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Towards the end of 2019 in Wuhan, suspicions of a new dangerous virus circulating in the air began to arise. It was the start of the world pandemic coronavirus disease 2019 (COVID-19). Since then, considerable research data and review papers about this virus have been published. Hundreds of researchers have shared their work in order to achieve a better comprehension of this disease, all with the common goal of overcoming this pandemic. The coronavirus is structurally similar to influenza A. Both are RNA viruses and normally associated with comparable infection symptoms. In this review, different case studies targeting polymeric materials were appraised to highlight them as an indispensable tool to fight these RNA viruses. In particular, the main focus was how polymeric materials, and their versatile features could be applied in different stages of viral disease, i.e., in protection, detection and treatment. [ABSTRACT FROM AUTHOR]

The ionic E-nanochannel (viroporin) is the weak point of SARS-CoV-2, the virus responsible for the (still threatening) COVID-19 since it is vital to the virus's budding and propagation. Therefore, targeting it to disable its functions ought to incapacitate, or at least weaken, the virus. The ionic currents inside this channel could be affected and disturbed by direct physical attack via the actions of external fields. The paper presents the first step towards the application of such methods in the fight against the current pandemic, numerical simulations of external fields' impact on ionic currents through viral channels. These simulations—based on the actual, detailed physical nanostructure of ionic channels, measured experimentally and reported in the literature—show that external physical fields can diminish the channel's currents and that the lower the channel's selectivity, the stronger the effect. Simulations suggest that SARS-CoV-2 E-viroporin is almost non-selective, which means that the whole virus ought to be highly vulnerable to the actions of external physical fields, much more vulnerable than the much more selective human cell ionic channels. If corroborated by experiment, this observation may result in an innovative method of dealing with the recent pandemic caused by SARS-CoV-2 and other similar viruses. [ABSTRACT FROM AUTHOR]

Since the outbreak of COVID-19 disease, a bidirectional interaction between kidney disease and the progression of COVID-19 has been demonstrated. Kidney disease is an independent risk factor for mortality of patients with COVID-19 as well as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leading to the development of acute kidney injury (AKI) and chronic kidney disease (CKD) in patients with COVID-19. However, the detection of kidney damage in patients with COVID-19 may not occur until an advanced stage based on the current clinical blood and urinary examinations. Some studies have pointed out the development of subclinical acute kidney injury (subAKI) syndrome with COVID-19. This syndrome is characterized by significant tubule interstitial injury without changes in the estimated glomerular filtration rate. Despite the complexity of the mechanism(s) underlying the development of subAKI, the involvement of changes in the protein endocytosis machinery in proximal tubule (PT) epithelial cells (PTECs) has been proposed. This paper focuses on the data relating to subAKI and COVID-19 and the role of PTECs and their protein endocytosis machinery in its pathogenesis. [ABSTRACT FROM AUTHOR]

In this paper, we deal with the problem of estimating the reproduction number R t during an epidemic, as it represents one of the most used indicators to study and control this phenomenon. In particular, we focus on two issues. First, to estimate R t , we consider the use of positive test case data as an alternative to the first symptoms data, which are typically used. We both theoretically and empirically study the relationship between the two approaches. Second, we modify a method for estimating R t during an epidemic that is widely used by public institutions in several countries worldwide. Our procedure is not affected by the problems deriving from the hypothesis of R t local constancy, which is assumed in the standard approach. We illustrate the results obtained by applying the proposed methodologies to real and simulated SARS-CoV-2 datasets. In both cases, we also apply some specific methods to reduce systematic and random errors affecting the data. Our results show that the R t during an epidemic can be estimated by using the positive test data, and that our estimator outperforms the standard estimator that makes use of the first symptoms data. It is hoped that the techniques proposed here could help in the study and control of epidemics, particularly the current SARS-CoV-2 pandemic. [ABSTRACT FROM AUTHOR]

COVID-19 made explicit the need for rethinking the way in which we conduct testing for epidemic emergencies. During the COVID-19 pandemic, the dependence on centralized lab facilities and resource-intensive methodologies (e.g., RT-qPCR methods) greatly limited the deployment of widespread testing efforts in many developed and underdeveloped countries. Here, we illustrate the development of a simple and portable diagnostic kit that enables self-diagnosis of COVID-19 at home from saliva samples. We describe the development of a do-it-yourself (DIY) incubator for Eppendorf tubes that can be used to conduct SARS-CoV-2 detection with competitive sensitivity and selectivity from saliva at home. In a proof-of-concept experiment, we assembled Eppendorf-tube incubators at our home shop, prepared a single-tube mix of reagents and LAMP primers in our lab, and deployed these COVID-19 detection kits using urban delivery systems (i.e., Rappifavor or Uber) to more than 15 different locations in Monterrey, México. This straightforward strategy enabled rapid and cost-effective at-home molecular diagnostics of SARS-CoV-2 from real saliva samples with a high sensitivity (100%) and high selectivity (87%). [ABSTRACT FROM AUTHOR]

Adult patients with asthma often access the emergency department (ED) for the management of exacerbations or uncontrolled symptoms. Sometimes the first diagnosis of asthma occurs right in the ED. In the last couple of years, the COVID-19 pandemic spread around the world, causing an acute respiratory syndrome named SARS-CoV-2, characterized mainly by respiratory symptoms, such as cough and shortness of breath, in addition to fever. This clinical pattern partially overlaps with that caused by asthma, thus generating confusion in terms of diagnosis and management. It is also unclear whether asthma may be associated with a worse prognosis in COVID-19 infection. This expert opinion paper provides specific recommendations to ease the challenges related to adult patients with asthma admitted to the ED during the COVID-19 pandemic, with particular reference to diagnosis and treatment. Moreover, it provides well-defined indications to guide decisions on discharge, hospital admission, as well as follow-up. A panel of experts composed of emergency medicine physicians, pulmonologists and allergologists discussed, voted and approved all the recommendations. [ABSTRACT FROM AUTHOR]

The evolution of some epidemics, such as influenza, demonstrates common patterns both in different regions and from year to year. On the contrary, epidemics such as the novel COVID-19 show quite heterogeneous dynamics and are extremely susceptible to the measures taken to mitigate their spread. In this paper, we propose empirical dynamic modeling to predict the evolution of influenza in Spain's regions. It is a non-parametric method that looks into the past for coincidences with the present to make the forecasts. Here, we extend the method to predict the evolution of other epidemics at any other starting territory and we also test this procedure with Spanish COVID-19 data. We finally build influenza and COVID-19 networks to check possible coincidences in the geographical distribution of both diseases. With this, we grasp the uniqueness of the geographical dynamics of COVID-19. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic remains a constant threat to human health, the economy, and social relations. Scientists around the world are constantly looking for new technological tools to deal with the pandemic. Such tools are the rapid virus detection tests, which are constantly evolving and optimizing. This paper presents a biosensor platform for the rapid detection of spike protein both in laboratory conditions and in swab samples from hospitalized patients. It is a continuation and improvement of our previous work and consists of a microcontroller-based readout circuit, which measures the capacitance change generated in an interdigitated electrode transducer by the presence either of sole spike protein or the presence of SARS-CoV-2 particles in swab samples. The circuit efficiency is calibrated by its correlation with the capacitance measurement of an LCR (inductance (L), capacitance (C), and resistance (R)) meter. The test result is made available in less than 2 min through the microcontroller's LCD (liquid-crystal display) screen, whereas at the same time, the collected data are sent wirelessly to a mobile application interface. The novelty of this research lies in the potential it offers for continuous and effective screening of SARS-CoV-2 patients, which is facilitated and enhanced, providing big data statistics of COVID-19 in terms of space and time. This device can be used by individuals for SARS-CoV-2 testing at home, by health professionals for patient monitoring, and by public health agencies for monitoring the spatio-temporal spread of the virus. [ABSTRACT FROM AUTHOR]

