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.

TFIIB-related factor 1 (BRF1) is an important transcription factor. It specifically regulates the transcription of RNA polymerase III-dependent genes (RNA Pol III genes). The products of these genes are some small non-coding RNAs, including transfer RNAs (tRNAs) and 5S ribosomal RNAs (5S rRNA). The transcription levels of tRNAs and 5S rRNA vary with changes in intracellular BRF1 amounts. tRNAs and 5S rRNA play a crucial role in determining protein synthesis. Studies have demonstrated that dysregulation of tRNAs and 5S rRNA is closely related to cell growth, proliferation, transformation, and even tumorigenesis. BRF1 is a key factor determining the generation of tRNAs and 5S rRNA. Increasing BRF1 expression enhances cell proliferation and transformation, promoting tumor development. In contrast, repressing BRF1 activity decreases the rates of cell proliferation and transformation, and inhibits tumor growth. High levels of BRF1 are found in the samples of patients suffering from hepatocellular carcinoma, breast cancer, gastric carcinoma, lung cancer, prostate carcinoma, and other cancers. It indicates that high levels of BRF1 are closely related to the occurrence of human cancer and may be a common landmark of tumors. But there is discrepancy in the regulatory mechanisms and signaling pathways of BRF1 overexpression in different cancers. In general, high levels of BRF1 in patients suffering from cancer show short survival period and poor prognosis. However, there is one exception, namely breast cancer. Approximate 80% of cases of breast cancer are estrogen receptor-positive (ER+) and 20% are ER-. The cases with high levels of BRF1 reveal longer survival period and better prognosis after they accepted the hormone treatment by Tamoxifen (Tam), compared to the cases with low level BRF1. It seems like a contradiction. Most of the cases with high levels of BRF1 belong to ER+ status. Tam has been used to treat ER+ cases of breast cancer after diagnosis and surgery. Thus, hormone therapy, such as Tam, is more effective on these patients. This is because, on one hand, that Tam competes with E2 (17β-estradiol) to bind to estrogen receptor α (ERα), but does not dissociate to occupy the receptors, blocking E2 binding to this receptor and inhibiting its biological effects. On other hand, Tam can inhibit the expression of BRF1, leading to a decline of intracellular BRF1 levels. Therefore, the actual levels of BRF1 are lower in the patients with ER+ breast cancer. It appears the prognosis of the high BRF1 expression cases better than that of the low BRF1 expression cases. Myocardial hypertrophy manifests magnification of cardiomyocyte volume rather than number increasing in the postnatal heart. Myocardial hypertrophy is a critical risk factor underlying cardiovascular diseases. No matter how myocardial hypertrophy occur, it will ultimately lead to myocardial dysfunction and heart failure. Hypertrophic growth of cardiomyocytes requires a large amount of protein synthesis to meet its needs of cardiomyocyte growth. Animal models and cell experiments have shown that myocardial hypertrophy stimulates a significant increase in BRF1 expression and transcription of tRNAs and 5S rRNA. Interestingly, elevated levels of BRF1 are found in the myocardium tissues of patients with myocardial hypertrophy. These studies demonstrate that BRF1 indeed plays a critical role in myocardial hypertrophy. In summary, high levels of BRF1 are found in patients suffering from different cancers and myocardial hypertrophy. It implies that BRF1 is a promising biological target of cancer and cardiomyopathy. BRF1 is expected to become a common biomarker for early diagnosis and prognostic observation of different human cancers. It is also an important biomarker for the diagnosis and treatment of cardiomyopathy. BRF1 not only holds an important position in the field of basic medical research but also has great prospects for translational medicine. In the present article, we summarize the progress on studies of BRF1 expressions in cancer and cardiomyopathy, proposes future research directions. It is a new research area. Here, we emphasize the significancy of BRF overexpression in the two huge diseases of human, cancer and cardiomyopathy to raise people's attention to this field.

Background Existing studies have confirmed that fine particulate matter (PM_2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM_2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg⁻¹ by gavage, n=10), PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ + saline by gavage, n=10), and Sal + PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ +Sal 60 mg·kg⁻¹ by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM_2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM_2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM_2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM_2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM_2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM_2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.

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

Objective:To evaluate the diagnostic value of non-targeted detection of metabolic fingerprinting in pulmonary nodules and to analyze the clinical effective model of multi-omics for assessing the malignant risk of pulmonary nodules.Methods:A total of 73 patients who underwent chest CT and completed pathological diagnosis and non-targeted detection of metabolic fingerprinting at Shandong Provincial Hospital Affiliated to Shandong First Medical University from November 2021 to October 2024 were selected as the research subjects. According to the postoperative histopathological diagnosis, the patients were divided into the lung malignant nodule group (61 cases) and the lung benign nodule group (12 cases). General clinical data of the patients, including sex, age, smoking history, and family history of tumors, as well as imaging data, including nodule density, nodule size, nodule location, nodule number, and special imaging manifestations (spiculation, lobulation, vacuole sign, vascular convergence sign, etc.), and non-targeted detection of metabolic fingerprinting results were collected. The above data were compared between the two groups of patients, and the receiver operator characteristic (ROC) curve was drawn to evaluate the predictive value of each model. Results:There were statistically significant differences in age ( t=4.41, P<0.001), nodule size ( Z=2.67, P=0.008), nodule density ( χ2=4.64, P=0.031), and spiculation ( χ2=7.67, P=0.006) between the lung malignant nodule group and the lung benign nodule group. There were no statistically significant differences in sex, smoking history, family history of lung cancer, nodule number, nodule location, lobulation, vacuole sign, vascular convergence sign, pleural indentation sign, calcification sign, bronchial truncation sign, vascular supply sign, and bronchial air sign (all P>0.05). The number of non-targeted detection of metabolic fingerprinting high-risk patients in the lung malignant nodule group (36 cases) was significantly higher than that in the lung benign nodule group (0 case) ( χ2=13.97, P<0.001). ROC curve analysis showed that the area under the curve of the Brock model combined with non-targeted detection of metabolic fingerprinting was 0.930 (95% CI: 0.872-0.988), which was greater than that of the Brock model (0.856, 95% CI: 0.769-0.942, Z=0.27, P=0.040) and non-targeted detection of metabolic fingerprinting (0.768, 95% CI: 0.650-0.887, Z=0.30, P=0.004) alone. Conclusions:Non-targeted detection of metabolic fingerprinting risk assessment may serve as a non-invasive method to assist the Brock model in the diagnosis of pulmonary nodules and has good application value. The combination of the Brock model and non-targeted detection of metabolic fingerprinting can more accurately distinguish the benign and malignant nature of pulmonary nodules.