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The molecular docking-based virtual screening technique evaluates the binding abilities between multiple ligand compounds and receptors to screen for the active compounds. In the context of the global spread of the COVID-19 pandemic, large-scale and rapid drug virtual screening is crucial for identifying potential drug molecules from massive datasets of ligand structures. The powerful computing power of supercomputer provides hardware guarantee for drug virtual screening, but the super large-scale drug virtual screening still faces many challenges that affects the effective execution of the calculation. Based on the analysis of the challenges, this paper proposes a centralized task distribution scheme with a central database, and designs a multi-level task distribution framework. The challenges are effectively solved through multi-level intelligent scheduling, multi-level compression processing of massive small molecule files, dynamic load balancing and high error tolerance management technology. An easy-touse"tree”multi-level task distribution system is implemented. A fast, efficient and stable drug virtual screening task distribution, calculation and result analysis function is realized, and the computing efficiency is nearly linear. Then, heterogeneous computing technology is used to complete the drug virtual screening of more than 2 billion compounds, for two different active sites for COVID-19, on the domestic super computing system, which provides a powerful computing guarantee for the super large-scale rapid virtual screening of explosive malignant infectious diseases. © 2023, Journal of Computer Engineering and Applications Beijing Co., Ltd.;Science Press. All rights reserved.
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Covid-19 virus variants identified so far are due to viral genetic diversity, genetic evolution, and variable infectivity, suggesting that high infection rates and high mortality rates may be contributed by these mutations. And it has been reported that the targeting strategies for innate immunity should be less vulnerable to viral evolution, variant emergence and resistance. Therefore, the most effective solution to Covid-19 infection has been proposed to prevent and treat severe exacerbation of patients with moderate disease by enhancing human immune responses such as NK cell and T cell. In previous studies, we demonstrated for the first time that gamma-PGA induced significant antitumor activity and antiviral activity by modulating NK cell-mediated cytotoxicity. Especially intranasal administration of gamma-PGA was found to effectively induce protective innate and CTL immune responses against viruses and we found out that gamma-PGA can be an effective treatment for cervical intraepithelial neoplasia 1 through phase 2b clinical trial. In this study, the possibility of gamma-PGA as a Covid-19 immune modulating agent was confirmed by animal experiments infected with Covid-19 viruses. After oral administration of gamma-PGA 300mug/mouse once a day for 5 days in a K18-hACE2 TG mouse model infected with SARS-CoV-2 (NCCP 43326;original strain) and SARS-CoV-2 (NCCP 43390;Delta variant), virus titer and clinical symptom improvement were confirmed. In the RjHan:AURA Syrian hamster model infected with SARS-CoV-2 (NCCP 49930;Delta variant), 350 or 550 mug/head of gamma-PGA was administered orally for 10 days once a day. The virus for infection was administered at 5 x 104 TCID50, and the titer of virus and the improvement of pneumonia lesions were measured to confirm the effectiveness in terms of prevention or treatment. In the mouse model infected with original Covid-19 virus stain, the weight loss was significantly reduced and the survival rate was also improved by the administration of gamma-PGA. And gamma-PGA alleviated the pneumonic lesions and reduced the virus titer of lung tissue in mice infected with delta variant. In the deltavariant virus infected hamster model, gamma-PGA showed statistically significant improvement of weight loss and lung inflammation during administration after infection. This is a promising result for possibility of Covid-19 therapeutics along with the efficacy results of mouse model, suggesting gammaPGA can be therapeutic candidate to modulate an innate immune response for Covid-19.
