Advanced Science

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.

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.

Hippocampal sclerosis (HS) is the most common pathology in drug-resistant temporal lobe epilepsy (TLE). However, clinical diagnosis, prevalent epileptogenicity, and drug drug-resistance in individuals with HS remain an ongoing challenge demanding multidisciplinary research efforts. In this study, we examined the mechanical properties of neurosurgically en bloc resected HS specimens (n=8) ex vivo under compression, tension, and torsional shear. We fitted a two-term Ogden hyperelastic model to the measured mechanical responses to quantify nonlinear mechanical tissue properties. The resulting parameters revealed higher strain stiffening under compression in HS compared to hippocampus obtained post mortem (n=7). The distinction was most noticeable in the large-strain regime, which has important implications for using mechanical tissue properties as valuable diagnostic biomarker. Furthermore, we correlated the tissue microstructure with mechanical parameters. We trained a deep-learning histopathology classifier to detect and classify neurons and glial cells from hematoxylin-stained whole slide images (WSI). We identified a strong association between the small-strain stiffness (shear modulus {micro}) and the overall cell density as well as the glial cell density. The negative relationship between the neuron-to-glia ratio and shear modulus is consistent with the hypothesis that neuronal cell loss and gliosis drives tissue stiffening, respectively. Magnetic resonance imaging (MRI) analysis of the specimens confirmed the previously reported negative association between MRI-derived fractional anisotropy and shear modulus {micro}. Taken together, our study establishes a direct link between tissue mechanics and microstructure, suggesting nonlinear continuum mechanics models as promising new tools for clinical diagnosis and novel research strategies.

Cell-penetrating peptides (CPPs) can deliver diverse cargos into cells. However, designing CPPs with receptor-selective interaction profiles remains difficult because interactions with individual cell-surface components cannot be tuned independently. Here, we developed a closed-loop in silico framework for receptor-selective CPP design, in which receptor interactions are formulated as explicit objectives in a multi-objective optimization problem. We first constructed a CPP-like candidate library using a sequence generative model fine-tuned on known CPPs. The framework then evaluated candidate peptides by receptor-wise docking, molecular dynamics simulations, and MM/GBSA to compute receptor-wise binding scores. These scores were used iteratively to propose subsequent candidates by multi-objective Bayesian optimization. Applied to a CXCR4/NRP1 design setting, the framework identified candidates with more favorable predicted interaction profiles, characterized by higher CXCR4 binding scores and lower NRP1 binding scores. We selected 10 peptides from the computationally identified candidates for cell-based imaging and found that 4 showed higher enrichment in CXCR4-positive regions than in NRP1-positive regions under the tested conditions. These results show that the proposed framework provides a practical in silico approach for designing CPPs with receptor-selective interaction profiles.

Alzheimer's disease (AD) is increasingly recognized to have systemic physiological correlates alongside central neurodegeneration. Here, we explored brain-organ network (BON) connectivity in AD (n=28) and healthy controls (n=23) using time-resolved quasi-dynamic analysis of plateau-phase total-body 18F-tau-PET. We found that AD-related pathophysiology was linked not only to cerebral tau aggregation, but also to altered signal synchronization across the brain-organ network, despite comparable body tracer distribution. Network topology analyses revealed the occipitotemporal cortex and the spinal cord as key nodes in this altered systemic network. Furthermore, exploratory mediation analyses demonstrated that BON dysregulation is cross-sectionally linked to cognitive deficits, with statistical associations observed for both cortical tau burden and imaging markers of impaired glymphatic clearance. This total-body PET study provides first-ever direct evidence repositioning AD as a multi-organ disorganization disease. These findings provide a novel framework for investigating brain-body interactions and systemic vulnerabilities in neurodegenerative disorders.

