ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Ductular reaction （DR） refers to the adaptive pathological changes that occur after hepatobiliary injury， and it is essentially a repair response involving the proliferation， fibrosis， and inflammation of biliary epithelial cell （BEC）. With the understanding of the biological function of BEC， the potential value of DR in disease prognosis and treatment has gradually become a research hotspot. This article systematically reviews the molecular mechanism of DR， its potential as a therapeutic target， and future development directions， as well as novel therapies suggested by targeting these molecular mechanisms， in order to provide a new direction for overcoming current bottlenecks in the treatment of bile duct diseases.

ObjectiveThis paper aims to explore the action and molecular mechanism of modified Tongluo Tangtai Formula（MTLTT） on myelin damage in diabetic peripheral neuropathy （DPN） based on network pharmacology and in vitro experiments. MethodsThe chemical components of the MTLTT were retrieved from the Traditional Chinese Medicine Systems Pharmacology （TCMSP） database and literature， and the component targets were collected from the SwissTargetPrediction database. The targets of DPN were collected from the GeneCards， OMIM， Disgenet， and GEO databases. Gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG） enrichment analyses were performed using the Metascape database， and a network diagram was constructed using Cytoscape software. The binding actions of core components with glycogen synthase kinase 3 beta （GSK-3β） and β-catenin were analyzed by Autodock Vina. An in vitro DPN model was established by high glucose-induced Schwann cells and dorsal root ganglion cells （SCs/DRGs）. The ultrastructural morphological changes of SCs and DRGs were observed by scanning electron microscope（SEM）， and the expressions of myelin-associated glycoprotein （MAG） and myelin basic protein （MBP） were detected by immunofluorescence staining. The mRNA and protein expression levels of MAG， MBP， myelin protein 0 （P0）， peripheral myelin protein 22 （PMP22）， and Wnt/β-catenin signaling pathway-related protein β-catenin， GSK-3β， Wnt family member 3α （Wnt3α）， and Wnt inhibitory factor-1 （Wif-1） were detected by real-time polymerase chain reaction （Real-time PCR） and Western blot. ResultsNetwork pharmacology analysis revealed that MTLTT components may treat DPN via the Wnt signaling pathway， involving key proteins such as GSK-3β， β-catenin and Wif-1. The molecular docking results indicate that atropine， apigenin， baicalein， isoflavanone， and albiflorin have good binding activity with GSK-3β， and that all 13 core components have stable binding activity with β-catenin. Cell experiments showed that compared with the blank group， SCs and DRGs in the model group exhibited severe morphological and structural abnormalities such as disintegration， shrinkage and axonal rupture， while these abnormal changes were improved after MTLTT intervention. Immunofluorescence results indicated that the fluorescence intensity of MAG and MBP was markedly decreased in the model group relative to the blank group（P<0.01）， while MTLTT treatment obviously upregulated the expression of MAG and MBP compared with the model group （P<0.01）. Real-time PCR and Western blot assays revealed that the expression levels of myelin-related molecules MAG， MBP， P0 and PMP22 were significantly reduced in the model group （P<0.05，P<0.01）， and MTLTT remarkably increased their expression levels （P<0.05）. In the Wnt/β-catenin signaling pathway， the mRNA levels of GSK-3β， Wif-1 and Wnt3α were elevated and β-catenin mRNA expression was declined in the model group （P<0.01）. Meanwhile， the protein expressions of GSK-3β and Wif-1 were upregulated， whereas those of Wnt3α and β-catenin were downregulated （P<0.01）. Compared with the model group， MTLTT at different doses reduced the mRNA and protein levels of GSK-3β and Wif-1 to varying degrees （P<0.05）， and distinctly enhanced the protein expression of Wnt3α and β-catenin（P<0.01）. ConclusionMTLTT can alleviate high glucose-induced myelin damage. Its protective mechanism may promote myelin repair by upregulating the expression of MAG， MBP， P0 and PMP22， and the therapeutic effect is possibly associated with the activation of Wnt/β-catenin signaling pathway.

BackgroundThe global prevalence of depressive disorders is high， with a significant treatment gap remaining. Escitalopram oxalate， as a commonly used antidepressant in clinical practice， has a single target and is prone to cause adverse reactions such as gastrointestinal discomfort. The traditional Mongolian medicine Zadi-5 pills has a multi-target anti-depression mechanism and unique advantages such as improving the intestinal flora. However， there is currently a lack of randomized controlled trial evidence for the combined treatment of first-episode depression， along with insufficient research on its metabolic safety and potential drug interactions. ObjectiveTo explore the efficacy and safety of Zadi-5 pills combined with escitalopram oxalate in the treatment of the first-episode depression， so as to provide references for Mongolian medicine in depression management. MethodsA randomized controlled trial was conducted. A total of 103 patients with first-episode depression who were treated in the outpatient or inpatient departments of the Inner Mongolia Autonomous Region Mental Health Center from January 2023 to December 2024 and met the diagnostic criteria for depressive episode as defined in International Classification of Diseases， tenth edition （ICD-10） were included. Random numbers were generated using the RAND function in Excel software， and the patients were divided into the study group （n=52） and the control group （n=51）. Both groups received escitalopram oxalate treatment， starting from 5 mg/d and gradually increasing to 20 mg/d. The study group additionally received Zadi-5 pills， 13 pills per day. The treatment duration for both groups was 6 weeks. Before treatment and at the 2^nd， 4^th， and 6^th weeks of treatment， the severity of depressive symptoms was evaluated using the Hamilton Depression Scale-24 item （HAMD-24）. At these time points， blood was collected on an empty stomach at 7∶00 for the detection of liver function （aspartate aminotransferase， alanine aminotransferase）， triglycerides， and the blood concentration of escitalopram oxalate. ResultsA total of 100 patients completed the study， with 50 cases in the study group and the control group. The results of the repeated measures ANOVA showed that the interaction effect between group and time in the HAMD-24 score was statistically significant （F _interaction= 18.070， P<0.01）. At the end of the 4^th and 6^th weeks of treatment， the HAMD-24 score of the study group was lower than those of the control group （P<0.05）. At each time point after treatment， the reduction rate of the HAMD-24 score in the study group was higher than those of the control group， and the differences were all statistically significant （P<0.05）. The interaction effect between the triglyceride level groups and time was statistically significant （F_interaction=3.381， P<0.05）.After treatment， the triglyceride levels in the study group showed a downward trend， while those in the control group showed an upward trend. There was no statistically significant interaction effect between the groups and time for liver function （aspartate aminotransferase and alanine aminotransferase） and the blood concentration of escitalopram oxalate （P>0.05）. ConclusionCompared with escitalopram oxalate treatment alone， the combination of Zadi-5 pills and escitalopram oxalate is more effective in treating the first-episode depression， without increasing the risk of liver damage. The combined medication may have a potential beneficial effect on lipid metabolism. ［Funded by Inner Mongolia Autonomous Region Health Science and Technology Planning Project （number， 202202107）］

