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Nonhalogenated solvents are promising for scalable fabrication of organic solar cells (OSCs). However, the intrinsically low solubility of high-molecular-weight donor polymers in nonhalogenated solvents, particularly those with tightly packed, highly crystalline backbones such as the pinnacle of donor materials (D18), disrupts multiscale morphology evolution and severely limits device performance. Here, without compromising the polymer's molecular weight or its intrinsic propensity for ordered packing, we establish a copolymerized "plasticizer" strategy that enhances the solvation interaction between a nonhalogenated solvent (toluene) and an appended plasticizing comonomer, thereby improving the processability. By integrating a plasticizing unit (bis(2-(2-methoxyethoxy)ethyl) thieno[3,2-b]thiophene-3,6-dicarboxylate) into the D18 backbone, the resulting D18-O exhibits markedly enhanced solubility through dipolar interactions with toluene. These interactions suppress excessive pre-aggregation, slow down crystallization kinetics of the donor, and ultimately guide the formation of well-defined nanocrystals and a hierarchy of optimized morphologies during nonhalogenated processing. This approach enables both OSCs and modules processed from toluene to achieve record power conversion efficiencies of 20.78% (certified 20.40%) and 17.83% (certified 17.29%), respectively, along with exceptional stability.

Glucan, a potent immunomodulator with well-established pharmacological activities, can be efficiently produced through the microbial transformation of low-value substrates. Here, the psychrotolerant Antarctic fungus Penicillium chrysogenum MS-02 was cultivated on potato starch. A homogeneous glucan with molecular weight 1.293 × 104 Da (termed PPS2-A) was then isolated from the fermentation broth using gel-filtration and ion-exchange chromatography. Structural characterization revealed that PPS2-A featured a linear backbone composed of (1 → 4)-linked α-d-glucopyranosyl (Glcp) residues, with α-(1 → 4)-linked Glcp side chains at C-6 positions, and lacked a triple-helical conformation. Studies on primary mouse immune cells demonstrated that PPS2-A significantly enhanced splenic lymphocyte proliferation, potentiated peritoneal macrophage phagocytic capacity, and upregulated NO secretion and acid phosphatase activity. Moreover, PPS2-A enhanced proliferation and phagocytosis, suppressed apoptosis, and promoted M1 polarization (elevated NO, cytokines TNF-α/IL-1β/IL-6, and CD86+). Collectively, these findings demonstrate the immunostimulatory potential of PPS2-A as a pro-inflammatory macrophage activator, and support its development as a candidate natural immunomodulator derived from the Antarctic fungus.

Spinal diseases are common and widely impactful health issues in modern society. With the advancement of computer vision and medical image analysis, image-based automatic recognition and classification of spinal diseases have become research hotspots. However, existing methods often show limited performance in recognizing spinal diseases from complex or low-quality X-ray images. Their performance is easily affected by noise and exposure variations, leading to the extraction of pseudo-features unrelated to the disease. In addition, discrepancies among data sources and imaging conditions result in poor model generalization, making it difficult to adapt to cross-domain variations in clinical applications. To address these challenges, this study proposes an Information Bottleneck-based Optimal Transport Network (IBOTSpine) for automated diagnosis of spinal diseases. The IBOTSpine model introduces an information bottleneck-constrained feature extraction module that effectively captures disease-relevant structural information while suppressing irrelevant noise. Moreover, by incorporating an optimal transport mechanism, the model learns domain-invariant features, thereby reducing the distribution discrepancy between training and testing data and enhancing robustness and generalization across multi-source datasets. Specifically, the model employs a Swin Transformer as the backbone network and jointly optimizes the information bottleneck and optimal transport losses to achieve synergistic improvement in feature extraction, domain adaptation, and classification performance. Experimental results on real spinal X-ray dataset demonstrate that the proposed model outperforms existing methods in classification accuracy, generalization capability, and feature discriminability, validating its effectiveness and application potential in intelligent spinal image diagnosis.

