Objective To Analyze the immunity to secondary infection in the elderly with severe acute pancreatitis.Methods Totally 105 old patients were included in the present study.The ratio of CD4+ to CD8+,and serum levels of tumor necrosis factor-α (TNF-α),interleukin-6 (IL-6),interleukin-10 (IL-10),and interleukin-4 (IL-4) were determined by flow cytometer analysis or ELISA within 3 days after diagnosis of secondary infection.Results Among 105 old patients,58 cases experienced secondary infection.At 3th day after severe acute pancreatitis,the levels of TNF-α,IL-6,IL-4,IL-10,CD4+,CD8+ and CD4+/ CD8+ were (81.3±5.5)ng/L,(141.2±13.7)ng/L,(61.1±7.4) ng/L,(153.8 ±15.2) ng/L,(43.5±5.5)％,(20.7±2.9)％ and (2.4±0.3) in infection group,as compared with those of (50.8±4.7)ng/1,(81.4±11.7)ng/L,(30.8±7.8)ng/L,(100.3± 13.8)ng/L,(31.6±4.6)ng/L,(29.7±3.5)and (1.1±0.4)in control group,respectively,with statistically significant differences betwveen the two groups (t=7.30,6.51,4.87,4.52,2.88,3.41,4.26,all P＜0.05).At 28th day after SAP,the levels of TNF-α,IL-6,IL-4,IL-10,CD4+,CD8 ± and CD4+ /CD8+ were (29.3±5.8)ng/L,(51.7±7.9)ng/L,(33.8±5.1)ng/L,(82.6±9.5)ng/L,(22.1±3.3)％,(47.1±4.3)％ and (0.6±0.3) in infection group,as compared with those of (44.4±5.5)ng/L,(82.2±7.1)ng/L,(65.3±5.5)ng/L,(109.1±9.5)ng/L,(40.5±2.7)ng/L,(33.4±4.5)ng/L and (1.8±0.4) in control group,respectively,showing statistically significant differences between the two groups(t=3.26,4.93,7.32,3.43,7.41,3.81,4.33,all P＜0.05).Conclusions An early excessive immune response and subsequent immune injury is closely related to secondary severe acute pancreatitis.

OBJECTIVE: To review the pathogenesis of diabetes under the guidance of the theories of neuroendocrine immunomodulation(NIM) network combined with the understanding of diabetes in traditional Chinese medicine.DATA SOURCES: Computer was used to search for the articles published from January 1980 to January 2005, with key words of "diabetes mellitus,pathogenesis, neuroendocrine immunomodulation, and traditional Chinese medicine " and the language of the papers was limited to "English". Also,computer and manual search for the articles in NLW and CNKI data banks from January 1990 to January 2005 were made with the language of the papers being limited to "Chinese" and key words of "diabetes, pathogenesis,neuroendocrine immunomodulation, traditional Chinese medicine" . Manual search was made for book chapters on the treatment of diabetes by traditional Chinese medicine and papers on the relation of diabetes with neuroendocrine immunoregulation network published after 1980.STUDY SELECTION: A rough check was made firstly to the materials to choose the articles on diabetes and the relationship with neuroendocrine immunoregulation network. Inclusion criteria: ① randomized clinical trial (RCT), single-, double- or non-blinded methods were used; ②non-randomized controlled trial; ③ anterior-posterior controlled trial. Exclusion criteria: repeated studies were excluded.DATA EXTRACTION: Thirty-three articles on pathogenesis of diabetes were obtained and among them 21 were consistent with the above criteria and 12 were excluded for repetition of the same studies.DATA SYNTHESIS: Twenty-one articles on the relation of the pathogenesis of diabetes with neuroendocrine immunoregulation and with the traditional Chinese medicine were analyzed to investigate the internal relations of the three.CONCLUSION: Diabetes mellitus is induced by the interaction between genetic and environmental factors, and the imbalance among insulin, counterregulatory hormones and other factors such as hypothalamic pituitary-adrenal (HPA) axis, thymus gland in neuroendocrine immunomodulation (NIM) network. The authors propose that the NIM network theory might be as a bridge to link modern medicine and the traditional Chinese medicine that is helpful to understand the pathogenesis of diabetes mellitus.CONCLUSION: Diabetes mellitus is induced by the interaction between genetic and environmental factors, and the imbalance among insulin, counterregulatory hormones and other factors such as hypothalamic pituitary-adrenal (HPA) axis, thymus gland in neuroendocrine immunomodulation (NIM) network. The authors propose that the NIM network theory might be as a bridge to link modern medicine and the traditional Chinese medicine that is helpful to understand the pathogenesis of diabetes mellitus.

Purpose To explore the value of predicting risk classification of gastrointestinal stromal tumors(GIST)based on the model established by dural-phase enhanced CT based radiomics.Materials and Methods Totally 200 patients with pathologically confirmed GIST from October 2017 to July 2023 in the Affiliated Hospital of Zunyi Medical University were enrolled,including 69 cases with low-risk group(very low-risk,low-risk)and 131 with high-risk group(medium-risk,high-risk).All patients were randomly divided into training set(n=139)and validation set(n=61)at the ratio of 7∶3.Univariate and multivariate Logistic regression analysis were used on clinical data and CT sings in the training set to obtain clinical-CT features for predicting the risk grade of GIST,and clinical-CT models were constructed.The radiomics features were extracted and screened from the three data sets of enhanced CT arterial phase,venous phase and arterial+venous phase,and the radiomics model was constructed to obtain the optimal radiomics features,respectively.The optimal radiomics features were obtained and combined with the clinical-CT features,a combination model was constructed and the normogram was drawn.The predictive efficiency of these models was evaluated by area under the curve(AUC).Results Tumor diameter was an independent predictor of GIST risk classification(OR=1.070,P＜0.001).The AUC of the combination model,model arterial+venous phase radiomics and model clinical-CT in the training set were 0.948,0.896 and 0.873,respectively;those in the validation set were 0.886,0.825 and 0.870,respectively.The AUC of the above three models showed statistical difference(Z=-3.167,-2.316,P＜0.05).Conclusion The radiomics features based on enhanced CT have good value in predicting risk classification of GIST.Compared with model clinical-CT and model radiomics,the combination model is the most effective in predicting the risk classification of GIST.