ObjectiveTo investigate the effect of Yuejuwan on lipid metabolism in serum， prefrontal cortex and hippocampus of depressed mice based on lipidomics， and to explore the potential pathways for improving lipid metabolism to prevent depression. MethodsSeven-week-old C57BL/6 mice were randomly divided into blank group， model group， Yuejuwan group（3.6 g·kg^-1） and fluoxetine group（10 mg·kg^-1）， and chronic unpredictable mild stress（CUMS） was used to establish the depression model. After 3 weeks of modeling， each administration group was gavaged with the corresponding drug solution according to the dose， and mice in the blank and model groups were given an equal volume of deionised water by gavage， one time/d for 2 weeks. After administration， the antidepressant effect of Yuejuwan was evaluated by neurobehavioral indices such as sucrose preference test， open field test， tail suspension test and forced swimming test. An automatic biochemical analyzer was used to measure contents of total cholesterol（TC）， triglyceride（TG）， low-density lipoprotein cholesterol（LDL-C）， high-density lipoprotein cholesterol（HDL-C）， aspartate aminotransferase（AST） and alanine aminotransferase（ALT） in mouse serum. Lipidomic analysis of mouse serum， prefrontal cortex and hippocampus was performed based on ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap mass spectrometry（UPLC-LTQ-Orbitrap-MS）， and the expression of mammalian target of rapamycin（mTOR）， ribosomal protein S6 kinase（S6K）， phosphorylation（p）-mTOR， p-S6K in gastric tissues of mice was detected by Western blot. ResultsCompared with the blank group， mice in the model group exhibited significantly reduced sucrose preference rate and center movement time in the open field test（P<0.01）， the immobility times in the tail suspension test and forced swimming test were significantly increased（P<0.01）， and serum levels of TC， TG， LDL-C， HDL-C， AST and ALT were significantly elevated（P<0.05， P<0.01）. Compared with the model group， the Yuejuwan group showed a significant increase in the sucrose preference rate and center movement time in the open field test（P<0.01）， the immobility times in the tail suspension test and forced swimming test were significantly reduced（P<0.01）， and the serum levels of TC， TG， LDL-C， AST and ALT were significantly decreased（P<0.05， P<0.01）. Lipidomic analysis revealed that Yuejuwan had a significant effect on lipid metabolism in serum， prefrontal cortex and hippocampus of depressed mice， and The differential lipid metabolites were mainly enriched in the metabolic pathways of glycerophospholipid metabolism， sphingolipid signaling， and glycosylphosphatidylinositol-anchored protein biosynthesis， among which the glycerophospholipid metabolic pathway was the most significant. Western blot results showed that compared with the blank group， the relative expression levels of p-mTOR/mTOR and p-S6K/S6K in the gastric tissues of mice in the model group were significantly increased（P<0.01）. In comparison with the model group， the relative expression levels of p-mTOR/mTOR and p-S6K/S6K in the gastric tissues of mice in the Yuejuwan group were significantly decreased（P<0.01）. ConclusionThe intervention of Yuejuwan on lipid metabolism is one of the potential pathways for its antidepressant effect， which may be related to the regulation of mTOR/S6K signaling pathway upstream of lipid metabolism in the gastric tissues.

Objective To develop an artificial intelligence (AI)-driven lung cancer database by structuring and standardizing clinical data, enabling advanced data mining for lung cancer research, and providing high-quality data for real-world studies. Methods Building on the extensive clinical data resources of the Department of Thoracic Surgery at Peking Union Medical College Hospital, this study utilized machine learning techniques, particularly natural language processing (NLP), to automatically process unstructured data from electronic medical records, examination reports, and pathology reports, converting them into structured formats. Data governance and automated cleaning methods were employed to ensure data integrity and consistency. Results As of September 2024, the database included comprehensive data from 18 811 patients, encompassing inpatient and outpatient records, examination and pathology reports, physician orders, and follow-up information, creating a well-structured, multi-dimensional dataset with rich variables. The database’s real-time querying and multi-layer filtering functions enabled researchers to efficiently retrieve study data that meet specific criteria, significantly enhancing data processing speed and advancing research progress. In a real-world application exploring the prognosis of non-small cell lung cancer, the database facilitated the rapid analysis of prognostic factors. Research findings indicated that factors such as tumor staging and comorbidities had a significant impact on patient survival rates, further demonstrating the database’s value in clinical big data mining. Conclusion The AI-driven lung cancer database enhances data management and analysis efficiency, providing strong support for large-scale clinical research, retrospective studies, and disease management. With the ongoing integration of large language models and multi-modal data, the database’s precision and analytical capabilities are expected to improve further, providing stronger support for big data mining and real-world research of lung cancer.

