Objectives:To investigate the predictive factors of stroke associated-pneumonia (SAP) in patients with acute stroke, develop nomogram and neural network prediction models and verify their predictive performance.Methods:Patients with acute stroke admitted to the First Affiliated Hospital of Kunming Medical University and Zhenxiong County People's Hospital were included retrospectively. Multivariate logistic regression analysis was used to determine the independent predictive factors of SAP, and develop nomogram and neural network prediction models. Receiver operating characteristic curve (ROC) curves were used to validate and compare the predictive performances. Results:A total of 450 patients with acute stroke were enrolled, including 286 males (63.6%), aged 64.28±13.24 years; 344 patientss (76.4%) had ischemic stroke and 106 (23.6%) had hemorrhagic stroke; 128 patients (28.4%) experienced SAP. According to the random number method, they were divided into a modeling cohort ( n=300) and a validation cohort ( n=150). Multivariate logistic regression analysis in the modeling cohort showed that a higher baseline National Institutes of Health Stroke Scale (NIHSS) score, gastric tube placement, use of proton pump inhibitors, heart failure, and higher neutrophil/lymphocyte ratio (NLR) were the independent predictive factors of SAP. ROC curve analysis showed that the area under the ROC curve of the nomogram model for predicting SAP in the modeling cohort and validation cohort was 0.841 (95% confidence interval [ CI] 0.795-0.880) and 0.863 (95% CI 0.798-0.914), respectively. The sensitivity for predicting SAP were 75.00% and 70.45%, respectively, and the specificity was 81.94% and 92.45%, respectively. The area under the ROC curve of the neural network model for predicting SAP in the modeling cohort and validation cohort was 0.847 (95% CI 0.802-0.866) and 0.862 (95% CI 0.796-0.913), respectively. The sensitivity for predicting SAP were 76.19% and 72.73%, and the specificity was 79.17% and 89.62%, respectively. Conclusions:Higher NIHSS score, gastric tube placement, use of proton pump inhibitors, heart failure, and higher NLR are the independent risk factors for SAP in patients with acute stroke. The nomogram and neural network prediction model developed using the above risk factors have higher predictive value for SAP.

Human parainfluenza virus（HPIV）is one of the important causes of respiratory infections in children，and it can occur year-round.There are four serotypes of HPIV，each with both similarities and certain differences.HPIV is associated with various diseases，but currently there are no effective therapeutic drugs or targeted vaccines on the market，mainly focusing on symptomatic supportive treatment.This review summarized the epidemiology，risk factors，pathogenic mechanisms，clinical characteristics，laboratory diagnosis，treatment，and prevention of HPIV，providing a basis for the early diagnosis，treatment，and prevention of HPIV.

Aim To explore the effect of activated SK channels(small conductance Ca2+-activated K+ channels) on morphine-induced hyperalgesia in the spinal cord in mice.Methods Adult C57BL6/N male mice were chosen to establish the model of morphine-hyperalgesia.The changes of tail withdrawal latency(TWL), mechanical withdrawal threshold(MWT) and the threshold of visceral pain were observed after intrathecal 1-EBIO, the agonist of SK channels.Results Compared with the control group, TWL, MWT and the threshold of visceral pain were decreased after morphine injection.After intrathecal 1-EBIO, the TWL, MWT and visceral pain threshold were increased.The level of spinal membrane SK2 expression in morphine-treated mice was decreased compared with that of control group.After intrathecal 1-EBIO, the level of spinal membrane SK2 expression was increased.Conclusion SK channels in the spinal cord are involved in morphine-induced hyperalgesia in mice.