A THEORETICAL STUDY ON FRACTIONAL EBOLA HEMORRHAGIC FEVER MODEL

The Ebola virus infection (EVI), generally known as Ebola hemorrhagic fever, is a major health concern. The occasional outbreaks of virus occur primarily in certain parts of Africa. Many researches have been devoted to the study of the Ebola virus disease. In this paper, we have taken susceptible-infected-recovered-deceased-environment (SIRDP) system to investigate the dynamics of Ebola virus infection. We adopted fractional operators for a better illustration of model dynamics and memory effects. Initially, the Ebola disease model is modified with Caputo–Fabrizio arbitrary operator in Caputo sense (CFC) and we employed the fixed-point results for the existence and uniqueness of the solution of the fractional system. Further, we adopted the arbitrary fractional conformable and [Formula: see text]-conformable derivatives to the alternative representation of the model. For the numerical approximation of the system, we show a numerical technique based on the fundamental theorem of fractional calculus for CFC derivative and a numerical scheme called the Adams–Moulton for conformable derivatives. Finally, for the validation of theoretical results, the numerical simulations are displayed.

Pooled Analysis of the Accuracy of Xpert Ebola Assay for Diagnosing Ebola Virus Infection

Background. West Africa has witnessed the unprecedented outbreak of Ebola virus disease (EVD). The Ebola virus (EBOV) can cause Ebola hemorrhagic fever, which is documented as the most deadly viral hemorrhagic fever in the world. RT-PCR had been suggested to be employed in the detection of Ebola virus; however, this method has high requirements for laboratory equipment and takes a long time to determine Ebola infection. Although Xpert Ebola is a fast and simple instrument for the detection of Ebola virus, its effect is still unclear. This study is aimed at evaluating the accuracy of Xpert Ebola in diagnosing Ebola virus infection. Methods. Using the keywords “Xpert” and “Ebola virus”, relevant studies were retrieved from the database of PubMed, Embase, Web of Science, and Cochrane. RT-PCR was employed as a reference standard to evaluate whether the study is eligible to be included in the meta-analysis. Data from these included studies were extracted by two independent assessors and were then analyzed by the Meta-DiSc 1.4 software to produce the heterogeneity of sensitivity (SEN), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic advantage ratio (DOR) of the study. The results of pooled analysis were plotted, together with the summary receiver operating characteristic (SROC) curve plotted by calculating the area under the curve (AUC). Generated pooled summary estimates (95% CIs) were calculated for the evaluation of the overall accuracy of this study. Results. Five fourfold tables were made from the four studies that were included in the meta-analysis. The pooled sensitivity of Xpert Ebola was 0.98 (95% confidence interval (CI) (0.95, 0.99)), and the pooled specificity was 0.98 (95% CI (0.97, 0.99)). The pooled values of positive likelihood ratio was 53.91 (95% CI (12.82, 226.79)), with negative likelihood ratio being 0.04 (95% CI (0.02, 0.08)) and diagnostic odds ratio being 2649.45 (95% CI (629.61, 11149.02)). The AUC was 0.9961. Conclusions. Compared with RT-PCR, Xpert Ebola has high sensitivity and specificity. Therefore, it is a valued alternative method for the clinical diagnosis of Ebola virus infection. However, the Xpert Ebola test is a qualitative test that does not provide quantitative testing of EBOV concentration. Whether it can completely replace other methods or not calls for further evidences.

Ebola virus infection induces a type I interferon response and the shutdown of key liver functions in human iPSC-derived hepatocytes

Liver damage and an exacerbated inflammatory response are hallmarks of Ebola virus (EBOV) infection. Little is known about the intrinsic response to infection in human hepatocytes and their contribution to the observed inflammatory response. Here, we present an iPSC-derived hepatocyte platform to define the hepato-intrinsic response to EBOV infection. Transcriptomics analysis revealed a delayed host response with minimal transcriptomic changes at one day post infection (dpi) followed by a general downregulation of genes associated with hepatic functions and upregulation of interferon signaling at two and three dpi. Using RNA-FISH, we showed at single cell resolution that IFNβ and CXCL10 were mainly expressed in bystander cells or cells with weak EBOV mRNA signal intensity. We did not observe an inflammatory signature at any timepoint. In conclusion, iPSC-derived hepatocytes are an immune competent platform to study intrinsic responses to EBOV infection that have not been observed in EBOV-infected hepatocarcinoma cell lines.