Amanitin (AMA), a highly toxic octapeptide from Amanita mushrooms, poses severe poisoning risks due to misidentification. Herein, we developed a flexible SERS substrate integrating MIL-101(Cr), gold nanobipyramids (AuBPs) and cellulose nanofibers (CNF) with a "dual-sieve" impurity-exclusion mechanism. This platform achieves ultra-sensitive (LOD: 10-8 mg/mL) and rapid discrimination of α-, β-, and γ-AMA subtypes, with robust anti-matrix interference performance. It enables efficient AMA subtyping, providing a portable, reliable strategy for emergency mushroom poisoning screening and food safety diagnostics.

Background:Hypoxemia is a common and serious complication during sedated gastrointestinal endoscopy for out- and in-patients. Though diagnostic and severity scoring systems of obstructive sleep apnea (OSA) and difficult airway assessment (DAA) are widely used to assess hypoxemia risk, there is no exclusively designed prediction model and convenient tool in real-world practice. We aimed to develop and validate a robust and accurate hypoxemia risk prediction model for pre-operative use in this context. Methods:Using data from out-patients undergoing gastrointestinal endoscopy between May 2020 and November 2023 across seven hospitals in China with diverse regional and ethnic backgrounds, we developed and independently validated a hypoxemia risk prediction model for sedated gastrointestinal endoscopy (HAPPY-12K). The model was developed to pre-operatively predict occurrence of hypoxemia during sedated gastrointestinal endoscopy, defined as SpO2 falling below 95% for a duration exceeding 10 s. HAPPY-12K was a logistic regression model incorporating eight predictors: body mass index, Mallampati grade, limited jaw protrusion, short thyromental distance, large tongue, history of snoring, short neck with large circumference and pre-operative mean arterial pressure. The model was constructed by a well-established 3-D modeling strategy composed of Double types of effects, Double steps of screening, and Double steps of modeling. The discriminative ability was evaluated using the area under the receiver operating characteristic curve (AUC). The model calibration was examined through calibration slope, expected-to-observed (E:O) ratio and Brier score. For clinical utility, decision curve analysis was performed to assess net benefit (NB) and net reduction (NR). Furthermore, we systematically compared HAPPY-12K with other newly developed models using scores or raw variables from questionaries of OSA and DAA using DeLong's test. This study is registered in the Chinese Clinical Trial Registry (ChiCTR2300074128). Findings:We included 11,957 patients, divided into a Training Set (n = 2,518, hypoxemia rate 10.37%), and five validation sets (n = 9,439, hypoxemia rate raining from 8.40% to 28.45%). HAPPY-12K was developed in a Han Chinese population and exhibited satisfactory discrimination ability with AUCs ranging from 0.818 to 0.895 in external populations of the same ethnicity, and an acceptable AUC of 0.771 in a Uygur Chinese population. Although its Brier scores were satisfactory across all ethnic populations, HAPPY-12K displayed acceptable calibration (calibration slope < 1.2) in external Han Chinese populations, and good calibration (E:O ratio = 0.962) in independent homogenous populations comparable to the training set. The average NB and NR were 45.2‰ and 59.5%, respectively. It was estimated that HAPPY-12K would identify over half a million patients with truly developing hypoxemia during sedated gastrointestinal endoscopy and could help avoid over six million unnecessary interventions annually in China. Meanwhile, a head-to-head comparison revealed that HAPPY-12K outperformed other models. HAPPY-12K has been implemented as an interactive online tool available at http://bigdata.njmu.edu.cn/HAPPY-12K/. Interpretation:HAPPY-12K could enable efficient and precise hypoxemia risk assessment before sedated gastrointestinal endoscopy, providing timely alerts for high-risk outpatients. Funding:National Natural Science Foundation of China; Noncommunicable Chronic Diseases-National Science and Technology Major Project; Science and Technology Project of Jiangsu Disease Control and Prevention Administration; Science and Technology Development Project of Nanjing Medical University; Priority Academic Program Development of Jiangsu Higher Education Institutions; and Outstanding Young Level Academic Leadership Training Program of Nanjing Medical University.