Mpox lesions can resemble other dermatological conditions, motivating image-based screening, yet published studies remain difficult to compare owing to differences in dataset construction, augmentation policy, and evaluation design. This study provides a leakage-aware benchmark for binary mpox classification using a unified dataset assembled from MSLD v1.0 and v2.0. Seven pretrained backbones and a weighted ensemble were compared under group-stratified five-fold cross-validation with original-only test evaluation, validation-based threshold selection, and temperature scaling. The weighted ensemble achieved mean accuracy 0.8729, F1-score 0.8334, and AUC 0.9388; ConvNeXt-Tiny was the strongest single model (F1 0.8159, AUC 0.9284). These grouped original-only results are intentionally conservative relative to augmentation-heavy or single-split designs and should be interpreted as deflated but more trustworthy reference values. Post hoc calibration analysis, content-level near-duplicate auditing, and a test-time augmentation ablation are provided to substantiate the methodological claims. The contribution is methodological: a transparent benchmark emphasizing reproducible dataset curation, grouped evaluation, and calibrated comparison, while highlighting the limitations of current public skin-image data. Accordingly, these results should be interpreted as a reproducible reference benchmark rather than a clinically validated diagnostic tool, and external clinical validation remains necessary before deployment.

Aspergillus oryzae NSAR1 is a versatile and commonly used heterologous expression host. Typically, this host is used to express exogenous biosynthetic genes for secondary metabolites (SMs). However, the metabolite profile of A. oryzae itself is not clearly understood. In our course to enrich minor metabolites from heterologous expression using in situ macroporous resins, two metabolites were found to be significantly enhanced in A. oryzae itself. These metabolites were isolated, purified, and identified as 2-pyridones, including leporin B (1), and protoleporin A (2), as the major compounds, along with a minor of leporin C (3). The structural elucidation was performed by detailed NMR and HRMS analysis, and by comparison with the literature. This was the first observation of leporin-type 2-pyridones from A. oryzae, among which compound 2 was a new compound. Leporin B was found to display inhibition against Phytophthora sojae. A putative biosynthetic gene cluster (BGC, Aolep) harboring a backbone PKS-NRPS encoding gene (AolepA) was identified for these metabolites through genome mining. Subsequently, AolepA was knocked out using homologous recombination via conventional gene knockout (KO) and CRISPR-Cas9 mediated gene-editing system. Successful disruption of AolepA was achieved using both strategies leading to abolish the production of 2-pyridones completely. The KO mutants showed a similar phenotype as compared to the parent strain, regarding the growth and sporulation. The utility of these mutants as a new chassis was demonstrated by heterologous expression of a 1,3,6,8-tetrahydroxynaphthalene synthase. Hence, a genetic dereplication version of A. oryzae (NSAR1∆L) was generated, featuring a reduced background in endogenous SM production, which should facilitate the study of exogenous genes in SM biosynthesis by alleviating undesired metabolic burden, simplifying the detection and purification of heterologous compounds.

Death receptor 6 (DR6), an orphan member of the tumor necrosis factor receptor superfamily, has been implicated in inflammation, autoimmunity, neurodegeneration, and cancer. Similar to other family members, its intracellular region, including caspase recruitment domain (CARD) and death domain (DD), mediates complex signaling networks by recruiting adaptor and downstream effectors. While studies have demonstrated that amyloid precursor protein (APP) binds to the extracellular domain of DR6, the conformational changes in its intracellular domains that initiate signaling remain unclear. In this study, we report the nearly complete backbone and sidechain resonance assignments of DR6-CARD, providing a foundation for studying the structural basis of DR6-mediated signaling pathways.

Adaptive immune receptors (AIRs), including antibodies and T-cell receptors (TCRs), mediate antigen recognition and represent a major class of therapeutic biomolecules. Their unique architecture, combining conserved framework with highly diverse complementarity-determining regions (CDRs), poses challenges for structure prediction and design. Recent advances in deep learning have transformed these fields, yet AIR-antigen interactions remain difficult targets due to limited structural data, weak co-evolutionary signals, and conformational heterogeneity. Herein, we review recent progress in structure-based deep learning approaches for AIRs, including AIR-specific language models, structure prediction, and epitope-conditioned design. We discuss commonly used datasets, evaluation metrics, and sources of bias that complicate cross-study comparisons and highlight the need for improved benchmarks. We also review emerging generative design strategies such as inverse folding, diffusion-based backbone generation, sequence-space diffusion, and sequence-structure co-design, and outline key challenges, including accurate modeling of flexible CDR loops, reliable ranking of AIR-antigen complexes, and scalable epitope-specific AIR design.

