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Epidemiological compartmental models, such as SEIR (Susceptible, Exposed, Infectious, and Recovered) models, have been generally used in analyzing epidemiological data and forecasting the trajectory of transmission of infectious diseases such as COVID-19. Experience shows that accurately forecasting the trajectory of COVID-19 transmission curve is a big challenge for researchers in the field of epidemiological modeling because multiple unquantified factors can affect the trajectory of COVID-19 transmission. In the past years, we used a new compartmental model, l-i SEIR model, to analyze the COVID-19 transmission trend in the United States. Unlike the conventional SEIR model and the delayed SEIR model that use or partially use the approximation of temporal homogeneity, the l-i SEIR model takes into account chronological order of infected individuals in both latent (l) period and infectious (i) period, and thus improves the accuracy in forecasting the trajectory of transmission of infectious diseases, especially during periods of rapid rise or fall in the number of infections. This paper describes (1) how to use the new SEIR model (a mechanistic model) combined with fitting methods to simulate or predict trajectory of COVID-19 transmission, (2) how social interventions and new variants of COVID-19 significantly change COVID-19 transmission trends by changing transmission rate coefficient βn, the fraction of susceptible people (Sn/N), and the reinfection rate, (3) why accurately forecasting COVID-19 transmission trends is difficult, (4) what are the strategies that we have used to improve the forecast outcome and (5) what are some successful examples that we have obtained. [ABSTRACT FROM AUTHOR]

The Susceptible-Exposed-Infectious-Recovered (SEIR) epidemic model has been commonly used to analyze the spread of infectious diseases. This 4-compartment (S, E, I and R) model uses an approximation of temporal homogeneity of individuals in these compartments to calculate the transfer rates of the individuals from compartment E to I to R. Although this SEIR model has been generally adopted, the calculation errors caused by temporal homogeneity approximation have not been quantitatively examined. In this study, a 4-compartment l-i SEIR model considering temporal heterogeneity was developed from a previous epidemic model (Liu X., Results Phys. 2021; 20:103712), and a closed-form solution of the l-i SEIR model was derived. Here, l represents the latent period and i represents the infectious period. Comparing l-i SEIR model with the conventional SEIR model, we are able to examine how individuals move through each corresponding compartment in the two SEIR models to find what information may be missed by the conventional SEIR model and what calculation errors may be introduced by using the temporal homogeneity approximation. Simulations showed that l-i SEIR model could generate propagated curves of infectious cases under the condition of l>i. Similar propagated epidemic curves were reported in literature, but the conventional SEIR model could not generate propagated curves under the same conditions. The theoretical analysis showed that the conventional SEIR model overestimates or underestimates the rate at which individuals move from compartment E to I to R in the rising or falling phase of the number of infectious individuals, respectively. Increasing the rate of change in the number of infectious individuals leads to larger calculation errors in the conventional SEIR model. Simulations from the two SEIR models with assumed parameters or with reported daily COVID-19 cases in the United States and in New York further confirmed the conclusions of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Recently, the stable light products and radiance calibrated products from Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System (OLS) have been useful for mapping global fossil fuel carbon dioxide (CO2) emissions at fine spatial resolution. However, few studies on this subject were conducted with the new-generation nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite, which has a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. Therefore, this study performed the first evaluation of the potential of NPP-VIIRS data in estimating the spatial distributions of global CO2 emissions (excluding power plant emissions). Through a disaggregating model, three global emission maps were then derived from population counts and three different types of nighttime lights data (NPP-VIIRS, the stable light data and radiance calibrated data of DMSP-OLS) for a comparative analysis. The results compared with the reference data of land cover in Beijing, Shanghai and Guangzhou show that the emission areas of map from NPP-VIIRS data have higher spatial consistency of the artificial surfaces and exhibit a more reasonable distribution of CO2 emission than those of other two maps from DMSP-OLS data. Besides, in contrast to two maps from DMSP-OLS data, the emission map from NPP-VIIRS data is closer to the Vulcan inventory and exhibits a better agreement with the actual statistical data of CO2 emissions at the level of sub-administrative units of the United States. This study demonstrates that the NPP-VIIRS data can be a powerful tool for studying the spatial distributions of CO2 emissions, as well as the socioeconomic indicators at multiple scales. [ABSTRACT FROM AUTHOR]

