Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Background Prenatal exposure to fine particulate matter (PM_2.5) is closely associated with cortical damage and neuroinflammation in offspring. The cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway is a key regulator of inflammation and may be subject to epigenetic regulation. Objective To investigate the role of cGAS-STING pathway activation in PM_2.5-induced cortical damage in offspring mice during pregnancy and the underlying epigenetic regulatory mechanisms. Methods Open field tests were used to assess depressive-like behavior in offspring mice. Morphological analysis was conducted to evaluate cortical damage and microglial activation in offspring brains. Real-time fluorescent quantitative PCR (RT-qPCR) and Western blot (WB) were performed to detect changes in the expression of key molecules in the cGAS-STING pathway in cortical tissue. A PM_2.5-induced microglial cell injury model was established in BV2 cells. Microglial activation was observed, cell viability was measured using the Cell Counting Kit-8 (CCK-8), and the expression levels of inducible nitric oxide synthase (iNOS) and key molecules in the cGAS-STING pathway were detected by RT-qPCR and WB. Bioinformatics analysis was performed to explore the epigenetic regulatory association between the STING signaling pathway and lysine-specific demethylase 5A (KDM5A). Changes in KDM5A mRNA and protein expression, as well as the protein level of histone H3 lysine 4 trimethylation (H3K4me3), were detected in an in vitro PM_2.5 injury model. Using small interfering RNA (siRNA) technology, the KDM5A gene was silenced in BV2 cells exposed to PM_2.5. The protein expression of H3K4me3 was detected to evaluate improvements in microglial activation, changes in inflammatory markers such as iNOS and mannose receptor (CD206), and alterations in the cGAS-STING pathway. Results Compared with the control group, the total distance of offspring mice in the PM_2.5 group was significantly reduced, and both the distance traveled and the time spent in the central area of the open field were significantly decreased (P<0.01, P<0.001), indicating depressive-like behavior in the offspring mice. Compared with the control group, the offspring mice in the PM_2.5 group exhibited disorganized cortical structure and significantly activated microglia (P<0.01), with significantly increased mRNA and protein levels of cGAS and STING (P<0.05, P<0.01, or P<0.001). The in vitro experiments demonstrated that the PM_2.5 treatment induced BV2 cells to polarize toward the M1 phenotype, exhibiting a distinct amoeboid morphology, with upregulated expression of the pro-inflammatory factor iNOS (P<0.05, P<0.01, or P<0.001) and activation of the cGAS-STING pathway (P<0.05, P<0.01). The analysis of RNA-seq data from KDM5A knockout cells revealed significantly downregulated STING expression, suggesting that KDM5A may activate the STING signaling pathway. The in vitro experiments further confirmed that the PM_2.5-treated BV2 cells exhibited significantly elevated mRNA and protein levels of KDM5A (P<0.01), while the H3K4me3 protein levels were markedly reduced (P<0.05). After silencing KDM5A in BV2 cells exposed to PM_2.5, compared with the PM_2.5+siNC group, the PM_2.5+siKDM5A group showed no obvious microglial activation and polarized toward the M2 phenotype, with significantly decreased expression levels of iNOS, cluster of differentiation 16 (CD16), and interleukin-1β (P<0.05, P<0.01), and significantly increased expression levels of anti-inflammatory factors CD206, YM1, and interleukin-10 (P<0.01, P<0.001). Meanwhile, the expression levels of cGAS and STING were also reduced (P<0.05, P<0.01). Conclusion KDM5A activates microglia through the cGAS-STING pathway, thereby contributing to PM_2.5-induced cortical damage in offspring mice during pregnancy.

Modern cataract surgery has completely moved beyond the traditional vision-restoring model and has fully entered a new era of refractive cataract surgery(RCS)centered on precise refractive correction. Its core objective is to provide patients with personalized visual experiences characterized by full-range, clear, and comfortable vision. Currently, although diagnostic and therapeutic technologies for RCS are rapidly evolving, there remain many bottlenecks in the precise management of the entire perioperative process that urgently need to be addressed. Preoperatively, the measurement consistency among ocular biometry devices based on different detection principles remains poor, and systematic measurement errors cannot be completely eliminated. Moreover, the individualized selection of intraocular lenses(IOLs)relies heavily on surgeons' clinical experience, lacking a standardized quantitative decision-making framework, which makes it difficult to achieve precise personalized matching. Intraoperatively, the quality of continuous curvilinear capsulorhexis is affected by multiple factors such as ocular anatomical characteristics and surgical proficiency, and its stability cannot be reliably ensured. Various intelligent surgical navigation systems are compromised by intraoperative ocular conditions, and their clinical performance fails to meet theoretical expectations. At the postoperative stage, existing IOL optical designs and materials have inherent limitations. The longterm prevention and control of posterior capsule opacification(PCO)remains a core factor restricting patients' long-term high-quality visual outcomes. This article systematically reviews the precise diagnostic and therapeutic challenges and core bottlenecks across the preoperative, intraoperative, and postoperative stages of RCS. It further explores frontier technological directions—including cross-device error compensation models, artificial intelligence-assisted decision-making, preoperative VR-based visual simulation, and the construction of intelligent surgical ecosystem platforms—to delineate targeted solutions and optimization pathways. This review aims to provide references and insights for the standardized clinical implementation, technological innovation, and future research endeavors in precision diagnosis and treatment of RCS.