OBJECTIVES:Optimal antimicrobial exposure in epithelial lining fluid (ELF) is critical for meropenem efficacy in pneumonia, yet ELF pharmacokinetic data remain scarce, particularly in children. To address this, we aimed to develop a model capable of predicting meropenem concentrations in both plasma and ELF for evaluating pharmacodynamic target attainment under clinical dosing strategies. METHODS:A physiologically based pharmacokinetic (PBPK) model was developed to simulate unbound meropenem concentrations in plasma and ELF. An empirical penetration coefficient (ρ) was incorporated to link lung intracellular concentrations to ELF concentrations, modelled as a function of clinical and inflammatory covariates. Following validation, the percentage of time over a dosing interval that the free drug concentration remains above the MIC(%ƒT > MIC), of meropenem plasma and ELF were related to in-hospital mortality. Monte Carlo simulations were conducted to assess the PTA for 40%ƒT >  MIC under varying regimens, MIC ranges (0.25-16 mg/L) and penetration scenarios. RESULTS:The PBPK model accurately predicted meropenem exposures in both plasma and ELF. ELF penetration was significantly influenced by physiological and pathological factors. ELF %ƒT >  MIC showed higher interindividual variability compared with that of plasma and was more strongly correlated with survival in both adult (P = 0.073) and paediatric patients (P = 0.013). Although prolonging the infusion improved ELF target attainment for susceptible pathogens (MIC ≤4 mg/L) with adequate penetration, it failed against high-MIC strains or with poor lung penetration. CONCLUSIONS:These findings underscore the importance of targeting infection-site pharmacokinetics over plasma exposure for better therapeutic efficacy in pneumonia. The model can be used to optimize dosing strategies.

INTRODUCTION:Postoperative delirium (POD) is a common neurological complication following acute type A aortic dissection surgery and is associated with poor clinical outcomes. Identifying reliable biomarkers, particularly those reflecting dynamic perioperative changes, may improve risk stratification and provide insights into POD pathophysiology. METHODS:This was a prospective observational study with a secondary analysis of perioperative serum samples from a registered clinical cohort (ChiCTR2200055980). A total of 128 acute type A aortic dissection patients undergoing open thoracotomy aortic surgery were enrolled, with 52 (40.6%) developing POD. For metabolomic analysis, 30 POD and 30 non-POD patients were matched for age, sex, and body mass index. Serum samples were collected at three time points: preoperatively, on intensive care unit admission, and on postoperative day 3. Untargeted metabolomics using liquid chromatography-mass spectrometry was performed. Differential metabolites were identified using multivariate and univariate analyses with false discovery rate correction. Receiver operating characteristic analysis was used to evaluate exploratory discriminative performance. RESULTS:After false discovery rate correction, no metabolites remained significant in preoperative samples, and only one metabolite, Acetyl-N-formyl-5-methoxykynurenamine, remained significant in postoperative comparisons. In contrast, several metabolites remained significant during the recovery stage. Notably, Acetyl-N-formyl-5-methoxykynurenamine exhibited a consistent temporal pattern, with increased levels in POD patients after surgery and a decline during recovery. Receiver operating characteristic analysis showed promising discriminative ability in postoperative (area under the curve: 0.833) and recovery-stage comparisons (area under the curve: 0.938), while preoperative performance was limited. CONCLUSIONS:Under stringent statistical correction, acetyl-N-formyl-5-methoxykynurenamine emerged as the most robust candidate dynamic biomarker associated with both POD occurrence and recovery. Its temporal pattern highlights the value of longitudinal metabolomic analysis and provides a basis for future validation studies.