The genome of Buzura suppressaria nucleopolyhedrovirus (BusuNPV) was sequenced by 454 pyrosequencing technology. The size of the genome is 120,420 bp with 36.8% G+C content. It contains 127 hypothetical open reading frames (ORFs) covering 90.7% of the genome and includes the 37 conserved baculovirus core genes, 84 genes found in other baculoviruses, and 6 unique ORFs. No typical baculoviral homologous repeats (hrs) were present but the genome contained a region of repeated sequences. Gene Parity Plots revealed a 28.8 kb region conserved among the alpha- and beta-baculoviruses. Overall comparisons of BusuNPV to other baculoviruses point to a distinct species in group II Alphabaculovirus. [ABSTRACT FROM AUTHOR]

Inactivated LRRC4 has been clinically detected in gliomas, and promoter hypermethylation has been implicated as the mechanism of inactivation in some of those tumors. Our previous researches indicated that LRRC4 is a target gene of miR-381, the interaction of miR-381 and LRRC4 is involved in glioma growth. In this study, we demonstrate that LRRC4 is a target gene of the other microRNA, miR-182. We found that the high expression of miR-182 and miR-381 in gliomas are involved in pathological malignant progression. The silencing of miR-182 and miR-381 inhibited the proliferation in vitro and growth of glioma cell with in vivo magnetic resonance imaging by intracranial transplanted tumor model in rats. We also demonstrated that BRD7, a transcriptional cofactor for p53, is highly expressed and negatively correlated with LRRC4 expression in gliomas. Disturbing miR-182 and miR-381 affected transcriptional regulation of the BRD7 gene. This finding was verified by ectopic overexpression of LRRC4 or restoration of endogenous LRRC4 expression by treatment with the DNA demethylating agent 5-Aza-dC. Taken together, miR-182 and miR-381 may be a useful therapeutic target for treatment of glioma. [ABSTRACT FROM AUTHOR]

The genome of Buzura suppressaria nucleopolyhedrovirus (BusuNPV) was sequenced by 454 pyrosequencing technology. The size of the genome is 120,420 bp with 36.8% G+C content. It contains 127 hypothetical open reading frames (ORFs) covering 90.7% of the genome and includes the 37 conserved baculovirus core genes, 84 genes found in other baculoviruses, and 6 unique ORFs. No typical baculoviral homologous repeats (hrs) were present but the genome contained a region of repeated sequences. Gene Parity Plots revealed a 28.8 kb region conserved among the alpha- and beta-baculoviruses. Overall comparisons of BusuNPV to other baculoviruses point to a distinct species in group II Alphabaculovirus. [ABSTRACT FROM AUTHOR]

Inactivated LRRC4 has been clinically detected in gliomas, and promoter hypermethylation has been implicated as the mechanism of inactivation in some of those tumors. Our previous researches indicated that LRRC4 is a target gene of miR-381, the interaction of miR-381 and LRRC4 is involved in glioma growth. In this study, we demonstrate that LRRC4 is a target gene of the other microRNA, miR-182. We found that the high expression of miR-182 and miR-381 in gliomas are involved in pathological malignant progression. The silencing of miR-182 and miR-381 inhibited the proliferation in vitro and growth of glioma cell with in vivo magnetic resonance imaging by intracranial transplanted tumor model in rats. We also demonstrated that BRD7, a transcriptional cofactor for p53, is highly expressed and negatively correlated with LRRC4 expression in gliomas. Disturbing miR-182 and miR-381 affected transcriptional regulation of the BRD7 gene. This finding was verified by ectopic overexpression of LRRC4 or restoration of endogenous LRRC4 expression by treatment with the DNA demethylating agent 5-Aza-dC. Taken together, miR-182 and miR-381 may be a useful therapeutic target for treatment of glioma. [ABSTRACT FROM AUTHOR]