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Graphical abstract, The type 2 coronavirus causes severe acute respiratory syndrome (SARS-CoV-2) and produces pneumonia with pulmonary alveolar collapse. In some cases it also causes sepsis and septic shock. There is no specific treatment for coronavirus disease 2019 (COVID-19). Vitamin C (Vit C), Vitamin E (Vit E), N-acetylcysteine (NAC) and Melatonin (MT) increase the intracellular content of GSH, kidnap free radicals and protect DNA, proteins in the cytosol and lipids in cell membranes. Pentoxifylline (Px) has anti-inflammatory activities. Here we evaluate the effect of Vit C, Vit E, NAC, and MT plus Px in COVID-19 patients with moderate and severe pneumonia. 110 patients of either sex were included. They were divided into five groups with 22 patients each. Group 1 received Vit C+Px, group 2 Vit E+Px, group 3 NAC+Px, group 4 MT+Px, and group 5 only Px. Oxidative stress (OS) markers such as lipid peroxidation (LPO) levels, total antioxidant capacity (TAC) and nitrites (NO2-) were evaluated in plasma. The antioxidant therapy improved the survival scores including the Sequential Organ Failure Assessment (SOFA), the Acute Physiology and chronic Health Evaluation II (Apache II), the Simplified Acute Physiology Score II (SAPS II), the Critical Illness Risk Score, Launched during COVID-19 crisis (COVIDGRAM) and the Glasgow Coma Scale (GCS). We found that LPO was elevated (p≤0.04) and TAC (p≤0.03), NO2- (p≤0.04) and inflammation markers such as interleukin-6 (IL-6, p≤0.01) C reactive protein (CRP, p≤0.01) and procalcitonin (PCT, p≤0.05) were diminished in COVID-19 patients upon admission to the hospital. The different antioxidants reversed this alteration at the end of the treatment. The treatment with antioxidant supplements such as Vit C, E, NAC, and MT plus Px could decelerate the aggressive and lethal development of COVID-19. Antioxidant therapy can be effective in this pandemia since it improves the survival scores including SOFA, Apache II, SAPS II, COVIDGRAM, GCS by lowering the LPO, IL-6, CRP, PCT and increasing systemic TAC and NO2-.

Purpose High-flow nasal cannula (HFNC) therapy in patients with hypoxemic respiratory failure due to COVID-19 is poorly understood and remains controversial. Methods We designed a prospective observational study of a large cohort of patients with COVID-19-related hypoxaemic respiratory failure at the Temporary COVID-19 Hospital in Mexico City. The primary outcome was the success rate of HFNC to prevent the progression to invasive mechanical ventilation (IMV). We also evaluated the risk factors associated with HFNC success or failure. Results This study included 378 patients who were admitted to the Temporary COVID-19 Hospital with a confirmed diagnosis of COVID-19 and hypoxemic respiratory failure. HFNC therapy effectively prevented IMV in 71.4% of patients (n = 270; 95% confidence interval [CI] 66.6–75.8%). Factors that were significantly different between patients who were only treated with HFNC therapy and those who progressed to IMV included age, the presence of hypertension, and the Charlson comorbidity index. Predictors of therapy failure included the CALL score at admission (adjusted hazard ratio [HR] 1.27; 95% CI 1.09–1.47; p p = 0.02), and no prior treatment with steroids (adjusted HR 0.34; 95% CI 0.19–0.62; p

Introduction:In response to the evolution of the coronavirus disease 2019 (COVID-19) pandemic, the admission protocol for the temporary COVID-19 hospital in Mexico City has been updated to hospitalize patients preemptively with an oxygen saturation (SpO2) of >90%.Methods:This prospective, observational, single-center study compared the progression and outcomes of patients who were preemptively hospitalized versus those who were hospitalized based on an SpO2⩽90%. We recorded patient demographics, clinical characteristics, COVID-19 symptoms, and oxygen requirement at admission. We calculated the risk of disease progression and the benefit of preemptive hospitalization, stratified by CALL Score: age, lymphocyte count, and lactate dehydrogenase (Results:Preemptive hospitalization significantly reduced the requirement for oxygen therapy (odds ratio 0.45, 95% confidence interval 0.31–0.66), admission to the intensive care unit (ICU) (0.37, 0.23–0.60), requirement for invasive mechanical ventilation (IMV) (0.40, 0.25–0.64), and mortality (0.22, 0.10–0.50). Stratification by CALL score at admission showed that the benefit of preemptive hospitalization remained significant for patients requiring oxygen therapy (0.51, 0.31–0.83), admission to the ICU (0.48, 0.27–0.86), and IMV (0.51, 0.28–0.92). Mortality risk remained significantly reduced (0.19, 0.07–0.48).Conclusion:Preemptive hospitalization reduced the rate of disease progression and may be beneficial for improving COVID-19 patient outcomes.