From the beginning of the COVID-19 pandemic, researchers assessed the impact of the disease in terms of loss of life, medical load, economic damage, and other key metrics of resiliency and consequence mitigation; these studies sought to parametrize the critical components of a disease transmission model and the resulting analyses were informative but often lacked critical parameters or a discussion of parameter sensitivities. Using SARS-CoV-2 as a case study, we present a robust modeling framework that considers disease transmissibility from the source through transport and dispersion and infectivity. The framework is designed to work across a range of particle sizes and estimate the generation rate, environmental fate, deposited dose, and infection, allowing for end-to-end analysis that can be transitioned to individual and population health models. In this paper, we perform sensitivity analysis on the model framework to demonstrate how it can be used to advance and prioritize research efforts by highlighting critical parameters for further analyses. [ABSTRACT FROM AUTHOR]

On 31 December 2019, a cluster of pneumonia cases of unknown etiology was reported in Wuhan (China). The cases were declared to be Coronavirus Disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 has been defined as SARS Coronavirus 2 (SARS-CoV-2). Some countries, e.g., Italy, France, and the United Kingdom (UK), have been subjected to frequent restrictions for preventing the spread of infection, contrary to other ones, e.g., the United States of America (USA) and Sweden. The restrictions afflicted the evolution of trends with several perturbations that destabilized its normal evolution. Globally, R t has been used to estimate time-varying reproduction numbers during epidemics. Methods: This paper presents a solution based on Deep Learning (DL) for the analysis and forecasting of epidemic trends in new positive cases of SARS-CoV-2 (COVID-19). It combined a neural network (NN) and an R t estimation by adjusting the data produced by the output layer of the NN on the related R t estimation. Results: Tests were performed on datasets related to the following countries: Italy, the USA, France, the UK, and Sweden. Positive case registration was retrieved between 24 February 2020 and 11 January 2022. Tests performed on the Italian dataset showed that our solution reduced the Mean Absolute Percentage Error (MAPE) by 28.44%, 39.36%, 22.96%, 17.93%, 28.10%, and 24.50% compared to other ones with the same configuration but that were based on the LSTM, GRU, RNN, ARIMA (1,0,3), and ARIMA (7,2,4) models, or an NN without applying the R t as a corrective index. It also reduced MAPE by 17.93%, the Mean Absolute Error (MAE) by 34.37%, and the Root Mean Square Error (RMSE) by 43.76% compared to the same model without the adjustment performed by the R t . Furthermore, it allowed an average MAPE reduction of 5.37%, 63.10%, 17.84%, and 14.91% on the datasets related to the USA, France, the UK, and Sweden, respectively. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has become a worldwide threat resulting in a pandemic in 2020. SARS-CoV-2 infection manifests itself as coronavirus disease 2019 (COVID-19) that is evidenced in a vast number of either specific or nonspecific symptoms. Except for typical (but nonspecific) symptoms such as fever, dry cough, or muscle weakness, the infected patients might also present atypical symptoms including neurological, dermatological, or ophthalmic manifestations. This paper summarizes the current state of knowledge regarding the onset, progression, and types of ophthalmic symptoms induced by SARS-CoV-2 infection recognized amongst the infected patients. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a case of COVID-19 in a newly diagnosed HIV-infected, severely immunodepressed patient with a long persistence of positive RT-PCR for RNA SARS-CoV-2. Indirect data suggests that viable virus persisted for a long time in the absence of an adequate defense of the host. Improved immunity after starting antiretroviral treatment was not associated with an increased inflammatory reaction as regarding the infection due to the coronavirus and, apparently, was the main factor to control the infection. Remdesivir used to combat the SARS-CoV-2 infection had no immediate effect on the recorded cycle-threshold. [ABSTRACT FROM AUTHOR]

According to many experts in the fields of psychology and psychiatry, the destabilization resulting from the coronavirus pandemic may not be as noticeable now as it will be after the pandemic period is over. Undoubtedly, the fact that the surrounding reality is standardized and normalized by many at present contributes to this. In the opinion of many researchers, the scale and degree of trauma experienced by society will only be noticed by many once the pandemic is over. Many also suggest that we will experience post-pandemic stress disorder. This literature review aims to bring together in one place the information that speaks to the nature of the problem, which is post-pandemic stress disorder. The main sections of the paper deal with exposure to the disorder in the general population and a review of the current literature on the subject. The second section deals with a group of medical personnel who are on the direct frontline in the fight against the COVID-19 pandemic; it is assumed here that they are those who are at much higher risk of developing post-pandemic stress disorder. [ABSTRACT FROM AUTHOR]

Patients with severely impaired antibody responses represent a group at-risk in the SARS-CoV-2 pandemic due to the lack of Spike-specific neutralizing antibodies. The main objective of this paper was to assess, by a longitudinal prospective study, COVID-19 infection and mortality rates, and disease severity in the first two years of the pandemic in a cohort of 471 Primary Antibody Defects adult patients. As secondary endpoints, we compared SARS-CoV-2 annual mortality rate to that observed over a 10-year follow-up in the same cohort, and we assessed the impact of interventions done in the second year, vaccination and anti-SARS-CoV-2 monoclonal antibodies administration on the disease outcome. Forty-one and 84 patients were infected during the first and the second year, respectively. Despite a higher infection and reinfection rate, and a higher COVID-19-related mortality rate compared to the Italian population, the pandemic did not modify the annual mortality rate for any cause in our cohort compared to that registered over the last ten years in the same cohort. PADs patients who died from COVID-19 had an underlying end-stage lung disease. We showed a beneficial effect of MoAbs administration on the likelihood of hospitalization and development of severe disease. In conclusion, COVID-19 did not cause excess mortality in Severe Antibody Deficiencies. [ABSTRACT FROM AUTHOR]

The worldwide spread of coronavirus disease 2019 (COVID-19), a condition caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen, led to the most unprecedented disease outbreak of this century, provoking around 770 million confirmed cases and nearly 7 million deaths globally [[1]]. Rahmati et al., reported that 41.7% of COVID-19 survivors still experienced post-COVID-19 symptoms two years after infection [[7]]. One study investigated sex differences in the development of COVID-19-associated onset symptoms and post-COVID-19 symptoms [[9]]. Since one clinical manifestation of pain sensitization is the presence of larger areas of pain [[19]], its association with other measures of central sensitization could reveal potential mechanisms of post-COVID-19 pain. [Extracted from the article]

As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused 5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to artificial intelligence, have been used for its detection, diagnosis, and surveillance. Meanwhile, fast and efficient point-of-care (POC) testing and self-testing kits have become necessary in the fight against COVID-19 and to assist healthcare personnel and governments curb the spread of the virus. This paper presents a review of the various types of COVID-19 detection methods, diagnostic technologies, and surveillance approaches that have been used or proposed. The review provided in this article should be beneficial to researchers in this field and health policymakers at large. [ABSTRACT FROM AUTHOR]

