Incidence of Cerebral Infarction in Northwest China From 2009 to 2018

miR-100-5p activation of the autophagy response through inhibiting the mTOR pathway and suppression of cerebral infarction progression in mice

In recent years, the association between microRNAs (miRNAs) and autophagy in cerebral infarction (CI) has attracted increasingly more attention. The mammalian target of the rapamycin (mTOR) pathway is a key protein regulating the autophagy response. miR-100-5p can bind to the mTOR protein, but its role in CI remains unclear yet. This experiment aims to clarify the role of miR-100-5p in CI. Bioinformatics analysis was performed to screen differentiated expressed functional genes between CI tissue and normal tissue specimens. In vivo experiments: the mouse model of CI was established by middle cerebral artery occlusion (MCAO) methods, After being treated with miR-100-5p-overexpressing lentivirus, the amount of terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling (TUNEL)-positive fluorescence and the fluorescent expression level of mTOR protein were significantly inhibited in the CI region. Western blotting analysis showed that miR-100-5p inhibited the protein expression level of phosphorylated mTOR and total mTOR and enhanced the expression of autophagy-related proteins Beclin, microtubule-associated protein light chain 3II (LC-3II), and autophagy-related gene 7 (ATG-7). For in vitro experiment, after the BV-2 cells were successfully infected with the control lentivirus and miR-100-5p-overexpression lentivirus, they were stimulated with 1% hypoxia and low-glucose medium in a tri-gas incubator for 24 h. It was found that miR-100-5p could significantly lower the protein expression level of phosphorylated mTOR and total mTOR, and increase the expression of the Beclin, LC-3II, ATG-7 autophagy related proteins. miR-100-5p promotes the autophagy response through binding to mTOR protein, thereby inhibiting apoptosis and delaying the progression of CI.

Effect of medical care linkage-continuous management mode in patients with posterior circulation cerebral infarction undergoing endovascular interventional therapy

BACKGROUND

Acute cerebral infarction is a severe type of ischemic stroke that can be divided into anterior circulation cerebral infarction and posterior circulation cerebral infarction (PCCI). PCCI affects the structure of the posterior circulation brain, because posterior part of the brain, which has more complex anatomical structures and more prone to posterior circulation vascular variation. Therefore, improving the prognosis of PCCI patients is necessary.

AIM

To explore the effect of medical care linkage-continuous management mode (MCLMM) on endovascular interventional therapy (EIT) for PCCI.

METHODS

Sixty-nine patients with PCCI who received EIT and conventional nursing intervention were selected as the control group, and 78 patients with PCCI who received EIT and MCLMM intervention were selected as the observation group. The incidence of postoperative complications, compliance and disease self-management behavior after six months of intervention, modified Rankin scale (mRS) and Barthel index (BI) scores in the acute phase and after one year of intervention, and recurrence within one year were compared between the two groups.

RESULTS

The total incidence rate of postoperative complications in the observation group (7.69%) was lower than that in the control group (18.84%) (P < 0.05). The scores for medical compliance behavior (regular medication, appropriate diet, and rehabilitation cooperation rates) and disease self-management behavior (self-will, disease knowledge, and self-care ability) in the observation group were higher than those in the control group (P < 0.05). After one year of intervention, in the observation group, the mRS score was significantly lower, and the BI score was significantly higher than those in the control group (P < 0.05). The recurrence rate within one year in the observation group (3.85%) was significantly lower than that in the control group (13.04%) (P < 0.05).

CONCLUSION

MCLMM can reduce the incidence of complications after EIT for PCCI, improve patient compliance behavior and disease self-management ability, and promote the recovery of neurological function.

Prediction Model between Serum Vitamin D and Neurological Deficit in Cerebral Infarction Patients Based on Machine Learning

Objective

Vitamin D is associated with neurological deficits in patients with cerebral infarction. This study uses machine learning to evaluate the prediction model's efficacy of the correlation between vitamin D and neurological deficit in patients with cerebral infarction.

Methods

A total of 200 patients with cerebral infarction admitted to the Department of Neurology of our hospital from July 2018 to June 2019 were selected. The patients were randomly divided into a training set (n = 140) and a test set (n = 60) in a 7 : 3 ratio. The prediction model is constructed from the training set's data, and the model's prediction effect was evaluated by test set data. The area under the receiver operator characteristic curve was used to assess the prediction efficiency of models.

Results

In the training set, the area under the curve (AUC) of the logistic regression model and XGBoost algorithm model was 0.727 (95% CI: 0.601~0.854) and 0.818 (95% CI: 0.734~0.934), respectively. While in the test set, the AUC of the logistic regression model and XGBoost algorithm model was 0.761 (95% CI: 0.640~0.882) and 0.786 (95% CI: 0.670~0.902), respectively.

Conclusion

The prediction model of the correlation between vitamin D and neurological deficit in patients with cerebral infarction based on machine learning has a good prediction efficiency.