Acoustic signals serve communication within and across species throughout the animal kingdom. Studying the genetics, evolution, and neurobiology of acoustic communication requires annotating acoustic signals: segmenting and identifying individual acoustic elements like syllables or sound pulses. To be useful, annotations need to be accurate, robust to noise, and fast.We here introduceDAS, a method that annotates acoustic signals across species based on a deep-learning derived hierarchical presentation of sound. We demonstrate the accuracy, robustness, and speed ofDASusing acoustic signals with diverse characteristics from insects, birds, and mammals.DAScomes with a graphical user interface for annotating song, training the network, and for generating and proofreading annotations. The method can be trained to annotate signals from new species with little manual annotation and can be combined with unsupervised methods to discover novel signal types.DASannotates song with high throughput and low latency, allowing realtime annotations for closed-loop experimental interventions. Overall,DASis a universal, versatile, and accessible tool for annotating acoustic communication signals.

Background: SARS-CoV-2 infection produces pneumonia with pulmonary alveolar collapse and in some cases sepsis and septic shock. There is no specific treatment for COVID-19. Vitamin C (Vit C), Vitamin E (Vit E), N-acetylcysteine (NAC) and Melatonin (MT) increase the intracellular content of GSH, kidnap free radicals and protect DNA, proteins in the cytosol and lipids of cell membranes. Pentoxifylline (Px) has anti-inflammatory activities. Methods: Here we evaluate the effect of Vit C, Vit E, NAC, and MT plus Px in COVID-19 patients with moderate and severe pneumonia. 110 patients of either sex were included. They were divided into five groups with 22 patients each. Group 1 received Vit C+Px, group 2 Vit E+Px, group 3 NAC+Px, group 4 MT+Px, and group 5 only Px. Oxidative stress markers as Lipid peroxidation levels, evaluation of total antioxidant capacity and nitrites were evaluate by spectrophotometry, and by ELISA assay IL-6 levels. Results: The antioxidant therapy improved the survival scores including SOFA, Apache II, SAPS II, COVIDGRAM and GCS. OS markers in plasma such as LPO (p≤0.04) and TAC (p≤0.03) decreased in COVID-19 patients administered with antioxidants. There was an increase of IL-6 (p≤0.01) and decreases of CRP (p≤0.01) and PCT (p≤0.05) in COVID-19 patients when entering the hospital and the different antioxidants reversed this alteration at the end of the hospital stay. Conclusions: This study confirms the presence of OS in COVID-19 patients. The results suggest that the treatment with antioxidant supplements such as Vit C, E, NAC, and MT plus Px could contribute to the deceleration of the aggressive and lethal development COVID-19. There is evidence that antioxidants in moderate doses decrease inflammation and control of OS; therefore, their use as an adjuvant therapy to improve prognosis is confirmed. The antioxidant therapy can be effective in this pandemia since it improves all of the survival scores including SOFA, Apache II, SAPS II, COVIDGRAM, GCS by lowering the LPO, IL-6, CRP, PCT and increasing systemic TAC.

[EN] This paper presents a new method to reduce the computational cost when using Neural Networks as Language Models, during recognition, in some particular scenarios. It is based on a Neural Network that considers input contexts of different length in order to ease the use of a fallback mechanism together with the precomputation of softmax normalization constants for these inputs. The proposed approach is empirically validated, showing their capability to emulate lower order N-grams with a single Neural Network. A machine translation task shows that the proposed model constitutes a good solution to the normalization cost of the output softmax layer of Neural Networks, for some practical cases, without a significant impact in performance while improving the system speed., This work was partially supported by the Spanish MINECO and FEDER founds under project TIN2017-85854-C4-2-R (to MJCB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.