COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images.

Currently, Coronavirus disease (COVID-19), one of the most infectious diseases in the 21st century, is diagnosed using RT-PCR testing, CT scans and/or Chest X-Ray (CXR) images. CT (Computed Tomography) scanners and RT-PCR testing are not available in most medical centers and hence in many cases CXR images become the most time/cost effective tool for assisting clinicians in making decisions. Deep learning neural networks have a great potential for building COVID-19 triage systems and detecting COVID-19 patients, especially patients with low severity.

in Captive Wild Felids of Mexico: Its Frequency and Capability to Eliminate Oocysts.

There is little information about in wild felids, even when these species have been associated with cases of toxoplasmosis in humans. In this study, samples of serum and whole blood were collected from 42 felids from 10 different species, in 4 Mexican zoos. Stool samples from 36 animals were also collected, corresponding to 82% of the felids included in the study.

Epidemiological survey of Trypanosoma cruzi infection in domestic owned cats from the tropical southeast of Mexico.

American trypanosomiasis is an infectious disease of importance for public health and caused by the protozoa Trypanosoma cruzi mainly transmitted by triatomine bugs. The precise role of cats in the peridomestic transmission of T. cruzi and the mechanism by which cats become infected remain uncertain.