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Objectives: This study aimed to determine disease severity, clinical features, clinical outcome in hospitalized patients with the Omicron variant and evaluate the effectiveness of one-dose, two-dose, and three-dose inactivated vaccines in reducing viral loads, disease course, ICU admissions and severe diseases. Method(s): Retrospective cohort analysis was performed on 5,170 adult patients (>=18 years) identified as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction admitted at Shanghai Medical Center for Gerontology between March 2022 and June 2022. COVID-19 vaccination effectiveness was assessed using logistic regression models evaluating the association between the risk of vaccination and clinical outcomes, adjusting for confounders. Result(s): Among 5,170 enrolled patients, the median age was 53 years, and 2,861 (55.3%) were male. 71.0% were mild COVID-19 cases, and cough (1,137 [22.0%]), fever (592 [11.5%]), sore throat (510 [9.9%]), and fatigue (334 [6.5%]) were the most common symptoms on the patient's first admission. Ct values increased generally over time and 27.1% patients experienced a high viral load (Ct value< 20) during their stay. 105(2.0%) of these patients were transferred to the intensive care unit after admission. 97.1% patients were cured or showed an improvement in symptoms and 0.9% died in hospital. The median length of hospital stay was 8.7+/-4.5 days. In multivariate logistic analysis, booster vaccination can significantly reduce ICU admissions and decrease the severity of COVID-19 outcome when compared with less doses of vaccine (OR=0.75, 95%CI, 0.62-0.91, P<=0.005;OR=0.99, 95%CI, 0.99-1.00, p<0.001). Conclusion(s): In summary, the most of patients who contracted SARSCoV-2 omicron variant had mild clinical features and patients with vaccination took less time to lower viral loads. As the COVID-19 pandemic progressed, an older and less vaccinated population was associated with higher risk for ICU admission and severe disease.Copyright © 2023
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Introduction: The COVID-19 pandemic has required clinical teams to function with an unprecedented amount of uncertainty, balancing complex risks and benefits in a highly fluid environment. This is especially the case when considering the delivery of a pregnant woman critically unwell with COVID-19. This is one maternal critical care team's reflections on establishing best practice and a shared mental model when undertaking a Caesarean section in critically unwell patients with COVID-19. Objective(s): We describe our experience of balancing the risks and streamlining the process of this high-risk intervention. Method(s): We used our standard clinical governance forums across four specialties (Obstetrics, Intensive care, Anaesthetics and Neonatology) to identify key challenges and learning points. We developed a working group to combine our learning and develop a shared mental model across the involved teams. Result(s): 1. The decision to deliver must be multidisciplinary involving Obstetrics, Intensive care, Anaesthetics, Neonatology and the patient according to their capacity to participate. The existing structure of twice daily ITU ward rounds could be leveraged as a 'pause' moment to consider the need for imminent delivery and review the risk-benefit balance of continued enhanced pharmacological thromboprophylaxis. 2. We identified a range of scenarios that our teams might be exposed to: 3. Perimortem Caesarean section 4. Critically unwell - unsafe to move to theatre 5. Critically unwell - safe to move to theatre 6. Recreating an obstetric theatre in the ICU Advantages Avoids moving a critically unstable patient, although our experience is increasing moving patients for ECMO. Some forms of maximal non-invasive therapy such as High Flow Nasal Oxygen may require interruption to move to theatre with resultant risk of harm or be difficult to continue in transport mode through a bulky ICU ventilator e.g. CPAP Disadvantages Significant logistics and coordination burden: multiple items of specialist equipment needing to be brought to the ICU. Human factors burden: performing a caesarean section in an unfamiliar environment is a significant increase in cognitive load for participating teams. Environmental factors: ICU side rooms may offer limited space vs the need to control the space if performed on an open unit. Delivering a Neonate into a COVID bubble. Conclusion(s): Developing a shared mental model across the key teams involved in delivering an emergency caesarean section in this cohort of critically unwell patients has enabled our group to own a common understanding of the key decisions and risks involved. We recommend a patient centred MDT decision making model, with a structure for regular reassessment by senior members of the teams involved. In most circumstances the human factors and logistical burden of recreating an operating theatre in the ICU outweighs the risk of transport to theatre. Pre-defined checklists and action cards mitigate the cognitive and logistical burden when multiple teams do perform an operative delivery in ICU. Action cards highlight key aspects of routine obstetric care to be replicated in the ICU environment.
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The COVID-19 pandemic created unprecedented disruptions in models for engineering student training. At The Citadel, an undergraduate-focused college in the Southeastern United States, a variety of modalities were implemented following the onset of the pandemic, including emergency online and Hyflex learning. We conducted a longitudinal study to analyze the cognitive load among our undergraduate engineering students throughout changing modalities. Using data from the NASA Task Load Index (TLX) and open-ended reflections on student challenges, we found that total workload (a surrogate for cognitive load) was generally highest during emergency online learning in the second half of Spring 2020 semester, with experiences possibly varying across different demographic and academic groups. Emergency online challenges were often related to time management, personal organization, and responsibility for learning. In contrast, HyFlex challenges were often related to technology and communication challenges. While emergency online learning was a cognitive load disruption, that disruption was often associated with personal and/or academic development. HyFlex learning mediated cognitive load disruption;although, student challenges may have been simple nuisances rather than mediators of developmental change. © 2023 American Society of Civil Engineers.
