Project description:=Since the COVID-19 outbreak in Wuhan City in December of 2019, numerous model predictions on the COVID-19 epidemics in Wuhan and other parts of China have been reported. These model predictions have shown a wide range of variations. In our study, we demonstrate that nonidentifiability in model calibrations using the confirmed-case data is the main reason for such wide variations. Using the Akaike Information Criterion (AIC) for model selection, we show that an SIR model performs much better than an SEIR model in representing the information contained in the confirmed-case data. This indicates that predictions using more complex models may not be more reliable compared to using a simpler model. We present our model predictions for the COVID-19 epidemic in Wuhan after the lockdown and quarantine of the city on January 23, 2020. We also report our results of modeling the impacts of the strict quarantine measures undertaken in the city after February 7 on the time course of the epidemic, and modeling the potential of a second outbreak after the return-to-work in the city.
Project description:A novel coronavirus pneumonia, first identified in Wuhan City and referred to as COVID-19 by the World Health Organization, has been quickly spreading to other cities and countries. To control the epidemic, the Chinese government mandated a quarantine of the Wuhan city on January 23, 2020. To explore the effectiveness of the quarantine of the Wuhan city against this epidemic, transmission dynamics of COVID-19 have been estimated. A well-mixed "susceptible exposed infectious recovered" (SEIR) compartmental model was employed to describe the dynamics of the COVID-19 epidemic based on epidemiological characteristics of individuals, clinical progression of COVID-19, and quarantine intervention measures of the authority. Considering infected individuals as contagious during the latency period, the well-mixed SEIR model fitting results based on the assumed contact rate of latent individuals are within 6-18, which represented the possible impact of quarantine and isolation interventions on disease infections, whereas other parameter were suppose as unchanged under the current intervention. The present study shows that, by reducing the contact rate of latent individuals, interventions such as quarantine and isolation can effectively reduce the potential peak number of COVID-19 infections and delay the time of peak infection.
Project description:This study used an emerging analytical technology (cDNA microarrays) to assess the potential effects of PFC exposure on largemouth bass in TCMA lakes. Microarrays simultaneously measure the expression of thousands of genes in various tissues from organisms exposed to different environmental conditions. From this large data set, biomarkers (i.e., genes that are expressed in response to an exposure to known stressors) and bioindicators (e.g., suites of genes that correspond to changes in organism health) can be simultaneously measured to clarify the relationship between contaminant exposure and organism health. Based on current scientific literature, we hypothesized that gene expression patterns would be altered in fish exposed to PFCs (as compared with fish from reference lakes), and that the magnitude of these changes would correspond to the concentrations of PFCs present throughout TCMA lakes. Patterns of gene expression in largemouth bass observed across the TCMA lakes corresponded closely with PFC concentration. Concentrations of PFCs in largemouth bass varied significantly across the sampled lakes, where the lowest concentrations were found in Steiger and Upper Prior Lakes and the highest concentrations were found in Calhoun and Twin Lakes. Patterns of gene expression were most different (relative to controls) in fish with the highest PFC tissue concentrations, where fish from Twin and Calhoun Lakes were observed to have between 5437 and 5936 differentially expressed genes in liver and gonad tissues. Although gene expression patterns demonstrated a high degree of correlation with PFC concentrations, microarray data also suggest there are likely additional factors influencing gene expression patterns in largemouth bass in TCMA lakes.
Project description:Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan 430060, RP China
Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, RP China
Project description:Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan 430060, RP China
Hubei Key Laboratory of Metabolic and Chronic Diseases, Wuhan, RP China
Project description:mRNA from primary PHH or iHCC was prepared according to the TruSeqTM RNA Sample Preparation Guide, and sequencing was performed on BGISEQ-500 (BGI, Wuhan, China).