Microbial metabolic engineering increasingly depends on identifying robust non-conventional yeast chassis with favorable metabolic traits. Although Saccharomyces cerevisiae remains the main model for isoprenoid engineering, alternative yeasts may provide superior native precursor availability. Here, we report the first comparative metabolomic characterization of Saccharomycopsis fibuligera, focusing on the mevalonate and terpenoid backbone biosynthesis pathways. LC-MS profiling revealed elevated levels of acetyl-CoA, HMG-CoA, and MVA in S. fibuligera, suggesting strong native flux through the MVA pathway. The universal isoprenoid precursors IPP and DMAPP accumulated at substantially higher levels than in S. cerevisiae, together with enrichment of FPP and ergosterol abundance, indicating efficient channeling toward sterol biosynthesis. Conversely, upper glycolysis metabolites were reduced, while TCA cycle intermediates were enriched, supporting the proposed Crabtree-negative phenotype of S. fibuligera. Amino acid profiling also indicated enhanced nitrogen storage capacity. These results position S. fibuligera as a metabolically favorable platform with high intrinsic MVA pathway activity and precursor availability for terpenoid production, highlighting its strong potential as an emerging microbial chassis for next‑generation terpenoid bioproduction.

Closed-loop chemical recycling of polymers with all-carbon backbones is an important component of plastic circularity but often requires either high temperatures (>400 °C) or noncommercial "designer" polymers. Although the feasibility of depolymerizing commercial poly(methyl methacrylate) at ≤150 °C was recently demonstrated, a large excess of (chlorinated) solvents was deemed essential to act as a radical source. Here, we report a novel and generalizable methodology that uses diverse commercial organic and inorganic photocatalysts to decouple catalytic reactivity from the solvent. This solvent-independent approach also allows for precise control over the radical flux in nonchlorinated media, achieving near-quantitative yields (>95%) even for challenging polymers like poly(benzyl methacrylate) and poly(2,2,2-trifluoroethyl methacrylate) that were previously difficult to process and depolymerize. Notably, our method is compatible with phase-changing solvents (liquid during reaction, solid at room temperature), which resolves the separation-temperature trade-off and allows straightforward, quantitative collection of regenerated monomers from a solid medium.

Current workflows for studying hydrocephalus in rodent models rely on manual segmentation or qualitative assessment of ventricular size on small animal magnetic resonance imaging, which are both inefficient and prone to variability. Atlas-based methods enable more streamlined segmentation, but their analysis is limited to morphologically normal samples. This study aimed to develop and internally validate a deep learning model that performs automated segmentation of lateral ventricles in rodent brain MRIs, allowing for 3D ventricle reconstruction, morphological analysis, and ventriculomegaly detection. Four U-Net++ neural networks, each with different encoder backbones, were trained using 343 rodent brain MRIs (298 rats, 45 mice), each with manually segmented lateral ventricles serving as the ground truth. Model performance was evaluated using the Dice coefficient and 95th percentile Hausdorff distance (HD95). The most optimal model was evaluated further for its ability to quantify ventricle volume, convexity, surface area, and symmetry. The U-Net++ model with an EfficientNet-B1 encoder achieved high accuracy (Dice: 0.819 ± 0.121; HD95: 2.493 ± 3.984). Further assessment of its morphological predictions found strong correlations with manual measurements of ventricular morphology, with Pearson and interclass correlation coefficients exceeding 0.95 across all metrics. The full validated pipeline was packaged into a publicly available application, hosted at https://ava-tar.org. This study introduces a deep learning tool for automated segmentation and morphological analysis of lateral ventricles in rodent MRIs. The tool's efficiency and accuracy in quantifying ventricle morphology offers significant utility in preclinical hydrocephalus research with potential future application in the clinical setting.

