OBJECTIVE To explore the main factors influencing the blood concentration of duloxetine， and provide a scientific basis for the individualized use of duloxetine. METHODS Retrospective analysis was conducted on 434 inpatients with depressive disorders at the First Hospital of Hebei Medical University， who were treated with duloxetine and underwent blood concentration monitoring between January 2022 and April 2024. The study examined the impact of various factors， including gender， age， body mass index （BMI）， gene phenotypes， combined medication， drug type （original/generic）， and genotyping results of gene single nucleotide polymorphism loci， on blood concentration and the concentration-to-dose （C/D） after dose adjustment. RESULTS The blood concentration of duloxetine was 76.65 （45.57， 130.31） ng/mL， and C/D was 0.96 （0.63， 1.60） ng·d/（mL·mg）. The blood concentration of duloxetine was positively correlated with the daily dose of administration （R2＝0.253 7， P＜0.001）. Blood concentration of duloxetine in 38.94% of patients exceeded the recommended range specified in the guidelines. Gender， age， BMI， combined use of CYP2D6 enzyme inhibitors， and CYP2D6 and CYP1A2 phenotypes had significant effects on C/D of duloxetine （P＜0.05）. CONCLUSIONS The patient’s age， gender， BMI， combined medication， and genetic phenotypes are closely related to the blood concentration of duloxetine.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

ObjectiveTo construct an intelligent model for literature screening， retrieval， and data extraction with a systematic review of coronary heart disease syndromes as an example， so as to improve the efficiency of evidence-based Chinese medicine research. MethodsBased on China National Knowledge Infrastructure （CNKI）， VIP and Wanfang Data Resource System， the articles related to coronary heart disease syndrome research published from January 1， 2000 to December 31， 2023 were retrieved. Automated tools were used to batch retrieve paper metadata. Using text similarity algorithms， papers were merged， deduplicated， and subjected to preliminary screening based on titles and abstracts. Further screening was performed using object detection and image processing technologies on the full texts and statistical tables. Natural language processing （NLP） techniques and pre-trained models were applied to extract information. ResultsThe initial search retrieved 56 255 coronary heart disease syndrome-related articles. By artificial intelligence-assisted preliminary and secondary screening， the manual verification scope was narrowed to 1075 articles. Ultimately， 646 coronary heart disease syndrome related studies were included manually. With accuracy verification showing over 90% consistency in semantic recognition and element decomposition processes， we achieved data extraction and standardization processing for both basic literature information and 38 syndrome element statistics. ConclusionBy incorporating natural language processing， pre-trained models， artificial intelligence image processing and other technologies， this study enabled efficient retrieval， screening and standardized data extraction of Chinese medicine research literature.

Metastatic dissemination is the major cause of death from breast-cancer (BC). Fusobacterium nucleatum (F.n) is widely enriched in BC and has recently been identified as one of the high-risk factors for promoting BC metastasis. Here, with an experimental model, we demonstrated that intratumoral F.n induced BC aggressiveness by transcriptionally activating Epithelial-mesenchymal transition-associated genes. Therefore, the F.n may be a potential target to prevent metastasis. Given the fact that cancer-associated fibroblasts (CAFs) are abundant in BC and located near blood vessels, we report an optogenetic system that drives CAF to in situ produce human antibacterial peptide LL37, with the characteristics of biosafety and freely intercellular trafficking, for depleting intratumoral F.n, leading to a 72.1% reduction in lung metastatic nodules number without affecting the balance of the systemic flora. Notably, mild photothermal treatment was found that could normalize CAF, contributing to synergistically inhibiting BC metastasis. In addition, the system can also simultaneously encode a gene of TNF-related apoptosis-inducing ligand to suppress the primary tumor. Together, our study highlights the potential of local elimination of tumor pathogenic bacteria to prevent BC metastasis.

Lacking therapeutic targets highlights the crucial roles of chemotherapy and radiotherapy in the clinical management of triple-negative breast cancer (TNBC). To relieve the side effects of the chemoradiotherapy combination regimen, we design and develop a self-assembled micelle nanosystem consisting of perfluorocarbon chain-modified cisplatin prodrug. By incorporating perfluorodecalin, this nanosystem can effectively carry ozone and promote irradiation-derived reactive oxygen species (ROS) production. By leveraging the perfluorocarbon sidechain, the nanosystem exhibits efficient internalization by TNBC cells and effectively escapes from lysosomal entrapment. Under X-ray irradiation, ozone-generated ROS disrupts the intracellular redox balance, thereby facilitating the release of cisplatin in a reduction-responsive manner mediated by reduced glutathione. Moreover, oxygen derived from ozone decomposition enhances the efficacy of radiotherapy by alleviating tumor hypoxia. Notably, the combination of irradiation with ozone-loaded cisplatin prodrug nano system synergistically prompts antitumor efficacy and reduces cellular/systemic toxicity in vitro and in vivo. Furthermore, the combo regimen remodels the tumor microenvironment into an immune-favored state by triggering immunogenic cell death and relieving hypoxia, which provides a promising foundation for a combination regimen of immunotherapy. In conclusion, our nanosystem presents a novel strategy for integrating chemotherapy and radiotherapy to optimize the efficacy and safety of TNBC clinical treatment.