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Due to improvements in information and communication technology and growth of sensor technologies, Internet of Things is now widely used in medical field for optimal resource management and ubiquitous sensing. In hospitals, many IoT devices are linked together via gateways. Importance of gateways in modernization of hospitals cannot be overstated, but their centralized nature exposes them to a variety of security threats, including integrity, certification, and availability. Block chain technology for level monitoring in oxygen cylinders is a scattered record containing the data related to oxygen levels in the cylinder, patient's name, patient's ID number, patient's medical history, and all connected information carried out and distributed among the hospitals (nodes) present in the locality (network). Designing an oxygen level monitoring technique in an oxygen cylinder used as the support system for COVID-19-affected patients is a challenging task. Monitoring the level of oxygen in the cylinders is very important because they are used for saving the lives of the patients suffering from COVID-19. Not only the COVID-19 patients are dependent on this system, but this system will also be helpful for other patients who require oxygen support. The present scenario many COVID-19 hospitalized patients rely upon oxygen supply through oxygen cylinders and manual monitoring of oxygen levels in these cylinders has become a challenging task for the healthcare professionals due to overcrowding. If this level monitoring of oxygen cylinders are automated and developed as a mobile App, it would be of great use to the medical field, saving the lives of the patients who are left unmonitored during this pandemic. This proposal is entitled to develop a system to measure oxygen level using a smartphone App which will send instantaneous values about the level of the oxygen inside the cylinder. Pressure sensors and load cell are fitted to the oxygen cylinders, which will measure the oxygen content inside the cylinder in terms of the pressure and weight. The pressure sensors and load cells are connected to the Arduino board and are programmed to display the actual level of oxygen inside the cylinder in terms of numerical values. A beep sound is generated as an indicator to caution the nurses and attendants of the patients regarding the level of the oxygen inside the cylinder when it is only 15% of the total oxygen level in the cylinder in correlation to the pressure and weight. The signal with respect to the level corresponding to the measured pressure and weight of the cylinder is further transmitted to the monitoring station through Global System for Mobile communication (GSM). Graphical display is used at monitoring end to indicate the level of oxygen inside all oxygen cylinders to facilitate actions like 100% full, 80% full, 60% full, 40% full, 20% full which states that either the oxygen cylinder is in good condition, or requires a replacement of empty cylinders with filled ones in correlation to the pressure and weight being sensed by the sensors. The levels of the oxygen monitored inside the cylinder and other related data can also be stored on a cloud storage which will facilitate the retrieval of the status at any point of time, as when required by the physicians and nurses. These results reported, are valued in monitoring the level of the oxygen cylinder remotely connected to the patients, affected by COVID-19, using a smartphone App. This mobile phone App is an effective tool for investigating the oxygen cylinder level used as a life-support system for COVID-19-affected patients. A virtual model of the partial system is developed using TINKER CAD simulation package. In real time, the sensor data analysis with cloud computing will be deployed to detect and track the level of the oxygen cylinders. © 2023 Elsevier Inc. All rights reserved.
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The use of machine learning and data-driven methods for predictive analysis of power systems offers the potential to accurately predict and manage the behavior of these systems by utilizing large volumes of data generated from various sources. These methods have gained significant attention in recent years due to their ability to handle large amounts of data and to make accurate predictions. The importance of these methods gained particular momentum with the recent transformation that the traditional power system underwent as they are morphing into the smart power grids of the future. The transition towards the smart grids that embed the high-renewables electricity systems is challenging, as the generation of electricity from renewable sources is intermittent and fluctuates with weather conditions. This transition is facilitated by the Internet of Energy (IoE) that refers to the integration of advanced digital technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) into the electricity systems. It has been further enhanced by the digitalization caused by the COVID-19 pandemic that also affected the energy and power sector. Our review paper explores the prospects and challenges of using machine learning and data-driven methods in power systems and provides an overview of the ways in which the predictive analysis for constructing these systems can be applied in order to make them more efficient. The paper begins with the description of the power system and the role of the predictive analysis in power system operations. Next, the paper discusses the use of machine learning and data-driven methods for predictive analysis in power systems, including their benefits and limitations. In addition, the paper reviews the existing literature on this topic and highlights the various methods that have been used for predictive analysis of power systems. Furthermore, it identifies the challenges and opportunities associated with using these methods in power systems. The challenges of using these methods, such as data quality and availability, are also discussed. Finally, the review concludes with a discussion of recommendations for further research on the application of machine learning and data-driven methods for the predictive analysis in the future smart grid-driven power systems powered by the IoE.