Silver nanoparticles (AgNPs) are widely employed in antimicrobial materials owing to their broad-spectrum and long-lasting antibacterial activity. Herein, a facile and environmentally friendly in situ strategy is proposed for the fabrication of antibacterial regenerated cellulose films (RCFs) via the in situ synthesis of finely dispersed AgNPs. Cellulose was dissolved in an aqueous N-methylmorpholine-N-oxide solvent, which activated the abundant hydroxyl functionalities along the cellulose backbones, enabling the reduction of Ag+ ions to Ag and the simultaneous immobilization of AgNPs within the regenerated cellulose matrix without additional reducing or stabilizing agents. FT-IR spectroscopy confirmed the involvement of oxygen-containing functional groups in AgNPs stabilization, while XRD analysis revealed the formation of crystalline AgNPs with crystallite sizes ranging from 4 to 13 nm. SEM imaging and EDX elemental mapping further demonstrated the homogeneous dispersion of AgNPs throughout the cellulose network. Owing to the uniform distribution and nanoscale dimensions of AgNPs, the AgNPs/RCFs exhibited pronounced antimicrobial activity against both Gram-positive (S. aureus) and Gram-negative (E. coli) bacteria, as well as fungus (C. albicans). This work provides a sustainable and environmentally benign route for the development of high-performance antimicrobial cellulose-based films with potential applications in biomedical, packaging, and water treatment fields.

Osteoporosis management remains challenging, partly due to the poor bioavailability of drugs in bone and the systemic side effects of current treatments. To address this, we engineered a targeted nanomedicine therapy using a DNA aptamer that specifically binds RANKL, a pivotal regulator of bone resorption. The aptamer is conjugated to PEGylated mesoporous silica nanoparticles (MSNs) to create a novel agent, aptRANKL@MSN. The nanoparticle platform enhances the aptamer's stability and may promote its accumulation in bone tissue, likely through a combination of passive targeting and the intrinsic affinity of the aptamer's phosphate backbone for bone mineral. In an ovariectomized mouse model of osteoporosis, aptRANKL@MSN treatment effectively reversed bone loss, restoring bone mass, microarchitecture, and mechanical strength to levels comparable to healthy controls. The therapy demonstrated a dual action, suppressing bone resorption while also enhancing bone formation as evidenced by increased mineral apposition rate and serum P1NP levels, thereby rebalancing bone homeostasis. Crucially, this bone-accumulating approach achieved superior efficacy over free aptamer and the conventional drug alendronate, while showing no significant toxicity over the 4-week treatment period. Our findings present aptRANKL@MSN as a precise and potent therapeutic strategy with strong potential for clinical translation in osteoporosis.

