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The prediction of refractory Mycoplasma pneumoniae pneumonia (RMPP) remains a clinically significant challenge. This study aimed to develop an early predictive model utilizing artificial intelligence (AI)-derived quantitative assessment of lung lesion extent on initial computed tomography (CT) scans and clinical indicators for RMPP in pediatric inpatients. A retrospective cohort study was conducted on patients with M. pneumoniae pneumonia (MP) admitted to the Children's Hospital of Nanjing Medical University, China from January 2019 to December 2020. An early prediction model was developed by stratifying the patients with Mycoplasma pneumoniae pneumonia (MPP) into two cohorts according to the presence or absence of refractory pneumonia. A retrospective cohort of 126 children diagnosed with Mycoplasma pneumoniae pneumonia (MPP) was utilized as a training set, with 85 cases classified as RMPP. Subsequently, a prospective cohort comprising 54 MPP cases, including 37 instances of RMPP, was assembled as a validation set to assess the performance of the predictive model for RMPP from January to December 2021. We defined a constant Φ which can combine the volume and CT value of pulmonary lesions and be further used to calculate the logarithm of Φ to the base of 2 (Log2Φ). A clinical-imaging prediction model was then constructed utilizing Log2Φ and clinical characteristics. Performance was evaluated by the area under the receiver operating characteristic curve (AUC). The clinical model demonstrated AUC values of 0.810 and 0.782, while the imaging model showed AUC values of 0.764 and 0.769 in the training and test sets, respectively. The clinical-imaging model, incorporating Log2Φ, temperature(T), aspartate aminotransferase (AST), preadmission fever duration (PFD), and preadmission macrolides therapy duration (PMTD), achieved the highest AUC values of 0.897 and 0.895 in the training and test sets, respectively. A prognostic model developed through automated quantification of lung disease on CT scans, in conjunction with clinical data in MPP may be utilized for the early identification of RMPP. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) have been confirmed to play a potential role in sepsis, but little is known about their role in sepsis-induced cardiomyopathy (SIC). Methods: The model of septic cardiomyopathy was constructed with H9c2 cells induced by lipopolysaccharide (LPS), and the expression of miR-539-5p was detected by qRT-PCR assay. ELISA, CCK-8, EdU TUNEL analysis were performed to evaluate the role of miR-539-5p in inflammation response, viability, proliferation and apoptosis of LPS-treated H9c2 cells. Moreover, miRWalk and TargetScan prediction, and dual-luciferase reporter gene assays were carried out to predict and confirm the target of miR-539-5p. Furthermore, the effects of target on inflammation response, proliferation and apoptosis of LPS-induced H9c2 cells mediated by miR-539-5p was further explored. Results: The expression of miR-539-5p was obviously down-regulated in LPS-induced H9c2 cells. In addition, over-expression of miR-539-5p significantly inhibited the inflammation response, promoted viability and proliferation, and suppressed apoptosis of LPS-treated H9c2 cells. Moreover, interleukin-1 receptor-associated kinase 3 (IRAK3) was verified as a target of miR-539-5p by dual-luciferase reporter gene assay. Besides, IRAK3 was highly expressed in H9c2 cells transfected with miR-539-5p inhibitor detected with qRT-PCR and western blot assays. Furthermore, over-expression of IRAK3 partially weakened the effects of miR-539-5p mimic on the inflammation response, proliferation and apoptosis of LPS-induced H9c2 cells. Conclusions: MiR-539-5p potentially plays an important role in the pathogenesis of LPS-induced sepsis by targeting IRAK3, suggesting that miR-539-5p may be a potential new target for the treatment of LPS-induced sepsis. [ABSTRACT FROM AUTHOR]

Since the outbreak of novel coronavirus infection pneumonia in Wuhan City, China, in late 2019, such cases have been gradually reported in other parts of China and abroad. Children have become susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) because of their immature immune function. As the outbreak has progressed, more cases of novel coronavirus infection/pneumonia in children have been reported. Compared with adults, the impact of SARS-CoV-2 infection in children is less severe, with a lower incidence and susceptibility in children, which results in fewer children being tested, thereby underestimating the actual number of infections. Therefore, strengthening the diagnosis of the disease is particularly important for children, and early and clear diagnosis can determine treatment strategies and reduce the harm caused by the disease to children. According to the Novel Coronavirus Infection Pneumonia Diagnosis and Treatment Standards (trial version 7) issued by National Health Committee and the latest diagnosis and treatment strategies for novel coronavirus infection pneumonia in children, this review summarizes current strategies on diagnosis and treatment of SARS-CoV-2 infection in children. [ABSTRACT FROM AUTHOR]