Observation of auxiliary efficacy of minocycline ointment on local inflammatory response in chronic periodontitis / 中国现代医生

Objective To investigate the effect of minocycline ointment in chronic periodontitis and its auxiliary efficacy on local inflammatory response.Methods From February to September 2022,88 patients with chronic periodontitis treated were randomly divided into control group(routine treatment)and study group(treated with minocycline ointment),44 cases in each group.The clinical therapeutic effects,inflammatory factors in gingival crevicular fluid,periodontal improvement and collagen indexes of the two groups were compared.Results At 2 weeks of treatment,the total clinical effective rates of the two groups were 81.82%and 63.64%respectively.The study group was slightly higher than the control group,but the difference was not statistically significant(P>0.05).At 4 weeks of treatment,the total effective rate in the study group(95.45%)was higher than that in the control group(77.27%),the difference was statistically significant(P<0.05).At 2 and 4 weeks of treatment,the levels of hypersensitive-C-reactive protein and interleukin-10 inflammatory factors in the study group were better than those in the control group,and the differences were statistically significant(P<0.05).At 2 and 4 weeks of treatment,the levels of plaque index,gingival index and periodontal pocket depth in the study group were better than those in the control group,and the differences were statistically significant(P<0.05).after one course of treatment and two courses of treatment,the collagen index of gingival crevicular fluid in the study group was better than that in the control group,and the difference was statistically significant(P<0.05).Conclusion Minocycline ointment can improve the inflammatory reaction process and microecological balance of local periodontal tissue in patients with chronic periodontitis.It has important clinical significance for promoting the recovery of periodontal tissue and is one of the ideal ways for clinical treatment of chronic periodontitis.

Progress of classification algorithms for motor imagery electroencephalogram signals / 生物医学工程学杂志

Motor imagery (MI), motion intention of the specific body without actual movements, has attracted wide attention in fields as neuroscience. Classification algorithms for motor imagery electroencephalogram (MI-EEG) signals are able to distinguish different MI tasks based on the physiological information contained by the EEG signals, especially the features extracted from them. In recent years, there have been some new advances in classification algorithms for MI-EEG signals in terms of classifiers versus machine learning strategies. In terms of classifiers, traditional machine learning classifiers have been improved by some researchers, deep learning and Riemannian geometry classifiers have been widely applied as well. In terms of machine learning strategies, ensemble learning, adaptive learning, and transfer learning strategies have been utilized to improve classification accuracies or reach other targets. This paper reviewed the progress of classification algorithms for MI-EEG signals, summarized and evaluated the existing classifiers and machine learning strategies, to provide new ideas for developing classification algorithms with higher performance.