Posterior or transforaminal lumbar interbody fusion (PLIF/TLIF) has become the standard procedure for treating degenerative lumbar diseases. With the increasing number of surgeries, adjacent segment disease (ASD) is becoming widely known as a postoperative complication. However, the association between lumbosacral sagittal alignment and ASD following L4-5 isolated fusion surgery has not been fully elucidated. The aim of this study was to identify the preoperative radiological risk factors for L3-4 ASD and L5-S1 ASD independently after isolated L4-5 PLIF/TLIF. The authors retrospectively reviewed the data of 151 patients with degenerative lumbar diseases who underwent isolated L4-5 PLIF/TLIF at their institution between April 2013 and August 2022. L3-4 ASD and L5-S1 ASD were evaluated separately, and these groups were compared with the non-ASD group. Radiological ASD was defined as disc height (DH) loss (> 3 mm), posterior opening (> 5°) on flexion, or progression of slippage (> 3 mm) as observed on plane radiographs. Symptomatic ASD was defined as the presence of symptoms attributable to the adjacent segment that required revision surgery within 2 years. Preoperative lumbosacral parameters, including slippage at L4-5 (Meyerding grade), pelvic tilt, sacral slope, pelvic incidence (PI), lumbar lordosis (LL), PI-LL, L1 sagittal vertical axis (SVA), and L4 SVA, were measured using standing radiographs. Intraoperative distraction at the L4-5 DH, preoperative disc degeneration (Pfirrman grade), vacuum phenomenon, foraminal stenosis, and additional decompression at adjacent segments were also evaluated. Of 151 unique patients, 31 (20.5%) had ASD, with 20 (13.2%) included in the L3-4 ASD group and 13 (8.6%) included in the L5-S1 ASD group (2 patients were included in both groups). Multivariate analysis revealed that additional L3-4 decompression and distraction at L4-5 DH were significantly associated with L3-4 ASD, whereas L1 SVA > L4 SVA (L1 plumb line anterior to the L4 plumb line) was associated with L5-S1 ASD. The risk of L5-S1 ASD increased by a factor of 4.13 (p = 0.004) in patients with sagittal imbalance, as indicated by L1 SVA > L4 SVA. These findings suggest distinct characteristics between L3-4 ASD and L5-S1 ASD. L3-4 ASD was not associated with lumbosacral sagittal imbalance. By contrast, an anterior shift of the lumbar loading axis, as indicated by L1 SVA > L4 SVA, was associated with the development of L5-S1 ASD. Preoperative L1 SVA > L4 SVA might serve as a convenient predictive parameter for L5-S1 ASD after isolated L4-5 fusion surgery.

Surgical management of nonambulatory patients with beak-type thoracic ossification of the posterior longitudinal ligament (T-OPLL) remains challenging, and the optimal extent of decompression is unexplored. This study aimed to evaluate neurological outcomes and perioperative characteristics of a selective posterior decompression with fusion (PDF)-first strategy, with circumferential decompression (CD) performed only when indirect decompression was deemed insufficient based on intraoperative assessment. Nonambulatory patients with beak-type T-OPLL who underwent thoracic spine surgery between September 2012 and July 2022 were retrospectively reviewed. All patients initially underwent PDF. Conversion to CD via a posterior approach was performed intraoperatively when persistent ventral spinal cord compression was identified based on dural sac refilling, spinal cord pulsation, and findings on intraoperative ultrasonography and neurophysiological monitoring. Neurological outcomes were assessed using the modified Japanese Orthopaedic Association (mJOA) score, recovery rate, ambulation status, and health-related quality of life (EQ-5D-5L score). Perioperative parameters and complications were recorded. A total of 31 patients met the inclusion criteria, including 19 treated with PDF alone and 12 who required additional CD. At final follow-up, significant neurological improvement was observed in the overall cohort, with 93.6% of patients regaining ambulatory ability. Both groups demonstrated significant postoperative improvements in mJOA and EQ-5D-5L scores compared with baseline. Patients who underwent CD had significantly longer operative times and greater estimated blood loss. The incidence of cerebrospinal fluid leakage was high but was successfully managed without permanent neurological sequelae. In nonambulatory patients with beak-type T-OPLL, a selective PDF-first surgical strategy resulted in favorable neurological recovery in the majority of patients. CD served as an effective adjunct when intraoperative findings indicated inadequate indirect decompression. These findings support an individualized, intraoperatively guided approach rather than the routine use of CD in this high-risk population.