Genome-wide association studies have predominantly implicated common variants in lung cancer susceptibility, whereas the contribution of rare non-coding variation remains incompletely defined. This study comprised 52,550 cases and 1,617,173 controls across three whole-genome sequencing (WGS) cohorts (UK Biobank, the 100,000 Genomes Project, and All of Us) and five imputed genotype-array datasets aimed to identify rare non-coding determinants of lung cancer risk. Two complementary approaches were applied: position-based single-variant testing for variants with adequate allele counts, and gene-based testing aggregating rare and ultra-rare ncRNA variants to increase power. Single-variant meta-analysis identified two novel rare non-coding variants reaching sequencing-based genome-wide significance: rs763076863C22orf46 at 22q13.2 [OR (95% CI): 5.94 (3.46-10.19), P = 4.55 × 10-9] and rs1014871851WWOX at 16q23.1 [OR (95% CI): 7.55 (4.50-12.67), P = 3.71 × 10-9]. Functional annotation-informed gene-based analyses prioritized 37 candidate ncRNAs using eQTL, expression, proteomics, prognosis, cis-Mendelian randomization drug-target evidence, and external replication. CLEC12A-AS1 ranked highest; multi-omics association and chain mediation analyses supported an indirect pathway linking CLEC12A-AS1 burden to lung cancer risk via modulation of CLEC12A. Collectively, results indicate contributions from both individually detectable rare variants and cumulative ultra-rare functional burden within ncRNA regions, highlighting the CLEC12A-AS1/CLEC12A axis as a potential biomarker and translational target.

Nemacheilus subfusca is an endemic fish species in the lower Yarlung Zangbo River. Its habitats are potentially threatened by geological disturbances and anthropogenic activities, but information on population status remains limited. However, existing research has been largely confined to basic biology, with limited information on its population genetic structure and connectivity. Consequently, targeted investigations are urgently needed to provide a scientific basis for the conservation of this species. In this study, genetic diversity and population structure were analyzed in 50 individuals from two geographic populations (Motuo (MT) and Chayu (CY)) in the lower Yarlung Zangbo River, using mitochondrial cytb and D-loop markers. The populations exhibited high haplotype diversity but relatively low nucleotide diversity (cytb: Hd = 0.870, Pi = 0.00281; D-loop: Hd = 0.931, Pi = 0.01655). Notably, the MT population exhibited lower diversity levels compared to the CY population (cytb: Hd = 0.757, Pi = 0.00205; D-loop: Hd = 0.633, Pi = 0.00153). Substantial genetic differentiation was observed between the two populations (cytb: FST = 0.322; D-loop: FST = 0.733); The observed mitochondrial divergence did not provide clear evidence of species-level differentiation (cytb = 0.00331; D-loop = 0.02492). The ML phylogenetic tree and haplotype network revealed geographically associated clustering of the two populations, indicating geographic structuring of mitochondrial haplotypes. Furthermore, demographic analyses were consistent with a possible historical population expansion. In conclusion, The mitochondrial data revealed high haplotype diversity but relatively low nucleotide diversity, together with substantial genetic differentiation between the two sampled populations, forming geographically associated clusters. This study elucidates the genetic background of this species’ germplasm resources, providing baseline genetic information for future conservation and management of this species.

Acute lung injury (ALI) is characterized by dysregulated pulmonary inflammation, in which alveolar macrophages (AMs) play a crucial role. The m⁶A reader protein YTHDF2, known to facilitate mRNA degradation, is implicated in inflammation; however, its specific function in ALI pathogenesis remains unclear. Using myeloid-specific Ythdf2 knockout mice subjected to cecal ligation and puncture (CLP)-induced ALI, we demonstrate that Ythdf2 deficiency significantly attenuates lung injury, as evidenced by reduced histopathological damage, pulmonary edema, and inflammatory cell infiltration, along with lower levels of pro-inflammatory cytokines (IL-6, TNF-α) in both bronchoalveolar lavage fluid and serum. Moreover, Ythdf2 deletion was accompanied by a substantial upregulation of Hmox1 protein expression in both lung tissues and AMs, an observation consistent with the known role of Ythdf2 in pulmonary hypertension. Furthermore, global m⁶A methylation levels and the expression of key methyltransferases (Mettl3, Mettl14) were elevated during ALI, coinciding with increased Ythdf2 expression. This upregulation of m⁶A regulators (YTHDF2, METTL3, METTL14) was also confirmed in pulmonary macrophages from human septic lungs. In conclusion, our findings support the concept that the myeloid-specific deletion of Ythdf2 ameliorates lung injury, an effect closely associated with the upregulation of Hmox1, highlighting Ythdf2 as a potential therapeutic target for ALI.