Transcriptomic data is highly sensitive to cancer state and progression, making transcriptome-based foundation models a great promise for diverse clinical ontological inference. However, analyses of transcriptome are conventionally hindered by technical batch effects and limited generalization across platforms. Here, we introduce RNABag, a foundation model designed to generalize well to external datasets. In particular, the model only focuses on highly variable genes to reduce noise; and extensive data augmentation was utilized to pretrain RNABag to learn robust representations, invariant to batch variations. We demonstrate that RNABag achieves superior performance in pan-cancer tissue-of-origin classification and cancer detection in internal validation sets, as well as in zero-shot generalization to external cohorts and in-house clinical samples. Furthermore, RNABag, after specialized finetuning, exhibits strong capabilities in a wide range of clinical applications. The model effectively stratifies patient survival and predicts relapse risks, highlighting key molecular pathways driving tumor progression. Crucially, we extend RNABags utility to liquid biopsies, achieving high diagnostic accuracy in plasma cfRNA and tumor-educated platelets (TEPs), thereby supporting its application in non-invasive cancer monitoring. Interpretability analysis revealed pivotal role of tumor immune escape in the cancer induced plasma cfRNA signals. In summary, our study indicates that cancer states and progression may be monitored in details and precision via comprehensive modeling of transcriptome across biopsy modalities.

Neuropathy caused by chemotherapy is a common and debilitating side-effect of cancer treatment. With 30% of patients experiencing chronic neuropathy and with no good evidence-based treatments; early detection triggering chemotherapy regime modification remains the best option for prevention. Early detection is challenging because of a lack of diagnostic tools with sufficient longitudinal temporal precision and convenience for patient/clinical adoption. To tackle this problem, we developed SenseCheQ; enabling self-administered autonomous sensory testing which can be used by patients at home. We present the instrumental engineering approach taken to address the challenge, including haptic self-calibration combined with skin thermal-clamping protocols, and demonstrate robustly reliable performance in the face of environmental and user-related variance in home settings. We present prospective case studies of people having chemotherapy treatment for cancer, conducting regular unsupervised quantitative sensory testing to monitor their nerve function at home. These proof-of-principle studies show SenseCheQ can detect sub-clinical changes in nerve function, matching patient reported outcomes and lab-based sensory testing. This highlights SenseCheQs promise as a scalable biomarker platform for neuropathy-detection and therapeutic development.

Type 2 diabetes and prediabetes affect hundreds of millions of people globally, yet the metabolic networks underlying disease development remain poorly understood. Using untargeted liquid chromatography-mass spectrometry (LC-MS/MS), we profiled a total of 15,470 (900 known) serum metabolite features across the human diabetes spectrum (the most comprehensive coverage reported to date). Weighted coexpression network analysis of samples from people with normal glucose tolerance, prediabetes, and type 2 diabetes, collected at baseline and 2 hours after an oral glucose tolerance test, revealed tightly coregulated modules strongly associated with glycemic dysregulation, insulin resistance, and islet dysfunction. Notably, short-chain organic acids, particularly crotonic acid, emerged as hubs of the diabetes-associated networks, accumulating progressively with disease severity. Reanalysis of extracellular vesicle proteomics from the same cohort showed that 16.5% of circulating proteins were crotonylated, with 47.6% correlated with crotonic acid and other hub metabolites, establishing a metabolome-crotonylome axis as a novel mechanism in diabetes development.

AO_SCPLOWBSTRACTC_SCPLOWSpatially resolved characterization of nanomaterial (NM) distribution within cellular ultrastructure is essential for understanding NM fate and activity in biological systems. Volume electron microscopy (vEM) is uniquely positioned to address this challenge, yet fully documented quantitative pipelines that simultaneously segment NMs and cellular structures remain scarce. Here, an end-to-end analytical pipeline is presented based on the example of serial block-face scanning electron microscopy (SBF-SEM) data of tumor spheroids containing nanoparticles (NPs). A hybrid segmentation strategy is adopted: a fine-tuned Cellpose-SAM model for cells and nuclei, and an empirical Bayes approach for AuNPs. The fine-tuned model outperforms both the pre-trained baseline and benchmark experiments in Amira, and shows good generalization to 2D EM datasets of varying sample types, suggesting potential as a general-purpose segmentation model for electron microscopy. Full 3D reconstruction of NP distributions reveals preferential clustering in the perinuclear region, with a median nucleus-to-NP distance of 2.57 {micro}m and NM uptake spanning several orders of magnitude across cells. Furthermore, morphological analysis of segmented cells and nuclei using 3D shape descriptors and local curvature metrics provides quantitative access to features inaccessible from single sections. Together, these results establish a reproducible, open framework for the joint quantitative analysis of NM distribution and cellular morphology in vEM data.