Objective: To investigate the prevalence and influencing factors of menopausal syndrome among postmenopausal women in Pan'an County, Zhejiang Province, so as to provide the basis for guiding the health management of postmenopausal women. Methods: From May 2023 to April 2024, the postmenopausal women aged 40 to 69 years in Pan'an County were selected using the random cluster sampling method. Demographic information, lifestyle and prevalence of gynecological diseases were collected through questionnaire surveys. The prevalence of menopausal syndrome was assessed by modified Kupperman Score Scale. Factors affecting menopausal syndrome were analyzed by a multivariable logistic regression model. Results: A total of 816 postmenopausal women were surveyed, with an mean age of (57.63±2.92) years and a mean natural menopause age of (49.85±2.13) years. There were 574 cases with menopausal syndrome, with a prevalence of 70.34%. Flashes and sweating, insomnia and irritability were common symptoms, accounting for 62.87%, 47.43% and 41.18%, respectively. Multivariable logistic regression analysis showed that monthly personal income of ≤5 000 yuan (<3 000 yuan, OR=3.124, 95%CI: 1.829-5.335; 3 000-5 000 yuan, OR=2.399, 95%CI: 1.370-4.201) and having gynecological diseases (OR=1.970, 95%CI: 1.292-3.004) were associated with a higher risk of menopausal syndrome, while average (OR=0.141, 95%CI: 0.072-0.276) or sufficient sleep quality (OR=0.095, 95%CI: 0.049-0.185) were associated with a lower risk of menopausal syndrome. Conclusion The prevalence of menopausal syndrome among postmenopausal women in Pan'an County is relatively high, and is mainly influenced by personal economic status, sleep quality and the presence of gynecological diseases.

Objective Wearable devices refer to a class of monitoring devices that can be tightly integrated with the human body and are designed to continuously monitor individual's activity without impeding or restricting the user's normal activities in the process. With the rapid advancement of chips, sensors, and artificial intelligence technologies, such devices have been widely used for patients with cardiovascular diseases who require continuous health monitoring. These patients require continuous monitoring of a number of physiological indicators to assess disease progression, treatment efficacy, and recovery in the early stages of the disease, during the treatment, and in the recovery period. Traditional monitoring methods require patients to see a doctor on a regular basis with the help of fixed devices and analysis by doctors, which not only increases the financial burden of patients, but also consumes medical resources and time. However, wearable devices can collect data in real time and transmit it directly to doctors via the network, thus providing an efficient and cost-effective monitoring solution for patients. In this paper, we will review the applications, advantages and challenges of wearable devices in the treatment of cardiovascular diseases, as well as the outlook for their future applications.

