No abstract

Since COVID-19 pneumonia emerged in Wuhan, China, there has been a search for knowledge that might prevent or minimize its spread. 1-3 In just over three months after its initial breakout, it gained worldwide reach such that it affected more than 2.5 million people, with more than 180,000 deaths in more than 200 countries. COVID-19 is caused by the SARS-CoV-2 virus, a member of the Coronaviridae family. 3 Its transmission occurs mainly through respiratory droplets. 1 The clinical spectrum of the disease is variable, and the majority of cases are asymptomatic or oligosymptomatic. The most severe cases, with acute respiratory distress syndrome, commonly affect elderly patients with comorbidities. 3 A positive real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for SARS-CoV-2, from nasopharyngeal swabs, is the current gold standard diagnostic test. The sensitivity of RT-PCR for SARS-CoV-2 is 50-70%; 4-10 around 30-40% of patients with early-stage COVID-19 are false-negative. 4 An inadequate technique for collecting sampling material or low viral load, limited development of nucleic acid detection technology and variation in the detection rate between different manufacturers may all be determinants for false negative results. 4,11 Use of computed tomography (CT) is based on the clinical context and time taken to make the diagnosis, especially in relation to use of RT-PCR and other clinical and laboratory investigations. 4,12,13

Recently, ocular biometrics in unconstrained environments using images obtained at visible wavelength have gained the researchers’ attention, especially with images captured by mobile devices. Periocular recognition has been demonstrated to be an alternative when the iris trait is not available due to occlusions or low image resolution. However, the periocular trait does not have the high uniqueness presented in the iris trait. Thus, the use of datasets containing many subjects is essential to assess biometric systems’ capacity to extract discriminating information from the periocular region. Also, to address the within-class variability caused by lighting and attributes in the periocular region, it is of paramount importance to use datasets with images of the same subject captured in distinct sessions. As the datasets available in the literature do not present all these factors, in this work, we present a new periocular dataset containing samples from 1122 subjects, acquired in 3 sessions by 196 different mobile devices. The images were captured under unconstrained environments with just a single instruction to the participants: to place their eyes on a region of interest. We also performed an extensive benchmark with several Convolutional Neural Network (CNN) architectures and models that have been employed in state-of-the-art approaches based on Multi-class Classification, Multi-task Learning, Pairwise Filters Network, and Siamese Network. The results achieved in the closed- and open-world protocol, considering the identification and verification tasks, show that this area still needs research and development.

Methods that rapidly decrease fat in steatotic hepatocytes may be helpful to recover severely fatty livers for transplantation. Defatting kinetics are highly dependent upon the extracellular medium composition; however, the pathways involved are poorly understood. Steatosis was induced in human hepatoma cells (HepG2) by exposure to high levels of free fatty acids, followed by defatting using plain medium containing no fatty acids, or medium supplemented with a cocktail of defatting agents previously described before. We measured the levels of 28 extracellular metabolites and intracellular triglyceride, and fed the data into a steady-state mass balance model to estimate strictly intracellular fluxes. We found that during defatting, triglyceride content decreased, while beta-oxidation, the tricarboxylic acid cycle, and the urea cycle increased. These fluxes were augmented by defatting agents, and even more so by hyperoxic conditions. In all defatting conditions, the rate of extracellular glucose uptake/release was very small compared to the internal supply from glycogenolysis, and glycolysis remained highly active. Thus, in steatotic HepG2 cells, glycolysis and fatty acid oxidation may co-exist. Together, these pathways generate reducing equivalents that are supplied to mitochondrial oxidative phosphorylation.