Disruptions within the microbiome-gut-bone axis are increasingly recognized as key contributors to impaired bone metabolism and leg disorders in broiler chickens. This study investigated the effects of a combined dietary additive containing Bacillus subtilis DSM 29784 and a phytogenic blend of garlic and essential oil components (BsP) on the modulation of microbial communities, intestinal integrity, mineral utilization, and bone-associated immune-osteogenic pathways. Five hundred and sixty-one-day-old male Ross 308 broilers were randomly assigned to a basal control diet or the same diet supplemented with BsP for 42 days, with eight replicates per treatment. Growth performance, cecal microbiome composition, jejunal tight junction expression, pro-inflammatory cytokines, ileal calcium-phosphate transporters, and femoral inflammatory and osteogenic gene expression were evaluated. The results demonstrated that BsP supplementation significantly improved body weight, weight gain, and feed conversion ratio while enhancing intestinal barrier function. Birds receiving BsP displayed upregulated expression of tight junction-related genes (CLDN-1, OCLD-1, TJP-1, MUC-2) and reduced jejunal inflammatory markers (TNF-, NF-{kappa}B). Improved mineral transport capacity was indicated by increased ileal CaSR and NaPi-IIb expression. Microbiome profiling revealed higher species richness (Chao1 and Shannon indices; P<0.05) and diversity (Bray-Curtis, PERMANOVA; P <0.001) on days 21, 35, and 42, with enrichment of beneficial taxa such as Clostridium butyricum, Enterococcus faecium, Lactobacillus salivarius, L. crispatus, and Bifidobacterium longum, accompanied by reduced Escherichia coli, and Enterococcus cecorum. Functional predictions suggested activation of serotonin-, melatonin-, and L-tryptophan-related pathways, indicating engagement of the microbiome-gut-brain axis. At the skeletal level, BsP reduced femoral expression of IL-6, IL-17, TNF-, and NLRP3 and enhanced BMP-2, SMAD-1, RUNX-2, and SPARC, aligning with improved mineral deposition. Network analysis revealed distinct inflammation-, bone-, and microbiota-dominant modules, highlighting the structured interactions linking microbial signals to osteoimmunological responses. Overall, BsP effectively modulated the microbiome-gut-bone axis, supporting intestinal homeostasis, mineral absorption, and bone formation. These findings underscore the potential of BsP as a functional feed additive to promote both intestinal and skeletal health in broilers.

Advances in multi-dimensional imaging method and probe developments have brought super-resolution fluorescence microscopy into a functional era. They capture additional single-molecule fluorescence information concurrently with spatial localization, enabling simultaneous identification of molecular species and interrogation of nanoscale environments with rich, high-dimensional imaging information. However, the adoption of multi-dimensional imaging has been hindered by fragmented analysis workflows, complex parameter tuning, and limited integration of advanced computational methods. Here, we introduce an agentic single-molecule multi-dimensional bioimaging AI, referred to as SIMBA, an AI-driven platform that unifies single-molecule localization, spectral processing and deep learning-based denoising within a single agentic and interactive framework. SIMBA incorporates large language model-based agents capable of interpreting user intent, orchestrating analysis pipelines, and dynamically selecting computational tools for automated data processing. We demonstrate that SIMBA enables supports standard single-molecule localization workflow, functional mapping of nanoscale environmental heterogeneity through single-molecule spectral analysis and denoising using developed supervised learning methods. By integrating extensible tool architectures with human language-guided workflows, SIMBA establishes a new paradigm for intelligent microscopy analysis, lowering barriers to multi-dimensional imaging adoption while enabling scalable, reproducible, and adaptive analysis of complex imaging datasets.

