Environmental pollution is a significant public health challenge worldwide, and investigating the causal relationship between environmental exposure and population health outcomes is a key objective of environmental epidemiology research. In recent years, the complexity of environmental exposures has increasingly come to the forefront, making it challenging for observational studies that dominate environmental epidemiology to accurately estimate causal effects. Causal inference methods are particularly advantageous in controlling for confounding factors, thus holding great potential in environmental epidemiology research. Researchers can use appropriate causal inference methods to simulate the process of randomization, providing strong support for revealing the causal relationship between environmental exposure and health outcomes. However, there is a lack of reviews on the application of causal inference methods in environmental epidemiology studies in China. Therefore, this study introduced the basic principles of common causal inference statistical methods in environmental epidemiology, summarized the applicable conditions, advantages and disadvantages of various methods, and provided R software implementation codes for these methods, aiming to offer guidance for optimizing research design and practicing causal inference statistical methods.

BackgroundIn recent years， the incidence of depression among adolescents has been increasing steadily， posing a serious threat to their physical and mental health and even leading to severe consequences such as self-harm and suicide. At the same time， the detection rate of subclinical depression symptoms among adolescents is even higher. Although these symptoms do not meet the clinical diagnostic criteria， they have significantly affected their quality of life， and their persistence over time may further develop into depression. Therefore， in-depth exploration of adolescent depression symptoms and the predictive factors holds significant practical significance and research value. However， up to now， no large-scale investigation and research on depression symptoms among children and adolescents has been conducted in Inner Mongolia Autonomous Region. ObjectiveTo understand the prevalence of depressive symptoms among children and adolescents in Inner Mongolia Autonomous Region， in order to provide references for formulating scientific and effective prevention strategies and intervention measures. MethodsBy using the cluster stratified random sampling method， 6 281 students from the third grade of primary school to the second grade of high school in 12 leagues and cities of Inner Mongolia Autonomous Region were selected in March 2024. A self-designed questionnaire and the Self-rating Depression Scale （SDS） were used for on-site investigation. ResultsA total of 6 058 （96.45%） children and adolescents completed the valid questionnaire survey， and 2 728 cases （45.03%） were found to have depressive symptoms. There were statistically significant differences in the detection rates of depressive symptoms among children and adolescents of different genders， ages， whether they were only children， different family types， family monthly income， parents' educational levels， and whether the mother was employed （χ²=33.769， 40.618， 48.593， 29.972， 142.648， 195.999， 168.190， 5.445， P<0.05 or 0.01）.The results of the Logistic regression analysis showed that for children and adolescents， being female， aged between 12 and 16， over 16 years old， not being an only child， living in a reconstituted family， having a monthly family income of less than 5 000 yuan， and having parents with an education level of primary school or below were predictors of depressive symptoms （OR=1.241， 1.427， 1.273， 1.177， 1.549， 1.278， 1.462， 1.417， 1.514， 1.929， 1.660， 1.528， P<0.05 or 0.01）. ConclusionThe detection rate of depressive symptoms among children and adolescents in Inner Mongolia Autonomous Region is relatively high. Factors that may predict depressive symptoms in children and adolescents include female gender， ages between 12 and 16， ages over 16 years old， non-only children， families with a restructured structure， monthly family income of less than 5 000 yuan， and parents with an education level of primary school or below. ［Funded by Science and Technology Planning Project of the Inner Mongolia Autonomous Region （number， 2022YFSH0119）］

Ferroptosis is a key driver of the onset and progression of chronic obstructive pulmonary disease （COPD）. By exploring the role of ferroptosis in COPD from the perspective of "qi deficiency with retention and stagnation"， it is considered that mitochondrial dysfunction and imbalanced antioxidant defenses are the microscopic manifestations of "qi deficiency"， whereas iron accumulation and lipid peroxide deposition constitute the pathological basis of "retention and stagnation". In traditional Chinese medicine （TCM）， the treatment principle is tonifying deficiency and benefiting qi， scattering retention and unblocking stagnation. Its mechanism involves improving the antioxidant system and mitochondrial function to enhance cellular resistance to ferroptosis， as well as relieving pulmonary iron overload， excessive lipid peroxidation， and inflammatory factor release to reduce the accumulation of pathological products， thereby exerting therapeutic effects on COPD.

