Serum superoxide dismutase level is a potential biomarker of disease prognosis in patients with HEV-induced liver failure

Background Viral hepatitis E clinically ranges from self-limiting hepatitis to lethal liver failure. Oxidative stress has been shown to mediate hepatic inflammation during HBV-induced liver failure. We investigated whether a biomarker of oxidative stress may be helpful in assessing severity and disease outcomes of patients with HEV-induced liver failure. Methods Clinical data were obtained from patients with HEV-induced acute viral hepatitis (AVH, n = 30), acute liver failure (ALF, n = 17), and acute-on-chronic liver failure (ACLF, n = 36), as well as from healthy controls (HC, n = 30). The SOD and HMGB1 levels were measured in serum by ELISA. HL-7702 cells were cultured and stimulated by serum from HEV-infected patients or by HMGB1; oxidative status was investigated by CellROX and apoptosis was investigated by flow cytometry. Results Patients with HEV-induced liver failure (including ALF and ACLF) showed increased SOD levels compared with HEV-AVH patients and healthy controls. SOD levels > 400 U/mL were associated with a significantly higher risk of mortality in HEV-ALF and HEV-ACLF patients. Serum from HEV-infected patients led to ROS accumulation, HMGB1 secretion, and apoptosis in HL-7702 cells. Antioxidant treatment successfully inhibited HEV-induced HMGB1 secretion, and HMGB1 promoted apoptosis in HL-7702 cells. Conclusion HEV increased oxidative stress in the pathogenesis of HEV-induced hepatic diseases. Early testing of serum SOD may serve as a predictor of both HEV-ALF and HEV-ACLF outcomes. Moreover, development of strategies for modulating oxidative stress might be a potential target for treating HEV-induced liver failure patients.

An Experimental Performance Evaluation of Cloud-API-Based Applications

Cloud Application Programming Interfaces (APIs) have been developed to link several cloud computing applications together. API-based applications are widely used to provide flexible and reliable services over cloud platforms. Recently, a huge number of services have been attached to cloud platforms and widely utilized during a very short period of time. This is due to the COVID-19 lockdowns, which forced several businesses to switch to online services instantly. Several cloud platforms have failed to support adequate services, especially for extended and real-time-based applications. Early testing of the available platforms guarantees a level of suitability and reliability for the uploaded services. In this work, we first selected two different API-based applications from education and professional taxonomies, the two most recently used applications that have switched to the cloud environment. Then, we aimed to evaluate the performance of different API-based applications under different cloud platforms, in order to measure and validate the ability of these platforms to support these services. The advantages and drawbacks of each platform were experimentally investigated for each application.

Evaluating the Efficacy of a Screening Protocol for Severe Acute Respiratory Syndrome Coronavirus 2 Virus in Asymptomatic Preoperative/Preprocedural Patients at a Military Hospital

ABSTRACT Introduction Facing the COVID-19 pandemic, many hospitals implemented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) screening protocols before aerosol-generating procedures (AGPs) in an effort to protect patients and health care workers. Given the limited prior evidence on the effectiveness of such protocols, we report the process improvement experience at a military treatment facility. Materials and Methods We evaluated the outcomes of patients undergoing AGPs from March to September 2020, divided into three cohorts: a preprotocol (PP) cohort who did not receive screening, an early testing (ET) cohort representing the early months of the screening protocol, and a late testing (LT) cohort managed under adaptive modifications to the screening protocol. We recorded identifiable post-procedure COVID-19 diagnoses. The study was approved as a process improvement protocol and was determined not to meet criteria for human subject research through an institutional approval process. Results Across the three cohorts, 4520 procedures were performed: 422 PP, 1297 ET, and 2801 LT. Among 4098 procedures in the ET and LT cohorts, 12 asymptomatic patients tested positive for SARS-CoV-2 (0.29% positivity rate). One left the health system before completing the procedure and another proceeded urgently under COVID precautions, while 10 were rescheduled and completed at a later date; 7 were cleared using a test-based strategy, while 3 were cleared using a time-based strategy. Of 445 patients who had SARS-CoV-2 tests performed within 30 days following their procedures, three patients with negative preoperative tests had a positive test within 30 days, all in the LT cohort but had evidence of acquiring the infection after the procedure or had a false-positive test. Conclusions Our strategy of preprocedural SARS-CoV-2 testing successfully identified asymptomatic infected patients before surgery. Care was delayed for most of these patients without apparent detriment. Adaptation to a time-based strategy for clearance might reduce such delays, but other considerations may still influence how soon procedures should be completed after a positive test.

Opinion: Early COVID-19 testing in Peru and its implications on transmission

As of September 8, 2021, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 222 million and killed more than 4.3 million people. Peru is among the countries most affected by COVID-19, with more than 2.1 million cases and a fatality rate of 9.2 %. To limit SARS-CoV-2 spread into the country, Peru closed its borders to international travel in March 2020, and established strict lockdowns, while at the public health front, interventions including laboratory testing, contact tracing and isolation of suspected and/or infected individuals were largely inaccessible in communities with active transmission. Anecdotal reports suggest that a weak healthcare system and political instability contributed to the poor management of COVID-19 in the country. Here, we provide an opinion focused on the country’s early testing response to the pandemic and discuss how it could have effectively leveraged diagnostic tools to control the spread of SARS-CoV-2.

