OBJECTIVES: To investigate the effect of Scleromitrion diffusum on gastric mucosal epithelial-mesenchymal transition (EMT) in rats with gastric precancerous lesion. METHODS: Fifty SD rats were randomly divided into blank control group (n=11), model control group (n=13), Scleromitrion diffusum (SD) group (n=13) and vitase group (n=13). Gastric precancerous lesion animal model was prepared by 1-methyl-3-nitro-1-nitrosoguanidine complex polyfactor method, and the drugs were administrated by gavage once a day for 6 weeks. The pathological changes of gastric mucosa were observed with hematoxylin and eosin staining, the expression of EMT marker proteins were detected with immunohistochemical staining and Western blotting. RESULTS: Compared with the model control group, the gastric mucosal injury was significantly attenuated in the Scleromitrion diffusum group, the mucosal tissue structure gradually recovered, the saccular expansion area was reduced, and the inflammatory infiltration was ameliorated. The expression of epithelial cadherin was higher, and the expression of neural cadherin and vimentin in the Scleromitrion diffusum group were lower than those of model control group (all P<0.05). CONCLUSIONS Scleromitrion diffusum can ameliorate gastric mucosal injury in rats with gastric precancerous lesion by reversing the EMT.
Animals ; Rats ; Rats, Sprague-Dawley ; Epithelial-Mesenchymal Transition/drug effects* ; Precancerous Conditions/metabolism* ; Gastric Mucosa/metabolism* ; Stomach Neoplasms/drug therapy* ; Male ; Cadherins/metabolism*

Immune checkpoint inhibitors （ICIs） can activate anti-tumour-related immunity in the treatment of malignant tumours， but at the same time， they can also cause non-specific immune activation， leading to the occurrence of immune-related adverse reactions （irAEs）. It is believed that under physiological conditions， ICIs can be classified as tonic agents in traditional Chinese medicine， exerting the effect of warming yang and benefiting qi， but when the immune response become over-excited， ICIs evolve into pathogen of exuberant fire， which is destructive to the body. Combining the different periods of immunotherapy and the degree of symptoms， irAEs are divided into two phases： symptom onset phase （exuberant fire consuming qi and essence） and intermittent phase （latent fire dispersing healthy qi in critical condition）， in which yang movement is excess fire leading to toxicity of the skin and oral mucous membranes， qi constraint transforming into fire leading to toxicity of gastrointestinal tract， qi block generating fire leading to cardiotoxicity， and qi and yin deficiencies leading to fire manifesting as ICIs-related diabetes. The general principle of “simultaneous treatment of qi and fire” is proposed to guide the treatment of irAEs. During the onset phase， draining fire， directing qi downward， and dispelling drug toxicity are used to remove excess fire； raising yang， dispersing fire， and dispelling drug toxicity are used to disperse fire constraint； promoting the flow of yang and qi and dispelling drug toxicity are used to close fire and smoothen the flow； cultivating qi， clearing fire， and dispelling drug toxicity are used to disperse the deficiency fire， so as to achieve the goal of clearing exuberant fire， eliminating drug toxicity， and alleviating acute symptoms. During the intermittent phase， the aim is to generate fire slightly to warm yang qi， block latent fire， and prevent recurrence， and ultimately restore the balance of qi and yang in human physiology to prevent and treat irAEs and improve the quality of life of patients.

Objective To investigate the effect of overexpression of ubiquitin-conjugating enzyme 2T(UBE2T)on radiosensitivity of hepatocellular carcinoma(HCC).Methods Hepa1-6 cells were transfected with a UBE2T-overexpressing or a control lentiviral vector,and the changes in their radiotherapy sensitivity and concentrations of glucose and lactate in the supernatant were assessed using colony-forming assay and colorimetric assay.The transfected cells were inoculated subcutaneously in nude mice or C57BL/6 mice,and tumor growth following irradiation were recorded.The xenografts were collected for analyzing infiltration of CD4+T cells and regulatory T cells(Tregs)using flow cytometry and detecting expressions of HK1 and LDHA using Western blotting.The correlations of UBE2T expression with immune cell infiltration,glycolysis and Tregs in HCC were analyzed using CIBERSORT algorithm and TCGA database,and the results were verified in a co-culture system of Hepa1-6 cells and Tregs.Results UBE2T overexpression caused radiotherapy resistance in both cultured Hepa1-6 cells and xenografts in the tumor-bearing mouse models(especially in C57BL/6 mice).CIBERSORT analysis suggested that a high expression of UBE2T was associated with increased percentages of dendritic cells,T follicular helper cells,M2 macrophages,monocytes,lymphocytes and Tregs in HCC.The UBE2T-overexpressing xenografts showed an increased percentage of Tregs and enhanced expressions of HK1 and LDHA,and irradiation increased infiltration of CD4+T cells and Tregs in the tumor microenvironment.Hepa1-6 cells overexpressing UBE2T showed a decreased glucose concentration and an increased lactate concentration.GSEA analysis suggested that a high UBE2T expression was positively correlated with increased glycolysis and Tregs infiltration in HCC.In the cell co-culture system,UBE2T overexpression significantly enhanced lactate production,proliferation and immunosuppressive functions of Tregs.Conclusion A high UBE2T expression results in radiotherapy resistance of HCC possibly by enhancing glycolysis and cause enrichment of Tregs in the tumor microenvironment.

We report a case of a male patient who developed persistent fever and central nervous system symptoms after eating raw snails for 10 days. The patient was diagnosed with Angiostrongyliasis depended on the clinical presentation, epidemiological history, and etiological results. The patient recovered after receiving albendazole anthelmintic and dexamethasone anti-inflammatory therapy. This article incorporates literature review to sort out the diagnosis and treatment of this patient, in order to provide feasible reference for clinicians.

We report a case of a male patient who developed persistent fever and central nervous system symptoms after eating raw snails for 10 days. The patient was diagnosed with Angiostrongyliasis depended on the clinical presentation, epidemiological history, and etiological results. The patient recovered after receiving albendazole anthelmintic and dexamethasone anti-inflammatory therapy. This article incorporates literature review to sort out the diagnosis and treatment of this patient, in order to provide feasible reference for clinicians.

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to find a light-weight,convenient prediction method through machine learning. METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation. RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the five most important features were acuity,arrival transportation,age,shock index,and respiratory rate. CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.