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The transition to Electric Vehicles (EV) in place of traditional internal combustion engines is increasing societal demand for electricity. The ability to integrate the additional demand from EV charging into forecasting electricity demand is critical for maintaining the reliability of electricity generation and distribution. Load forecasting studies typically exclude households with home EV charging, focusing on offices, schools, and public charging stations. Moreover, they provide point forecasts which do not offer information about prediction uncertainty. Consequently, this paper proposes the Long Short-Term Memory Bayesian Neural Networks (LSTM-BNNs) for household load forecasting in presence of EV charging. The approach takes advantage of the LSTM model to capture the time dependencies and uses the dropout layer with Bayesian inference to generate prediction intervals. Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals. Moreover, the impact of lockdowns related to the COVID-19 pandemic on the load forecasting model is examined, and the analysis shows that there is no major change in the model performance as, for the considered households, the randomness of the EV charging outweighs the change due to pandemic.
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Objective: COVID-19 has emerged as a significant global health crisis causing devastating effects on world population accounting for over 6 million deaths worldwide. Although acute RTI is the prevalent cause of morbidity, kidney outcomes centered on a spectrum of AKI have evolved over the course of the pandemic. Especially the emerging variants have posed a daunting challenge to the scientific communities, prompting an urging requirement for global contributions in understanding the viral dynamics. In addition to canonical genes, several subgroup- specific accessory genes are located between the S and E genes of coronaviruses regarding which little is known. Previous studies have shown that accessory proteins (aps) in viruses function as viroporins that regulate viral infection, propagation and egress [1]. In this study we attempted to characterize the function of aps of coronavirus variants as ion channels. Furthermore, we also probed the interaction of ap4 with the host system. Method(s): Serial passaging (selection pressure), growth kinetics, confocal imaging, genome sequence analysis and proteomics were performed in Huh-7, MRC5 cells and/or human monocyte derived macrophages. Potassium uptake assay was performed in a Saccharo myces cerevisiae strain, which lacks the potassium transporters trk1 and trk2. Ion conductivity experiments were performed in Xenopus laevis oocytes using Two Electrode Voltage Clamp (TEVC) method. Result(s): Serial passaging demonstrated the acquisition of several frameshift mutations in ORF4 resulting in C-terminally truncated protein versions (ap4 and ap4a) and indicate a strong selection pressure against retaining a complete ORF4 in vitro. Growth kinetics in primary cells illustrated a reduction of viral titers when the full-length ap4 was expressed compared to the C-terminally truncated protein ap4a. Confocal imaging showed that ap4 and ap4a are not exclusively located in a single cellular compartment. Potassium uptake assay in yeast and TEVC analyses in Xenopus oocytes showed that ap4 and ap4a act as a weak K+ selective ion channel. In addition, accessory proteins of other virus variants also elicited microampere range of currents. Conclusion(s): Our study provides the first evidence that ap4 and other accessory proteins of coronavirus variants act as viroporins. Future studies are aimed at demonstrating the role of ap4 during the viral life cycle by modulating ion homeostasis of host cell in vivo (interacting proteins obtained from proteomic studies) and thereby serve as a tool for potential drug target.