Development and initial tests of an urban comfort monitoring system

The paper presents a newly developed low-cost measurement system for outdoor comfort monitoring. The solution is based on IoT (Internet of Things) technologies and is cloud-connected. The system is able to collect physical environment data, and includes a movable GPS monitoring station as well as the subjective thermal sensation of pedestrians via a devoted app. The cloud interface promptly elaborates the received data to calculate outdoor thermal comfort indices such as UTCI (Universal Thermal Climate Index), MRT (mean radiant temperature), and ET (effective temperature). The system is conceived for supporting both fixed and traveling measurements, and to support correlation studies between monitored environmental variables and personal comfort sensations to promote the local adaptation of comfort indices. Results from early testing are also reported.

Spotlight influenza: Extending influenza surveillance to detect non-influenza respiratory viruses of public health relevance: analysis of surveillance data, Belgium, 2015 to 2019

Background Seasonal influenza-like illness (ILI) affects millions of people yearly. Severe acute respiratory infections (SARI), mainly influenza, are a leading cause of hospitalisation and mortality. Increasing evidence indicates that non-influenza respiratory viruses (NIRV) also contribute to the burden of SARI. In Belgium, SARI surveillance by a network of sentinel hospitals has been ongoing since 2011. Aim We report the results of using in-house multiplex qPCR for the detection of a flexible panel of viruses in respiratory ILI and SARI samples and the estimated incidence rates of SARI associated with each virus. Methods We defined ILI as an illness with onset of fever and cough or dyspnoea. SARI was defined as an illness requiring hospitalisation with onset of fever and cough or dyspnoea within the previous 10 days. Samples were collected in four winter seasons and tested by multiplex qPCR for influenza virus and NIRV. Using catchment population estimates, we calculated incidence rates of SARI associated with each virus. Results One third of the SARI cases were positive for NIRV, reaching 49.4% among children younger than 15 years. In children younger than 5 years, incidence rates of NIRV-associated SARI were twice that of influenza (103.5 vs 57.6/100,000 person-months); co-infections with several NIRV, respiratory syncytial viruses, human metapneumoviruses and picornaviruses contributed most (33.1, 13.6, 15.8 and 18.2/100,000 person-months, respectively). Conclusion Early testing for NIRV could be beneficial to clinical management of SARI patients, especially in children younger than 5 years, for whom the burden of NIRV-associated disease exceeds that of influenza.

Predicting COVID-19 Incidences from Patients’ Viral Load using Deep-Learning

The transmission of the contagious COVID-19 is known to be highly dependent on individual viral dynamics. Since the cycle threshold (Ct) is the only semi-quantitative viral measurement that could reflect infectivity, we utilized Ct values to forecast COVID-19 incidences. Our COVID-19 cohort (n=9531), retrieved from a single representative cross-sectional virology test center in Lebanon, revealed that low daily mean Ct values are followed by an increase in the number of national positive COVID-19 cases. A subset of the data was used to develop a deep neural network model, tune its hyperparameters, and optimize the weights for minimal mean square error of prediction. The final model’s accuracy is reported by comparing its predictions with an unseen dataset. Our model was the first to capture the interaction of the previously reported Ct values with the upcoming number of COVID-19 cases and any temporal effects that arise from population dynamics. Our model was deployed as a publicly available and easy-to-use estimator to facilitate prospective validation. Our model has potential application in predicting COVID-19 incidences in other countries and in assessing post-vaccination policies. Aside from emphasizing patient responsibility in adopting early testing practices, this study proposed and validated viral load measurement as a rigid input that can enhance outcomes and precision of viral disease predicting models.

Bisphenols exert detrimental effects on neuronal signaling in mature vertebrate brains

Bisphenols are important plasticizers currently in use and are released at rates of hundreds of tons each year into the biosphere1–3. However, for any bisphenol it is completely unknown if and how it affects the intact adult brain4–6, whose powerful homeostatic mechanisms could potentially compensate any effects bisphenols might have on isolated neurons. Here we analyzed the effects of one month of exposition to BPA or BPS on an identified neuron in the vertebrate brain, using intracellular in vivo recordings in the uniquely suited Mauthner neuron in goldfish. Our findings demonstrate an alarming and uncompensated in vivo impact of both BPA and BPS—at environmentally relevant concentrations—on essential communication functions of neurons in mature vertebrate brains and call for the rapid development of alternative plasticizers. The speed and resolution of the assay we present here could thereby be instrumental to accelerate the early testing phase of next-generation plasticizers.

Legionella pneumophila — The causative agent of Legionnaires’ disease

Over the years, Legionella pneumophila has increasingly become a public health threat that causes sporadic and epidemic community-acquired and nosocomial-acquired pneumonia. Thus, this review aims to discuss the current knowledge of L. pneumophila, focusing on the global epidemiology, clinical features, diagnosis and treatment of Legionnaires’ disease (LD). Legionella bacteria are Gram-negative rod-shaped bacteria that are ubiquitous in aquatic environments. L. pneumophila was first discovered in 1976 and recognized as the causative agent of LD. L. pneumophila is a facultative intracellular pathogen that infects and replicates within eukaryotic host cells such as macrophages and protozoan. Diagnosis of LD remains a significant challenge as the clinical manifestation of LD is hardly distinguishable from pneumonia caused by other respiratory pathogens. Therefore, early testing and appropriate treatment are keys to alleviating the rising morbidity and mortality caused by LD.