Stroke is a cerebrovascular disease with high fatality and disability rates， which brings heavy psychological burden along with physical disorder to patients. In recent years， transcranial magnetic stimulation （TMS） has attracted great attention in the research on functional prognosis of stroke patients. TMS can reveal the degree of corticospinal tract injury from a neurophysiological point of view and provide key information for functional recovery， and it is widely used in the rehabilitation treatment of post-stroke dysfunction. This article reviews the basic principle， classification， mechanism of TMS in promoting functional recovery of stroke， as well as its application in rehabilitation treatment， so as to lay a foundation for individualized neurological rehabilitation and improve the long-term prognosis of patients to the largest extent.
Stroke ; Prognosis

Objective:To study the correlation of TCM syndrome elements of large artery atherosclerosis (LAA) cerebral infarction with the new four thrombotic markers and cerebrovascular disease risk factors.Methods:Retrospective analysis was conducted for the baseline data and four diagnosis of 174 patients with LAA cerebral infarction in Department of Neurology, Shanxi Provincial People's Hospital from August 2022 to September 2023. These patients were classified into six TCM syndrome elements: internal wind, qi deficiency, internal fire, blood stasis, yin deficiency, and phlegm-dampness. Thrombomodulin (TM), fibrin-α2 antifibrinolytic inhibitor complex (PIC), thrombin-antithrombinogen complex (TAT), and tissue-type plasminogen activator-plasminogen activator inhibitor complex (t-PAIC) tests were performed in 24 h. Correlation analysis was conducted between the TCM syndrome typing of LAA stroke patients and baseline data, as well as the results of four thrombotic tests.Results:Among the 174 patients with LAA cerebral infarction, 49 (28.16%) were in the internal wind type, 37 (21.26%) in the phlegm-dampness type, 37 (21.26%) in the qi deficiency type, 16 (9.20%) in the internal fire type, 18 (10.35%) in the yin deficiency type, and 17 (9.77%) in the blood stasis type. Comparison of plasma TM ( P=0.003), PIC ( P=0.022), TAT ( P<0.001) and t-PAIC ( P=0.007) levels of each TCM syndrome element showed statistically significant differences ( P<0.05). Logistic regression analysis showed that gender was an influencing factor for the internal wind syndrome element and qi deficiency syndrome element [ OR (95% CI)=0.140 (0.037-0.536)] and blood stasis syndrome element [ OR (95% CI)=0.185 (0.042-0.820)] in TCM; TM was an influencing factor for the internal wind syndrome element and yin deficiency syndrome element [ OR (95% CI)=0.617 (0.423-0.900)], and blood stasis syndrome element [ OR (95% CI)=0.693 (0.496-0.968) ]; TAT was an influencing factor for internal wind syndrome element and phlegm-dampness syndrome element [ OR (95% CI)=2.143 (1.364-3.367)], qi deficiency syndrome element [ OR (95% CI)=1.937 (1.221-3.073)], and internal fire syndrome element [ OR (95% CI)=1.937 (1.221-3.073)], internal fire evidence element [ OR (95% CI)=2.949 (1.796-4.842)], and blood stasis evidence element [ OR (95% CI)=2.118 (1.246-30 600)]; t-PAIC was an influential factor for internal wind syndrome element and qi deficiency syndrome element [ OR (95% CI)=1.140 (1.033-1.258)] ( P<0.05). The ROC curve suggested that a TM level of 8.05 TU/ml had a diagnostic performance of 71.8% for the yin deficiency syndrome; a TAT level of 2.45 ng/L had a diagnostic performance of 71.2% for the internal wind syndrome; a TAT level of 1.65 ng/L had a diagnostic performance of 72.6% for the internal fire syndrome; and a t-PAIC level of 17.55 ng/L had a diagnostic performance of 70.4% for the qi deficiency syndrome. The diagnostic performance of t-PAIC was 70.4% at a t-PAIC level of 17.55 ng/L. Conclusion:Plasma TM, TAT, and t-PAIC levels are independent risk factors for different syndrome elements in patients with LAA cerebral infarction and can be used as markers for early determination of different syndrome elements.

In order to study the effect of middle ear malformations on energy absorbance, we constructed a mechanical model that can simulate the energy absorbance of the human ear based on our previous human ear finite element model. The validation of this model was confirmed by two sets of experimental data. Based on this model, three common types of middle ear malformations,
Ear Ossicles ; Humans ; Incus ; Malleus