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Problem: COVID-19 placentitis is a rare complication of maternal SARS-CoV-2 respiratory infection associated with serious adverse obstetric outcomes, including intra-uterine death. The precise role of SARS-CoV-2 in COVID-19 placentitis is uncertain, as trophoblast infection is only observed in around one-half of the affected placenta. Method of Study: Through multi-omic spatial profiling, including Nanostring GeoMX digital spatial profiling and Lunaphore COMET multiplex IHC, we provide a deep characterization of the immunopathology of placentitis from obstetrically complicated maternal COVID-19 infection. Result(s):We show that SARS-CoV-2 infection of placental trophoblasts is associated with a distinct innate and adaptive immune cell infiltrate, florid cytokine expression and upregulation of viral restriction factors. Quantitative spatial analyses reveal a unique microenvironment surrounding virus-infected trophoblasts characterizedd by multiple immune evasion mechanisms, including immune checkpoint expression, cytotoxic T-cell exclusion, and interferon blunting. Placental viral loads inversely correlated with the duration of maternal infection consistent with progressive virus clearance, potentially explaining the absence of virus in some cases. Conclusion(s): Our results demonstrate a central role for placental SARS-CoV-2 infection in driving the unique immunopathology of COVID-19 placentitis.
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Objective. To assess the T-cell immune status against SARS-CoV-2 in HIV patients with or without antiretroviral therapy. Patients and methods. The study included 21 HIV patients who had laboratory-confirmed COVID-19 between September and December 2021 without previous immunization against SARS-CoV-2. The characteristics of HIV infection (CD4-lymphocytes count, HIV viral load in blood plasma, the presence of antiretroviral therapy) and COVID-19 (the severity degree and duration of the disease) were analyzed, the T-cell immune response to SARS-CoV-2 was assessed using the ELISPOT method 1 month after COVID-19. Statistical analysis was carried out by non-parametric methods (Mann-Whitney U test, Spearman's rank correlation coefficient) using the IBM SPSS Statistics 22 software package. Results. The study showed a more favorable course of COVID-19 in HIV-infected persons who achieved HIV suppression in the blood: a mild form of the disease was significantly more common, and the virus was eliminated faster. T-cell immune response to SARS-CoV-2 was recorded more frequently in these patients. Significant correlation of T-cell immune status with the CD4-lymphocytes count and HIV suppression in the blood was revealed. Conclusion. Thus, T-cell immune response to SARS-CoV-2 as assessed using the ELISPOT method was registered significantl.Copyright © 2023, Dynasty Publishing House. All rights reserved.
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Background: The quantification of SARS-CoV-2 in wastewater is a tool that allows determining the trend of viral circulation in a particular geographical area. Aim(s): To quantify the SARS-CoV-2 virus in 15 wastewater treatment plants in different Chilean cities to establish a comparison with the variables of: I) Active cases per 100,000 inhabitants;ii) daily positivity (novel cases);and iii) phases of the lockdown strategy. Method(s): SARS-CoV-2 was concentrated from wastewater samples. To obtain the number of virus genomes per liter, absolute quantification was performed using qRT-PCR. Result(s): Between January and June 2021, 253 samples were processed, all of which were positive for the presence of the virus. Likewise, it will be determined that the rate of active cases per 100,000 inhabitants is the variable that best fits the trends obtained with the quantification of the viral load in wastewater. Conclusion(s): The quantification of SARS- CoV-2 in wastewater as a continuous strategy is an efficient tool to determine the trend of the viral circulation in a delimited geographical area and, combined with genomic surveillance, it can constitute an ideal sentinel surveillance alert on future outbreaks.Copyright © 2022, Sociedad Chilena de Infectologia. All rights reserved.