Gastric cancer （GC） has an insidious onset and is mostly diagnosed in the middle and late stages after clinical detection. It is one of the malignant tumors with high incidence and mortality rates in the world. At present， the treatment plans are optimized mainly in terms of surgery， radiotherapy， and intervention， while the endpoints of clinical trials， such as patients' overall survival， progression-free survival， and disease-free survival， are still unsatisfactory. Therefore， effectively delaying the dynamic inflammation-cancer transformation has become an urgent bottleneck in the prevention and treatment of GC. In 1920s， Professor Otto Warburg discovered the phenomenon that tumor cells can accelerate glycolysis. Since then， the abnormal metabolic network inside tumor cells has gradually entered into researchers' view， and the hot academic research topic of metabolic reprogramming has been proposed. Tumor cells can meet their own energy consumption and adapt to external changes by adjusting their metabolic pathways to achieve rapid proliferation. In recent years， traditional Chinese medicine （TCM） is resolutely pursuing innovation in inheritance and the continuous refinement of research has led to the precision-oriented transition of TCM theories. Therefore， linking TCM with the treatment of tumors and precancerous diseases has certain research connotations. The searching and review of the publications in this field revealed that the number of publications in tumor-related metabolism increased dramatically， while there were only a few studies using TCM as a therapeutic solution. The research group has long been committed to the study of precancerous lesions of gastric cancer （PLGC） in Chinese and Western medicine. This article explained the dynamic process of inflammation-cancer transformation from the perspective of spleen deficiency-Qi stagnation-collateral stasis. The molecules of hypoxia-inducible factor （HIF）-1α， cancer-Myc （c-Myc）， apolipoprotein E （APOE） and pyruvate kinase M2 （PKM2） were selected to reflect the biological connotation of inflammation-cancer transformation. The current achievements of TCM in regulating the metabolic reprogramming to intervene in inflammation-cancer transformation were summarized， with a view to providing more information for TCM to intervene in the inflammation-cancer transformation of gastric mucosa.

Gastric cancer （GC） has an insidious onset and is mostly diagnosed in the middle and late stages after clinical detection. It is one of the malignant tumors with high incidence and mortality rates in the world. At present， the treatment plans are optimized mainly in terms of surgery， radiotherapy， and intervention， while the endpoints of clinical trials， such as patients' overall survival， progression-free survival， and disease-free survival， are still unsatisfactory. Therefore， effectively delaying the dynamic inflammation-cancer transformation has become an urgent bottleneck in the prevention and treatment of GC. In 1920s， Professor Otto Warburg discovered the phenomenon that tumor cells can accelerate glycolysis. Since then， the abnormal metabolic network inside tumor cells has gradually entered into researchers' view， and the hot academic research topic of metabolic reprogramming has been proposed. Tumor cells can meet their own energy consumption and adapt to external changes by adjusting their metabolic pathways to achieve rapid proliferation. In recent years， traditional Chinese medicine （TCM） is resolutely pursuing innovation in inheritance and the continuous refinement of research has led to the precision-oriented transition of TCM theories. Therefore， linking TCM with the treatment of tumors and precancerous diseases has certain research connotations. The searching and review of the publications in this field revealed that the number of publications in tumor-related metabolism increased dramatically， while there were only a few studies using TCM as a therapeutic solution. The research group has long been committed to the study of precancerous lesions of gastric cancer （PLGC） in Chinese and Western medicine. This article explained the dynamic process of inflammation-cancer transformation from the perspective of spleen deficiency-Qi stagnation-collateral stasis. The molecules of hypoxia-inducible factor （HIF）-1α， cancer-Myc （c-Myc）， apolipoprotein E （APOE） and pyruvate kinase M2 （PKM2） were selected to reflect the biological connotation of inflammation-cancer transformation. The current achievements of TCM in regulating the metabolic reprogramming to intervene in inflammation-cancer transformation were summarized， with a view to providing more information for TCM to intervene in the inflammation-cancer transformation of gastric mucosa.

Gentianopsis barbata (G. barbata) represents a significant plant species with considerable ornamental and medicinal value in China. This investigation sought to elucidate the primary constituents within the plant and investigate their pharmacological properties. Fifty triterpenoids (1-50), including nine previously undescribed compounds (1, 2, 7, 10, 20, 28, 29, 37, and 41) were isolated and characterized from the whole plants of G. barbata. Notably, compounds 1 and 2 exhibited the novel 3,4;9,10-diseco-24-homo-cycloartane triterpenoid skeleton. The isolated triterpenoids demonstrated substantial anti-inflammatory activity through inhibition of tumor necrosis factor α (TNF-α) and interleukin-6 (IL-6) cytokine secretion in LPS-induced RAW264.7 macrophages, and hepatoprotective effects by preventing tert-butyl hydroperoxide (t-BHP)-induced oxidative injury in HepG2 cells. These results demonstrate both the presence of diverse triterpenoids in G. barbata and their therapeutic potential for inflammatory and hepatic conditions, providing scientific evidence supporting the clinical application of this traditional Mongolian medicinal plant.
Triterpenes/isolation & purification* ; Mice ; Anti-Inflammatory Agents/isolation & purification* ; Animals ; Humans ; RAW 264.7 Cells ; Hep G2 Cells ; Interleukin-6/genetics* ; Tumor Necrosis Factor-alpha/genetics* ; Medicine, Mongolian Traditional ; Macrophages/immunology* ; Protective Agents/isolation & purification* ; Liver/drug effects* ; Gentianaceae/chemistry* ; Plant Extracts/chemistry* ; Molecular Structure