A pneumonia outbreak was primarily reported in the fall of 2019 in Wuhan, Hubei province, China, with the identity SARS-CoV-2, a novel coronavirus. It quickly grew from a local epidemic to a global pandemic and was declared a public health emergency by the WHO. A total of three prominent waves were identified across the globe, with a slight temporal variability as per the geographical locations, and has impacted several sectors which connect the world. By March 2022, the coronavirus had infected 444.12 million people and claimed 6.01 million human lives worldwide, and these numbers have not yet stabilized. Our paper enlightens readers on the seven strains of human coronaviruses, with special emphasis on the three severe deadliest outbreaks (SARS-2002, MERS-2012, and COVID-19). This work attempts a comprehensive understanding of the coronavirus and its impact on the possible sectors that link the world through the economic chain, climate conditions, SDGs, recycling of the event, and mitigations. There are many points that are raised by the authors in the possible sectors, which are emerging or are as yet unnoticed and thus have not been taken into consideration. This comprehension will leave sets of new challenges and opportunities for the researchers in various streams, especially in earth sciences. Science-integrated research may help to prevent upcoming disasters as a by-product of (existing) epidemics in the form of coronavirus. [ABSTRACT FROM AUTHOR]

As a result of the COVID-19 pandemic, various joint efforts have been made to support the creation of vaccines. Different projects have been under development, of which some are in the clinical evaluation stage and others in are in phase III with positive results. The aim of this paper was to describe the current situation of the development and production of vaccines available to the population to facilitate future research and continue developing and proposing ideas for the benefit of the population. So, we carried out a systematic review using databases such as PubMed, ScienceDirect, SciELO, and MEDLINE, including keywords such as "vaccines," "COVID-19," and "SARS-CoV-2". We reviewed the development and production of the anti-COVID vaccine and its different platforms, the background leading to the massive development of these substances, and the most basic immune aspects for a better understanding of their physiological activity and the immune response in those who receive the vaccine. We also analyzed immunization effects in populations with any medical or physiological conditions (such as immunosuppression, people with comorbidities, and pregnancy), as well as the response to immunization with heterologous vaccines and the hybrid immunity (the combination of natural immunity to SARS-CoV-2 with immunity generated by the vaccine). Likewise, we address the current situation in Mexico and its role in managing the vaccination process against SARS-CoV-2 at the national and international levels. There are still many clinical and molecular aspects to be described, such as the duration of active immunity and the development of immunological memory, to mention some of the most important ones. However, due to the short time since the global vaccination roll-out and that it has been progressive (not counting children and people with medical conditions), it is premature to say whether a second vaccination schedule will be necessary for the near future. Thus, it is essential to continue with health measures. [ABSTRACT FROM AUTHOR]

On 11 March 2020, the World Health Organization made the assessment that a new disease (COVID-19) caused by a novel coronavirus (SARS-CoV-2) could be characterized as a pandemic. From that point, a chain reaction of events and difficult decisions requiring action was launched. National governments all over the world announced partial or total quarantine lockdowns in an effort to control the virus' spreading in order to save as many lives as possible. The effects of the pandemic were multifaceted and transport was not excluded. The current paper examines data regarding the level of usage (provided by the administrator) of bike-sharing systems in three case studies/medium-sized Greek cities (Igoumenitsa, Chania, and Rhodes) and through a statistical analysis identifies if there is a correlation between the implemented measures and the modal choice of the residents. The main results and conclusions of this analysis reveal that the level of usage of these specific bike-sharing systems was significantly increased during the lockdown period compared to the situation before the lockdown and the pandemic in general. [ABSTRACT FROM AUTHOR]

The world has been severely challenged by the Coronavirus Disease (COVID-19) outbreak since the early 2020s. Worldwide, there have been more than 66 million cases of infection and over 3,880,450 deaths caused by this highly contagious disease. All sections of the population including those who are affected, those who are not affected and those who have recovered from this disease, are suffering physiologically, psychologically or psychophysiologically. In this paper we briefly discuss the consequences of COVID-19 on physiological, psychological and psychophysiological vulnerability. We also attempt to provide evidence in support of exercise management as a prevention strategy for improving and minimizing the physiological, psychological and psychophysiological effects of COVID-19. Moderate exercise including walking, yoga and tai-chi to name but a few exercise regimes are critical in preventing COVID-19 and its complications. Governments, public health authorities and the general population should maintain physical activity during the COVID-19 pandemic to prevent additional physical and mental distress. [ABSTRACT FROM AUTHOR]

The study presented in the paper aims to analyze the Russian print media market before and during the COVID-19 pandemic, as well as the prospects of local media transformation in the challenging environment. In the pre-pandemic decade, there was a growing body of literature on media convergence in emerging markets confirming that this concept is growing in importance as a strategic path of conventional media transformation. Still, the research on the Russian conventional media transformation is scarce, the impact of the COVID-19 pandemic risks on Russian print media and their business models have not been investigated so far. To fill the gap, we combined desk research, processing of published industry statistics, and data obtained by means of expert interviews. The results confirm that in the first decades of the 21st century Russian print media paid less attention to the opportunities of media convergence than Western ones. At the same time, those Russian conventional media that set ambitious goals for their future considered the adoption of the media convergence approach as crucial, even before the pandemic. The findings show the lack of systemic measures to improve the overall situation on the national media market that faces difficult times, and the need to take into account pandemic risks in the print media management activities. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a member of the genus Betacoronavirus in the family Coronaviridae, possesses an unusually large single-stranded viral RNA (ssvRNA) genome of about ~29,811 nucleotides (nt) that causes severe and acute respiratory distress and a highly lethal viral pneumonia known as COVID-19. COVID-19 also presents with multiple ancillary systemic diseases and often involves cardiovascular, inflammatory, and/or neurological complications. Pathological viral genomes consisting of ssvRNA, like cellular messenger RNA (mRNA), are susceptible to attack, destruction, neutralization, and/or modulation by naturally occurring small non-coding RNAs (sncRNAs) within the host cell, some of which are known as microRNAs (miRNAs). This paper proposes that the actions of the 2650 known human miRNAs and other sncRNAs form the basis for an under-recognized and unappreciated innate-immune regulator of ssvRNA viral genome activities and have implications for the efficiency of SARS-CoV2 invasion, infection, and replication. Recent research indicates that both miRNA and mRNA abundance, speciation, and complexity varies widely amongst human individuals, and this may: (i) In part explain the variability in the innate-immune immunological and pathophysiological response of different human individuals to the initiation and progression of SARS-CoV-2 infection in multiple tissue types; and (ii) further support our understanding of human biochemical and genetic individuality and the variable resistance of individuals to ssvRNA-mediated viral infection and disease. This commentary will briefly address current findings and concepts in this fascinating research area of non-coding RNA and innate-immunity with special reference to natural host miRNAs, SARS-CoV-2, and the current COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The use of artificial neural networks (ANNs) is a great contribution to medical studies since the application of forecasting concepts allows for the analysis of future diseases propagation. In this context, this paper presents a study of the new coronavirus SARS-COV-2 with a focus on verifying the virus propagation associated with mitigation procedures and massive vaccination campaigns. There were two proposed methodologies in making predictions 28 days ahead for the number of new cases, deaths, and ICU patients of five European countries: Portugal, France, Italy, the United Kingdom, and Germany. A case study of the results of massive immunization in Israel was also considered. The data input of cases, deaths, and daily ICU patients was normalized to reduce discrepant numbers due to the countries’ size and the cumulative vaccination values by the percentage of population immunized (with at least one dose of the vaccine). As a comparative criterion, the calculation of the mean absolute error (MAE) of all predictions presents the best methodology, targeting other possibilities of use for the method proposed. The best architecture achieved a general MAE for the 1-to-28-day ahead forecast, which is lower than 30 cases, 0.6 deaths, and 2.5 ICU patients per million people. [ABSTRACT FROM AUTHOR]

