From Biowaste to Lab-Bench: Low-Cost Magnetic Iron Oxide Nanoparticles for RNA Extraction and SARS-CoV-2 Diagnostics.

The gold standard for diagnostics of SARS-CoV-2 (COVID-19) virus is based on real-time polymerase chain reaction (RT-PCR) using centralized PCR facilities and commercial viral RNA extraction kits. One of the key components of these kits are magnetic beads composed of silica coated magnetic iron oxide (Fe2O3 or Fe3O4) nanoparticles, needed for the selective extraction of RNA. At the beginning of the pandemic in 2019, due to a high demand across the world there were severe shortages of many reagents and consumables, including these magnetic beads required for testing for SARS-CoV-2. Laboratories needed to source these products elsewhere, preferably at a comparable or lower cost. Here, we describe the development of a simple, low-cost and scalable preparation of magnetic nanoparticles (MNPs) from biowaste and demonstrate their successful application in viral RNA extraction and the detection of COVID-19. These MNPs have a unique nanoplatelet shape with a high surface area, which are beneficial features, expected to provide improved RNA adsorption, better dispersion and processing ability compared with commercial spherical magnetic beads. Their performance in COVID-19 RNA extraction was evaluated in comparison with commercial magnetic beads and the results presented here showed comparable results for high throughput PCR analysis. The presented magnetic nanoplatelets generated from biomass waste are safe, low-cost, simple to produce in large scale and could provide a significantly reduced cost of nucleic acid extraction for SARS-CoV-2 and other DNA and RNA viruses.

Laboratory diagnosis of emerging human infections by SARS-COVID-19: Prevalence and challenges

The COVID-19 pandemic has created a global storm in the world, and nations worldwide are skirmishing with this unprecedented health crisis. The outbreak of Corona Virus Disease-19 (COVID-19), caused by Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2), had a significant impact on the healthcare system, especially in the clinical microbiology laboratories worldwide. The choice of a correct anatomical site for good samples collections with the proper precautions is essential for prompt and accurate diagnosis of COVID-19. This review aimed to cover the challenges faced during the choice of appropriate sample collection sites, transport and tests for detection of SARS-CoV-2 infection. The diagnosis tests of COVID-19 can be divided into direct, indirect and complementary tests. In the direct tests, Real-time polymerase chain reaction (RT-PCR) assays are the molecular tests of choice for the diagnosis of COVID-19. The remaining direct tests include GeneXpert and TrueNAT assays. In the indirect testing's;antigen-antibody-based techniques are recommended for surveillance of the disease, which may help to formulate the control measures. These tests not only help in assessing the disease severity, but also they benefit in evaluating the prognosis and management strategies. © 2022, Egyptian Association for Medical Mycologists (EAMM). All rights reserved.

Prevalence and Clinical Presentation of COVID 19 in Health Care Workers in Two Main Hospitals During the Pandemic in Shiraz, Iran

Background: Given that immunocompromised patients are more at risk for the infection of SARS-CoV-2, epidemiological data are critical for assessing the corresponding prevalence among health care workers (HCWs) and patients at health centers. Objective(s): This study aims to investigate the prevalence of SARS-CoV-2 infection among the staff of two hospitals that take care of immunocompromised patients, including pediatrics and adults with special medical conditions. Method(s): This cross-sectional study includes all HCWs of the two hospitals;Abu Ali Sina Transplant Hospital (AASTH) and Amir al-Momenin Burn Injury Hospital (AABIH) in Shiraz, southern Iran, conducted from April 11, 2020, to June 16, 2021. The TaqMan real-time PCR assay was used to assess the SARS-CoV-2 infection rate in the suspected HCWs. Result(s): Out of 1232 sampled HCWs, 694 (56%) were female. Two hundred sixty-five samples (21.5%) and 967 samples (78.5%) were prepared from AABIH, and AASTH, respectively. The results showed that 30% (373) of the clinically suspected employees had positive test results. There was a significant correlation between the risk of exposure to COVID-19 patients and the PCR positivity rate, which could be explained by the fact that 58% of the infected HCWs were in a high-risk group, 20% medium-risk, and the remaining 22% were low-risk (P < 0.0001). The rates of positive cases in females were higher than that among male counterparts (P < 0.05). Conclusion(s): In order to protect health care workers and reduce the prevalence and transmission of diseases, deficiencies must be identified and eliminated. Copyright © 2022, Author(s).