Chimeric antigen receptor (CAR) T cell therapy has demonstrated clinical success in hematologic malignancies but has limited efficacy in solid tumors due to tumor microenvironment (TME) barriers that impede CAR T cell recognition, infiltration, and sustained function. Traditional 2D assays inadequately recapitulate these constraints, necessitating improved in vitro models. This study validated a 3D tumor spheroid platform using an agarose microwell system to generate uniform B7-H3-positive spheroids from multiple solid tumor cell lines, enabling the evaluation of CAR T cell activity. TME-relevant immune modulation under 3D conditions was analyzed by flow cytometry for B7-H3, MHC I/II, and antigen processing machinery (APM), followed by co-culture with B7-H3 CAR T cells to assess cytotoxicity, spheroid integrity, tumor viability, and CAR T cell activation, exhaustion, and cytokine production. Two human cancer-cell-line-derived spheroids, DU 145 (prostate cancer) and SUM159 (breast cancer), retained B7-H3 expression, while MC38 (mouse colon cancer)-derived spheroids served as a B7-H3 negative control. Under 3D culture conditions, DU 145 and SUM159 spheroids acquire TME-like immune evasion characteristics and specifically downregulated MHC-I and APM (TAP1, TAP2, LMP7) with concurrent upregulation of MHC-II and calreticulin. Co-culture showed effective spheroid infiltration, cytotoxicity, and structural disruption, with infiltrating CAR T cells displaying higher CD4+ fraction, activation, exhaustion, effector/terminal differentiation, and IFN-γ/TNF-α production. This 3D platform recapitulates critical TME constraints and provides a cost-effective, feasible preclinical tool to assess CAR T therapies beyond conventional 2D assays.

Calciphylaxis (calcific uremic arteriolopathy, CUA) is a rare, fatal disorder primarily affecting chronic kidney disease patients, characterized by microvascular calcification, thrombosis, and skin necrosis. In a discovery cohort (3 CUA, 10 uremic), plasma proteomics identified Thrombospondin-1 (THBS1) as the top upregulated hub in CUA, significantly reduced after human amnion-derived mesenchymal stem cell (hAMSC) therapy, alongside latent TGF-β binding protein 1, both linked to coagulation and wound healing. In vitro proteomics indicated that THBS1/TGF-β1 blockade impaired CUA serum-induced endothelial adhesion and coagulation. ELISA in combined discovery and validation cohorts (8 CUA, 20 uremic) confirmed this reduction post-treatment (6 patients), independent of systemic inflammation. Multiplex immunofluorescence revealed THBS1 and CD47 co-localized with CD31 and integrin β3 in injured microvessels. A human microvascular chip showed that THBS1 inhibition or hAMSC-conditioned medium alleviates injury. These findings implicate THBS1 as a key factor and potential biomarker in calciphylaxis, suggesting hAMSC therapy as a promising mechanism-based approach. Video Abstract:

Prognostic prediction models can aid clinical decision-making for high-risk non-small cell lung cancer (NSCLC) patients. We conducted a systematic search across multiple databases and evaluated eligible studies using PRISMA and PROBAST checklists. Of 28,833 references screened, 233 studies describing 268 models were included. Among them, 89 underwent external validation; 67 (75.28%) were classified with high risk for bias. Most models were developed in North America (45.06%). The median area under the receiver operating characteristic curve (AUC) for 1-, 3-, and 5-year predictions were 0.759, 0.720, and 0.691, respectively. The most common predictors were age (54.85%) and stage (58.21%). And, 47.01% of models were sex-specific. Recently, easily accessible radiomic features have been increasingly used in statistical modeling compared to molecular omics. Models integrating radiomic and clinical features showed potential for improved performance (1-, 3-, and 5-year AUCs: 0.931, 0.985, 0.942). Model discrimination varied across different studies, and there is a lack of model calibration and clinical utility. This review highlights advances and limitations in NSCLC prognostic models. To enhance model reliability and generalizability, it remains crucial to adhere to the TRIPOD guideline to perform prediction model study, and to emphasize comprehensive model validation and bias-reduction strategies. Following a step-by-step guide to develop and validate clinical prediction models by Efthimiou, et al. (BMJ, 2024), along with a multifaceted, multidisciplinary and multi-regional approach, is the key way to facilitate the development and clinical application of qualified models.

Content generation modeling has emerged as a promising direction in computational pathology, offering capabilities such as data-efficient learning, synthetic data augmentation, and task-oriented generation across diverse diagnostic tasks. This review provides a comprehensive synthesis of recent progress in the field, organized into four key domains: image generation, text generation, molecular profile-morphology generation, and other specialized generation applications. By analyzing over 150 representative studies, we trace the evolution of content generation architectures-from early generative adversarial networks to recent advances in diffusion models and generative vision-language models. We further examine the datasets and evaluation protocols commonly used in this domain and highlight ongoing limitations, including challenges in generating high-fidelity whole slide images, clinical interpretability, and concerns related to the ethical and legal implications of synthetic data. The review concludes with a discussion of open challenges and prospective research directions, with an emphasis on developing integrated and clinically deployable generation systems. This work aims to provide a foundational reference for researchers and practitioners developing content generation models in computational pathology.

BACKGROUND: The cardiac voltage-gated sodium channel Nav1.5, encoded by SCN5A, plays a critical role in cardiac electrophysiology. SCN5A variants represent a series of frequently identified genetic findings in molecular autopsies, with established associations across multiple arrhythmia syndromes including long QT syndrome type 3, Brugada syndrome, progressive cardiac conduction disease, sinus node dysfunction, atrial fibrillation, atrial standstill, and dilated cardiomyopathy. Recently, an increasing number of familial cases with early-onset sick sinus syndrome (SSS) were reported, bringing more challenges in forensic genetic diagnosis. METHODS: We investigated a four-generation family with SSS, characterized by a history of pacemaker implantation and sudden cardiac death (SCD). Genetic analyses were performed to identify the underlying pathogenic variant, and electrophysiological properties were evaluated using patch-clamp recordings. RESULTS: We identified a rare SCN5A missense variant, NM_198056.3(SCN5A,rs199473620): c.4720G>A (p.E1574K), in this family. Subsequent analyses demonstrated that the mutated site is highly conserved in the voltage-gated sodium channel family, as well as across species. Electrophysiological experiments showed that this mutation significantly attenuated the function of Nav1.5 channel, potentially revealing the pathogenic mechanism of SCN5A c.4720G>A variant. CONCLUSIONS: Our study identified a rare SCN5A missense variant and classified it as likely pathogenic following the ACMG framework, thereby expanding the phenotypic spectrum of SCN5A-associated SSS and providing a potential forensic diagnostic molecular target for unexplained deaths with negative morphological alterations.