Testing for the SARS-CoV-2 infection is critical for tracking the spread of the virus and controlling the transmission dynamics. In the early phase of the pandemic in Italy, the decentralized healthcare system allowed regions to adopt different testing strategies. The objective of this paper is to assess the impact of the extensive testing of symptomatic individuals and their contacts on the number of hospitalizations against a more stringent testing strategy limited to suspected cases with severe respiratory illness and an epidemiological link to a COVID-19 case. A Poisson regression modelling approach was adopted. In the first model developed, the cumulative daily number of positive cases and a temporal trend were considered as explanatory variables. In the second, the cumulative daily number of swabs was further added. The explanatory variable, given by the number of swabs over time, explained most of the observed differences in the number of hospitalizations between the two strategies. The percentage of the expected error dropped from 70% of the first, simpler model to 15%. Increasing testing to detect and isolate infected individuals in the early phase of an outbreak improves the capability to reduce the spread of serious infections, lessening the burden of hospitals. [ABSTRACT FROM AUTHOR]

The research problem is that the COVID-19 pandemic has become a threat to the sustainable development of the EEU and caused uncertainty in terms of the management of corporate social responsibility. This paper is aimed at identifying the impact of the COVID-19 pandemic on sustainable development of the EEU from the perspective of the interaction of the member states of the integration association and their mutual trade risks through the prism of the management of corporate social responsibility. The methodological foundation of the research is composed of the provisions of a comprehensive approach that has been used as a basis for determining the cause-and-effect relationship between the member states of the integration association and their mutual trade risks in the age of the COVID-19 pandemic in 2020. The analysis of statistical data is based on the methodology of econometric theory; in particular, the methods of horizontal and trend analysis. This paper analyzes the measures that were taken by the EEU member states to fight the pandemic of a new coronavirus infection both at the national level and at the level of the EEU institutions. The authors showed the asynchronous nature of measures introduced at the national level, while in certain circumstances the economic inefficiency of the introduction of measures, taken at the supranational level, and the impact of imposed restrictions on the current situation with mutual trade in goods and services, and free movement of workers. It has been substantiated that the examination of the economic interaction of the EEU member states in the period of restrictions dictated by a new coronavirus infection has revealed several endemic problems and had a major impact on the achievement of the main objectives of the integration association, transforming the terms for the management of corporate social responsibility. The originality of the paper is that the unique experience of the integration association of the EEU is for the first time studied from the perspective of the impact of the risks of mutual trade during a pandemic on it through the prism of the management of corporate social responsibility. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic revealed a pressing need for the development of sensitive and low-cost point-of-care sensors for disease diagnosis. The current standard of care for COVID-19 is quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). This method is sensitive, but takes time, effort, and requires specialized equipment and reagents to be performed correctly. This make it unsuitable for widespread, rapid testing and causes poor individual and policy decision-making. Rapid antigen tests (RATs) are a widely used alternative that provide results quickly but have low sensitivity and are prone to false negatives, particularly in cases with lower viral burden. Electrochemical sensors have shown much promise in filling this technology gap, and impedance spectroscopy specifically has exciting potential in rapid screening of COVID-19. Due to the data-rich nature of impedance measurements performed at different frequencies, this method lends itself to machine-leaning (ML) algorithms for further data processing. This review summarizes the current state of impedance spectroscopy-based point-of-care sensors for the detection of the SARS-CoV-2 virus. This article also suggests future directions to address the technology's current limitations to move forward in this current pandemic and prepare for future outbreaks. [ABSTRACT FROM AUTHOR]

Background: Coronavirus Disease 2019 (COVID-19) is the main discussed topic worldwide in 2020 and at the beginning of the Italian epidemic, scientists tried to understand the virus diffusion and the epidemic curve of positive cases with controversial findings and numbers. Objectives: In this paper, a data analytics study on the diffusion of COVID-19 in Lombardy Region and Campania Region is developed in order to identify the driver that sparked the second wave in Italy. Methods: Starting from all the available official data collected about the diffusion of COVID-19, we analyzed Google mobility data, school data and infection data for two big regions in Italy: Lombardy Region and Campania Region, which adopted two different approaches in opening and closing schools. To reinforce our findings, we also extended the analysis to the Emilia Romagna Region. Results: The paper shows how different policies adopted in school opening/closing may have had an impact on the COVID-19 spread, while other factors related to citizen mobility did not affect the second Italian wave. Conclusions: The paper shows that a clear correlation exists between the school contagion and the subsequent temporal overall contagion in a geographical area. Moreover, it is clear that highly populated provinces have the greatest spread of the virus. [ABSTRACT FROM AUTHOR]

Wastewater-based epidemiology (WBE) is useful for detecting pathogen prevalence and may serve to effectively monitor diseases across broad scales. WBE has been used throughout the COVID-19 pandemic to track disease burden through quantifying SARS-CoV-2 RNA present in wastewater. Aside from case load estimation, WBE is being used to assay viral genomic diversity and emerging potential SARS-CoV-2 variants. Here, we present a study in which we sequenced RNA extracted from sewage influent obtained from eight wastewater treatment plants representing 16 million people in Southern California from April 2020 to August 2021. We sequenced SARS-CoV-2 with two methods: Illumina Respiratory Virus-Enriched metatranscriptomic sequencing (N = 269), and QIAseq SARS-CoV-2-tiled amplicon sequencing (N = 95). We classified SARS-CoV-2 reads into lineages and sublineages that approximated named variants and identified single nucleotide variants (SNVs), of which many are putatively novel SNVs and SNVs of unknown potential function and prevalence. Through our retrospective study, we also show that several SARS-CoV-2 sublineages were detected in wastewater before clinical detection, which may assist in the prediction of future variants of concern. Lastly, we show that sublineage diversity was similar across Southern California and that diversity changed over time, indicating that WBE is effective across megaregions. As the COVID-19 pandemic moves to new phases, and SARS-CoV-2 variants emerge, monitoring wastewater is important to understand local- and population-level dynamics of the virus. These results will aid in our ability to monitor the evolutionary potential of SARS-CoV-2 and help understand circulating SNVs to further combat COVID-19. [ABSTRACT FROM AUTHOR]

