RESUMEN
In an attempt to reduce the infection rate of the COrona VIrus Disease-19 (Covid-19) countries around the world have echoed the exigency for an economical, accessible, point-of-need diagnostic test to identify Covid-19 carriers so that they (individuals who test positive) can be advised to self isolate rather than the entire community. Availability of a quick turn-around time diagnostic test would essentially mean that life, in general, can return to normality-at-large. In this regards, studies concurrent in time with ours have investigated different respiratory sounds, including cough, to recognise potential Covid-19 carriers. However, these studies lack clinical control and rely on Internet users confirming their test results in a web questionnaire (crowdsourcing) thus rendering their analysis inadequate. We seek to evaluate the detection performance of a primary screening tool of Covid-19 solely based on the cough sound from 8,380 clinically validated samples with laboratory molecular-test (2,339 Covid-19 positive and 6,041 Covid-19 negative) under quantitative RT-PCR (qRT-PCR) from certified laboratories. All collected samples were clinically labelled, i.e., Covid-19 positive or negative, according to the results in addition to the disease severity based on the qRT-PCR threshold cycle (Ct) and lymphocytes count from the patients. Our proposed generic method is an algorithm based on Empirical Mode Decomposition (EMD) for cough sound detection with subsequent classification based on a tensor of audio sonographs and deep artificial neural network classifier with convolutional layers called 'DeepCough'. Two different versions of DeepCough based on the number of tensor dimensions, i.e., DeepCough2D and DeepCough3D, have been investigated. These methods have been deployed in a multi-platform prototype web-app 'CoughDetect'. Covid-19 recognition results rates achieved a promising AUC (Area Under Curve) of [Formula: see text] 98 . 80 % ± 0 . 83 % , sensitivity of [Formula: see text] 96 . 43 % ± 1 . 85 % , and specificity of [Formula: see text] 96 . 20 % ± 1 . 74 % and average AUC of [Formula: see text] 81 . 08 % ± 5 . 05 % for the recognition of three severity levels. Our proposed web tool as a point-of-need primary diagnostic test for Covid-19 facilitates the rapid detection of the infection. We believe it has the potential to significantly hamper the Covid-19 pandemic across the world.
RESUMEN
The contamination of food commodities by fungal toxins has attracted great interest because many of these mycotoxins are responsible for different diseases, including cancer and other chronic illnesses. Ochratoxin A (OTA) is a mycotoxin naturally present in food, and long-term exposure to food contaminated with low levels of OTA has been associated with renal cancer. In the present study, the cytotoxicity, cytostaticity, and genotoxicity of OTA (0.075-15 µM) in human lymphocytes were evaluated. A comet assay, a modified comet assay (DNA repair assay), which uses N-hydroxyurea (NHU) to detect non-repaired lesions produced by OTA, and a cytokinesis-blocked micronucleus assay were used. Treatments with OTA were not cytotoxic, but OTA caused a cytostatic effect in human lymphocytes at a concentration of 15 µM. OTA (0.075-5 µM) produced a slight increase in the percentage of DNA in the comets and a delay in the DNA repair capacity of the lymphocytes. Micronucleus (MN) induction was observed at OTA concentrations of 1.5 and 5 µM. Our results indicate that OTA induces DNA stable damage at low doses that are neither cytotoxic nor cytostatic, and OTA delays the DNA repair kinetics. These findings indicate that OTA affects two pivotal events in the carcinogenesis pathway.