Chemotherapy-induced nausea and vomiting (CINV) is among the most prevalent adverse reactions in cancer treatment. It significantly diminishes the quality of life of patients and their treatment compliance. Traditional Chinese medicine (TCM) exhibits unique characteristics and potential for the prevention and treatment of CINV. This review summarizes the latest research progress on TCM for CINV, encompassing the theoretical foundation, mechanism of action, and clinical evidence. "Fuzheng Quxie" formulas (reinforcing healthy Qi and eliminating pathogenic factors) and herbs (e.g., Liu-Jun-Zi-Tang, ginseng) enhance the body's tolerance to chemotherapy by enhancing immunity, reducing inflammation and oxidative damage, and promoting tissue repair. "Hewei Jiangni" formulas (harmonizing the stomach and directing rebellious Qi downward), including Xiao-Ban-Xia-Tang, ginger, and external therapies (e.g., acupuncture, moxibustion, acupoint application) directly alleviate nausea and vomiting by regulating gastrointestinal motility, antagonizing emesis-related receptors, and inhibiting inflammatory pathways. Clinical research shows that combining TCM with conventional antiemetic regimens improves the control of delayed CINV and enhances patients' quality of life, while maintaining a favorable safety profile. However, current evidence remains limited by small sample sizes, insufficient mechanistic investigations, and lack of standardized treatment plans. Future research should prioritize high-quality and large-sample clinical trials and clarify its mechanism of action using modern scientific approaches, so as to promote the standardized and efficient application of TCM for the prevention and treatment of CINV.

IntroductionCritically ill patients with severe infections demonstrate profound alterations in pharmacokinetic behavior. Therapeutic drug monitoring (TDM)-informed antimicrobial dose optimization is thus essential in intensive care settings to ensure maximal bactericidal activity while mitigating toxicity, creating an urgent need for accessible analytical methodologies. Although various studies exist in this domain, the inherent technical constraints of current methodologies persistently prevent the full resolution of these unmet clinical requirements.MethodsA rapid and sensitive LC-ESI-MS/MS method was developed and validated for the simultaneous quantification of 11 antimicrobials in human plasma. Sample preparation was performed by a simple one-step protein precipitation using methanol containing 0.1% formic acid. The analytes were separated on a Kinetex C18 column with a “corner-folded cleaver-shaped” gradient elution program and detected using multiple reaction monitoring (MRM) in positive ionization mode.Results and DiscussionThe gradient elution program achieved baseline separation of all tested analytes within 8 min, with symmetrical peak shapes and no endogenous interference. The developed method was proven to be free of matrix effects, excellent linearity (R2 > 0.99 for all analytes), and met international bioanalytical validation criteria across clinically relevant concentration ranges. Notably, this validated method was successfully applied to children receiving mono- or combination therapy for infections. The assay meets requirements for clinical TDM implementation, providing pediatricians with reliable antibiotic concentration measurements within a clinically relevant timeframe.

Objectives: The identification of early warning biomarkers and associated molecular mechanisms of sudden cardiac death (SCD) caused by acute coronary syndrome (ACS) through the analysis of peripheral blood plasma extracellular vesicles (EVs) remains a significant gap in current knowledge. We aimed to screen for novel EV metabolic markers and validate their prediction ability, thereby providing novel early diagnostic biomarkers for the risk of sudden death due to ACS; based on the premise that EVs mirror cellular metabolic stress, we hypothesized that specific EV metabolic signatures can predict SCD risk in ACS patients. Methods: In this nested case–control study, plasma EVs from 18 non-ST-segment elevation ACS (NSTE-ACS), 21 ST-segment elevation myocardial infarction, 16 ACS-related SCD patients, and 41 matched controls were isolated and characterized in accordance with the Minimal Information for Studies of Extracellular Vesicles 2018 guidelines. We performed a combined liquid chromatography-tandem mass spectrometry–based metabolomic and proteomic analysis of plasma EVs, conducted multiomics integration for pathway and network analysis, and validated candidate biomarkers by enzyme-linked immunosorbent assay. Receiver operating characteristic curve analysis and multivariate/univariate statistical methods were applied to evaluate the SCD risk predictive value of the identified markers. Results: We identified 27 differential metabolites associated with the progression of SCD in plasma EVs of ACS patients. The combined analysis suggested that glycolysis and the tricarboxylic acid cycle might be key metabolic pathways in SCD. Notably, EV-derived pyruvate and lactic dehydrogenase B (LDHB) levels were significantly elevated in SCD patients compared with controls ( P < 0.05), despite no differences in plasma concentrations, suggesting EV-derived pyruvate and LDHB as early biomarkers to predict SCD in ACS patients. Integration of EV-derived pyruvate and LDHB with traditional biomarkers (creatine kinase isoenzyme and myoglobin) improved SCD risk prediction (area under the curve: 0.786 for pyruvate + LDHB; area under the curve: 0.9 when combined with creatine kinase isoenzyme), underscoring their potential for enhancing risk stratification. Conclusion: In this nested case–control study of ACS patients, multiomics profiling of plasma EVs revealed altered distinct metabolic signatures in SCD cases, particularly the LDHB–pyruvate–spermine–spermidine network involved in glycolysis and the tricarboxylic acid cycle. LDHB and pyruvate emerged as codiagnostic biomarkers, enhancing predictive accuracy for cardiovascular events when combined with clinical indicators.