To analyze potential adverse drug events(ADEs) associated with ustekinumab and upadacitinib in the treatment of inflammatory bowel disease(IBD) based on an international authoritative database, thereby providing evidence for clinical medication safety.

The clinical practice guidelines of traditional Chinese medicine （TCM） have problems such as limited clinical application and unclear implementation effects， which may be related to the lack of clinical practice evidence. To provide reliable and precise evidence for clinical practice， this article proposes a model of combining TCM guidelines with real-world study， which includes 4 steps. Firstly， during the implementation process of the guidelines， a high-quality research database is established. Secondly， the recommendations in the guidelines are evaluated based on the established database in multiple dimensions， including applicability， effectiveness， safety， and cost-effectiveness， and thus their effectiveness in practical applications can be determined. Thirdly， based on the established database， core prescriptions are identified， and the targeted populations and medication plans are determined. That is， the best treatment regimen is established based on the analysis of abundant clinical data regarding the effects of different medication frequencies， dosages， and duration on efficacy. Fourthly， the guidelines are updated according to the real-world evidence. The research based on this model can provide real-world evidence for ancient and empirical prescriptions， improving their application in clinical practice. Moreover， this model can reduce research costs and improve research efficiency. When applying this model， researchers need to pay attention to the quality of real-world evidence， ensuring that it can truly reflect the situation in clinical practice. In addition， importance should be attached to the clinical application of guideline recommendations， ensuring that doctors can conduct standardized diagnosis and treatment according to the guidelines. Finally， full-process participation of multidisciplinary experts is encouraged to ensure the comprehensiveness and scientificity of the study. In conclusion， the application of this model will contribute to the development of TCM guidelines responsive to the needs of clinical practice and achieve the goal of promoting the homogenization of TCM clinical diagnosis and treatment.

As a supplement to randomized controlled trials， observational studies can provide evidence for the effectiveness of traditional Chinese medicine （TCM） treatment measures. They can also study influencing factors of diseases， etiology， and prognosis. However， there is a confounding effect due to the lack of randomization， which seriously affects the causal inference between the study factors and the outcome， resulting in confounding bias. Therefore， identifying and controlling confounding factors are key issues to be addressed in TCM observational studies. According to the causal network and the characteristics of TCM theory， confounding factors can be categorized into measured and unmeasured confounding factors. In addition， attention must be paid to identifying confounding factors and intermediate variables， as well as the interaction between confounding factors and study factors. For methods of controlling confounding factors， measured confounding factors can be controlled by stratification， multifactor analysis， propensity scores， and disease risk scores. Unmeasured and unknown confounding factors can be corrected using instrumental variable methods， difference-in-difference methods， and correction for underlying event rate ratios. Correcting and controlling confounding factors can ensure a balance between groups， and confounding bias can be reduced. In addition， methods such as sensitivity analysis and determination of interactions make the control of confounding factors more comprehensive. Due to the unique characteristics of TCM， observational studies of TCM face unique challenges in identifying and controlling confounding factors， including the ever-changing TCM treatment measures received by patients， the often-overlooked confounding effects in the four diagnostic information of TCM， and the lack of objective criteria for TCM evidence-based diagnosis. Some scholars have already conducted innovative explorations to address these issues， providing a methodological basis for conducting higher-quality TCM observational studies， so as to obtain more rigorous real-world evidence of TCM and gradually develop quality evaluation criteria for OS that are consistent with the characteristics of TCM.