Irritable bowel syndrome （IBS） is a functional bowel disorder characterized primarily by abdominal pain and altered defecation habits. In recent years， traditional Chinese medicine （TCM） has made progress in multiple aspects of IBS research and treatment， including syndrome distribution， development of TCM formulas， clinical efficacy evaluation， external therapies， and psychosocial regulation. However， it still faces challenges such as over-reliance on symptomatic manifestations rather than biomarkers for diagnostic criteria， and the lack of high-quality evidence-based data supporting the efficacy of TCM formulas in treating IBS. This paper proposed that TCM diagnosis and treatment of IBS should adhere to the strategy of integrating the holistic concept with syndrome differentiation and treatment， combining TCM external therapies such as acupuncture， moxibustion and acupoint application）， and emphasizing individualized diagnosis and treatment for psychosomatic abnormalities. Future research should integrate multi-omics technologies， artificial intelligence and other methods to deepen the understanding of the pathogenesis of IBS and the mechanisms of TCM formulas， so as to promote the standardization and internationalization of TCM in the diagnosis and treatment of IBS.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Objective To explore the influencing factors of acute kidney injury in severe burn patients,and to construct a visual risk nomogram model.Methods A total of 390 patients with severe burn admitted to the Institute of Burn Frostbite and Tissue Function Reconstruction of Chinese People's Armed Police Force Specialty Medical Center from January 2018 to January 2022 were collected as an internal training data set,and 50 patients with severe burn admitted from February to December 2022 were collected as an external validation data set.The 390 patients of the internal training data set were divided into the acute kidney injury group and the non-acute kidney injury group according to the occurrence of acute kidney injury,and the baseline data of patients in the two groups were compared.Univariate and multivariate Logistic regression were used to analyze the risk factors of acute kidney injury in severe burn patients of the internal training data set,and a nomogram model was drawn.Subsequently,the model was verified both internally and externally.Kaplan-Meier analysis and Log-rank test were used to compare the 90-day survival rate of patients between the acute kidney injury group and the non-acute kidney injury group.Results The burn area(OR=1.18,95%CI:1.06 to 2.36,P=0.004),sequential organ failure assessment(SOFA)score(OR=1.81,95%CI:1.21 to 5.92,P<0.001),inhalation injury(OR=3.21,95%CI:1.23 to 6.35,P<0.001),neutrophil to lymphocyte ratio(NLR)(OR=1.22,95%CI:1.05 to 3.65,P<0.001)and albumin(ALB)(OR=0.78,95%CI:0.57 to 0.92,P=0.011)were the independent risk factors for the development of acute kidney injury in severe burn patients.The nomogram model was established by the above factors.The area under the receiver operating characteristic curve(AUC)of the internal training data set was 0.833(95%CI:0.752 to 0.935),the sensitivity was 81.2%,and the specificity was 83.2%.The AUC of the external validation data set was 0.842(95%CI:0.762 to 0.912),the sensitivity 87.2%,and the specificity was 78.7%.The 90-day survival rate of patients in the acute kidney injury group after burns was significantly lower than that in the non-acute kidney injury group(P<0.001).Conclusion Larger burn area,higher SOFA score,combined inhalation injury,increased NLR,and decreased ALB level are the risk factors for the occurrence of acute kidney injury in severe burn patients,which are related to the 90-day survival rate of patients after burns.The nomogram model based on the risk factors can provide certain reference for clinical individualized prevention and treatment of acute kidney injury in severe burn patients.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Chronic gastritis is a chronic inflammation of the gastric mucosa caused by various etiologies and can be categorized into chronic non-atrophic gastritis and chronic atrophic gastritis.Chronic atrophic gastritis is a common disorder of the digestive system characterized by gastric mucosal gland atrophy,mucosal thinning,and basal layer thickening.The development of intestinal metaplasia and atypical hyperplasia on this basis is recognized as a precancerous lesion of gastric cancer and represents a key stage in the"inflammation-cancer transformation"of chronic gastritis.However,universally recognized and effective treatment strategies for this"inflammation-cancer transformation"process are lacking in clinical practice.This study integrates Correa′s cascade reaction with clinical practice,summarizing the pathogenesis of the"inflammation-cancer transformation"of chronic gastritis as weakness of the middle jiao and blood stasis.It suggests that the"inflammation-cancer transformation"process involves the pathological development of spleen and stomach deficiency,transportation and transformation dysfunction,turbid phlegm,blood stasis,and the gradual formation of cancerous toxins,with spleen and stomach weakness as the core mechanism and phlegm and blood stasis as the crucial pathological link.Based on an in-depth exploration of the deficiency of the middle jiao and blood stasis,supported by pharmacological research and clinical experience,this paper proposes the therapeutic approach of strengthening the spleen and replenishing qi,expelling phlegm and activating blood.It discusses the related prescriptions in preventing and treating the"inflammation-cancer transformation"of chronic gastritis.This study aims to provide new perspectives and insights for the prevention and treatment of chronic gastritis with traditional Chinese medicine,offering a novel framework for clinical treatment.

Chronic gastritis is a chronic inflammation of the gastric mucosa caused by various etiologies and can be categorized into chronic non-atrophic gastritis and chronic atrophic gastritis.Chronic atrophic gastritis is a common disorder of the digestive system characterized by gastric mucosal gland atrophy,mucosal thinning,and basal layer thickening.The development of intestinal metaplasia and atypical hyperplasia on this basis is recognized as a precancerous lesion of gastric cancer and represents a key stage in the"inflammation-cancer transformation"of chronic gastritis.However,universally recognized and effective treatment strategies for this"inflammation-cancer transformation"process are lacking in clinical practice.This study integrates Correa′s cascade reaction with clinical practice,summarizing the pathogenesis of the"inflammation-cancer transformation"of chronic gastritis as weakness of the middle jiao and blood stasis.It suggests that the"inflammation-cancer transformation"process involves the pathological development of spleen and stomach deficiency,transportation and transformation dysfunction,turbid phlegm,blood stasis,and the gradual formation of cancerous toxins,with spleen and stomach weakness as the core mechanism and phlegm and blood stasis as the crucial pathological link.Based on an in-depth exploration of the deficiency of the middle jiao and blood stasis,supported by pharmacological research and clinical experience,this paper proposes the therapeutic approach of strengthening the spleen and replenishing qi,expelling phlegm and activating blood.It discusses the related prescriptions in preventing and treating the"inflammation-cancer transformation"of chronic gastritis.This study aims to provide new perspectives and insights for the prevention and treatment of chronic gastritis with traditional Chinese medicine,offering a novel framework for clinical treatment.

Aim To investigate the expression of or-ganic anion transporting polypeptide 4C1(Oatp4c1)-P-glycoprotein(P-gp)in the kidneys of obese mice in-duced by high-fat diet(HFD),and its impact on the pharmacokinetic changes of digoxin.Methods C57BL/6 mice were randomly divided into the Chow group and the HFD group.Body weight and blood glu-cose were recorded weekly.After successful model es-tablishment,digoxin was intraperitoneally injected,and blood was collected at different time points.Part of the blood samples was used for LC-MS/MS detection,and the other part was used for the detection of other bio-chemical indicators.After 16 weeks,the organs were removed and weighed.HE and immunohistochemical staining was used to observe the renal pathology and the expression of Villin,a marker of proximal tubules.Western blot and qPCR were combined to detect the expression of Villin,Oatp4c1 and P-gp.Results In the HFD group,body weight and blood glucose in-creased significantly.The blood concentration of digox-in rose,the area under the curve increased,and the half-life was prolonged.The proximal tubular epithelial cells shed,and the protein expression of Villin,Oatp4c1 and P-gp decreased significantly.Conclu-sions The down-regulation of Oatp4c1-P-gp expres-sion in the kidneys of HFD mice leads to an increase in the blood concentration of digoxin and a decrease in re-nal clearance.

Aim To investigate the role of FRMD4A in autophagy of placental trophoblast cells in preeclampsia(PE).Methods The placental tissues and clinical data of normal pregnancy and PE were obtained,and the histopathological changes were observed by HE staining.An in vitro model of hypoxia-induced HTR-8/SVneo trophoblast cells was established.The expres-sions of LC3B Ⅱ/Ⅰ and p62 in placental tissues and hypoxic cell models were analyzed by Western blot.The expression of FRMD4A was detected by qRT-PCR,Western blot and immunofluorescence,and the correlation between the expression level of FRMD4A and the clinical characteristics of the subjects was ana-lyzed by Pearson correlation analysis.Hypoxia induced trophoblast cells were transfected with si-FRMD4A,and the expression of LC3 B Ⅱ/Ⅰ and p62 was analyzed by Western blot.Results Compared with the normal group,the expression of LC3B Ⅱ/Ⅰ in PE placental tissues and hypoxia-induced trophoblast models was significantly upregulated,while the expression of p62 was significantly downregulated.Meanwhile,the ex-pression of FRMD4A increased significantly.Moreo-ver,its expression was positively correlated with the maternal systolic blood pressure,diastolic blood pres-sure,and platelet count,but negatively correlated with the neonatal weight(P＜0.01).In addition,hypoxia-induced trophoblast cells transfected with si-FRMD4A showed a significant decrease in LC3B Ⅱ/Ⅰ and an increase in p62 expression.Conclusions The expres-sion of FRMD4A is upregulated in PE placenta and hy-poxia-induced trophoblast cell model.Interfering with it can significantly hinder the autophagy process of trophoblast cells,suggesting that it may serve as a po-tential molecular target to participate in the pathologi-cal process of PE.

Background and Aims:Sleeve gastrectomy(SG)has become the most widely performed bariatric procedure worldwide,but postoperative gastroesophageal reflux disease(GERD)remains a major concern.This multicenter study aimed to identify independent risk factors associated with GERD after SG to guide preoperative assessment and intraoperative management.Methods:Clinical data of 672 patients who underwent SG between January 2020 and December 2022 in six bariatric centers and completed a 12-month follow-up were retrospectively analyzed.Demographic characteristics,esophagogastric junction(EGJ)integrity graded by the AFS system,operative parameters,and postoperative outcomes were compared between patients with and without GERD.Multivariate logistic regression was used to identify predictors of postoperative GERD.Results:The overall incidence of GERD after SG was 24.7%(166/672).Multivariate analysis revealed that a preoperative BMI>35 kg/m2(OR=1.68,P=0.033),EGJ integrity AFS grade>2(OR=2.90,P=0.006),and preoperative reflux symptoms(OR=2.44,P=0.030)were independent risk factors for GERD.A staple line more than 1 cm from the angle of His(OR=0.45,P<0.001)and a bougie size>36 Fr(OR=0.08,P=0.001)were protective factors.Conclusion:High BMI,impaired EGJ integrity,and preoperative reflux symptoms significantly increase the risk of GERD after SG,whereas adequate preservation of the His angle and appropriate bougie calibration may reduce it.Comprehensive preoperative EGJ assessment and standardized surgical techniques are essential for minimizing postoperative reflux.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.