high concordance for anchored gene models between haplotypes. Applying this haplotype-resolved T2T annotation to publicly available pig-to-human kidney xenograft transcriptomes further allows the resolution of xenograft cell states and reveals newly resolved, cell-type-enriched genes. Cross-species synteny and orthology analyses against human identified a subset of high-confidence pig-specific genes with limited human counterparts, thus, refining the genomic basis of interspecies divergence. By integrating these orthology features with organ transcriptomes, we further defined an Interspecies Chimerism Compatibility score to prioritize organ-enriched, highly conserved loci with minimal redundancy imbalance, providing haplotype consistent targets for engineering organ-deficient pigs. Together, this haplotype-resolved T2T pig genome provides a foundational resource for mechanistic studies and rational genome engineering in xenotransplantation and interspecies chimerism.

genomics↗

bioRxiv2026

Therapeutic targeting inflammation linking periodontitis and atherosclerotic comorbidities using cell-free DNA-capturing nanomaterials

Periodontitis-associated systemic inflammation makes it a great challenge to explore therapeutic options applicable to periodontitis and atherosclerotic comorbidities. Here, we identify the crucial role of cell-free DNA (cfDNA) that underlies these comorbidities. Hypothesizing cfDNA as a therapeutic target, we engineer polyamidoamine dendrimer-functionalized nanomaterials to modulate such local-systemic inflammatory crosstalk. Periodontium-originated DNA can be systemically captured by cationic nanomaterials, and capturing cfDNA, whether locally or systemically, alleviates both periodontitis and atherosclerosis prior to severe atherosclerotic development in vivo. The transcriptomic and single-cell RNA sequencing analyses together reveal that cfDNA-capturing nanomaterials regulate inflammatory foam cell transformation in macrophages by modulating the expression of lipid-related foamy markers Spp1 and Fabp4. This study provides a proof of concept for cfDNA-driven periodontitis-atherosclerosis crosstalk, and offers a cfDNA-capturing nanoplatform for therapeutic intervention targeting periodontitis and atherosclerotic comorbidities in a holistic fashion.

immunology↗

bioRxiv2026

Unleashed condensation by recurrent mutations of an epigenetic regulator promotes cancer

The pathological mechanisms and significance for the prevalent hotspot mutations in disordered protein regions are poorly understood. ASXL1 is an obligate co-factor for BAP1 in H2AK119 deubiquitination. ASXL1 mutations are very frequent in myeloid malignancies, and are mostly C-terminal truncating mutations concentrated in a specific disordered region of ASXL1. ASXL1 truncations are gain-of-function mutations that promote myeloid malignancies, but the underlying mechanisms remain poorly understood. Here we show that the frequently truncated mutants of ASXL1 possess an intrinsic property of forming phase-separated biomolecular condensates, and this property is normally suppressed by the frequently deleted regions. A disease-mutant of the endogenous ASXL1 in leukemia cells forms dynamic nuclear co-condensates with other endogenous factors important for gene activation. The ASXL1 disease-mutants can greatly enhance H2A deubiquitination activity of BAP1 in cells and in vitro reconstituted system, enhance myeloid leukemia cell growth, and promote leukemogenesis in a mouse transplant model by turning on myeloid leukemogenic transcriptional programs. However, substitution of residues important for condensation disrupted or impaired all these abilities, suggesting that the condensation property is crucially important for the ASXL1 mutants in promoting cancer. Moreover, we discover that the conserved negative charges in the highly disordered and frequently deleted region on ASXL1 suppress the condensation of the wild type ASXL1. Charge-neutralizing mutations in this region restores condensation of the full-length ASXL1, and are sufficient to turn ASXL1 into a leukemogenic protein. Biochemical, biophysical, and simulation analyses suggest the intramolecular interactions normally mask the N-terminal region in engaging intermolecular interactions required for phase separation, and disease truncations escape from the regulatory interactions and unleash the phase separation property to form nuclear hubs to promote expression of tumorigenic gene programs. Finally, by showing a striking correlation of the mutation frequencies with the condensation properties and leukemogenesis activity for a series of human patient mutations, we suggest that dysregulation of condensation is a central mechanism for ASXL1 mutations in promoting myeloid malignancies. This suggests that dysregulation of condensation may be a key mechanism for some of the prevalent hotspot disease mutations in the disordered proteomes.

biochemistry↗

bioRxiv2025

Cell cycle-driven epigenetic resetting maintains stem cell fate for shoot branching

