Establishment of models to predict factors influencing periodontitis in patients with type 2 diabetes mellitus.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with periodontitis. Currently, there are few studies proposing predictive models for periodontitis in patients with T2DM. AIM: To determine the factors influencing periodontitis in patients with T2DM by constructing logistic regression and random forest models. METHODS: In this a retrospective study, 300 patients with T2DM who were hospitalized at the First People's Hospital of Wenling from January 2022 to June 2022 were selected for inclusion, and their data were collected from hospital records. We used logistic regression to analyze factors associated with periodontitis in patients with T2DM, and random forest and logistic regression prediction models were established. The prediction efficiency of the models was compared using the area under the receiver operating characteristic curve (AUC). RESULTS: Of 300 patients with T2DM, 224 had periodontitis, with an incidence of 74.67%. Logistic regression analysis showed that age [odds ratio (OR) = 1.047, 95% confidence interval (CI): 1.017-1.078], teeth brushing frequency (OR = 4.303, 95%CI: 2.154-8.599), education level (OR = 0.528, 95%CI: 0.348-0.800), glycosylated hemoglobin (HbA1c) (OR = 2.545, 95%CI: 1.770-3.661), total cholesterol (TC) (OR = 2.872, 95%CI: 1.725-4.781), and triglyceride (TG) (OR = 3.306, 95%CI: 1.019-10.723) influenced the occurrence of periodontitis (P < 0.05). The random forest model showed that the most influential variable was HbA1c followed by age, TC, TG, education level, brushing frequency, and sex. Comparison of the prediction effects of the two models showed that in the training dataset, the AUC of the random forest model was higher than that of the logistic regression model (AUC = 1.000 vs AUC = 0.851; P < 0.05). In the validation dataset, there was no significant difference in AUC between the random forest and logistic regression models (AUC = 0.946 vs AUC = 0.915; P > 0.05). CONCLUSION: Both random forest and logistic regression models have good predictive value and can accurately predict the risk of periodontitis in patients with T2DM.

Influence of dexamethasone on mesenteric lymph node of rats with severe acute pancreatitis.

AIM: To study the influence and mechanisms of dexamethasone on mesenteric lymph node of rats with severe acute pancreatitis (SAP). METHODS: The SAP rats were assigned to model, treated or sham-operated groups. The mortality, pathological changes of mesenteric lymph nodes, expression levels of NF-kappa B, P-selectin, Bax, Bcl-2 and caspase-3 protein and changes in apoptotic indexes in lymph nodes were observed at 3, 6 and 12 h after operation. The blood levels of endotoxin, superoxide dismutase (SOD), malondialdehyde (MDA), and endothelin-1 (ET-1) in blood were determined. RESULTS: SOD content, expression of Bax protein and apoptotic index were significantly higher in the treated group than in the model group at different time points (P < 0.05 or P < 0.01). Other blood-detecting indexes and histopathological scores of mesenteric lymph nodes were lower in the treated than in the model group (P < 0.05, P < 0.01 or P < 0.01). NF-kappa B protein expression was negative in all groups. Comparing P-selectin and caspase-3 expression levels among all three groups, there was no marked difference between the model and treated group. CONCLUSION: Dexamethasone can protect mesenteric lymph nodes. The mechanism may be by reducing the content of inflammatory mediators in the blood and inducing lymphocyte apoptosis.

Application of tissue microarrays to study the influence of dexamethasone on NF-kappaB expression of pancreas in rat with severe acute pancreatitis.

To discuss the influence of dexamethasone on NF-kappaB expression of pancreas in rat with severe acute pancreatitis (SAP). Ninety rat SAP models were divided into the model group and dexamethasone treatment group with 45 rats in each group; another healthy 45 rats were selected to be the sham operation group. The groups were divided into the 3, 6 and 12 h group with 15 rats in each group. The survivals, pancreas pathological changes were observed 3, 6 and 12 h after operation. The changes in expression levels of NF-kappaB protein of pancreas tissue microarray were observed. The treatment group was significantly lower than the model group at 3 and 6 h (P < 0.05) and than the model group at 12 h in pancreas pathological scores (P < 0.01). The expression level of NF-kappaB protein of pancreas head of the treatment group was significantly less than that of the model group at 3 h (P < 0.01). The alleviation of pancreatic tissue injury by dexamethasone during SAP might be closely related to its role in inhibiting NF-kappaB expression and regulating cytokines. The advantages of tissue microarrays in pancreatitis pathological examination include time and energy savings, high efficiency and representative results.

Methylation status of FHIT gene in plasma and expression of FHIT gene in cancer tissue of cervical cancer patients / 中华医学遗传学杂志

<p><b>OBJECTIVE</b>To explore the methylation status of 5' CpG island of fragile histidine triad (FHIT) gene in plasma and the expression of FHIT protein in cancer tissue of cervical cancer patients.</p><p><b>METHODS</b>Methylation-specific PCR (MS-PCR) was employed to examine methylation of FHIT gene in 151 plasma samples before treatment. The immunohistochemistry was used to the expression of FHIT protein in cancer tissues.</p><p><b>RESULTS</b>CpG island methylation of FHIT was detected in 31.13% of plasma samples. The expression of FHIT protein was decreased or discarded in 59.60% of cervical cancer tissues. Among them 47.78% was included in methylation positive samples.</p><p><b>CONCLUSION</b>CpG island methylation of FHIT gene in plasma plays an important role on cervical cancer, which results in decreased expression of FHIT protein. It can be used to diagnose and evaluate the effect of treatment to cervical cancers.</p>