Research on Early Warning Mechanism and Model of Liver Cancer Rehabilitation Based on CS-SVM.

Since the 20th century, cancer has become one of the main diseases threatening human health. Liver cancer is a malignant tumor with extremely high clinical morbidity and fatality rate and easy recurrence after surgery. Research on the postoperative recurrence time and recurrence location of patients with liver cancer has a crucial influence on the postoperative intervention of patients. Evaluation of the clinical manifestations of patients after liver cancer surgery is conducted according to medical knowledge or national standards to determine the main factors affecting liver cancer rehabilitation. In order to better study the mechanism of liver cancer recurrence, this paper uses CS-SVM to predict the recurrence time of liver cancer patients, so as to timely intervene the patients. There are five evaluation indicators which are basic indicators, immune indicators, microenvironment indicators, psychological indicators, and nutritional indicators, respectively. This paper collects the clinical evaluation data of postoperative follow-up visits for patients with liver cancer in a hospital, improves the parameter selection process of the support vector machine by using the search ability of the cuckoo algorithm, and establishes an algorithm-optimized prediction model of support vector machine for the prognosis of liver cancer to predict the location and approximate time of recurrence. According to the clinical evaluation data of patients with liver cancer after surgery, logistics regression, BP neural network, and other related methods are used to predict the prognosis of liver cancer patients after surgery. The prediction effects of several methods are compared, and the superiority of the model is discussed. At the end of this article, we conducted an empirical analysis on the clinical evaluation data of patients with liver cancer after surgery. For the collected samples of 776 liver cancer recurrences after surgery, the established liver cancer prognosis outcome prediction model was used to predict the recurrence time and recurrence location, respectively. The mean square error of recurrence time prediction is 9.2101, which is much smaller than the prediction mean square error of BP neural network of 177.9451; the prediction accuracy of recurrence location is 95.7%, which is much higher than the 63.14% of logistic regression. The empirical analysis results show that the improved support vector machine model based on cuckoo established in this paper can effectively predict the time and location of cancer recurrence.

Effect of lead exposure on neuroinflammation of hippocampus and cognitive impairment in diabetic rats / 中国职业医学

OBJECTIVE: To explore the effects of lead exposure on inflammatory damage of hippocampus and cognitive impairment in diabetic rats. METHODS: The specific pathogen free(SPF) male healthy Wistar rats were randomly divided into control group and lead-exposed group. The SPF male Goto-Kakisaki Wistar rats rats were randomly divided into diabetes group and diabetes lead-exposed group, with 10 rats in each group. Rats in lead-exposed group and diabetes lead-exposed group were continuously exposed to lead acetate water with a mass fraction of 0.025% for 9 weeks. Rats in control group and diabetes group were given distilled water. The body weight and blood glucose level of rats were measured before lead exposure and at 1, 3, 5, 7 and 9 weeks after exposure. After the exposure, Morris water maze test was used to evaluate the learning and memory ability of rats. The lead levels in whole blood and hippocampal tissues were detected by inductively coupled plasma mass spectrometry, and the expression of mRNA and protein expression of inflammatory factors in hippocampal tissues of rats were detected by real-time fluorescence quantitative polymerase chain reaction and enzyme-linked immunoadsorption, respectively. RESULTS: At the end of lead exposure, the difference of body mass of rats in the diabetes group and the diabetes lead-exposed group was not statistically significant compared with that in the same group before exposure(all P values were >0.05); but the body mass of rats in these two groups was lower than that of the control group and the lead-exposure group(all P values were <0.05). The blood glucose levels of rats were higher in the diabetic group and the diabetes lead-exposed group than that in the control group and the lead-exposed group, respectively(all P values were <0.05). Morris water maze test showed that the escape latency of rats in the 1 st, 2 nd and 3 rd day were longer in diabetes group and the diabetes lead-exposed group than that in the control group and the lead-exposed group(all P values were <0.05). The number of times of crossing platforms were less in the lead-exposed group and the diabetes group than that of the control group(all P values were <0.05). The number of times of crossing platforms was more in the diabetes lead-exposed group than that in the other 3 groups(all P values were <0.05). The levels of lead in blood and hippocampus of rats were higher in the lead-exposed group than those in the control group(all P values were <0.05), and those in the diabetes lead-exposed group were higher than that in the other 3 groups(all P values were <0.05). The relative expression of mRNA of interferon-γ(ifn-γ) and interleukin(il)-6 in hippocampal tissues of rats was higher in the lead-exposed group and the diabetes group than that of the control group(all P values were <0.05). The relative expression of mRNA of tumour necrosis factor-α(tnf-α) and il-1β in the hippocampal tissues of rats was higher in the diabetes group than that of the control group and the lead-exposed group, respectively(all P values were <0.05). The relative expression of mRNA of ifn-γ, tnf-α, il-1β and il-6 in hippocampal tissues of rats was higher in the diabetes lead-exposed group than that of the other 3 groups(all P values were <0.05). The relative protein expression of IFN-γ, TNF-α, IL-4 and IL-6 in hippocampal tissues of rats was higher in lead-exposed group than that of the control group(all P values were <0.05). The relative protein expression of IFN-γ, TNF-α, IL-1β and IL-6 in hippocampal tissues of rats was higher in diabetes group than that of the control group(all P values were <0.05). The relative protein expression of IFN-γ, IL-1β and IL-6 in hippocampal tissues of rats was higher in diabetes group than that of the other 3 groups(all P values were <0.05). CONCLUSION: Diabetes can promote the lead accumulation in the blood and hippocampus of rats. The combined effect of lead exposure and diabetes can up-regulate the expression of pro-inflammatory cytokines in the hippocampal tissues of rats, aggravate the inflammatory response, and have a synergistic effect on the cognitive impairment in rats.

Study on the theoretical basis of medical informatics based on knowledge management / 中华医院管理杂志

Traditional theories on information management have made an extreme of studies and practice on medical informatics, which has hampered the development of medical informatics. Knowledge management is a brand new theory based on information and aiming at innovation of knowledge, and is in accordance with the nature of medical informatics. Medical informatics based on knowledge management promotes management of medical information, which not only benefits the integration and development of disciplines of medical informatics, also benefits hospital informatization, implementation of evidence-based medicine, and education in medical informatics. Basic studies on medical informatics, personnel training and management should be guided by knowledge management theory in the field of informatics.