Spatial transcriptomics (ST) enables the study of cell-cell communication in native tissue context, but current methods for the ligand-receptor interaction (LRI) inference generally rely on static, distance-based assumptions. Here we present SpaFlow, a reaction-diffusion framework that models ligand diffusion, binding, dissociation, production and degradation to infer spatially resolved LRI activity and hotspots from ST data. Across paired 10x Visium and CosMx metastatic renal cell carcinoma datasets, SpaFlow outperformed existing methods in recovering spatially coherent LRIs, with inferred LRI activity showing stronger association with downstream signaling. In hepatocellular carcinoma after neoadjuvant immunotherapy, SpaFlow identified CXCL12-CXCR4 hotspots enriched at immune-rich tumor boundaries in responders. In aging mouse heart, SpaFlow resolved niche-specific pro-fibrotic and senescence-associated signaling, highlighting Postn-Itgav/Itgb5 as an additional pro-fibrotic axis and Angptl2-Pirb as a candidate mediator of inter-niche senescence-related communication. In human idiopathic pulmonary fibrosis lung, SpaFlow localized CXCL12-CXCR4 signaling between adventitial fibroblasts and CD4 T cells, CD8 T cells, and B cells in the fibrotic surrounding regions. Together, SpaFlow provides a physically informed framework for quantifying spatially constrained cell-cell communication and mechanistically interpreting signaling patterns in complex tissues.

Stimulus-responsive nanomedicines promise spatiotemporally controlled therapy, yet most systems rely on passive delivery and lack precise, externally programmable activation while maintaining clinical compatibility. Here we engineer sub-200 nm, perfluorocarbon (PFC)-core nanodroplets (NDs) that integrate efficient core drug loading, physiological stability, and acoustically programmable activation within a single nanoscale agent. These NDs are fabricated using microfluidic nanoassembly to achieve controlled size and composition, and are designed to encapsulate fluorinated payloads directly within the liquid core. Upon exposure to a sequential dual-frequency ultrasound (US) paradigm, the NDs undergo acoustic droplet vaporization followed by low-frequency cavitation, enabling spatially confined mechanical disruption and on-demand payload release within clinically relevant acoustic limits. These properties are engineered to overcome physicochemical barriers in solid tumors, including dense extracellular matrix and restricted drug penetration. This approach achieves enhanced payload release and induces potent mechanochemical cytotoxicity in vitro. In vivo, NDs exhibit prolonged circulation and tumor accumulation, while US activation drives substantial tissue fractionation, control drug release, and increases subsequent nanoparticle uptake. When applied to a solid tumor model, this combined mechanochemical strategy improves tumor control and significantly extends survival compared to either modality alone. These acoustically activatable NDs provide a versatile system for stimulus-responsive, site-targeted drug delivery and mechanical tumor disruption, with strong potential for clinical translation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/719550v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@5d9753org.highwire.dtl.DTLVardef@7a07e1org.highwire.dtl.DTLVardef@19b69f3org.highwire.dtl.DTLVardef@48f332_HPS_FORMAT_FIGEXP M_FIG C_FIG

Insects body barriers rely on specialized extracellular matrices that protect against harmful environmental influences. The outer barrier is the cuticle, which is composed of chitin, cuticle proteins and lipids. The peritrophic matrix (PM) serves as an inner barrier lining the midgut epithelium. It is composed of chitin fibers that are organized by PM proteins. While cuticle and PM proteins have received considerable attention in the past, supramolecular organization and physicochemical properties of the chitin component - particularly of the PM - remain poorly understood. Here, we combine synchrotron-based X-ray diffraction data from the PMs of lepidopteran and coleopteran insects with RNA interference (RNAi), mass spectrometric and histochemical analyses of the PM from Tribolium castaneum to determine chitins allomorphic state and degree of acetylation. The chitin of the PM exhibits signatures characteristic of dihydrate {beta}-chitin along the entire midgut. In contrast, the cuticle is made of tightly packed -chitin nanofibrils. Mass spectrometry revealed that the PMs chitin is highly acetylated (>95%). RNAi silencing of gut-specific genes encoding chitin deacetylasesTcCDA6-9 further increases the degree of acetylation. Histochemical analyses staining chitin with different degrees of acetylation confirm the predominance of highly acetylated chitin in the PM. Notably, the larval cuticle has a layered organization with deacetylated chitin present in exo- and highly acetylated chitin in endocuticles. Depletion of both TcCDA1 or TcCDA2 impairs chitin deacetylation, which indicates that both proteins cooperate in their activity in the integument. These results establish fundamental principles of polysaccharide-based extracellular matrices, with broad implications for insect biology.