Background Ozone (O₃) is a major air pollutant. The existing monitoring system has uneven distribution of sites, insufficient coverage in underdeveloped areas, and low temporal resolution, making it difficult to obtain hourly data. This limits the dynamic identification of pollution and the formulation of prevention and control strategies. Objective To construct an hourly O₃ concentration estimation model based on ensemble machine learning, aiming to improve the accuracy of pollution exposure assessment and explore O₃ health impacts. Methods This study integrated land use regression modeling with modern machine learning techniques, employing random forest and XGBoost algorithms to construct base models, and stacking integration using non-negative least squares. The ensemble model was trained and validated across China using high-resolution, multi-source geographic data (e.g., meteorologicaldata, population density, land cover types, and aerosol optical thickness). It was tested in Taiyuan City, combined with a distributed lag non-linear model to analyze the association between O₃ and emergency admissions. Results The constructed ensemble model performed well in predicting O₃ concentration, with a higher coefficient of determination (R²) and a lower root-mean-square deviation (RMSE) compared to the single models. The R² improved from 0.90 to 0.92, and the RMSE decreased from 11.41 to 10.62, enhancing both prediction accuracy and generalization ability. In the application to Taiyuan City, the model successfully imputed the hourly-level data for the entire year. The distributed lag non-linear model analysis revealed that the relative risk (RR) values for the 6th to 8th days following O₃ exposure were 1.14 (95%CI: 1.01, 1.29), 1.16 (95%CI: 1.02, 1.31), and 1.14 (95%CI: 1.01, 1.29), respectively, which were significantly higher than 1, indicating a significant lagged association (lagged 6-8 d) between O₃ and the number of emergency room visits. Conclusion A high-precision, hourly-level O₃ concentration estimation model is successfully constructed by combining the land use regression model with an ensemble machine learning approach to provide a scientific basis for environmental policy formulation and public health intervention. The application of the model verifies its generalization ability and practical application value, which can provide a new technical framework for subsequent environmental health research.

Purpose: This study aimed to evaluate the safety and efficacy of gemcitabine and cisplatin (GP) regimen in combination with immune checkpoint inhibitor sintilimab as neoadjuvant therapy for muscle-invasive bladder cancer (MIBC) patients and the feasibility of the following selective bladder sparing surgery. Materials and Methods: Patients with histopathologically confirmed urothelial carcinoma without distant metastases (T2-4a, N ≤ 1, M0, American Joint Committee of Cancer 8th) and with adequate organ function will be enrolled. The therapeutic regimen was sintilimab 200 mg once on day 8, gemcitabine 1,000 mg/m2 and cisplatin 35 mg/m2 once on days 1 and 8, every 21 days for four cycles. The primary endpoint was pathologic complete response (pCR, pT0N0) rate. The secondary end points were ypT < 2 rate, R0 resection rate, event-free survival, and safety. Results: From May 4, 2020, to May 20, 2023, 55 patients were enrolled. Forty-six patients were evaluated for efficacy. Among the 42 patients who underwent surgery, 16 patients (38.0%) achieved pCR. Thirty-three patients (78.6%) achieved pT < 2. With a median follow-up of 15.7 months, the 1-year event-free survival was 91.3%. Notwithstanding the poor pathological baseline characteristic of a high T3-T4a proportion (39.1%), a promising bladder preservation (including 22 patients transurethral resection of bladder tumor, 5 patients partial cystectomy, and 4 surveillances) rate was achieved (67.4%). The most common grade ≥ 3 treatment-related adverse events was neutropenia (n=15, 27.3%), which was related to chemotherapy. There were no grade 3 immune-related adverse events. Conclusion Neoadjuvant GP plus sintilimab is a promising regimen for MIBC patients, with relatively high pT < 2 rate and triggering the emerging roles for the multi-disciplinary team decision-making for bladder sparing surgery.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The high pressure generated from urinary tract obstruction can cause damage to the tissues and cells of the urinary tract. Persistent damage can induce urinary tract fibrosis, ultimately resulting in the loss of urinary tract function and severe clinical problems. In recent years, the role of a novel mechanosensitive ion channel in urinary tract fibrosis, Piezo1, has drawn due attention. This review systematically summarizes the mechanisms of Piezo1. In upper urinary tract fibrosis, Piezo1 participates in fibrotic process through the Calcium-Calpain2-integrin β1-adhesion protein pathway and Piezo1-p38MAPK-YAP signaling pathway. In lower urinary tract fibrosis, Piezo1 mediates bladder fibrosis via the YAP1 and TGF-β1/Smad pathways, and may contribute to prostate cancer-associated urethral obstruction through the Akt/mTOR signaling pathway. This study elucidates the critical roles of Piezo1 in urinary tract fibrosis, providing a theoretical foundation for developing novel Piezo1targeted therapeutic strategies. Future research can leverage advanced technologies such as microfluidic organ-on-a-chip system to explore the precise regulatory mechanisms of Piezo1, thus offering new insights for the clinical management of urinary stricture diseases.

