Objective: To evaluate the safety and efficacy of the retroauricular transmeatal approach in the treatment of condylar head and neck fractures, and to provide a reference for clinical practice. Methods: This study has been reviewed and approved by the institutional medical ethics committee and has obtained informed consent from the patients. A retrospective analysis was conducted on the clinical data of patients with condylar head and neck fractures treated via the retroauricular transmeatal approach between March and October 2024. Postoperative follow-up was performed for at least 3 months, including clinical and radiographical evaluations. The assessed parameters included facial nerve function, temporal region numbness, hematoma, infection, salivary fistula, mouth opening, malocclusion, mandibular movement function, temporomandibular joint (TMJ) pain and clicking, external auditory canal (EAC) stenosis, hearing function impairment, surgical scar concealment, postoperative reduction and fixation outcomes. Results: A total of 16 patients with condylar fractures were treated via the retroauricular transmeatal approach, including 10 unilateral and 6 bilateral cases. Specifically, 18 sides were condylar head fractures, and 4 sides were condylar neck fractures. All patients achieved a House-Brackmann Grade I, indicating normal facial nerve function postoperatively. On postoperative day 1, 3 sides experienced temporal numbness in the temporal region on the surgical side, with spontaneous resolution in all cases. All patients recovered after surgery without hematoma, infection, or salivary fistula. Limited mouth opening was improved (14 cases with restricted mouth opening preoperatively vs. 3 cases postoperatively). No malocclusion occurred in any patient. All patients achieved satisfactory recovery of postoperative mandibular movement function, manifested as restored range of motion without pain. No TMJ clicking was observed within 3 months after surgery. One keloid-prone patient developed progressive EAC stenosis (2 mm lumen constriction) accompanied by conductive hearing impairment, which recovered after dilation therapy. All patients were satisfied with the aesthetic outcomes. Radiographically parametric assessment demonstrated satisfactory fracture reduction and fixation; with no loosening of titanium plates or screws. Conclusion The retroauricular transmeatal approach effectively reduces the risk of facial nerve injury and salivary fistulas formation with providing concealed scarring and high patient satisfaction. However, caution should be exercised regarding EAC stenosis, especially for keloid-prone patients.

Polycystic ovary syndrome （PCOS） is a common endocrine and metabolic disorder among women of reproductive age. Hyperandrogenism （HA）， one of its core pathological features， is closely associated with the clinical manifestations and metabolic complications of the disease. Current western medical treatments for PCOS-HA mainly include anti-androgen therapy and ovulation induction， such as short-acting oral contraceptives like Diane-35 and Yasmin. However， long-term use of these medications may result in adverse reactions like increasing the risk of liver dysfunction and exacerbating lipid metabolism disorders， with unsatisfactory long-term efficacy when used alone. Traditional Chinese medicine offers unique advantages in the treatment of PCOS-HA due to its holistic approach and multi-target regulatory mechanisms. In the view of traditional Chinese medicine， PCOS-HA is classified under the categories such as "delayed menstruation"， "amenorrhea"， and "infertility"， with kidney deficiency as the root， as well as liver stagnation and spleen deficiency as the manifestations. Phlegm and blood stasis are considered to be intertwined throughout the disease course. Modern studies have shown that traditional Chinese medicine is significantly effective in improving the androgen levels， restoring ovulation， and improving insulin resistance in PCOS-HA patients. Representative prescriptions， such as Erxian Tang， Jiawei Xiaoyaosan， Guizhi Fulingwan， and Cangfu Daotantang， exert therapeutic effects through various mechanisms including regulation of the hypothalamic-pituitary-ovarian axis， reduction of ovarian androgen synthase activity， improvement of insulin signaling pathways， and inhibition of inflammation and oxidative stress， which demonstrates the characteristics of comprehensive treatment with traditional Chinese medicine. Based on the perspectives of etiology and pathogenesis of traditional Chinese medicine， modern medical cognition， typical prescriptions， and action mechanisms， this paper reviewed the research progress of traditional Chinese medicine in the treatment of PCOS-HA， aiming to provide a reference for in-depth research and clinical applications in this field.

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.

Myopia is a highly prevalent refractive error worldwide, with scleral remodeling accompanying excessive axial elongation being one of its core pathological features. As the crucial outer layer responsible for maintaining eyeball morphology and biomechanical stability, the sclera plays a decisive role in the pathogenesis and progression of myopia through abnormal alterations in its cellular components, extracellular matrix(ECM)metabolism, and regulatory networks. This review systematically summarizes recent research advances in scleral remodeling. It focuses on elucidating, from cellular and molecular perspectives, the mechanisms by which dysfunction of scleral fibroblasts, dysregulation of ECM metabolism(e.g., decreased collagen content, disrupted MMP-2/TIMP-2 balance), and complex regulatory networks involving multiple signaling pathways such as TGF-β, Wnt/β-catenin, and MAPK drive scleral thinning and reduced mechanical strength. Concurrently, the review provides a comprehensive analysis of the potential roles and existing controversies regarding factors like inflammatory responses and novel regulatory axes(e.g., FOXM1/METTL3/APOA1)in scleral remodeling. Furthermore, it discusses the current research status and application prospects of sclera-targeted intervention strategies(e.g., modulating specific pathways, supplementing exogenous factors), aiming to provide a theoretical basis and directional reference for a deeper understanding of myopia pathogenesis and the development of new prevention and treatment approaches.