POSTER: Diagnosis of COVID-19 through Transfer Learning Techniques on CT Scans: A Comparison of Deep Learning Models

The novel coronavirus disease (COVID-19) constitutes a public health emergency globally. It is a deadly disease which has infected more than 230 million people worldwide. Therefore, early and unswerving detection of COVID-19 is necessary. Evidence of this virus is most commonly being tested by RT-PCR test. This test is not 100% reliable as it is known to give false positives and false negatives. Other methods like X-Ray images or CT scans show the detailed imaging of lungs and have been proven more reliable. This paper compares different deep learning models used to detect COVID-19 through transfer learning technique on CT scan dataset. VGG-16 outperforms all the other models achieving an accuracy of 85.33 % on the dataset. © 2022 IEEE.

COVID-19 PREDICTION USING TRANSFER-LEARNING ON RT-PCR CONFIRMED CXR-IMAGES

Corona-virus is a disease which caused immense destruction to human lives in 21st century. This virus outbreak is considered as an epidemic that spread globally. Crores of people are infected by this virus all over the world. Early detection of the virus is very much important to overcome Covid-19 crisis. This model proposes a convolution neural network model implemented using VGG-19accompanied with Transfer LearningTechnique for the Covid-19 Detection. The Covid-19 dataset considered in this model is a verified report of positive cases confirmed by both RT-PCR and CXR images. Initially, One Hot Encoding Method is used for CXR image data conversion and then pre-processing is done to extract features and then filtered data is forwarded through the VGG-19 and is further processed to Fully Connected Layers. Therefore, the model is later fine-tuned to achieve better classification results. The achieved model accuracy is around 0.94 with a loss is about 0.55. © 2022, Engg Journals Publications. All rights reserved.

Rapid Detection of Coronavirus (COVID-19) Using Microwave Immunosensor Cavity Resonator.

This paper presents a rapid diagnostic device for the detection of the pandemic coronavirus (COVID-19) using a micro-immunosensor cavity resonator. Coronavirus has been declared an international public health crisis, so it is important to design quick diagnostic methods for the detection of infected cases, especially in rural areas, to limit the spread of the virus. Herein, a proof-of-concept is presented for a portable laboratory device for the detection of the SARS-CoV-2 virus using electromagnetic biosensors. This device is a microwave cavity resonator (MCR) composed of a sensor operating at industrial, scientific and medical (ISM) 2.45 GHz inserted in 3D housing. The changes of electrical properties of measured serum samples after passing the sensor surface are presented. The three change parameters of the sensor are resonating frequency value, amplitude and phase of the reflection coefficient |S11|. This immune-sensor offers a portable, rapid and accurate diagnostic method for the SARS-CoV-2 virus, which can enable on-site diagnosis of infection. Medical validation for the device is performed through biostatistical analysis using the ROC (Receiver Operating Characteristic) method. The predictive accuracy of the device is 63.3% and 60.6% for reflection and phase, respectively. The device has advantages of low cost, low size and weight and rapid response. It does need a trained technician to operate it since a software program operates automatically. The device can be used at ports' quarantine units, hospitals, etc.

Comparison of Positivity Rates of Rapid Antigen Testing and Real-Time Polymerase Chain Reaction for COVID-19 During the First and Second Waves of the Pandemic in Eastern Uttar Pradesh, India.

Background The advent of the second wave of coronavirus disease 2019 (COVID-19) in India caused a new range of challenges in diagnosing the virus. Various point-of-care tests have been introduced for rapid diagnosis. Although rapid antigen tests are the most commonly used, the false-negative rates are high. Therefore, the purpose of this study was to compare the positivity rate of real-time polymerase chain reaction (RT-PCR) testing in rapid antigen-negative cases of COVID-19 during the first and second waves of the COVID-19 pandemic. Methodology This was an observational study conducted in the Department of Microbiology, All India Institute of Medical Sciences, Gorakhpur. Results In total, 2,168 patients were tested. The percentage positivity rate of the RT-PCR tests among the antigen-negative samples was 4.34% in the first wave of the pandemic whereas it was 8.08% in the second wave. Conclusions The main conclusion of this study was that antigen tests should never be used alone for the diagnosis of COVID-19. Instead, they should be confirmed with a RT-PCR test.