Monoterpene indole alkaloids (MIAs) are a major class of plant natural products with important pharmaceutical activities, yet the biosynthetic pathway to their universal precursor, strictosidine, has been fully elucidated in only Catharanthus roseus. In kratom (Mitragyna speciosa), only the first and last steps of strictosidine biosynthesis were previously known. Here, we applied multiplex pathway engineering in yeast to accelerate the discovery, reconstruction, and optimization of the kratom strictosidine pathway. Iterative multiplex integration and screening identified 13 functional kratom genes and enabled rapid validation of functional pathway modules, thereby completing the kratom strictosidine pathway from geranyl pyrophosphate and tryptophan. We also identified a vacuolar secologanin transporter, MsNPF2.6, which increased strictosidine production by 62% in yeast. Pathway optimization through the incorporation of nepetalactol-producing enzymes from other plants further supported strictosidine production in yeast from fed geraniol and tryptophan. These results establish the strictosidine pathway in kratom and highlight multiplex engineering as a powerful platform for rapid plant pathway discovery and optimization.

Breast cancer is globally the most common cancer among women. Although the five-year survival rate exceeds 80% for patients with localized disease, it drops to approximately 30% once metastasis occurs, underscoring the urgent need to define mechanisms that drive metastatic progression. Breast is a highly innervated organ and most of its innervation is sensory. However, whether sensory neurons can directly impact breast cancer cells remains an understudied topic. Here, we show that mammary tumors have increased CGRP sensory innervation. Using our novel microfluidic Device for Cancer cell-Axon Interaction Testing (DACIT), we demonstrate that the presence of axons strongly inhibits ECM-degrading ability of cancer cells. The sensory neuron secretome suppresses assembly and function of invadopodia, which are cancer cell protrusions controlling ECM degradation, and essential for intravasation and metastasis. We identify calcitonin gene-related peptide (CGRP) as the key component of the sensory neuron secretome responsible for the inhibitory effect. CGRP signaling occurs through the CRLR/RAMP1 receptor complex expressed by breast cancer cells, inducing a rapid increase in intracellular cAMP levels in breast cancer cells, followed by an increase in RhoC activity and suppression of invadopodia and ECM degradation. Loss of RAMP1 function enhances 3D spheroid invasion, cancer cell motility in vivo and significantly increases the number and the size of lung metastatic foci. Consistently, in silico analyses of both mouse and human RNASeq data point to a link between increasingly invasive subtypes with a gradual decrease in expression of RAMP1 and CRLR. To validate in silico findings, we compare RAMP1 expression in the patient breast tumors with adjacent normal tissues, confirming the invasive breast tumors have reduced levels of RAMP1. Together, our findings identify a protective role for the paracrine CGRP signaling in limiting breast cancer invasion and metastasis. We also demonstrate how cancer cells circumvent CGRP inhibition by suppressing RAMP1 expression, highlighting CGRP-RAMP1-cAMP axis as a potential therapeutic target in breast cancer.

Childhood obesity remains a pressing global health challenge, yet the impact of dynamic adiposity changes during active developmental window retains poorly understood. Leveraging longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study (N=8519 at baseline; N=1873 at 4-year follow-up), our study reveals distinct neurodevelopmental implications of central fat dynamics during adolescence. At baseline, central fat indices (body roundness index, BRI / waist-to-height ratio, WHtR) outperformed BMI in predicting cognitive deficits, showing robust associations with impaired inhibitory control and episodic memory. The prediction effect was partially mediated by cortical changes in prefrontal and temporal regions. Longitudinally, the rate of fat accumulation ({Delta}) emerged as a critical predictor: faster adiposity accrual predicted attenuated cortical thinning (i.e., slower development) in parietal lobes and poorer executive function at follow-up, while baseline adiposity showed no significant effects on the follow-up brain morphology or cognitive development. Notably, subgroup analyses uncovered that obese adolescents with central fat reduction exhibited accelerated cortical thinning in posterior cingulate (change difference p=0.006-0.029) alongside rapid improvement in inhibitory control (Flanker slope difference p<0.05), whereas those with persistent adiposity showed delayed thinning in the postcentral gyrus. The study reveals that central fat (BRI/WHtR) is closely linked to neurocognitive risks, and longitudinal fat accumulation?rather than baseline adiposity?drives cortical alteration. Notably, fat reduction activated adaptive neural change in obese adolescents, underscoring the importance of weigh regulation during neurodevelopment.