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To evaluate the efficacy of circumferential surgery, involving combined anterior and posterior approaches, in the management of multisegmental cervical pyogenic spondylitis (CPS). A retrospective analysis was conducted on 12 patients with multisegmental CPS who underwent circumferential surgical intervention between January 2015 and November 2023. The study evaluated medical records, spinal alignment correction, postoperative complications, and neurological functional recovery. In total, 12 patients (8 men and 4 women; mean age: 57.1 years) met the inclusion criteria. Identified risk factors included diabetes mellitus in four patients, a history of substance abuse in two patients, and long-term immunosuppressive therapy following organ transplantation in one patient. Preoperatively, nine patients presented with spinal cord or nerve root compression. All patients underwent circumferential surgery with anterior column reconstruction using autologous bone grafts; titanium alloy plates were additionally used in two cases. Posterior stabilization was achieved using pedicle screws or lateral mass screws. The mean number of corpectomies performed was 3.7 (range, 3-5); the mean number of fused levels was 4.8 (range, 4-7). The mean follow-up duration was 19.4 (range, 6-38) months. Cervical alignment improved significantly, with the mean C2-7 Cobb angle changing from - 5° preoperatively to 3° postoperatively. Neurological function significantly improved in all patients (P = 0.023), and successful bone fusion was achieved in 11 patients (91.7%) at the final follow-up. Pathogens were identified in seven cases, including Staphylococcus aureus Staphylococcus epidermidis (n = 2), Klebsiella pneumoniae (n = 1), and Escherichia coli (n = 1). All patients received intravenous antibiotic therapy for 4-6 weeks postoperatively, followed by oral antibiotic treatment for an additional 6-8 weeks. No intraoperative complications were reported. Postoperatively, one patient developed pneumonia with respiratory failure, and another experienced posterior cervical wound infection. Circumferential surgical intervention combined with appropriate antibiotic therapy appears to be an effective treatment strategy for achieving satisfactory outcomes in patients with multisegmental CPS.

Preoperative risk-stratification tools, including frailty, nutritional, and surgical risk metrics, are used to predict complications after spine surgery. The relative performance of these tools across complication types and surgical subgroups is not well characterized. This study aimed to compare the predictive performance of 5 risk metrics, American College of Surgeons Surgical Risk Calculator (ACS SRC), serum albumin, Risk Analysis Index (RAI), modified 5-item frailty index (mFI-5), and Geriatric Nutritional Risk Index (GNRI), for perioperative complications. The authors analyzed 362,145 adult spine surgery patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) from 2017 to 2022. Adjusted odds ratios were estimated via multivariable logistic regression, controlling for age, sex, urgency, and procedure type (defined by Current Procedural Terminology [CPT] codes). Subgroup analyses were stratified by ICD-10 diagnosis category, including degenerative disease, tumor, trauma, infection, and spinal deformity. Discrimination for predicting complications was assessed using C-statistics and DeLong's test. Across all endpoints, ACS SRC had the best predictive accuracy: mortality C-statistic (95% CI) 0.908 (0.900-0.916), Clavien-Dindo grade IV (CD-IV) 0.823 (0.816-0.830), and major complications 0.749 (0.745-0.752). Serum albumin, despite being a single laboratory value, ranked second with mortality C-statistic (95% CI) 0.820 (0.807-0.833), CD-IV 0.734, and major complications 0.682 and showed strong discrimination for infectious complications (e.g., sepsis, septic shock, surgical site infection, and urinary tract infection), as well as for hospital length of stay and nonhome discharge. Compared to frailty-based metrics, albumin showed significantly better predictive value (p < 0.001 for pairwise comparisons) and maintained its advantages across all subgroups, including high-risk groups such as infection, trauma, and tumor cases. RAI provided moderate mortality prediction (C-statistic 0.807) and was most effective for predicting cardiovascular events, while both GNRI (0.753) and mFI-5 (0.647) were less consistent and demonstrated weaker associations with adverse outcomes. Multivariable regression confirmed that lower preoperative albumin and higher ACS SRC predictions were robust, independent predictors of increased risk for major complications, CD-IV events, and mortality. These performance patterns remained stable across surgical indications and in subgroup analyses. ACS SRC remains among the comprehensive tools for risk stratification in spine surgery. Serum albumin offers strong, consistent predictive value, especially for infectious, respiratory, and life-threatening complications, and may be a valuable alternative when calculator inputs are incomplete.