Background/Objectives: During the COVID-19 pandemic and the burden on hospital resources, the rapid categorization of high-risk COVID-19 patients became essential, and lung ultrasound (LUS) emerged as an alternative to chest computed tomography, offering speed, non-ionizing, repeatable, and bedside assessments. Various LUS score systems have been used, yet there is no consensus on an optimal severity cut-off. We assessed the performance of a 12-zone LUS score to identify adult COVID-19 patients with severe lung involvement using oxygen saturation (SpO2)/fractional inspired oxygen (FiO2) ratio as a reference standard to define the best cut-off for predicting adverse outcomes. Methods: We conducted a single-centre prospective study (August 2020–April 2021) at Hospital del Mar, Barcelona, Spain. Upon admission to the general ward or intensive care unit (ICU), clinicians performed LUS in adult patients with confirmed COVID-19 pneumonia. Severe lung involvement was defined as a SpO2/FiO2 ratio <315. The LUS score ranged from 0 to 36 based on the aeration patterns. Results: 248 patients were included. The admission LUS score showed moderate performance in identifying a SpO2/FiO2 ratio <315 (area under the ROC curve: 0.71; 95%CI 0.64–0.77). After adjustment for COVID-19 risk factors, an admission LUS score ≥17 was associated with an increased risk of in-hospital death (OR 5.31; 95%CI: 1.38–20.4), ICU admission (OR 3.50; 95%CI: 1.37–8.94) and need for IMV (OR 3.31; 95%CI: 1.19–9.13). Conclusions: Although the admission LUS score had limited performance in identifying severe lung involvement, a cut-off ≥17 score was associated with an increased risk of adverse outcomes. and could play a role in the rapid categorization of COVID-19 pneumonia patients, anticipating the need for advanced care. [ABSTRACT FROM AUTHOR]

The global urgency in response to the COVID-19 pandemic has catalyzed extensive research into discovering efficacious antiviral compounds against SARS-CoV-2. Among these, Nirmatrelvir (PF-07321332) has emerged as a promising candidate, exhibiting potent antiviral activity by targeting the main protease of SARS-CoV-2, and has been marketed in combination with ritonavir as the first oral treatment for COVID-19 with the name of PaxlovidTM. This review outlines the synthetic approaches to Nirmatrelvir, ranging from Pfizer's original method to newer, more sustainable strategies, such as flow chemistry strategies and multicomponent reactions. Each approach's novelty and contributions to yield and purification processes are highlighted. Additionally, the synthesis of key fragments comprising Nirmatrelvir and innovative optimization strategies are discussed. [ABSTRACT FROM AUTHOR]

Background and Objectives: Our aim was to perform a retrospective analysis of the volume of cervical screening tests, the number of patients treated with an excision method, and the incidence of invasive and non-invasive cervical during a pandemic and pre-pandemic period of 24 months. Materials and Methods: The study compared 404 patients who underwent cervical cone biopsy for cervical cancer. The study examined patients' specimens based on histopathological characteristics and categorized cervical lesions based on pap smear. Results: There was a statistically significant age difference between the two study periods. The mean difference was 32 years before the pandemic and 35 years during the pandemic (p-value > 0.05). The biggest patient loss ratio identified by age group was in the 50–59-year group, with a 14.53% loss in the pre-pandemic period and a 9.1% loss in the pandemic period. In the pandemic period, patients from rural areas presented in the clinical trial with a lower rate of 39.52% (83 patients) vs. 60.47% (127 patients) in urban areas. A higher percentage of patients experiencing cervicorrhagia as a clinical manifestation in the pandemic period vs. the pre-pandemic period, with an increase in more severe lesions in the pandemic period, had a statistical significance of 8% more newly diagnosed compared to the pre-pandemic period. Conclusions: The addressability of the patients during the COVID period was not affected in a drastic way in our study. We encountered a decrease in appointments in the age group of 50–59 years and a decrease in patients with rural residence. In our study, we found an increase in cervical bleeding as a reason for consultation in the pandemic period with a higher lesion degree, both on a pap smear and on a cervical biopsy. [ABSTRACT FROM AUTHOR]

Advantageous variants of the SARS-CoV-2 virus have arisen through mutations, particularly on a single amino acid basis. These point mutations can cause changes in the structure of SARS-CoV-2 and affect the efficiency of interaction with the ACE2 protein. N501Y and E484K mutations affecting binding by ACE2 have been widely observed. This study aimed to predict SARS-CoV-2 mutations that could be as effective as N501Y and E484K and pose a danger due to their high contagiousness. Experimental data on SARS-CoV-2 and ACE2 binding and stability were associated with different amino acid properties and integrated into machine learning and computational biology techniques. As a result of the analyses made in algorithms, N501M, Q414A, N354K, Q498H and N460K have been predicted to be likely to have a dangerous effect. The N501W mutations are most likely to have dangerous effects on the spread of the coronavirus. We suggest that attention should be paid to the position 501 mutation since this position is repeated in the lists of mutations that the algorithm detected as dangerous. G446, G447, Y505, T500, Q493, Y473, and G476 were determined as the positions where dangerous variants could be seen as a result of the analyses of the multiple interaction data created with the ACE2 and RBD interaction data. The 13 dangerous positions and mutations have been detected to accurately describe the position of the mutations caused by the Omicron variant and were among the known dangerous mutations similar to those occurring at Q498, G446, Y505 and Q493 positions. [ABSTRACT FROM AUTHOR]

Bronchial asthma (BA) continues to be a difficult disease to diagnose. Various factors have been described in the development of BA, but to date, there is no clear evidence for the etiology of this chronic disease. The emergence of COVID-19 has contributed to the pandemic course of asthma and immunologic features. However, there are no unambiguous data on asthma on the background and after COVID-19. There is correlation between various trigger factors that provoke the development of bronchial asthma. It is now obvious that the SARS-CoV-2 virus is one of the provoking factors. COVID-19 has affected the course of asthma. Currently, there is no clear understanding of whether asthma progresses during or after COVID-19 infection. According to the results of some studies, a significant difference was identified between the development of asthma in people after COVID-19. Mild asthma and moderate asthma do not increase the severity of COVID-19 infection. Nevertheless, oral steroid treatment and hospitalization for severe BA were associated with higher COVID-19 severity. The influence of SARS-CoV-2 infection is one of the protective factors. It causes the development of severe bronchial asthma. The accumulated experience with omalizumab in patients with severe asthma during COVID-19, who received omalizumab during the pandemic, has strongly suggested that continued treatment with omalizumab is safe and may help prevent the severe course of COVID-19. Targeted therapy for asthma with the use of omalizumab may also help to reduce severe asthma associated with COVID-19. However, further studies are needed to prove the effect of omalizumab. Data analysis should persist, based on the results of the course of asthma after COVID-19 with varying degrees of severity. [ABSTRACT FROM AUTHOR]

Despite evidence demonstrating the risks of developing diabetes mellitus because of SARS-CoV-2, there is, however, insufficient scientific data available to elucidate the relationship between diabetes mellitus and COVID-19. Research indicates that SARS-CoV-2 infection is associated with persistent damage to organ systems due to the systemic inflammatory response. Since COVID-19 is known to induce these conditions, further investigation is necessary to fully understand its long-term effects on human health. Consequently, it is essential to consider the effect of the COVID-19 pandemic when predicting the prevalence of diabetes mellitus in the future, especially since the incidence of diabetes mellitus was already on the rise before the pandemic. Additional research is required to fully comprehend the impact of SARS-CoV-2 infection on glucose tolerance and insulin sensitivity. Therefore, this article delves deeper into the current literature and links the perceived relationship between SARS-CoV-2 and diabetes. In addition, the article highlights the necessity for further research to fully grasp the mechanisms that SARS-CoV-2 utilises to induce new-onset diabetes. Where understanding and consensus are reached, therapeutic interventions to prevent the onset of diabetes could be proposed. Lastly, we propose advocating for the regular screening of diabetes and pre-diabetes, particularly for the high-risk population with a history of COVID-19 infection. [ABSTRACT FROM AUTHOR]