ObjectiveTo investigate the role and underlying mechanism of the Wnt/β-catenin signaling pathway in the process of Xiaojinwan （XJW）-containing serum interfering with endothelial-mesenchymal transition （EMT） in human breast cancer MDA-MB-231 cells. MethodsXJW-containing serum was prepared by intragastric administration of XJW （4 g·kg^-1） to SD rats. MDA-MB-231 cells were cultured in vitro. β-Catenin overexpression and knockdown plasmids were constructed and transfected into MDA-MB-231 cells. The optimal XJW-containing serum （4 g·kg^-1） according to previous studies was used for β-catenin intervention and overexpression experiments. The groups for intervention/overexpression experiments included intervention/overexpression blank group， β-catenin intervention/overexpression group， intervention/overexpression blank + XJW group， and β-catenin intervention/overexpression + XJW group. Cell morphology was observed under a microscope. Flow cytometry was used to detect and record apoptosis rates. Western blot was performed to measure apoptosis-related proteins ［B-cell lymphoma 2 （Bcl-2）， Bcl-2-associated X protein （Bax）， and active-Caspase-3］ and EMT-related proteins （E-cadherin， N-cadherin， and vimentin）. Real-time polymerase chain reaction （Real-time PCR） was used to detect β-catenin mRNA expression levels in different groups. ResultsIntervention experiment results showed that compared with the intervention blank group， the β-catenin intervention group and the intervention blank + XJW group showed increased apoptosis rates （P<0.05， P<0.01）， elevated protein levels of Bax， active Caspase-3， and E-cadherin （P<0.05， P<0.01）， and decreased protein levels of Bcl-2 and Vimentin （P<0.05， P<0.01）. β-catenin mRNA expression was reduced in the β-catenin intervention group （P<0.05， 0.63 ± 0.15） and the intervention blank + XJW group （P<0.05， 0.79 ± 0.33）. Compared with the β-catenin intervention group， the β-catenin intervention + XJW group exhibited an increased apoptosis rate （P<0.01）， elevated Bax and active Caspase-3 protein levels （P<0.05， P<0.01）， and decreased Bcl-2， N-cadherin， and Vimentin protein levels （P<0.05）. β-catenin mRNA expression was further reduced in the β-catenin intervention + XJW group （P<0.01， 0.22 ± 0.08）. Compared with the intervention blank + XJW group， the β-catenin intervention + XJW group showed an increased apoptosis rate （P<0.01）， elevated Bax， active Caspase-3， and E-cadherin protein levels （P<0.05， P<0.01）， and decreased Bcl-2， N-cadherin， and vimentin protein levels （P<0.05， P<0.01）. β-catenin mRNA expression was also reduced （P<0.05）. Overexpression experiment results showed that compared with the overexpression blank group， the β-catenin overexpression group exhibited a reduced apoptosis rate （P<0.01）， while the overexpression blank + XJW group showed an increased apoptosis rate （P<0.05）. In the β-catenin overexpression and β-catenin overexpression + XJW groups， Bax and E-cadherin protein levels decreased （P<0.05， P<0.01）， while Bcl-2， N-cadherin， and vimentin levels increased （P<0.05）. In the overexpression blank + XJW group， Bax and E-cadherin levels increased （P<0.05， P<0.01）， while Bcl-2， N-cadherin， and vimentin levels decreased （P<0.05， P<0.01）. β-catenin mRNA expression increased in the β-catenin overexpression group （P<0.01， 7.26 ± 1.03） but decreased in the overexpression blank + XJW group （P<0.05， 0.73 ± 0.14）. Compared with the β-catenin overexpression group， the β-catenin overexpression + XJW group showed an increased apoptosis rate （P<0.01）， elevated Bax and E-cadherin levels （P<0.05）， and decreased N-cadherin and vimentin levels （P<0.05）. β-catenin mRNA expression was reduced （P<0.05， 4.65 ± 1.02）. Compared with the overexpression blank + XJW group， the β-catenin overexpression + XJW group exhibited a reduced apoptosis rate （P<0.01）， decreased Bax and E-cadherin levels （P<0.01）， and increased Bcl-2， N-cadherin， and Vimentin levels （P<0.05）. β-catenin mRNA expression increased （P<0.01）. ConclusionXJW-containing serum inhibits breast cancer cell proliferation by suppressing EMT， which is associated with the regulation of the Wnt/β-catenin pathway.

