Objectives Rapid and accurate diagnosis of coronavirus disease 2019 is critical during the epidemic. We aim to identify differences in CT imaging and clinical manifestations between pneumonia patients with and without COVID-19, and to develop and validate a diagnostic model for COVID-19 based on radiological semantic and clinical features alone. Methods A consecutive cohort of 70 COVID-19 and 66 non-COVID-19 pneumonia patients were retrospectively recruited from five institutions. Patients were divided into primary (n = 98) and validation (n = 38) cohorts. The chi-square test, Student's t test, and Kruskal-Wallis H test were performed, comparing 1745 lesions and 67 features in the two groups. Three models were constructed using radiological semantic and clinical features through multivariate logistic regression. Diagnostic efficacies of developed models were quantified by receiver operating characteristic curve. Clinical usage was evaluated by decision curve analysis and nomogram. Results Eighteen radiological semantic features and seventeen clinical features were identified to be significantly different. Besides ground-glass opacities (p = 0.032) and consolidation (p = 0.001) in the lung periphery, the lesion size (1-3 cm) is also significant for the diagnosis of COVID-19 (p = 0.027). Lung score presents no significant difference (p = 0.417). Three diagnostic models achieved an area under the curve value as high as 0.986 (95% CI 0.966~1.000). The clinical and radiological semantic models provided a better diagnostic performance and more considerable net benefits. Conclusions Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. A model composed of radiological semantic and clinical features has an excellent performance for the diagnosis of COVID-19.Xiaofeng Chen and Yanyan Tang contributed equally to this work.Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00330-020-06829-2) contains supplementary material, which is available to authorized users. Key Points• Based on CT imaging and clinical manifestations alone, the pneumonia patients with and without COVID-19 can be distinguished. • A diagnostic model for COVID-19 was developed and validated using radiological semantic and clinical features, which had an area under the curve value of 0.986 (95% CI 0.966~1.000) and 0.936 (95% CI 0.866~1.000) in the primary and validation cohorts, respectively.

The ability of the brain to predict future events based on the pattern of recent sensory experience is critical for guiding animal's behavior. Neocortical circuits for ongoing processing of sensory stimuli are extensively studied, but their contributions to the anticipation of upcoming sensory stimuli remain less understood. We, therefore, used in vivo cellular imaging and fiber photometry to record mouse primary auditory cortex to elucidate its role in processing anticipated stimulation. We found neuronal ensembles in layers 2/3, 4, and 5 which were activated in relationship to anticipated sound events following rhythmic stimulation. These neuronal activities correlated with the occurrence of anticipatory motor responses in an auditory learning task. Optogenetic manipulation experiments revealed an essential role of such neuronal activities in producing the anticipatory behavior. These results strongly suggest that the neural circuits of primary sensory cortex are critical for coding predictive information and transforming it into anticipatory motor behavior.

Dioscin, extracted from the root of Polygonatum zanlanscianense pamp, exhibits cytotoxicity towards human myeloblast leukemia HL-60 cells. Proteomic analysis revealed that the expression of mitochondrial associated proteins was substantially altered in HL-60 cells corresponding to the dioscin treatment, suggesting that mitochondria are the major cellular target of dioscin. Mitochondrial functional studies validated that mitochondrial apoptotic pathway was initiated by dioscin treatment. Changes in proteome other than mitochondrial related proteins implicate that other mechanisms were also involved in dioscin-induced apoptosis in HL-60 cells, including the activity impairment in protein synthesis, alterations of phosphatases in cell signaling, and deregulation of oxidative stress and cell proliferation. Current study of protein alterations in dioscin-treated HL-60 cells suggested that dioscin exerts cytotoxicity through multiple apoptosis-inducing pathways.