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Background & Aim: Adoptive T cell immunotherapy holds great promise for the treatment of viral complications. Our group has been developing and trialling virus-specific T cell therapies for more than 20 years. Recently, we have generated a repository of multi-virus-specific T cells for our clinical trials. Unfortunately, for many patients with viral complications, there is no suitable trial through which to access these therapies. In Australia, the Therapeutic Goods Administration has a Special Access Scheme (SAS) to enable provision of unapproved therapies for compassionate use. Our research group is now a leading Australian provider of "off-the-shelf" and custom-grown allogeneic virus-specific T cells to hospitals for patients with no other treatment options. Methods, Results & Conclusion(s): We have generated a repository of multi-virus-specific T cells from 20 healthy donors, with up to 150 doses of T cells per donor generated from a single blood sample. Each product batch is thoroughly characterised in terms of viral antigen specificity, HLA restriction and alloreactivity. These T cells target a combination of Epstein-Barr virus, cytomegalovirus, BK polyomavirus, John Cunningham virus and adenovirus epitopes. We have also generated a repository of SARS-CoV-2-specific T cells and occasionally grow custom patient-specific batches of T cells from nominated donors, on request. Since 2008, we have provided virus-specific T cells to 15 hospitals across Australia, and the volume of supply requests has significantly increased in recent years, as clinicians have gained interest in adoptive immunotherapy. In 2022, we provided T cells for 26 patients via the SAS. The majority were experiencing post-transplant complications, including cytomegalovirus disease, BK virus-associated haemorrhagic cystitis and post-transplant lymphoproliferative disorder. Through our clinical trials, we have developed rigorous processes for T cell therapy manufacture and characterisation, in addition to a computer-based selection algorithm, which we apply to SAS cases. As these cases are not part of a clinical trial, concomitant therapy varies, and monitoring is not uniform. However, we have received reports of clinical benefit from adoptive T cell therapy. These include cases of reduction in viral load, improvement in symptoms, and complete resolution of infection. We believe that these promising T cell therapies should be available to hospitals through a nationally funded centre for cellular therapies for critically ill patients.Copyright © 2023 International Society for Cell & Gene Therapy
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Background/Objectives: Current pandemic situation, together with the continuous emergence of new SARS-CoV-2 variants reveal the need to develop a more versatile tool than PCR-based methods that allows both high throughput COVID-19 diagnostic and specific variant detection at reduced cost and fast turnaround times. Thus, with the aim of overcoming current test limitations and providing a strategy with these characteristics arises our novel next generation sequencing based approach. Method(s): The developed strategy works with RNA samples obtained from nasopharyngeal swabs. RNA samples are processed with our custom laboratory protocol and can be sequenced with any Illumina platform to generate results within a 24h timeframe. A tailored bioinformatic pipeline analyzes the data and generates a clinical-level report. Result(s): Clinical validation results have shown that the designed solution, sensitively and specifically identifies negative and positive samples that display a broad range in viral loads and readily identifies the following major SARS-CoV-2 variants of concern (VoC): Alpha, Beta, Gamma, Delta, Lambda and Omicron (BA.1 and BA.2). Conclusion(s): The versatility of our solution allows the capability of identifying the presence of other common respiratory viruses as well as identifying patients at risk through the identification of susceptibility human variants in the host. This, together with the possibility of easily adding new VoC as they emerge, will make VoC monitoring in entire populations feasible, providing a new perspective on the application of NGS methods in the field of clinical microbiology.
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BACKGROUND: SARS-CoV-2 virus infection is a pandemic that began to emerge in December 2019 in various countries with high death rates of 4-9% until now. In March 2020, Indonesia found its first case where the condition of the infection kept spreading to various regions in Indonesia. Different regional conditions in Indonesia make it difficult to manage this virus infection. The capability of the regional hospitals to detect this virus infection with their facilities and infrastructure is required. CASE PRESENTATION: A 17-year-old man came to the Ajibarang Regional Hospital with complaints of coughs and colds felt for 4 days and fever for 2 days. Physical examination found a good general condition, moderate pain, the temperature of 38.8degreeC, pharyngeal hyperemia, and minimal lung crackles sound. Laboratory tests showed normal leukocytes, platelet, and hemoglobin levels. Chest radiograph was suggestive of bronchitis. The patient was hospitalized for approximately 4 days until the fever resolved and was discharged. Five days after the patient was discharged from the hospital, the results of the viral load examination using real-time polymerase chain reaction confirmed positive for Coronavirus Disease 2019 (COVID-19). CONCLUSION(S): This case showed unusual conditions of a mild clinical COVID-19 infection, laboratory results that did not support viral infections, as well as radiology examination of only bronchitis. The viral load test was found to be positive. Therefore, the diagnosis of the COVID-19 infection requires a comprehensive interpretation of complete history taking, clinical examination, laboratory, and radiology examinations for clinicians working with limited hospital facilities and infrastructures.Copyright © 2023 Edward Kurnia Setiawan Limijadi, Inge Cahya Ramadhani, Dian Tunjungsari Hartutiningtyas, Gara Samara Brajadenta.