Patients with chronic obstructive pulmonary disease (COPD) infected with SARS-CoV-2 indicate a higher risk of severe COVID-19 course, which is defined as the need for hospitalization in the intensive care unit, mechanical ventilation, or death. However, simple tools to stratify the risk in patients with COPD suffering from COVID-19 are lacking. The current study aimed to evaluate the predictive value of the C2HEST score in patients with COPD. A retrospective analysis of medical records from 2184 patients hospitalized with COVID-19 at the University Hospital in Wroclaw from February 2020 to June 2021, which was previously used in earlier studies, assessed outcomes such as mortality during hospitalization, all-cause mortality at 3 and 6 months, non-fatal discharge, as well as adverse clinical incidents. This re-analysis specifically examines the outcomes using a COPD split. In the COPD group, 42 deaths were recorded, including 18 in-hospital deaths. In-hospital mortality rates at 3 and 6 months did not significantly differ among C2HEST strata, nor did their impact on subsequent treatment. However, a notable association between the C2HEST score and prognosis was observed in the non-COPD cohort comprising 2109 patients. The C2HEST score's predictive ability is notably lower in COPD patients compared to non-COPD subjects, with COPD itself indicating a high mortality risk. However, C2HEST effectively identifies patients at high risk of cardiac complications during COVID-19, especially in non-COPD cases. [ABSTRACT FROM AUTHOR]

Background: The long-term survival of patients hospitalized with COVID-19 and the factors associated with poorer survival months after infection are not well understood. The aims of the present study were to analyze the overall mortality 10 months after admission. Methods: 762 patients with COVID-19 disease were included. Patients underwent a complete clinical evaluation, routine laboratory analysis and chest X-ray. Data collected included demographic and clinical data, such as vascular risk factors, tobacco or alcohol use, comorbidity, and institutionalization. Results: Ten-month mortality was 25.6%: 108 deaths occurred in-hospital, while 87 patients died after discharge. In-hospital mortality was independently related to NT-proBNP values > 503.5 pg/mL [OR = 4.67 (2.38–9.20)], urea > 37 mg/dL [3.21 (1.86–7.31)] and age older than 71 years [OR = 1.93 (1.05–3.54)]. NT-proBNP values > 503.5 pg/mL [OR = 5.00 (3.06–8.19)], urea > 37 mg/dL [3.51 (1.97–6.27)], cognitive impairment [OR = 1.96 (1.30–2.95), cancer [OR = 2.23 (1.36–3.68), and leukocytes > 6330/mm3 [OR = 1.64 (1.08–2.50)], were independently associated with long-term mortality. Conclusions: the risk of death remains high even months after COVID-19 infection. Overall mortality of COVID-19 patients during 10 months after hospital discharge is nearly as high as that observed during hospital admission. Comorbidities such as cancer or cognitive impairment, organ dysfunction and inflammatory reaction are independent prognostic markers of long-term mortality. [ABSTRACT FROM AUTHOR]

Infection with the novel coronavirus SARS-CoV-2, the cause of coronavirus disease (COVID-19), has emerged as a global pandemic, with a high toll on casualties, economic impact, and human lifestyle. Despite the recent approval of various vaccines against the virus, challenges remain, including the limited availability of these vaccines, the prevalent rejection of vaccination by a large proportion of the population, and the recurrent appearance of new variants of the virus due to mutations. This context raises the alarm for scientists and clinicians to seek alternative and complementary therapies. In this context, natural products and their derivatives serve as reservoirs for potential therapeutic compounds that can be exploited in the research and production of antiviral drugs against COVID-19. Among these substances, lectin and polysaccharides isolated from fauna and flora emerge as complementary strategies for treating coronavirus infection. The review objective is to cover and analyze the specific role of polysaccharides and lectins and their synergy in the fight against this deadly SARS-CoV-2 virus. For this purpose, a primary literature search was conducted on Google Scholar, PubMed, and Web of Sciences using relevant keywords like "SARS-CoV-2 Variants"; "Antiviral Strategies"; "Antiviral Polysaccharides"; "Antiviral Lectins"; and "Synergistic effect". The results demonstrate that lectins and polysaccharides exhibit antiviral activities against SARS-CoV-2 via mechanisms related to binding and steric blocking, the binding of glycan-based decoys, chemical reactions, virus particle disruption strategies, and steric blocking for competitive inhibition to block SARS-CoV-2 and its variants' entry. In addition, this review analyzes the rationale behind combining polysaccharides and lectins, emphasizing complementary mechanisms of action. By simultaneously targeting multiple stages of the viral life cycle, this dual strategy aims to comprehensively inhibit viral propagation and enhance the durability of antiviral strategies over time. [ABSTRACT FROM AUTHOR]

The emergence of the novel coronavirus in Wuhan, China since 2019, has put the world in an exotic state of emergency and affected millions of lives. It is five times more deadly than Influenza and causes significant morbidity and mortality. COVID-19 mainly affects the pulmonary system leading to respiratory disorders. However, earlier studies indicated that COVID-19 infection may cause cardiovascular diseases, which can be detected using an electrocardiogram (ECG). This work introduces an advanced deep learning architecture for the automatic detection of COVID-19 and heart diseases from ECG images. In particular, a hybrid combination of the EfficientNet-B0 CNN model and Vision Transformer is adopted in the proposed architecture. To our knowledge, this study is the first research endeavor to investigate the potential of the vision transformer model to identify COVID-19 in ECG data. We carry out two classification schemes, a binary classification to identify COVID-19 cases, and a multi-class classification, to differentiate COVID-19 cases from normal cases and other cardiovascular diseases. The proposed method surpasses existing state-of-the-art approaches, demonstrating an accuracy of 100% and 95.10% for binary and multiclass levels, respectively. These results prove that artificial intelligence can potentially be used to detect cardiovascular anomalies caused by COVID-19, which may help clinicians overcome the limitations of traditional diagnosis. [ABSTRACT FROM AUTHOR]

Essential in halting the COVID-19 pandemic caused by SARS-CoV-2, it is crucial to have stable, effective, and easy-to-manufacture vaccines. We developed a potential vaccine using a tobacco mosaic virus (TMV) epitope display model presenting peptides derived from the SARS-CoV-2 spike protein. The TMV-epitope fusions in laboratory tests demonstrated binding to the SARS-CoV-2 polyclonal antibodies. The fusion constructs maintained critical epitopes of the SARS-CoV-2 spike protein, and two in particular spanned regions of the receptor-binding domain that have mutated in the more recent SARS-CoV-2 variants. This would allow for the rapid modification of vaccines in response to changes in circulating variants. The TMV-peptide fusion constructs also remained stable for over 28 days when stored at temperatures between −20 and 37 °C, an ideal property when targeting developing countries. Immunogenicity studies conducted on BALB/c mice elicited robust antibody responses against SARS-CoV-2. A strong IFNγ response was also observed in immunized mice. Three of the six TMV-peptide fusion constructs produced virus-neutralizing titers, as measured with a pseudovirus neutralization assay. These TMV-peptide fusion constructs can be combined to make a multivalent vaccine that could be adapted to meet changing virus variants. These findings demonstrate the development of a stable COVID-19 vaccine candidate by combining SARS-CoV-2 spike protein-derived peptides presented on the surface of a TMV nanoparticle. [ABSTRACT FROM AUTHOR]