Ischemic stroke （IS） is a serious cerebrovascular disease with high clinical incidence. Cerebral ischemia and hypoxia can induce metabolic reprogramming of cellular glycolysis. Hypoxia-inducible factor-1α （HIF-1α） serves as the core transcription factor in the hypoxic response. This article systematically reviews the molecular mechanisms of HIF-1α-mediated glycolytic reprogramming， elaborates on the effects of this metabolic alteration on the functional status of different immune cells， and summarizes the research progress of traditional Chinese medicine （TCM） interventions in this pathological process. HIF-1α reshapes glucose metabolic flux and shifts cellular metabolism toward glycolysis by regulating the transcription of key genes， including glucose transporters， glycolytic rate-limiting enzymes， and mitochondrial oxidative inhibitors. This metabolic disturbance can regulate the activation status， phenotypic differentiation， and functional remodeling of microglia， astrocytes， and peripherally infiltrated immune cells， thereby participating in the mediation of neuroinflammatory responses after IS. Moreover， multiple signaling pathways and the metabolite of glycolysis lactate can exert feedback regulation on this metabolic-immune process. Various active components of TCM and herbal formulas， such as astragaloside Ⅳ， salvianolic acid C， Ginkgo biloba extract， and Mailuo shutong pills， can inhibit abnormal glycolysis， reduce lactate accumulation， and restore the homeostasis of glucose oxidative metabolism by regulating signaling pathways including AMP-activated protein kinase/mammalian target of rapamycin/HIF-1α， HIF-1α/pyruvate kinase M2， and HIF-1α/lactate dehydrogenase A. Consequently， they effectively alleviate neuroimmune inflammation and attenuate ischemic brain injury.

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.

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

Background The decline of physical activity in the elderly due to aging may increase the risk of sarcopenia. Currently, there is a lack of evidence from large natural populations on the relationship between PA and sarcopenia. Objective To explore the relationship between PA and sarcopenia in the elderly aged 60 years and above in 10 provinces (autonomous regions) of China. Methods Data were retrieved from the 2022—2023 round of the China Development and Nutrition Health Impact Cohort. Personal basic information and PA data were collected by questionnaire survey. Skeletal muscle mass was measured by bio-electrical impedance analysis, muscle strength was measured using a grip dynamometer, and physical performance was reflected by 6-meter walk speed. The Asian Working Group for Sarcopenia (AWGS) 2019 criteria were used to diagnose sarcopenia. Light physical activity (LPA) duration, moderate-to-vigorous physical activity (MVPA) duration, and total physical activity volume were calculated. A total of 3326 residents aged ≥60 years with complete data were selected as the survey participants. Multiple logistic regression models and restricted cubic splines (RCS) were used to assess the association between PA duration/volume and sarcopenia. Results In 10 provinces (autonomous regions) of China, the prevalence of sarcopenia in the elderly aged 60 years and above was 5.5% (95%CI: 4.7%, 6.2%). The logistic regression analysis showed that compared with the elderly reporting 0-7.0 h·week⁻¹ in LPA duration, the risk of sarcopenia in the elderly with LPA duration of >14.0-21.0 h·week⁻¹ was reduced by 51% (OR=0.49, 95%CI: 0.26, 0.96). Compared with the elderly with total physical activity ≥15.0 metabolic equivalent of task (MET)-h·week⁻¹, those with <7.5 MET-h·week⁻¹ had a 2.24-fold increased risk of sarcopenia (OR=2.24, 95%CI: 1.17, 4.29). The RCS results found that LPA duration and total physical activity volume each showed a nonlinear dose-response relationship with the risk of sarcopenia (P_overall<0.05, P_non-linear<0.05). Compared with the elderly with an LPA duration of 0 h· week⁻¹, the risk of sarcopenia in the elderly with an LPA duration of 12.6 h· week⁻¹ was the lowest (OR=0.42, 95%CI: 0.21, 0.83). Compared with the elderly with a total physical activity volume of 15.0 MET-h· week⁻¹, the elderly with a total physical activity volume of 46.0 MET-h· week⁻¹ had the lowest risk of sarcopenia (OR=0.57, 95%CI: 0.38, 0.84). There was no statistically significant association between weekly MVPA duration and the risk of sarcopenia (P>0.05). Conclusion Increasing weekly LPA duration and total physical activity volume would help to reduce the risk of sarcopenia.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.