Biomaterial implantation can trigger a foreign body response (FBR) that impedes tissue-implant integration. To investigate how implant porosity influences this response, we compared the immune response to subcutaneous implants of microporous annealed particle (MAP) scaffolds and nanoporous hydrogels using mass cytometry, single-cell RNA sequencing, and multiplex cytokine assays. MAP scaffolds promoted vascularization and tissue integration, marked by increased endothelial and regulatory T cells, and reduced proinflammatory immune cells and cytokines. In contrast, nanoporous hydrogels demonstrated enrichment of basophils, natural killer cells, and macrophage populations associated with fibrosis. Transcriptomic and proteomic analyses revealed that MAP scaffolds suppressed activation of the complement-fibroblast-macrophage signaling loop, particularly the C5a signaling crosstalk pathway. This was confirmed using C5-deficient mice, where complement-driven cytokine production was significantly reduced only in nanoporous implants. These findings demonstrate that scaffold porosity modulates immune and complement responses, identifying a key mechanism by which MAP scaffolds reduce FBR and improve biomaterial integration.

Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that mediate intercellular communication through the transfer of bioactive molecules. Their growing relevance in translational applications demands downstream purification workflows that are selective, scalable, and compatible with robust impurity control. Conventional EV isolation methods primarily rely on physicochemical properties such as size, density, or charge and therefore co-enrich overlapping EV fractions together with non-vesicular impurities. Here, we establish a Nanofitin(R)-based affinity chromatography workflow for selective enrichment of a CD81-positive EV fraction under EV-compatible elution conditions. Nanofitin(R) candidate NF06 was identified by ribosome display against the large extracellular loop of CD81 and combined nanomolar affinity with favorable release behavior while retaining binding after repeated regeneration cycles. Static screening with recombinant CD81 and HEK293-derived EVs identified 1 M arginine at pH 10 as the most suitable elution condition. Dynamic chromatography on a 1 mL column using tangential flow filtration-concentrated HEK293 conditioned medium achieved 66.9% overall recovery with an elution step yield of 57.7%. In parallel, dsDNA, host cell protein, and total protein were reduced by 2 to 3 log relative to conditioned medium. Nano flow cytometry showed enrichment of the CD81-positive EV fraction from 40% in conditioned medium to more than 90% in the eluates, together with a smaller and narrower particle size distribution. These results demonstrate that Nanofitin(R)-based affinity chromatography provides a practical route toward marker-defined EV enrichment that combines selective capture, EV-compatible release, and substantial impurity clearance in a chromatography-compatible process format.

Low-pH and hypoxic conditions commonly develop in oral surgical sites and mucosal wounds, impairing cell viability and delaying healing. This study presents a simple, cell-free, and clinically translatable hydrogel patch incorporating microencapsulated calcium peroxide granules to locally deliver oxygen and buffer acidity. Calcium peroxide particles in the range of 50 to 150 micrometers, were coated with a thin PLGA shell to moderate reactivity and embedded into a GelMA-AlgMA composite membrane. In acidic artificial saliva, pH 5.2, patches containing 0.25% calcium peroxide released oxygen steadily for up to 8 hours and restored pH to physiological levels within 90 minutes. When applied to a DPSC-seeded collagen wound model exposed to lactic-acid challenge, the patches significantly improved metabolic activity and cell viability compared to acidified controls, without signs of cytotoxicity. These findings indicate that calcium peroxide-integrated hydrogels offer a low-cost, practical approach to counteract hypoxia and acidosis in oral wound environments, supporting early regenerative processes and providing a translationally viable platform for future preclinical development.