Objective: To compare the changes in the concentration of relevant growth factors released from platelet-rich plasma (PRP) stored at -80℃ by cryopreservation and at 4℃ by refrigerated lyophilization over 2 years, aiming to provide a theoretical basis for prolonging PRP storage duration. Methods: PRP (n=15) was separated using a blood cell separator and stored under -80℃ cryopreservation (F-PRP group) and 4℃ refrigerated freeze-drying conditions (FD-PRP group). The contents of growth factors (PDGF-AA, PDGF-BB, EGF, TGF-β1, and VEGF) in both groups were measured by ELISA at 1, 3, 6, 9, 12 and 24 months. Results: PDGF-AA and VEGF maintained good stability in both groups for up to 24 months. PDGF-BB and TGF-β1 showed high stability in the first 12 months but their stability decreased gradually from 12th to 24th months. EGF demonstrated good stability in the first 6 months, and its stability gradually decreased from the 9th to 24th months. Comparing the F-PRP and FD-PRP groups, the concentrations of the five growth factors in the FD-PRP group were either not statistically different or higher than those in the F-PRP group at all time points. Specifically, the concentrations of EGF were significantly higher in the FD-PRP group at all time points. Conclusion: Both -80℃ freezing and 4℃ freeze-drying enable long-term preservation of PRP. Freeze-drying imposes less stringent storage requirements and facilitates growth factor compared to frozen storage.

Human carboxylesterase 2A (hCES2A) plays pivotal roles in prodrug activation and hydrolytic metabolism of ester-bearing chemicals. Targeted inhibition of intestinal hCES2A represents a feasible strategy to mitigate irinotecan-triggered gut toxicity (ITGT), but the orally active, selective, and efficacious hCES2A inhibitors are rarely reported. Here, a novel drug-like hCES2A inhibitor was developed via three rounds of structure-based drug design (SBDD) and structural optimization. Initially, donepezil was identified as a moderate hCES2A inhibitor from 2000 US Food and Drug Administration (FDA)-approved drugs. Following two rounds of SBDD and structural optimization, a donepezil derivative (B7) was identified as a strong reversible hCES2A inhibitor. Subsequently, nine B7 carbamates were rationally designed, synthesized and biologically assayed. Among all synthesized carbamates, C3 showed the most potent time-dependent inhibition on hCES2A (IC₅₀ = 0.56 nmol/L), excellent specificity and favorable drug-like properties. C3 could covalently modify the catalytic serine of hCES2A with high selectivity, while this agent also showed favorable safety profiles, high intestinal exposure, and impressive effects for ameliorating ITGT in both human intestinal organoids and tumor-bearing mice. Collectively, this study showcases a rational strategy for developing drug-like and serine-targeting covalent inhibitors against target serine hydrolase(s), while C3 emerges as a promising orally active drug candidate for ameliorating ITGT.

OBJECTIVES: To explore the value of serum cystatin C (CysC) levels in evaluating renal prognosis in IgA nephropathy (IgAN) patients. METHODS: We retrospectively collected the clinical data of IgAN patients diagnosed by renal biopsy at Guangdong Provincial People's Hospital from January, 2014 to December, 2018. Based on baseline serum CysC levels, the patients were divided into high serum CysC (>1.03 mg/L) group and normal serum CysC (≤1.03 mg/L) group. The composite endpoint for poor renal prognosis was defined as ≥50% decline in estimated glomerular filtration rate (eGFR) and/or progression to end-stage renal disease (ESRD). Lasso regression, multivariate Cox regression and Kaplan-Meier survival analysis were used to identify the risk factors and compare renal survival rates between the two groups. Smooth curves fitting and threshold effect analysis were used to explore the relationship between serum CysC levels and the outcomes. A nomogram model was constructed and its predictive performance was evaluated using concordance index, calibration curve, receiver operating characteristic (ROC) curve and the area under curve (AUC). RESULTS: A total of 356 IgAN patients were enrolled, who were followed up for 4.65±0.93 years. The composite endpoint occurred in 74 patients. High serum CysC was identified as an independent risk factor for poor renal prognosis in IgAN (HR=2.142, 95% CI 1.222 to 3.755), and the patients with high serum CysC levels had a lower renal survival rate (Log-rank χ²=47.970, P<0.001). In patients with serum CysC below 2.12 mg/L, a higher CysC level was associated with an increased risk of poor renal prognosis (β=3.487, 95% CI: 2.561-4.413, P<0.001), while above this level, the increase of the risk was not significant (β=0.676, 95% CI: -0.642-1.995, P=0.315). The nomogram model based on serum CysC and 3 other independent risk factors demonstrated good internal validity with a concordance index of 0.873 (95% CI: 0.839-0.907) and an AUC of 0.909 (95% CI: 0.873-0.945). CONCLUSIONS Serum CysC levels are associated with renal prognosis in IgAN patients, and high serum CysC an independent risk factor for poor renal prognosis.
Humans ; Glomerulonephritis, IGA/diagnosis* ; Cystatin C/blood* ; Prognosis ; Risk Factors ; Retrospective Studies ; Glomerular Filtration Rate ; Kidney Failure, Chronic ; Male ; Female ; Adult ; Nomograms ; Middle Aged

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male