Duhuo Jisheng Decoction (DHJSD) shows promise for treating intervertebral disc degeneration (IVDD), but its mechanisms concerning autophagy and fibrosis are unclear. Using network pharmacology, metabolomics, UHPLC-Q-TOF/MS, and functional studies (in vitro and in vivo), we systematically explored DHJSD's molecular mechanisms. DHJSD has 254 constituents; those may regulate inflammation, apoptosis, and metabolic processes. DHJSD attenuates ECM/fibrosis-related changes, lowers BMP2 expression, is associated with reduced TGF-β/Smad2/3 phosphorylation, and partially improves annulus fibrosus morphology. SB431542 attenuated IL-1β-induced TGF-β pathway activation and BMP2 expression, supporting the involvement of this pathway in DHJSD-related regulation of fibrosis markers. The levels of serum IL-1β and TNF-α significantly decreased in animal models. Through glycerophospholipid and sphingolipid metabolism, DHJSD reshapes lipid homeostasis and may be associated with reduced TGF-β overactivation by downregulating pro-fibrotic compounds and upregulating anti-inflammatory metabolites. DHJSD modulates autophagy-related markers via controlling the LC3-II/LC3-I ratio and BCL2, P62 expression. DHJSD may affect glycolysis-related and oxidative phosphorylation-related changes and may be associated with phosphatidylcholine/ethanolamine-related mitochondrial membrane changes. DHJSD treats IVDD via a "metabolic reprogramming-TGF-β-related regulation-autophagy/mitochondrial-related remodeling" network, suggesting a potential multi-target strategy and demonstrating the value of multi-omics in analyzing traditional medicine.

Inspiration-induced mechanical stretching serves as the primary driving force for pulmonary surfactant secretion from alveolar epithelial type II (AT2) cells. However, the mechanism by which AT2 cells sense mechanical stimuli remains elusive. Here, we demonstrate that TMEM63B functions as a critical mechanosensor on the plasma membrane of AT2 cells. We find that stretch induces significant currents in AT2 cells. Using Tmem63bHA-fl/HA-fl mice, we show that TMEM63B is expressed on the plasma membrane of AT2 cells. Deletion of TMEM63B in AT2 cells abolishes the stretch-induced currents and suppresses the secretion of pulmonary surfactant. Activation of TMEM63B causes Ca2+ influx, lamellar body (LB) fusion, and pulmonary surfactant secretion. These processes are markedly impaired upon TMEM63B deletion. In contrast, ATP-induced Ca2+ influx and LB fusion are unaffected by TMEM63B deletion, indicating that TMEM63B plays a specialized role in sensing mechanical stretch in the lungs. Therefore, our study establishes TMEM63B as a key mechanosensor critical for AT2 cell-mediated pulmonary surfactant secretion.