The aim of the present study was to determine the association between Alzheimer's disease (AD) and microRNA‑222 in the serum of patients with AD. The expression of microRNAs was detected and the results were verified using microarray analysis and reverse transcription‑quantitative polymerase chain reaction. The results indicated that there were 35 strips of microRNA in the mild AD group, in which the difference of expression signal was >500 IU/ml. There were 26 strips of microRNA with a difference in expression signal of >500 IU/ml in the mild and moderate AD groups. The downregulation of microRNA‑222 in the mild and moderate groups was statistically significant (P<0.01), and the expression of microRNA‑222 in the moderate group was significantly lower, compared with that in the mild AD group (P<0.05). It was concluded that microRNA‑222 may affect the occurrence and development of AD through a variety of mechanisms, and may serve as a biomarker for the early diagnosis of AD.

Objective: To explore the MRI T2 fluid-attenuated inversion recovery (FLAIR) vascular hyperintensities (FVH) combined with diffusion-weighted imaging (DWI) Alberta Stroke Program Early CT Score (ASPECTS) in predicting the prognosis of acute cerebral infarction (ACI) with endovascular treatment. Methods: The patients with ACI in the anterior circulation who underwent endovascular treatment from June 2016 to December 2020 were divided into a good prognosis group and a poor prognosis group according to the modified Rankin Scale (mRS) score at 90 days after the operation. The differences in general clinical baseline data, CT-ASPECTS, FVH, and DWI-ASPECTS between the two groups were analyzed. The receiver operating characteristic (ROC) curve was used to analyze the predictive power of prediction models on prognosis. Results: The results of the Binomial Logistic regression equation showed initial National Institute of Health stroke scale (NIHSS), Mori grade, DWI-ASPECTS, and FVH were independent risk factors for prognosis. The predictive power of the FVH+DWI-ASPECTS prediction model was highest, and the predictive power of DWI-ASPECTS was higher than that of CT-ASPECTS Conclusion: DWI-ASPECTS is better than CT-ASPECTS in predicting the prognosis of ACI with endovascular treatment, and the combined prediction model of FVH and DWI-ASPECTS has higher prediction performance, which can be used as a preoperative evaluation method to predict the effect of endovascular treatment for ACI.