Rationale: Some patients with coronavirus disease 2019 (COVID-19) rapidly develop respiratory failure or even die, underscoring the need for early identification of patients at elevated risk of severe illness. This study aims to quantify pneumonia lesions by computed tomography (CT) in the early days to predict progression to severe illness in a cohort of COVID-19 patients. Methods: This retrospective cohort study included confirmed COVID-19 patients. Three quantitative CT features of pneumonia lesions were automatically calculated using artificial intelligence algorithms, representing the percentages of ground-glass opacity volume (PGV), semi-consolidation volume (PSV), and consolidation volume (PCV) in both lungs. CT features, acute physiology and chronic health evaluation II (APACHE-II) score, neutrophil-to-lymphocyte ratio (NLR), and d-dimer, on day 0 (hospital admission) and day 4, were collected to predict the occurrence of severe illness within a 28-day follow-up using both logistic regression and Cox proportional hazard models. Results: We included 134 patients, of whom 19 (14.2%) developed any severe illness. CT features on day 0 and day 4, as well as their changes from day 0 to day 4, showed predictive capability. Changes in CT features from day 0 to day 4 performed the best in the prediction (area under the receiver operating characteristic curve = 0.93, 95% confidence interval [CI] 0.87~0.99; C-index=0.88, 95% CI 0.81~0.95). The hazard ratios of PGV and PCV were 1.39 (95% CI 1.05~1.84, P=0.023) and 1.67 (95% CI 1.17~2.38, P=0.005), respectively. CT features, adjusted for age and gender, on day 4 and in terms of changes from day 0 to day 4 outperformed APACHE-II, NLR, and d-dimer. Conclusions: CT quantification of pneumonia lesions can early and non-invasively predict the progression to severe illness, providing a promising prognostic indicator for clinical management of COVID-19.
MicroRNAs (miRNAs) emerge as important regulators of stem cell lineage commitment and bone development. MiRNA-26a (miR-26a) is one of the important miRNAs regulating osteogenic differentiation of both bone marrow-derived mesenchymal stem cells (BMSCs) and adipose tissue-derived mesenchymal stem cells (ADSCs). However, miR-26a functions oppositely in osteogenic differentiation of BMSCs and ADSCs, suggesting distinct post-transcriptional regulation of tissue-specific MSC differentiation. However, the molecular basis is largely unknown. Here, we report that the function of miR-26a is largely depended on the intrinsic signaling regulation network of MSCs. Using bioinformatics and functional assay, we confirmed that miR-26a potentially targeted on GSK3β and Smad1 to regulate Wnt and BMP signaling pathway. Overall comparative analysis revealed that Wnt signaling was enhanced more potently and played a more important role than BMP signaling in osteogenic differentiation of BMSCs, whereas BMP pathway was more essential for promoting osteogenic differentiation of ADSCs. The distinct activation pattern and role of signaling pathways determined that miR-26a majorly targeted on GSK3β to activate Wnt signaling for promoting osteogenic differentiation of BMSCs, whereas it inhibited Smad1 to suppress BMP signaling for interfering with the osteogenic differentiation of ADSCs. Taken together, our study demonstrated that BMSCs and ADSCs applied different signaling pathway to facilitate their osteogenic differentiation, which determined the inverse function of miR-26a. The distinct transcriptional regulation and post-transcriptional regulation network suggested the intrinsic molecular differences between tissue-specific MSCs and the complexity in MSC research and MSC-based cell therapy.
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