OBJECTIVES: To investigate the impact of high expression of transmembrane and coiled helix structural domain 1 (TMCO1) on prognosis of gastric cancer and the possible mechanisms. METHODS: TMCO1 expression in gastric cancer and its effect on gastric cancer progression and prognosis were analyzed using publicly available databases and clinical data of patients undergoing radical surgery in our hospital, and its possible biological functions were explored using KEGG and GO analyses. In gastric cancer HGC-27 cells, the effects of lentivirus-mediated TMCO1 overexpression and TMCO1 silencing on cell apoptosis, proliferation, invasion and migration were examined. RESULTS: TMCO1 expression was significantly elevated in gastric cancer tissues (P<0.05), and its high expression was positively correlated with cancer progression (P<0.001) and a lowered postoperative 5-year survival rate of the patients (P<0.05). Bioinformatic analyses suggested that TMCO1 may affect gastric cancer cell apoptosis via Wnt signaling. In HGC-27 cells, TMCO1 overexpression significantly promoted tumor cell proliferation, inhibited cell apoptosis, and enhanced cell migration and invasion, whereas TMCO1 silencing produced the opposite effects. Western blotting showed that β-catenin levels were significantly upregulated in TMCO1-overexpressing cells and downregulated in cells with TMCO1 silencing. CONCLUSIONS TMCO1 is overexpressed in gastric cancer tissues, and its high expression promotes gastric cancer progression and affects long-term prognosis of the patients possibly by activating the Wnt/ β-catenin signaling pathway to inhibit apoptosis of gastric cancer cells.
Humans ; Stomach Neoplasms/metabolism* ; Apoptosis ; Prognosis ; Cell Line, Tumor ; Cell Proliferation ; Cell Movement ; Wnt Signaling Pathway ; beta Catenin/metabolism* ; Gene Expression Regulation, Neoplastic

Hemorrhagic shock is a common clinical emergency that can aggravate cell injury after resuscitation. Astrocytes are crucial for the survival of neurons because they regulate the surrounding ionic microenvironment of neurons. Although hemorrhagic shock and resuscitation (HSR) injury can impair cognition, it remains unclear how this insult directly affects astrocytes. In this study, we established an HSR model by bleeding and re-transfusion in mice. The social interaction test and new object recognition test were applied to evaluate post-operative cognitive changes, and the results suggest that mice experience cognitive impairment following exposure to HSR. In the HSR group, the power spectral density of β and γ oscillations decreased, and the coupling of the θ oscillation phase and γ oscillation amplitude was abnormal, which indicated abnormal neuronal oscillation and cognitive impairment after HSR exposure. In brief, cognitive impairment in mice is strongly correlated with Ca²⁺ signal strength in lateral septum astrocytes following HSR.
Animals ; Astrocytes/metabolism* ; Shock, Hemorrhagic/metabolism* ; Resuscitation/adverse effects* ; Male ; Mice ; Calcium Signaling/physiology* ; Mice, Inbred C57BL ; Septal Nuclei/metabolism* ; Cognitive Dysfunction/etiology* ; Disease Models, Animal ; Cognition Disorders/etiology*

Protrusive facial deformities, characterized by the forward displacement of the teeth and/or jaws beyond the normal range, affect a considerable portion of the population. The manifestations and morphological mechanisms of protrusive facial deformities are complex and diverse, requiring orthodontists to possess a high level of theoretical knowledge and practical experience in the relevant orthodontic field. To further optimize the correction of protrusive facial deformities, this consensus proposes that the morphological mechanisms and diagnosis of protrusive facial deformities should be analyzed and judged from multiple dimensions and factors to accurately formulate treatment plans. It emphasizes the use of orthodontic strategies, including jaw growth modification, tooth extraction or non-extraction for anterior teeth retraction, and maxillofacial vertical control. These strategies aim to reduce anterior teeth and lip protrusion, increase chin prominence, harmonize nasolabial and chin-lip relationships, and improve the facial profile of patients with protrusive facial deformities. For severe skeletal protrusive facial deformities, orthodontic-orthognathic combined treatment may be suggested. This consensus summarizes the theoretical knowledge and clinical experience of numerous renowned oral experts nationwide, offering reference strategies for the correction of protrusive facial deformities.
Humans ; Orthodontics, Corrective/methods* ; Consensus ; Malocclusion/therapy* ; Patient Care Planning ; Cephalometry

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic