ObjectiveBased on literature data mining， this study explores the modeling elements of diarrhea-predominant irritable bowel syndrome （IBS-D） animal models in China and abroad， providing references and suggestions for improving modeling methods and evaluation indicators. MethodsRelevant literature on IBS-D animal experiments from 2014 to 2024 was retrieved through computer searches in databases such as China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP， Chinese Medical Journals Full-text Database， and PubMed. Information on experimental animal species， gender， body weight， modeling methods， modeling periods， intervention controls， modeling standards， and detection indicators was organized. Microsoft Excel 2021 software was used to establish a database and perform statistical analysis to examine the characteristics of IBS-D animal models. ResultsA total of 398 articles that met the inclusion criteria were reviewed. The IBS-D animal models were predominantly established using SD rats， Wistar rats， and C57BL/6 mice. Male animals were more commonly used， with rats typically aged 6-8 weeks and mice aged 4-6 weeks. In terms of interventions， piverium bromide was the main Western medicine， Tongxieyaofang was the primary Chinese medicine， and electroacupuncture was the primary acupuncture method. Among the modeling methods， the multi-factor combined composite modeling approach was the most common. Modeling periods were mainly concentrated between 1-14 days and 15-30 days. The success criteria for modeling were mainly evaluated based on the animal's general condition， fecal appearance， visceral sensitivity， gastrointestinal motility， behavior， and pathology. Detection indicators included apparent indexes， pathological markers， biochemical indicators， oxidative stress， brain-gut peptides， neurotransmitters， inflammatory factors， immune function， intestinal permeability， autophagy， apoptosis， proteins related to relevant signaling pathways， intestinal microbiota and its metabolites， etc. ConclusionThere are various methods for establishing IBS-D animal models， but no unified and universally accepted method has been established. The operation of the same modeling methods and the evaluation standards of the models vary across studies. Based on the results of data mining， the authors suggest that the multi-factor combined composite modeling approach most closely reflects the pathophysiological processes of IBS-D， better simulating the complex clinical symptoms of IBS-D patients， such as abdominal pain and diarrhea， and has a high degree of clinical relevance. This method is relatively recommended. While animal models in general align with Western medicine standards， models incorporating traditional Chinese medicine （TCM） syndromes are relatively few. Therefore， one of the future directions for research is to establish IBS-D animal models that meet the combined clinical disease and syndrome requirements of both Western and Chinese medicine.

Cocaine,as a widely abused and highly addictive drug,has a serious impact on the physical and mental health of individuals and carries a certain degree of social harm and economic burden.Acupuncture can assist in the treatment of cocaine addiction with fewer side effects.However,a well-defined mode of stimulation is an important factor in elucidating the various mechanisms by which acupuncture treats disease.This paper summarizes the problems in the mechanism of cocaine addiction,such as different parameters of stimulation,unstable depth of acupuncture,different acupoint selection,and different lengths of acupuncture time.To standardize the intervention measures of acupuncture experiments,it is suggested that in future research,the stimulation method should explore the best parameters,the selection of acupoints should be based on clinical practice,the timing of acupuncture should be objective,and the treatment course should consider the effects of acupuncture.

Objective:To explore the impact of applying micro-video tracing training model to emerging infectious diseases (EIDs) knowledge training on the autonomous learning ability and learning outcomes among emergency department nurses.Methods:In this study, the training content was developed from the perspective of the historical development of EIDs. The training program was constructed in the form of a micro-video classification module and periodic WeChat group push-based autonomous learning. Convenience sampling was used to select 85 emergency nurses ( n=85) from a grade A tertiary general hospital in Shanghai for micro-video tracing training. The nurses were provided with EIDs knowledge training using a module consisting of 11 episodes, each of which included 5 sessions, i.e., enlightening thinking, micro-video learning, key point consolidation, key point analysis, and extension and expansion. After the intervention, the nurses were compared for their autonomous learning ability and their knowledge, belief, and action levels of EIDs, and their degree of satisfaction with the training model was evaluated. SPSS 20.0 and GraphPad Prism 9.3.0 were used for non-parametric Wilcoxon paired tests of quartiles ( Q25, M, and Q75). Results:After the training, the emergency department nurses had significantly higher scores in overall autonomous learning ability ( Z=-4.69, P<0.001) and in each dimension: concept of self-motivation ( Z=-4.48, P<0.001), task analysis ( Z=-4.06, P<0.001), self-monitoring and regulation ( Z=-4.50, P<0.001), and self-evaluation ( Z=-4.82, P<0.001); they had significantly higher scores in overall knowledge, belief, and action levels of EIDs ( Z=-4.65, P<0.001) and in each dimension: knowledge ( Z=-4.04, P<0.001), belief ( Z=-3.24, P=0.001), and action ( Z=-4.05, P<0.001). Emergency department nurses had a high degree of satisfaction with the training model (degree of satisfaction for each item >90%). Conclusions:The micro-video tracing training model can effectively improve the autonomous learning ability of emergency department nurses and their knowledge, belief, and action levels of EIDs, with a high degree of satisfaction among the nurses, making it promising for wide use.

Objective To explore the predictive effect of empowerment and theory of planned behavior(TPB)on the four core behaviors of type 2 diabetes mellitus(T2DM)self-management,and analyze the influence path of TPB model and behavioral intention on the four core behaviors.Methods A total of 500 T2DM patients who were hospitalized in the Endocrinology Department of three tertiary general hospitals in different provinces from December 2022 to May 2023 were selected for investigation.Hierarchical multiple regression analysis was used to explore the predictive effects of empowerment and TPB models on self-management behaviors.Bootstrap method was used to analyze the influence path of TPB model and behavior intention on self-management behaviors.Results Empowerment had a predictive effect on self-management behavior,which was improved after the addition of TPB,with medication R2=0.194,blood glucose monitoring R2=0.308,regular diet R2=0.337 and regular exercise R2=0.343,respectively.Mediation effect analyses revealed that attitude,subjective norm,and perceived behavioral control were observed to predict behavior intention across the four behaviors,and the three except through the behavior intention indirectly affect behavior,can also directly affect the behavior.Conclusions Empowerment can predict self-management behavior,and adding TPB to this can improve the prediction effect.Attitude,subjective norms and perceived control can indirectly or directly affect self-management behavior through behavioral intention.

Objective To observe the effects of Angelicae Sinensis Radix-Paeoniae Radix alba combined with bone marrow mesenchymal stem cells(BM-MSCs)transplantation on liver inflammation and hepatocytes regeneration in non-alcoholic steatohepatitis(NASH)associated cirrhosis;To discuss its possible mechanism.Methods West diet combined with carbon tetrachloride was used to prepare the NASH related cirrhosis model.The mice were randomly divided into control group,model group,Angelicae Sinensis Radix-Paeoniae Radix alba group,BM-MSCs group,and Angelicae Sinensis Radix-Paeoniae Radix alba+BM-MSCs group,with 12 mice in each group.After successful modeling,corresponding interventions were given according to grouping for 4 consecutive weeks.HE staining was used to observe the morphology of liver tissue;the contents of serum ALT,AST,TBil,TG,ALB,AFP,as well as the contents of IL-1β,TNF-α and HGF in liver tissue were detected;RT-qPCR was used to detect TLR9,MyD88,TRAF6 and NF-κBp65 mRNA expression in liver cells;primary liver cells were separated,CpG ODN 2216 stimulation was induced in vitro,cells supernatant was extracted,and IL-1β and TNF-α content were detected.Results Compared with the control group,inflammatory cell infiltrated in liver tissue of model group mice,accompanied by hepatocyte necrosis and collagen deposition,forming pseudo lobules;the contents of serum ALT,AST,TBil and TG increased,the content of ALB decreased,the content of HGF in liver tissue decreased,the contents of IL-1β and TNF-α increased,with statistical significance(P<0.05);the mRNA expressions of TLR9,MyD88,TRAF6 and NF-κBp65 in liver cells increased(P<0.05),and the contents of IL-1β and TNF-α in cells supernatant increased after CpG ODN 2216 induction(P<0.05).Compared with the model group,the inflammatory infiltration in liver tissue and necrosis of liver cells were reduced and the degree of liver fibrosis was alleviated in the Angelicae Sinensis Radix-Paeoniae Radix alba+BM-MSCs group,the liver tissue damage in Angelicae Sinensis Radix-Paeoniae Radix alba group and BM-MSCs group were slightly improved;except for the TG content in BM-MSCs group,all detection indicators showed significant improvement in each intervention group(P<0.05).Compared with the Angelicae Sinensis Radix-Paeoniae Radix alba group and BM-MSCs group,the Angelicae Sinensis Radix-Paeoniae Radix alba+BM-MSCs group showed statistical significance in related detection indicators(P<0.05),and demonstrated a synergistic effect.Conclusion Angelicae Sinensis Radix-Paeoniae Radix alba combined with BM-MSCs transplantation could effectively improve the liver function and promote liver cell regeneration.The mechanism is associated with the down-regulation of TLR9/NF-κB signaling pathway expressions and function,the inhibition of inflammatory cytokines secretions,and the improvement of liver inflammatory microenviroment.

Objective:To explore the relationship between normal serum creatinine(Scr) level and diabetic kidney disease(DKD) in patients with type 2 diabetes mellitus(T2DM).Methods:This was a prospective cohort study. Patients with yet not DKD who were regularly followed up at six centers of Li′s United Clinic in Taiwan, China from January 1, 2002 to December 31, 2018 were selected. At baseline, clinic information and lab tests were collected. According to whether the patients developed DKD during the follow-up period, they were divided into DKD group and non-DKD(NDKD) group. The exposure factor was the Scr(μmol/L) value, and it was used as a categorical variable. According to the quartiles of Scr, they were divided into 4 groups: Q1 group(Scr<57.68 μmol/L), Q2 group(57.68 μmol/L≤Scr<68.51 μmol/L), Q3 group(68.51 μmol/L≤Scr<80.44 μmol/L) and Q4 group(Scr≥80.44 μmol/L). The Cox regression model was used to explore the relationship between Scr level and the incidence of DKD. Receiver operating characteristic(ROC) curve was used to analyze the predictive effect of normal level Scr on DKD. Results:A total of 2 202 T2DM patients without DKD at baseline were included. After a follow-up period of(5.2±2.17) years, there were 966 patients in the DKD group and 1 236 patients in the NDKD group. Compared with the NDKD group, the DKD group had older age, longer duration of diabetes, higher BMI, SBP, DBP, LDL-C, Scr, and UACR(all P<0.05). Cox regression analysis results showed that compared with the Q1 group as the reference, the risk of developing DKD in the Q2, Q3, and Q4 groups after adjusting for confounding factors was 1.394, 1.688, and 2.821 times higher, respectively(all P<0.05). ROC curve analysis results showed that the area under the curve(AUC) for predicting DKD occurrence using normal serum creatinine level was 0.70(95% CI 0.678-0.722), with an optimal cutoff value of 74.27 μmol/L, sensitivity of 0.54, and specificity of 0.76. The cumulative risk plot showed that after adjusting for confounding factors, patients in the Q4 group had a higher cumulative risk of developing DKD compared to the Q1, Q2, and Q3 groups(all P<0.05). Conclusion:Scr is an independent risk factor for developing DKD in patients with T2DM. The higher the Scr level, the greater the risk, especially when Scr is greater than 74.27 μmol/L.

Objective:To construct an evidence-based prediction model for early recurrence after surgery of hepatocellular carcinoma (HCC) based on Meta-analysis and to do external validation study.Methods:The literatures in Chinese National Knowledge Infrastructure, Wanfang, VIP, Chinese Science Citation Database (CSCD), Chinese Social Science Citation System (CCSCI), PubMed, Web of Science and IEEE databases between January 2019 and December 2023 were searched based on the subject words. According to the inclusion and exclusion criteria, 9 literatures were included to screen the risk factors affecting the early recurrence of HCC. When the same risk factor was found in ≥5 included literatures, Meta-analysis was performed by using Review Manager 5.4.1 software. External validation data were collected from 401 patients with primary HCC who underwent surgery in Liaoning Cancer Hospital between March 2014 and March 2017. The patients were divided into early recurrence group (176 cases) and early non-recurrence group (225 cases) according to whether they relapsed 2 years after surgery. The OR values of all risk factors obtained in the Meta-analysis were converted into modeling, and postoperative early recurrence rate of HCC in the Meta-analysis was used to calculate β 0, and finally the logistic model was obtained. The OR value was incorporated into the logit (P) model, and the morbidity (P) of the external validation data was calculated. Taking the recurrence 2 years after surgery or not as the dependent variable and P as the independent variable, the receiver operating characteristic (ROC) curve was drawn to calculate the area under the curve (AUC). Results:A total of 8 risk factors for early HCC recurrence were screened out from 9 literatures (x 1: alpha-fetoprotein ≥ 400 ng/ml; x 2: tumor number ≥ 2; x 3: the longest tumor diameter ≥ 5 cm; x 4: Barcelona staging B-C; x 5: microvascular invasion; x 6: moderate to low differentiation; x 7: incomplete capsule; x 8: nonanatomic hepatectomy). The Meta-analysis included 1 757 HCC cases, with 960 postoperative early recurrences and an early recurrence rate of 45.36%, finally the β 0 value was -0.201. The predictive model for 2-year recurrence of HCC was constructed and calculated as logit (P) = -0.201+0.835x 1+0.905x 2+0.783x 3+1.008x 4+0.765x 5+0.831x 6+1.533x 7+0.940x 8. Analysis of variance by external validation data showed that the differences in ascites, alpha-fetoprotein, tumor number, tumor diameter, Barcelona staging, microvascular invasion, tumor differentiation degree, capsule invasion, resection type, and systemic inflammation index were statistically significant between early recurrence group and early non-recurrence group (all P < 0.05). ROC curve analysis showed that AUC of postoperative early recurrence of HCC predicted by the model was 0.718, (95% CI: 0.689-0.753), the optimal cut-off value was 3.11, the Yoden index was 0.288, the sensitivity was 69.32%, and the specificity was 69.56%. Conclusions:The evidence-based prediction model constructed based on Meta-analysis for postoperative early recurrence of HCC has a high predictive value. However, further verification and optimization with big data is still needed.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Objective:To evaluate the relationship between hemoglobin(Hb) level and the risk of diabetic retinopathy(DR) in patients with type 2 diabetes mellitus(T2DM).Methods:This study was a prospective cohort study. A total of 1 730 T2DM patients without DR, who received regular management at the Li′s Clinic in Taiwan, China starting from 2002, were selected as the study population. All patients underwent annual dilated fundus examination by professional ophthalmologists. General patient information and laboratory results were collected and analyzed. Based on the occurrence of DR during patient follow-up, patients were divided into the DR group and the non-DR(NDR) group. The impact of Hb levels on DR was explored using a generalized linear mixed model, and the relationship between Hb levels and DR was studied using Cox proportional hazards regression model.Results:After an average follow-up of 9.79 years, 481 patients with DR were detected. Compared with NDR group, DR group displayed a longer course of diabetes, higher rates of cataract, insulin use, and anemia, and higher systolic blood pressure, HbA 1C, and UACR as well as lower Hb. The results of the generalized linear mixed model showed a negative correlation between Hb and the occurrence of DR( β=-0.015, P<0.001). The Cox proportional hazards regression model showed that, after adjusting for confounding variables and based on quartiles of average Hb levels during follow-up, the risk of developing DR increased by 56.9% in the Q1 group(Hb≤127 g/L) compared to the Q4 group(Hb≥142 g/L). The cumulative risk plot showed that, after adjusting for confounding variables, the Q1 group had the highest cumulative risk of developing DR, and the difference was statistically significant( P<0.05). Conclusion:Hb was negatively correlated with DR, and the lower Hb levels were associated with the occurrence of DR, independent of other influencing factors.

ObjectiveTo investigate the mortality and years of life lost of pancreatic cancer in Baoshan District of Shanghai，from 2009 to 2021， and to provide scientific evidence for the prevention and control of pancreatic cancer in the future. MethodsThe death surveillance data of Baoshan District from 2009 to 2021 were collected from the Shanghai chronic disease surveillance information management system. Crude mortality， standardized mortality，potential years of life lost （PYLL）， potential years of life lost rate （PYLLR） ， average years of potential life lost （AYLL） ， annual percentage change （APC） were calculated to analyze the trend of mortality and life loss of pancreatic cancer. ResultsFrom 2009 to 2021， a total of 2117 deaths of pancreatic cancer were reported in Baoshan District， accounting for 7.05% of all cancer deaths. The average age of the death cases was （71.18±10.97）years. The youngest was 3 years old and the oldest was 96 years old. The death component ratio of pancreatic cancer increased with time （P<0.05）， and the average death age of women was higher than that of men （P<0.05）. The crude mortality of pancreatic cancer was 17.38/10⁵ in Baoshan District from 2009 to 2021， showing a rising tendency （P<0.05） with APC of 3.74%. The standardized mortality of pancreatic cancer was 7.84/10⁵. The crude mortality of pancreatic cancer was 19.71/10⁵ in men and 14.89/10⁵ in women， both showed a tendency towards a rise （P<0.05 ） with APC of 4.44% and 2. 89%， respectively. The crude mortality of pancreatic cancer showed a tendency towards a decline in residents at ages of 45 to 60 years （ P<0.05 ）， with APC of 4.74%. The PYLL and PYLLR of pancreatic cancer were 8 115 person-years and 0.67‰ in Baoshan District from 2009 to 2021， while the AYLL of pancreatic cancer was 3.83 years per person. The PYLL was higher in men than in women. ConclusionThe mortality rate of pancreatic cancer in Baoshan District shows an increasing trend. The healthy life of elderly and men is affected largely by pancreatic cancer. It is necessary to strengthen the health education on the prevention/control of pancreatic cancer and healthy life style， thereby improving the tertiary prevention system of pancreatic cancer.