Foot-and-mouth disease virus (FMDV) with a stable FLAG epitope in the VP1 G-H loop as a new tool for studying FMDV pathogenesis.

Foot-and-mouth disease virus (FMDV) VP1 G-H loop contains the major antigenic site. By replacing the sequence upstream of the RGD motif with a FLAG epitope, a marker virus for pathogenesis studies was generated. In cell culture, the recombinant virus containing FLAG (A24-FLAG) exhibited similar plaque phenotypes and growth kinetics to parental virus. A24-FLAG was distinguished, neutralized, and immunoprecipitated by FLAG anti-sera. A24-FLAG infected cattle exhibited FMD and an antibody response similar to parental virus. FLAG epitope stability was confirmed both in vitro and in vivo. Interestingly, no anti-FLAG antibodies were detectable in cattle up to 21 days post-inoculation. A24-FLAG G-H loop modeling suggested FLAG was rendered a cryptic site, inaccessible to the host immune system. These studies demonstrate the FMDV VP1 G-H loop tolerance to substitutions without detriment to pathogenesis and antigenicity. Finally, A24-FLAG manifested virulence in cattle as parental virus, and could be distinguished and tracked by tag-specific anti-sera

A Novel Technique for Non-Invasive Measurement of Human Blood Component Levels From Fingertip Video Using DNN Based Models

Blood components such as hemoglobin, glucose, creatinine measuring are essential for monitoring one's health condition. The current blood component measurement approaches still depend on invasive techniques that are painful, and uncomfortable for the patients. To facilitate measurement at home, we proposed a novel non-invasive technique to measure blood hemoglobin, glucose, and creatinine level based on PPG signal using Deep Neural Networks (DNN). Fingertip videos from 93 subjects have been collected using a smartphone. The PPG signal is generated from each video, and 46 characteristic features are then extracted from the PPG signal, its derivatives (1st and 2nd) and from Fourier analysis. Additionally, age and gender are also included to feature because of the significant effects on hemoglobin, glucose, and creatinine. A correlation-based feature selection (CFS) using genetic algorithms (GA) has been used to select the optimal features to avoid redundancy and over-fitting. Finally, DNN based models have been developed to estimate the blood Hemoglobin (Hb), Glucose (Gl), and Creatinine (Cr) levels from the selected features. The approach provides the best-estimated accuracy of R2 = 0.922 for Hb, R2 = 0.902 for Gl, and R2 = 0.969 for Cr. Experimental aftermaths show that the proposed method is a suitable technique to be used clinically to measure human blood component levels without taking blood samples. This paper also reveals that smartphone-based PPG signal has a great potential to measure the different blood components

Corrections to “A Novel Technique for Non-Invasive Measurement of Human Blood Component Levels From Fingertip Video Using DNN Based Models”

In the above article [1], the details of the data collection source and data collection protocol were not included

Theiler's murine encephalomyelitis virus contrasts with encephalomyocarditis and foot-and-mouth disease viruses in its functional utilization of the StopGo non-standard translation mechanism

The picornaviruses’ genome consists of a positive-sense ssRNA. Like many picornaviruses, cardioviruses synthesize two distinct polyprotein precursors from adjacent but non-overlapping genome segments. Both the [L-1ABCD-2A] and the [2BC-3ABCD] polyproteins are proteolytically processed to yield mature capsid and non-structural proteins, respectively. An unusual translational event, known as ‘StopGo’ or ‘Stop-Carry on’, is responsible for the release of the [L-1ABCD-2A] polyprotein from the ribosome and synthesis of the N-terminal amino acid of the [2BC-3ABCD] polyprotein. A common feature of these viruses is the presence of a highly conserved signature sequence for StopGo: –D(V/I)ExNPG(↓)P–, where –D(V/I)ExNPG are the last 7 aa of 2A, and the last P- is the first amino acid of 2B. Here, we report that, in contrast to encephalomyocarditis virus and foot-and-mouth disease virus, a functional StopGo does not appear to be essential for Theiler’s murine encephalomyelitis virus viability when tested in vitro and in vivo