The health care industry is witnessing a rapid proliferation of medical devices. Health care organizations need effective tools to identify devices that best align with their needs, and ensure seamless integration into clinical processes. Existing conceptualizations of expert knowledge remain fragmented, and no comprehensive decision support systems exist to assist stakeholders in evaluating and introducing new medical devices. Ontology-based approaches offer a promising avenue to formalize such complex, multidisciplinary knowledge. This study aims to develop and validate an ontology designed as the backbone of a decision support system to facilitate the informed adoption of medical devices in health care organizations. The ontology was developed using a 5-phase methodology: (1) Elicitation of knowledge through a systematic literature review, a review of existing conceptualizations, and expert interviews; (2) Conceptualization of a preliminary conceptual map; (3) Co-design of a refined map through focus groups with experts; (4) Development of the ontology using the Prot&#xe9;g&#xe9; ontology editor; and (5) Validation of the ontology through interviews with experts. Forty experts from 13 companies across 3 European countries participated, ensuring multidisciplinary coverage. The resulting ontology provides a modular and comprehensive conceptualization of medical devices that balances granularity, conciseness, and practical relevance. It explicitly models key dimensions required for informed adoption decisions, including medical conditions addressed by the device, health services enabled, roles and activities of health care professionals, manufacturer-related information, medical device applications, and structured evidence derived from Health Technology Assessment reports. The ontology's instantiability and practical applicability were validated by populating it with data from 4 Health Technology Assessment reports and by expert assessment, confirming its ability to address stakeholders' core decision-making needs. This study presents a validated ontology to support the informed adoption of medical devices in health care organizations. It addresses a literature gap by providing a comprehensive, structured conceptualization of medical devices that meets stakeholders' key information needs. By formalizing complex expert knowledge, the ontology lays a foundation for future research and the practical development of decision support systems that enable transparent, effective, and efficient medical device adoption.

During chronic liver injury, hepatocytes promote liver fibrosis by interacting with hepatic stellate cells (HSCs). However, the key intracellular factors that regulate intercellular communication in hepatocytes remain poorly understood. Although cluster of differentiation 146 (CD146) is predominantly recognized as an endothelial cell marker, our study found that CD146 is substantially upregulated in hepatocytes under fibrotic stress and may play an independent role in transcellular signaling. This study aimed to elucidate the functions and underlying mechanisms of hepatocyte CD146 in liver fibrosis. We evaluated CD146 expression in liver tissues and serum soluble CD146 (sCD146) levels in patients with liver fibrosis and mouse models. Hepatocyte-specific CD146-overexpressing mice (AAV8-CD146) were generated and fed either a normal chow diet (NCD) or a high-fat diet (HFD); hepatocyte-specific CD146 knockout mice (CD146Alb-Cre) were subjected to carbon tetrachloride (CCl&#x2084;)-induced fibrosis. Comprehensive molecular, biochemical, and histological analyses were performed to systematically assess the role of CD146 in the initiation and progression of liver fibrosis. A co-culture system of hepatocytes and HSCs was also established to investigate the paracrine regulatory effects of CD146 on HSCs. The levels of sCD146 were positively correlated with the progression and severity of chronic liver disease. A diagnostic model incorporating sCD146 and other serological markers showed improved diagnostic performance for decompensated cirrhosis. Compared with healthy controls, hepatocyte CD146 expression was markedly upregulated in liver tissues from patients with cirrhosis and fibrotic mice. Under HFD conditions, hepatocyte-specific CD146 overexpression exacerbated hepatic inflammation and fibrosis in mice, whereas hepatocyte-specific CD146 deletion significantly attenuated CCl&#x2084;-induced liver fibrosis. Transforming growth factor-&#x3b2;1 (TGF-&#x3b2;1) induced CD146 upregulation in hepatocytes and increased the release of sCD146. Released sCD146 bound to integrin &#x3b1;v&#x3b2;1 on the surface of HSCs, activated the p38 mitogen-activated protein kinase (p38 MAPK) pathway, and promoted HSC activation and type I collagen production. These findings identify hepatocyte-derived CD146/sCD146 as a TGF-&#x3b2;1-inducible mediator of hepatocyte-HSC communication that promotes liver fibrosis through the CD146/sCD146-integrin &#x3b1;v&#x3b2;1-p38 MAPK signaling axis. They also support serum sCD146 as a potential non-invasive biomarker for advanced chronic liver disease.