Amid the global challenges posed by the COVID-19 pandemic, unraveling the genomic intricacies of SARS-CoV-2 became crucial. This study explores viral evolution using an innovative high-throughput next-generation sequencing (NGS) approach. By taking advantage of nasal swab and mouthwash samples from patients who tested positive for COVID-19 across different geographical regions during sequential infection waves, our study applied a targeted enrichment protocol and pooling strategy to increase detection sensitivity. The approach was extremely efficient, yielding a large number of reads and mutations distributed across 10 distinct viral gene regions. Notably, the genes Envelope, Nucleocapsid, and Open Reading Frame 8 had the highest number of unique mutations per 1000 nucleotides, with both spike and Nucleocapsid genes showing evidence for positive selection. Focusing on the spike protein gene, crucial in virus replication and immunogenicity, our findings show a dynamic SARS-CoV-2 evolution, emphasizing the virus–host interplay. Moreover, the pooling strategy facilitated subtle sequence variability detection. Our findings painted a dynamic portrait of SARS-CoV-2 evolution, emphasizing the intricate interplay between the virus and its host populations and accentuating the importance of continuous genomic surveillance to understand viral dynamics. As SARS-CoV-2 continues to evolve, this approach proves to be a powerful, versatile, fast, and cost-efficient screening tool for unraveling emerging variants, fostering understanding of the virus's genetic landscape. [ABSTRACT FROM AUTHOR]

Wastewater-based epidemiology has garnered considerable research interest, concerning the COVID-19 pandemic. Restrictive public health interventions and mobility limitations are measures to avert a rising case prevalence. The current study integrates WBE monitoring strategies, Google mobility data, and restriction information to assess the epidemiological development of COVID-19. Various SARIMAX models were employed to predict SARS-CoV-2 cases in Liechtenstein and two Austrian regions. This study analyzes four primary strategies for examining the progression of the pandemic waves, described as follows: 1—a univariate model based on active cases; 2—a multivariate model incorporating active cases and WBE data; 3—a multivariate model considering active cases and mobility data; and 4—a sensitivity analysis of WBE and mobility data incorporating restriction policies. Our key discovery reveals that, while WBE for SARS-CoV-2 holds immense potential for monitoring COVID-19 on a societal level, incorporating the analysis of mobility data and restriction policies enhances the precision of the trained models in predicting the state of public health during the pandemic. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has significantly impacted global healthcare, underscoring the importance of exploring the virus's effects on infected individuals beyond treatments and vaccines. Notably, recent findings suggest that SARS-CoV-2 can infect the gut, thereby altering the gut microbiota. This study aimed to analyze the gut microbiota composition differences between COVID-19 patients experiencing mild and severe symptoms. We conducted 16S rRNA metagenomic sequencing on fecal samples from 49 mild and 43 severe COVID-19 cases upon hospital admission. Our analysis identified a differential abundance of specific bacterial species associated with the severity of the disease. Severely affected patients showed an association with Enterococcus faecium, Akkermansia muciniphila, and others, while milder cases were linked to Faecalibacterium prausnitzii, Alistipes putredinis, Blautia faecis, and additional species. Furthermore, a network analysis using SPIEC-EASI indicated keystone taxa and highlighted structural differences in bacterial connectivity, with a notable disruption in the severe group. Our study highlights the diverse impacts of SARS-CoV-2 on the gut microbiome among both mild and severe COVID-19 patients, showcasing a spectrum of microbial responses to the virus. Importantly, these findings align, to some extent, with observations from other studies on COVID-19 gut microbiomes, despite variations in methodologies. The findings from this study, based on retrospective data, establish a foundation for future prospective research to confirm the role of the gut microbiome as a predictive biomarker for the severity of COVID-19. [ABSTRACT FROM AUTHOR]

The long-term sequelae of SARS-CoV-2 infection are still under research, since extensive studies showed plenty of systemic effects of the viral infection, extending even after the acute phase of the infection. This study evaluated kidney function tests six months after SARS-CoV-2 infection in patients clinically diagnosed with Post-COVID Syndrome, hypothesizing persistent renal dysfunction evidenced by altered kidney function tests compared to baseline levels. Continuous eGFR decrease <30 at six months post-infection was considered the main study outcome. Conducted at the "Victor Babes" Hospital, this retrospective observational study involved adults with laboratory-confirmed SARS-CoV-2 infection and clinically-diagnosed Post-COVID Syndrome, excluding those with prior chronic kidney disease or significant renal impairment. Kidney function tests, including serum creatinine, blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), alongside markers of kidney damage such as proteinuria and hematuria, were analyzed. Among 206 participants, significant differences were observed between the control (n = 114) and the Post-COVID group (n = 92). The Post-COVID group exhibited higher serum creatinine (109.7 μmol/L vs. 84.5 μmol/L, p < 0.001), lower eGFR (65.3mL/min/1.73 m2 vs. 91.2 mL/min/1.73 m2, p < 0.001), and elevated BUN levels (23.7 mg/dL vs. 15.2 mg/dL, p < 0.001) compared to the control group. Regression analysis highlighted significant predictors of continuous eGFR decrease <30 at six months post-infection. The development of acute kidney injury (AKI) during the initial COVID-19 illness emerged as a strong predictor of reduced eGFR (β = 3.47, p < 0.001). Additional factors, including a creatinine increase (23 μmol/L above the normal range) and an elevated Albumin to Creatinine Ratio (ACR) (>11 mg/g above the normal range), were significantly associated with eGFR reduction. Patients with Post-COVID Syndrome demonstrate significant renal impairment six months post-SARS-CoV-2 infection. The study's findings stress the need for ongoing monitoring and intervention strategies for renal health in affected individuals, underscoring the persistent impact of COVID-19 on renal function. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has underscored the critical need for the advancement of diagnostic and therapeutic platforms. These platforms rely on the rapid development of molecular binders that should facilitate surveillance and swift intervention against viral infections. In this study, we have evaluated by three independent research groups the binding characteristics of various published RNA and DNA aptamers targeting the spike protein of the SARS-CoV-2 virus. For this comparative analysis, we have employed different techniques such as biolayer interferometry (BLI), enzyme-linked oligonucleotide assay (ELONA), and flow cytometry. Our data show discrepancies in the reported specificity and affinity among several of the published aptamers and underline the importance of standardized methods, the impact of biophysical techniques, and the controls used for aptamer characterization. We expect our results to contribute to the selection and application of suitable aptamers for the detection of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

