Risk factor analysis and prediction model construction for severe adenovirus pneumonia in children.

BACKGROUND: Severe adenovirus pneumonia in children has a high mortality rate, but research on risk prediction models is lacking. Such models are essential as they allow individualized predictions and assess whether children will likely progress to severe disease. METHODS: A retrospective analysis was performed on children with adenovirus pneumonia who were hospitalized at the Children's Hospital of Nanjing Medical University from January 2017 to March 2024. The patients were grouped according to clinical factors, and the groups were compared using Ridge regression and multiple logistic regression to identify risk factors associated with severe adenovirus pneumonia. A prediction model was constructed, and its value in clinical application was evaluated. RESULTS: 699 patients were included in the study, with 284 in the severe group and 415 in the general group. Through the screening of 44 variables, the final risk factors for severe adenovirus pneumonia in children as the levels of neutrophils (OR = 1.086, 95% CI: 1.054‒1.119, P < 0.001), D-dimer (OR = 1.005, 95% CI: 1.003‒1.007, P < 0.001), fibrinogen degradation products (OR = 1.341, 95% CI: 1.034‒1.738, P = 0.027), B cells (OR = 1.076, 95%CI: 1.046‒1.107, P < 0.001), and lactate dehydrogenase (OR = 1.008, 95% CI: 1.005‒1.011, P < 0.001). The value of the area under the receiver operating characteristic curve was 0.974, the 95% CI was 0.963-0.985, and the P-value of the Hosmer-Lemeshow test was 0.547 (P > 0.05), indicating that the model had strong predictive power. CONCLUSION: In this study, the clinical variables of children with adenovirus pneumonia were retrospectively analyzed to identify risk factors for severe disease. A prediction model for severe disease was constructed and evaluated, showing good application value.

miR-214-3p promotes the pathogenesis of Parkinson's disease by inhibiting autophagy.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characterized by dopaminergic neuron death in the substantia nigra, leading to motor dysfunction. Autophagy dysregulation has been implicated in PD pathogenesis. This study explores the role of miR-214-3p in PD, focusing on its impact on autophagy and dopaminergic neuron viability. Using in vitro and in vivo models, we demonstrate that miR-214-3p inhibits autophagy and promotes dopaminergic neuron apoptosis. Behavioral assessments and molecular analyses reveal exacerbation of PD symptoms upon miR-214-3p overexpression. Furthermore, mechanistic investigations identify ATG3 as a target, shedding light on miR-214-3p's regulatory role in autophagy. These findings enhance our understanding of PD pathogenesis and propose miR-214-3p as a potential biomarker and therapeutic target for modulating autophagy and neuronal survival in PD.