Dry eye disease(DED)is a common ocular surface disorder worldwide, primarily characterized by a loss of homeostasis of the tear film, and frequently associated with meibomian gland dysfunction(MGD), decreased tear film stability, ocular discomfort, and visual impairment. In recent years, factors such as the widespread use of digital devices,the aging population, and environmental changes have contributed to a significant increase in its global prevalence, making it a major public health concern. Red light therapy(RLT), also known as low-level laser therapy(LLLT)or photobiomodulation(PBM), is a non-invasive treatment that utilizes low-energy red or near-infrared light to irradiate tissues. It exerts photobiomodulatory effects to promote cellular repair and functional recovery. This therapy has demonstrated considerable potential in treating various ocular conditions. Its broader clinical application could improve therapeutic outcomes, alleviate patient discomfort and financial burden, and reduce the consumption of healthcare resources, thereby yielding significant socio-economic benefits. This paper systematically reviews the multifaceted mechanisms and application prospects of RLT in managing DED, including its anti-inflammatory effects, improvement of meibomian gland function, promotion of conjunctival goblet cell repair, and alleviation of visual fatigue, aiming to provide a theoretical foundation and practical reference for its clinical adoption.

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）］

Polycystic ovary syndrome （PCOS） is a common endocrine and metabolic disorder among women of reproductive age. Hyperandrogenism （HA）， one of its core pathological features， is closely associated with the clinical manifestations and metabolic complications of the disease. Current western medical treatments for PCOS-HA mainly include anti-androgen therapy and ovulation induction， such as short-acting oral contraceptives like Diane-35 and Yasmin. However， long-term use of these medications may result in adverse reactions like increasing the risk of liver dysfunction and exacerbating lipid metabolism disorders， with unsatisfactory long-term efficacy when used alone. Traditional Chinese medicine offers unique advantages in the treatment of PCOS-HA due to its holistic approach and multi-target regulatory mechanisms. In the view of traditional Chinese medicine， PCOS-HA is classified under the categories such as "delayed menstruation"， "amenorrhea"， and "infertility"， with kidney deficiency as the root， as well as liver stagnation and spleen deficiency as the manifestations. Phlegm and blood stasis are considered to be intertwined throughout the disease course. Modern studies have shown that traditional Chinese medicine is significantly effective in improving the androgen levels， restoring ovulation， and improving insulin resistance in PCOS-HA patients. Representative prescriptions， such as Erxian Tang， Jiawei Xiaoyaosan， Guizhi Fulingwan， and Cangfu Daotantang， exert therapeutic effects through various mechanisms including regulation of the hypothalamic-pituitary-ovarian axis， reduction of ovarian androgen synthase activity， improvement of insulin signaling pathways， and inhibition of inflammation and oxidative stress， which demonstrates the characteristics of comprehensive treatment with traditional Chinese medicine. Based on the perspectives of etiology and pathogenesis of traditional Chinese medicine， modern medical cognition， typical prescriptions， and action mechanisms， this paper reviewed the research progress of traditional Chinese medicine in the treatment of PCOS-HA， aiming to provide a reference for in-depth research and clinical applications in this field.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective To elucidate the changes in the gut microbiota and molecular mechanism of huaier in enhancing the efficacy of oxaliplatin (OXA) chemotherapy in gastric cancer (GC). Methods The effects of huaier on the gut microbiota structure and intestinal barrier function in MKN45-bearing mice were analyzed by using 16S rRNA sequencing, RT-qPCR, and IHC. UPLC-MS and network pharmacology, as well as in vivo experimental approaches, were employed to investigate the key bioactive constituents of huaier systematically and elucidate the underlying mechanisms by which huaier exerts therapeutic effects against GC. The expression of the PI3K/AKT/SREBP pathway was detected in cancer cells and tissues via Western blot analysis. The safety profile of huaier combined with OXA was verified through serum biochemistry and HE-stained tissue section analyses. Results Huaier inhibited the PI3K/AKT/SREBP pathway by increasing the abundance of Akkermansia muciniphila, reduced lipid droplet deposition, and ultimately enhanced the sensitivity to OXA in the treatment of GC. Conclusion This study demonstrates the value of huaier in gastric cancer treatment by enhancing chemosensitivity and provides novel insights into its systemic therapeutic effects through molecular mechanisms and gut microbiota modulation.

ObjectiveTo analyze the research hotspots and development trends of brain-computer interface (BCI) in the treatment for spinal cord injury (SCI). MethodsRelevant literatures on BCI applied in SCI treatment, published from the inception of the Web of Science Core Collection to July, 2025, were retrieved. Visualization analysis was performed using CiteSpace, VOSviewer and Tableau Desktop. ResultsA total of 437 literatures were included, and the annual number of publications showed an overall increasing trend. The United States ranked first in the number of publications; Graz University of Technology was the institution with the highest number of publication; Gernot R Mueller-Putz was the most productive author, while Jonathan R Wolpaw was the most cited author. Brain-computer interface and artificial intelligence were identified as the high-frequency and bursting keywords in this field. The researches were characterized by the cross-integration of five core disciplines: neuroscience and rehabilitation medicine, biomedical engineering, computer science and artificial intelligence, neurophysiology, and materials science. ConclusionResearches on BCI in SCI treatment are accelerating continuously, and technological integration is becoming the core trend.