Diagnostic Value of High-Resolution Computed Tomography Scan in COVID-19: Do We Need to Think Outside the Box?

Background and objective The ambiguous nature and high infectivity of the coronavirus disease 2019 (COVID-19) have caused soaring morbidity and mortality worldwide. Real-time polymerase chain reaction (RT-PCR) is preferred for detecting COVID-19. However, its poor sensitivity and the emerging use of high-resolution CT (HRCT) scan for disease severity make the use of RT-PCR quite obsolete. In light of this, our study aimed to explore the beneficial role of HRCT and compare the HRCT findings across various patient demographics and parameters. Methods This cross-sectional study included 100 patients with clinical suspicion of COVID-19. All patients underwent a chest HRCT scan preceded by RT-PCR testing. We used the CT severity score (CTSS) of the chest to calculate disease severity. Demographical data and results of radiological findings were tabulated and compared across RT-PCR positivity, age, and gender. Independent samples t-test and chi-square test were used to analyze the data. Results Glass ground opacity was the most prevalent finding in 99% of the patients, followed by lymph node involvement, consolidation, and crazy-paving pattern. Pleural effusion was observed in only 10% of the patients while pericardial effusion and hiatal hernia were present in 5%. In RT-PCR-positive patients, the posterior basal segment of the lower lobe of the right and left lungs were found to be dominantly involved; however, the upper and middle lobes of the right lung were more commonly involved than the left lung. The mean CTSS was significantly higher in patients aged above 50 years (p<0.001). The mean CTSS of RT-PCR-negative patients was higher than that of RT-PCR-positive patients (15.18 vs. 14.31, p=0.537). Conclusion RT-PCR has a limited role in the diagnosis of COVID-19. The HRCT scan can detect typical COVID-19 findings even in patients with negative RT-PCR results. Moreover, the use of HRCT scan in determining the disease severity and extent of lung damage can lead to a better assessment of critically ill patients.

Perplexity vs Clarity in choosing the right molecular diagnostic techniques for SARS-COV2 detection in Indian setup.

After the havoc created by Spanish flu a century ago, the world is witnessing exactly a similar pandemic situation since the beginning of the year 2020. The unexplained respiratory illness with high morbidity & mortality which started in Wuhan, China and spread across the world was finally termed as COVID-19 disease caused by SARS-CoV-2 and later announced as pandemic by WHO. This novel virus SARS-CoV-2 is a new variant of SARS corona virus with high infectivity and mysterious pathophysiology. The major step towards containment of this pandemic is to scale up the testing for SARS-CoV-2 and thereby isolating and managing the patients at the earliest. Molecular amplification based methods such a Real time Polymerase chain reaction (RT-PCR), CBNAAT and TrueNAT are the most commonly used techniques for detection of SARS-CoV2. To utilize these diagnostic facilities optimally in the management of the suspected COVID 19 patients, it is of utmost importance for the healthcare providers to understand the intricacies related to these technologies. Thus, the technical details along with the pros & cons of these three amplification-based technologies for proper understanding of these diagnostic modalities for SARS COV-2 diagnosis are discussed herewith.

Erratum to: Transmission risk of patients with COVID-19 meeting discharge criteria should be interpreted with caution.

Erratum to: J Zhejiang Univ-Sci B (Biomed & Biotechnol) 2020 21(5):408-410. https://doi.org/10.1631/jzus.B2000117. The original version of this article unfortunately contained a mistake. For Fig. 1a in p.409, the citation of a reference, as well as the permission to reprint this picture, was missing. The correct version and the corresponding reference are given below: (a) Chest computed tomography (CT) image of Patient 1 on admission presents multiple ground-glass opacities distributed in the periphery of inferior lobe of both lungs. Reprinted from Zhang et al. (2020), with kind permission from Springer Nature.