SARS-CoV-2 RNA Detection in Wastewater and Its Effective Correlation with Clinical Data during the Outbreak of COVID-19 in Salamanca.

Wastewater treatment plants (WWTPs) are the final stage of the anthropogenic water cycle where a wide range of chemical and biological markers of human activity can be found. In COVID-19 disease contexts, wastewater surveillance has been used to infer community trends based on viral abundance and SARS-CoV-2 RNA variant composition, which has served to anticipate and establish appropriate protocols to prevent potential viral outbreaks. Numerous studies worldwide have provided reliable and robust tools to detect and quantify SARS-CoV-2 RNA in wastewater, although due to the high dilution and degradation rate of the viral RNA in such samples, the detection limit of the pathogen has been a bottleneck for the proposed protocols so far.

Statistical Analysis of Methotrexate Degradation by UV-C Photolysis and UV-C/TiO Photocatalysis.

Methotrexate (MTX) is a folic acid analog and has been used to treat a wide variety of malignant and non-malignant diseases. The wide use of these substances has led to the continuous discharge of the parent compound and its metabolites in wastewater. In conventional wastewater treatment plants, the removal or degradation of drugs is not complete.

Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity.

Human brain activity generates scalp potentials (electroencephalography - EEG), intracranial potentials (iEEG), and external magnetic fields (magnetoencephalography - MEG). These electrophysiology (e-phys) signals can often be measured simultaneously for research and clinical applications. The forward problem involves modeling these signals at their sensors for a given equivalent current dipole configuration within the brain.

Aspirin Therapy on Prophylactic Anticoagulation for Patients Hospitalized With COVID-19: A Propensity Score-Matched Cohort Analysis of the HOPE-COVID-19 Registry.

Background COVID-19 is an infectious illness, featured by an increased risk of thromboembolism. However, no standard antithrombotic therapy is currently recommended for patients hospitalized with COVID-19. The aim of this study was to evaluate safety and efficacy of additional therapy with aspirin over prophylactic anticoagulation (PAC) in patients hospitalized with COVID-19 and its impact on survival.

Study of coliforms and Clostridium bacteria inactivation in wastewaters by a pilot photolysis process and by the maturation lagoons of a low-cost nature-based WWTP.

The inactivation processes of coliform bacteria (total and fecal) and sulphito-reducing Clostridium bacteria (vegetative species and spores) in water maturation lagoon of a low-cost nature-based wastewater treatment plant using constructed wetlands and through processes of photolysis in a pilot photoreactor have been comparatively studied. The different inactivation mechanisms by photolysis of these bacteria have been studied following the criteria of different statistical and kinetic models. Clostridium disinfection treatments fit models in which two types of bacteria populations coexist, one sensitive (vegetative species) and the other (spores) resistant to the treatment, the sensitive one (94%) with an inactivation rate of k = 0.

Prevalence and 30-Day Mortality in Hospitalized Patients With Covid-19 and Prior Lung Diseases.

Introduction: Patients with pre-existing respiratory diseases in the setting of COVID-19 may have a greater risk of severe complications and even death.

Methods: A retrospective, multicenter, cohort study with 5847 COVID-19 patients admitted to hospitals. Patients were separated in two groups, with/without previous lung disease.

Antiplatelet therapy and outcome in COVID-19: the Health Outcome Predictive Evaluation Registry.

Background: Standard therapy for COVID-19 is continuously evolving. Autopsy studies showed high prevalence of platelet-fibrin-rich microthrombi in several organs. The aim of the study was therefore to evaluate the safety and efficacy of antiplatelet therapy (APT) in hospitalised patients with COVID-19 and its impact on survival.

Impact of smoking on COVID-19 outcomes: a HOPE Registry subanalysis.

Background: Smoking has been associated with poorer outcomes in relation to COVID-19. Smokers have higher risk of mortality and have a more severe clinical course. There is paucity of data available on this issue, and a definitive link between smoking and COVID-19 prognosis has yet to be established.

Renin-angiotensin system inhibitors effect before and during hospitalization in COVID-19 outcomes: Final analysis of the international HOPE COVID-19 (Health Outcome Predictive Evaluation for COVID-19) registry.

Background: The use of Renin-Angiotensin system inhibitors (RASi) in patients with coronavirus disease 2019 (COVID-19) has been questioned because both share a target receptor site.

Methods: HOPE-COVID-19 (NCT04334291) is an international investigator-initiated registry. Patients are eligible when discharged after an in-hospital stay with COVID-19, dead or alive.

Artificial neural network detects human uncertainty.

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data.

Fast Neural Dynamics of Proactive Cognitive Control in a Task-Switching Analogue of the Wisconsin Card Sorting Test.

One common assumption has been that prefrontal executive control is mostly required for target detection (Posner and Petersen in Ann Rev Neurosci 13:25-42, 1990). Alternatively, cognitive control has also been related to anticipatory updating of task-set (contextual) information, a view that highlights proactive control processes. Frontoparietal cortical networks contribute to both proactive control and reactive target detection, although their fast dynamics are still largely unexplored.

Efficient Computation of Functional Brain Networks: toward Real-Time Functional Connectivity.

Functional Connectivity has demonstrated to be a key concept for unraveling how the brain balances functional segregation and integration properties while processing information. This work presents a set of open-source tools that significantly increase computational efficiency of some well-known connectivity indices and Graph-Theory measures. PLV, PLI, ImC, and wPLI as Phase Synchronization measures, Mutual Information as an information theory based measure, and Generalized Synchronization indices are computed much more efficiently than prior open-source available implementations.

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various support vector machine (SVM) classifiers were developed. The data were from a 2-year, prospective, longitudinal study of 81 patients (age 9-17 years) with early-onset FEP and a stable diagnosis during follow-up and 42 age- and sex-matched healthy controls (HC).

Dynamics of brain networks in the aesthetic appreciation.

Neuroimage experiments have been essential for identifying active brain networks. During cognitive tasks as in, e.g.

Differential patterns of connectivity in progressive mild cognitive impairment.

It is now widely accepted that Alzheimer's disease is characterized by a functional disconnection between brain regions. The disease appears to begin up to decades prior to clinical diagnosis. Therefore, in the present study, we combined magnetoencephalography, a memory task, and functional connectivity analysis in mild cognitive impairment subjects in order to identify functional connectivity patterns that could characterize subjects who would eventually go on to develop the disease.

Alteration and reorganization of functional networks: a new perspective in brain injury study.

Plasticity is the mechanism underlying the brain's potential capability to compensate injury. Recently several studies have shown how functional connections among the brain areas are severely altered by brain injury and plasticity leading to a reorganization of the networks. This new approach studies the impact of brain injury by means of alteration of functional interactions.