Adult mammalian stem cells typically maintain stem cell identity through proliferative quiescence. In contrast, we demonstrate that stem cell maintenance in Arabidopsis bud precursor cells requires active cell-cycle progression. Inhibiting division silences the shoot meristem marker gene SHOOT MERISTEMLESS (STM) and promotes differentiation. Whereas proliferation dilutes H3K27me3 levels to counteract silencing. Meanwhile, we identified two classes of transcription factors recruiting polycomb repressive complex 2 (PRC2) to epigenetically silence STM. The balance between these forces establishes a cell cycle-coupled epigenetic "Sisyphus" mechanism that maintains pluripotency. This cell fate switch is bistable; modeling and experimental data confirm that prolonged quiescence triggers irreversible differentiation. We propose that sequence-dependent PRC2 recruitment in plants enables precise silencing of fate-determining genes, while cell proliferation sustains pluripotency by resetting epigenetic marks.

plant biology↗

bioRxiv2025

NSF is required for diverse endocytic modes by promoting fusion and fission pore closure in secretory cells

The ATPase N-ethylmaleimide-sensitive factor (NSF), known for disassembling SNARE complexes, plays key roles in neurotransmitter release, neurotransmitter (AMPA, GABA, dopamine) receptor trafficking, and synaptic plasticity, and its dysfunction or mutation is linked to neurological disorders. These roles are largely attributed to SNARE-mediated exocytosis. Here, we reveal a previously unrecognized role for NSF: mediating diverse modes of endocytosis--including slow, fast, ultrafast, overshoot, and bulk--by driving closure of both fusion and fission pores. This function was consistently observed across large calyx nerve terminals, small hippocampal boutons, and chromaffin cells using capacitance recordings, synaptopHluorin imaging, electron microscopy, and multi-color pore-closure imaging. Results were robust across four NSF inhibitors, gene knockout, knockdown, and specific mutations. These findings establish NSF as a central regulator of membrane fission, kiss-and-run fusion, endocytosis, and exo-endocytosis coupling--offering new mechanistic insights into its diverse physiological and pathological roles in synaptic transmission, receptor trafficking, and neurological diseases.

neuroscience↗

bioRxiv2025

Visualising sub-second dynamics of nanoparticle extravasation in vivo

Altered vascular integrity is a hallmark for many diseases. Monitoring vascular permeability, including its extent and underlying transport pathways, is thus important for advancing our understanding of disease mechanisms towards innovative diagnosis and treatment. Here we show real-time fluorescence imaging using lanthanide-based upconversion nanoparticles as contrast agents to visualise subtle changes to vascular permeability in vivo. Based on simultaneous confocal imaging of the vasculature alongside single particle tracking in the wide-field at video rate, we performed high-throughput surveillance across live zebrafish larvae to pinpoint locations of potential nanoparticle extravasation, achieving superior sensitivity and specificity over conventional fluorescent dyes. Further analyses of the sub-second dynamics of individual nanoparticle extravasation events unveiled distinct characteristics to distinguish between transcellular and paracellular transport. We applied the technique to evaluate the blood-brain barrier (BBB) in zebrafish larvae at different developmental stages, and potential BBB perturbation strategy via nanoparticle functionalisation with polysorbates. Significantly increased BBB penetration by 36.5 folds was shown for the functionalised particles compared to phospholipid-coated particles, attributed to enhanced transcellular crossing. The technique is readily applicable to monitoring vascular integrity and investigating endothelial transport for improved understanding of vascular biology, facilitating advanced research in disease diagnostics and drug delivery towards translation.

biophysics↗

bioRxiv2025

Complexes between Netrin G Ligands and Chiral Nanoparticles Promote Axons Regeneration under Near-Infrared Illumination

Chiral nanoparticles combine functionalities of inorganic materials and large biomacromolecules enabling stimulation of neurons. However, multiple challenges remain in their use for central nervous system including identifying suitable cell signaling pathways and traversing the blood-brain barrier. In this study, we show that glutathione-coated Ni(OH)2 nanoparticles form nanoscale complexes with netrin-G1 ligands (NGL-1), critical for neuronal regeneration. NGL-1 features a semispherical pocket with a 2.5 nm radius of curvature, fitting well with nanoparticles sized 3 {+/-} 1.2 nm. D-NPs with D-glutathione surface ligands activate D-glutathione receptors on epithelial cells, facilitating their transport into the brain. When illuminated with 980 nm light, the nanoparticle-protein complex stimulates axon regeneration through localized IGF-1 production. This approach successfully regenerated (a) hippocampal neurons in Alzheimers disease mice and (b) dorsal root ganglion neurons in spinal cord-injured mice. The nanoparticles were thoroughly tested for safety and excreted intact. The local, rather than systemic, IGF-1 upregulation minimizes its side effects.

neuroscience↗