Background Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children and adolescents. Current research suggests that environmental factors, such as per- and polyfluoroalkyl substances (PFAS), may be associated with an increased risk of ADHD in offspring. However, most epidemiological evidence originates from non-Chinese populations, with limited research investigating the association between prenatal PFAS and ADHD-like symptoms in Chinese school-aged children. Objective To examine the association between prenatal PFAS exposure and ADHD-like symptoms in 7-year-old children. Methods Based on the Shanghai Birth Cohort, this study included 488 mother-child pairs. PFAS were measured in maternal serum during the second trimester using ultra-performance liquid chromatography-tandem mass spectrometry. The analysis focused on eight specific compounds from three PFAS categories [perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), and perfluorohexanesulfonic acid (PFHxS)]. The hyperactivity subscale of the Strengths and Difficulties Questionnaire (SDQ) was used to assess ADHD-like symptoms in children at age 7. Basic demographic information was collected via questionnaires and medical records. Negative binomial regression models were used to evaluate the relationship between individual exposures to the three typical PFAS categories (PFOA, PFOS, and PFHxS) and children's ADHD-like symptoms, while the bayesian kernel machine regression (BKMR) mixture model was employed to assess the overall effect of PFAS mixture exposure on ADHD-like symptoms. Results The detection rates of the eight target PFAS in maternal second-trimester serum were all above 85%, with PFOA exhibiting the highest median concentration (10.21 ng·mL⁻¹). Overall, 14.75% of the children exhibited ADHD-like symptoms. Results from the negative binomial regression models showed that second-trimester exposures to PFOA (IRR=1.15, 95%CI: 1.05, 1.26), n-PFOS (IRR=1.08, 95%CI: 1.01, 1.15), 6m-PFOS (IRR=1.13, 95%CI: 1.05, 1.21), and 1m-PFOS (IRR=1.11, 95%CI: 1.03, 1.18) were associated with an increased risk of ADHD-like symptoms in 7-year-old children. Stratified analyses suggested potentially statistically significant associations in girls [e.g., for PFOA, boys vs. girls: 1.09 (0.96, 1.23) vs. 1.25 (1.09, 1.44), P-int=0.31]. The BKMR mixture model indicated that the risk of ADHD-like symptoms trended upward with increasing PFAS mixture concentrations, although this association was statistically significant only among girls (P < 0.05). Conclusion Prenatal PFAS exposure may be associated with an increased risk of ADHD-like symptoms in 7-year-old children, and this adverse association appears to be more prominent in girls.

Parkinson's disease （PD）， with its incidence increasing year by year and its onset age gradually becoming younger， has become a major chronic multisystem movement disorder that threatens public health. The microbiota-gut-brain axis （MGBA） is a bidirectional communication system connecting the enteric nervous system and the central nervous system. Its core functions rely on the synergistic interactions among gut microbiota， neural signal transmission， endocrine regulation， and immune interactions， and it plays an indispensable role in maintaining gut-brain dynamic homeostasis， regulating neurotransmitter metabolism， and modulating inflammatory responses. Current studies have found that the gut microbiota of patients with PD exhibits dual dysbiosis characterized by the enrichment of opportunistic pathogens and beneficial bacteria， accompanied by abnormal metabolite levels， which accumulate and trigger neuroinflammation， demonstrating the pivotal regulatory role of the MGBA in the early pathology of PD. Furthermore， this article summarizes Chinese medicines， their active components， and compound formulas that may prevent and treat PD through intervention in the MGBA. These agents can modulate microbial composition， suppress inflammation and oxidative stress， protect the intestinal barrier， and ameliorate dopaminergic neuron damage. By systematically summarizing the central mechanisms of the MGBA in PD and reviewing the research progress of traditional Chinese medicine （TCM） mediated regulation of this pathway in PD intervention， this article aims to provide a theoretical reference for the clinical prevention and treatment of PD and scientific research design.