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The role of contaminated surfaces as a potential source for SARS-CoV-2 transmission has not been clear at the beginning of the pandemic. Numerous laboratory studies show that SARS-CoV-2 can remain infectious at room temperature on different types of surfaces for a few days and substantially longer in the dark. A higher temperature such as 30 °C or 40 °C and a higher relative humidity result in a shorter persistence. On surfaces in the surrounding of confirmed COVID-19 patients the detection rates of SARS-CoV-2 RNA were mostly less than 30% with Ct-values mostly >30 suggesting a low viral load and the absence of infectious SARS-CoV-2. The RNA detection rates on public surfaces were low with 0-22.1%, the corresponding Ct values were mostly >30. Infectious SARS-CoV-2 was only detected in 2 of 11 studies in the immediate surrounding of COVID-19 patients with 0.7% or 10.5% of the samples being positive. A major limitation of the results, however, is that in one study 7 of 8 positive samples were obtained in the surrounding of only one patient with persistent cough and frequent sputum spitting during sampling. Overall, the probability of surfaces to be the source of SARS-CoV-2 transmission is low, especially for public surfaces. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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Objective: To identify and describe the risk factors that increase susceptibility in older adults to infection by SARS-CoV-2 (Covid-19). Material(s) and Method(s): Descriptive, cross-sectional study in adults over 60 years, patients with a positive result (RT-PCR) were analysed to detect SARS-CoV-2. The study was carried out from May 17 to July 21, 2020. A multiple logistic regression model was used to analyse the risk factors of the study population. Result(s): 102 older adults were included with a mean age of 82.5 +/- 8.8 years, 55 (54%) were positive and 47 (46%) were negative. When analysing the risk factors related to higher mortality coupled with Covid-19 infection, the statistically significant variable was frailty, with an OR of 11.6 in frail adults compared to robust individuals (p-value = 0.024.) Conclusion(s): In the vulnerable population, risk factors must be identified and treated, but above all, such factors must be prevented in advance;early detection, isolation, effective treatment must be carried out as well as follow-up of contacts and prevention of the spread of the new virus to reduce mortality in vulnerable groups.Copyright © 2022 Sociedad Medica del Hospital General de Mexico. Published by Permanyer.
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Background & Aim: Despite the successful implementation of vaccines worldwide, COVID-19 remains a risk in patients with a compromised immune system. Emerging viral variants have also reduced the effectiveness of monoclonal antibody therapies in these patients. New treatment options are therefore required to improve clinical outcomes. Methods, Results & Conclusion(s): T cell immunotherapy has proven effective for the treatment of a number of refractory viral diseases in patients with a compromised immune system. We have now completed the manufacture of a bank of SARS-CoV-2 specific T cells and commenced an open-label phase I clinical trial at the Royal Brisbane and Women's Hospital, Australia. Patients enrolled in the study receive two doses of partially HLA-matched allogeneic T cells at a fortnightly interval. We have thus far recruited and treated three immune compromised patients with SARS-CoV-2 T cells. In two of the three patients treated thus far, the administration of T cell therapy was coincident with the clearance of viral load after 28 days. Viral clearance in these patients was also associated with an increase in circulating SARS-CoV-2 specific T cells. Our preliminary observations suggest that SARS-CoV-2 specific T cell therapy is well tolerated and has the potential to impact viral control in immune compromised patients.Copyright © 2023 International Society for Cell & Gene Therapy
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The current outbreak of COVID-19 is caused by the SARS-CoV-2 virus that has affected > 210 countries. Various steps are taken by different countries to tackle the current war-like health situation. In India, the Ministry of AYUSH released a self-care advisory for immunomodulation measures during the COVID-19 and this review article discusses the detailed scientific rationale associated with this advisory. Authors have spotted and presented in-depth insight of advisory in terms of immunomodulatory, antiviral, antibacterial, co-morbidity associated actions, and their probable mechanism of action. Immunomodulatory actions of advised herbs with no significant adverse drug reaction/toxicity strongly support the extension of advisory for COVID-19 prevention, prophylaxis, mitigations, and rehabilitation capacities. This advisory also emphasized Dhyana (meditation) and Yogasanas as a holistic approach in enhancing immunity, mental health, and quality of life. The present review may open-up new meadows for research and can provide better conceptual leads for future researches in immunomodulation, antiviral-development, psychoneuroimmunology, especially for COVID-19.Copyright © 2021, Institute of Korean Medicine, Kyung Hee University.