In responding to the COVID-19 pandemic, evidence-based policymaking and risk mitigation have been confronted with limited decision-making mechanisms under conditions of increased uncertainty. Such methods are particularly called for in contexts where reliable data to a large extent are missing and where the chosen policy would impact a variety of sectors. In this paper, we present an application of an integrated decision-making framework under ambiguity on how to contain the COVID-19 virus spread from a national policy point of view. The framework was applied in Jordan and considered both local epidemiologic and socioeconomic estimates in a multistakeholder multicriteria context. In particular, the cocreation process for eliciting attitudes, perceptions, and preferences amongst relevant stakeholder groups has often been missing from policy response to the pandemic, even though the containment measures' efficiency largely depends on their acceptance by the impacted groups. For this, there exist several methods attempting to elicit criteria weights, values, and probabilities ranging from direct rating and point allocation methods to more elaborated ones. To facilitate the elicitation, some of the approaches utilise elicitation methods whereby prospects are ranked using ordinal importance information, while others use cardinal information. Methods are sometimes assessed in case studies or more formally by utilising systematic simulations. Furthermore, the treatment of corresponding methods for the handling of the alternative's values has sometimes been neglected. We demonstrate in our paper an approach for cardinal ranking in policy decision making in combination with imprecise or incomplete information concerning probabilities, weights, and consequences or alternative values. The results of our cocreation process are aggregated in the evaluation of alternative mitigation measures for Jordan, showcasing how a multistakeholder multicriteria decision mechanism can be employed in current or future challenges of pandemic situations, to facilitate management and mitigation of similar crises in the future, in any region. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, wastewater-based epidemiology has been extensively used as a helpful tool for evaluation of the epidemic situation in catchments of wastewater treatment plants. In this context, knowledge about the rate of virus inactivation in wastewater is important for characterization of the influence of retention times in sewers on virus concentrations, of the storage periods before analysis in the laboratory, on virus elimination during treatment and for modeling approaches. In the present study, we genotyped SARS-CoV-2 in the respiratory tract specimens of infected patients and spiked the raw wastewater of five treatment plants with aliquots of these samples. The test preparations were incubated under practically relevant temperature conditions (14 °C) over 31 days. The linear decay rates resulted in comparable T90 values (30.5 d) for the Delta and the Omicron BA1 variants of SARS-CoV-2 without differences in using the E or S gene of the virus as the target for amplification. In contrast, the origin of wastewater influenced the inactivation rate of both variants significantly, with the mean T90 values varying between 24.3 and 53.1 days in the wastewater from the five plants. The data suggest that the inactivation rate of SARS-CoV-2 in wastewater is more strongly determined by the composition of the water than by the virus variant. [ABSTRACT FROM AUTHOR]

Background/Objectives: Upper-limb function of chronic stroke patients declined when outpatient rehabilitation was interrupted and outings restricted, owing to the novel coronavirus infection (COVID-19) pandemic. We investigated whether these patients recovered upper-limb function post-resumption of outpatient rehabilitation. Methods: In this observational study, 43 chronic stroke hemiparesis patients with impaired upper extremity function were scored for limb function via the Fugl-Meyer assessment of the upper extremity (FMA-UE) and the Action Research Arm Test (ARAT) after a structured interview, evaluation, and intervention. Scores at 6 and 3 months pre- and 3 months post-rehabilitation interruption were examined retrospectively; scores immediately and at 3 and 6 months post-resumption of care were examined prospectively. The amount of change for each time period and an analysis of covariance were performed with time as a factor, changes in the FMA-UE and the ARAT scores as dependent variables, and statistical significance at 5%. Results: The time of evaluation significantly impacted the total score, as well as part C and part D of FMA-UE and total, pinch, and gross movement of the ARAT. Post-hoc tests showed that the magnitude of change in limb-function scores from immediately to 3 months post-resumption was significantly higher than the change from 3 months pre- to immediately post-interruption for the total score and part D of the FMA-UE, as well as grip and gross movement of the ARAT (p < 0.05). Conclusions: Upper-limb functional decline in chronic stroke patients, caused by the COVID-19 pandemic-related therapy interruption and outing restrictions, was resolved approximately 3 months post-resumption of rehabilitation therapy. Our data can serve as reference standards for planning and evaluating treatment for chronic stroke patients with inactivity-related impaired upper-limb function. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic prompted rapid research on SARS-CoV-2 pathogenicity. Consequently, new data can be used to advance the molecular understanding of SARS-CoV-2 infection. The present bioinformatics study discusses the "spikeopathy" at the molecular level and focuses on the possible post-transcriptional regulation of the SARS-CoV-2 spike protein S1 subunit in the host cell/tissue. A theoretical protein–RNA recognition code was used to check the compatibility of the SARS-CoV-2 spike protein S1 subunit with mRNAs in the human transcriptome (1-L transcription). The principle for this method is elucidated on the defined RNA binding protein GEMIN5 (gem nuclear organelle-associated protein 5) and RNU2-1 (U2 spliceosomal RNA). Using the method described here, it was shown that 45% of the genes/proteins identified by 1-L transcription of the SARS-CoV-2 spike protein S1 subunit are directly linked to COVID-19, 39% are indirectly linked to COVID-19, and 16% cannot currently be associated with COVID-19. The identified genes/proteins are associated with stroke, diabetes, and cardiac injury. [ABSTRACT FROM AUTHOR]

Background: Neutrophil gelatinase-associated lipocalin (NGAL) is part of the innate immune system and acute-phase protein. Current data state that acute COVID-19 patients have higher levels of serum NGAL (sNGAL), but it is not known if higher protein levels are maintained in the convalescents. As post-COVID complications are currently the most important aspect of the disease, further research into metabolic and immunological consequences of the disease is needed. Methods: We aimed to determine the levels of sNGAL in a patient population 3 months after the acute phase of the disease and to identify the factors that may be related to the elevation of sNGAL levels in the mentioned cohort. The study included 146 patients diagnosed with COVID-19 in different stages of the disease. Three months after COVID-19 diagnosis, patients' sera were sampled and tested. Results: We demonstrate an association between the severity of the disease in the acute phase and elevated sNGAL levels three months after recovery, with the exception of the most severe hospitalized patients, who received early treatment. Moreover, we establish that sNGAL levels could be associated with prolonged dyspnea and the regulation of hunger and satiety in COVID-19 convalescents. Conclusions: These observations support the view that the introduction of antiviral treatment, steroids, and intense oxygen therapy reduces post-COVID immune-associated complications. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has brought about diverse impacts on the global population. Individuals with comorbidities were more susceptible to the severe symptoms caused by the virus. Within the crisis scenario, metabolomics represents a potential area of science capable of providing relevant information for understanding the metabolic pathways associated with the intricate interaction between the viral disease and previous comorbidities. This work aims to provide a comprehensive description of the scientific production pertaining to metabolomics within the specific context of COVID-19 and comorbidities, while highlighting promising areas for exploration by those interested in the subject. In this review, we highlighted the studies of metabolomics that indicated a variety of metabolites associated with comorbidities and COVID-19. Furthermore, we observed that the understanding of the metabolic processes involved between comorbidities and COVID-19 is limited due to the urgent need to report disease outcomes in individuals with comorbidities. The overlap of two or more comorbidities associated with the severity of COVID-19 hinders the comprehension of the significance of each condition. Most identified studies are observational, with a restricted number of patients, due to challenges in sample collection amidst the emergent situation. [ABSTRACT FROM AUTHOR]