COVID-19 Diagnostic Methods and Detection Techniques

Characterizing a visual lateral flow device for rapid SARS-CoV-2 virus protein detection: pre-clinical and system assessment

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections have affected more than 769 million individuals worldwide over the last few years. Although the pandemic is transitioning into an endemic, the COVID-19 outbreak is still a global concern. A rapid screening platform is needed for effective preventive and control measures. Herein, a visual rapid lateral flow platform for SARS-CoV-2 nucleocapsid protein detection is developed. Under optimal conditions, the system demonstrated good detection sensitivity and selectivity against tested respiratory viruses. The system provides direct visual detection with a limit of 0.7 ng of the nucleocapsid protein per mL of a sample (0.7 ng mL-1) within 15 minutes. Further, a correlation between direct visual detection and semi-quantitative analysis using a reader showed a similar detection limit (R2 = 0.9571). The repeatability and reproducibility studies highlighted the potential of the system for the rapid screening of SARS-CoV-2 infection, with variations within 5% and 10% at high and low protein concentrations, respectively. Subsequent pre-clinical validation to correlate the performance with the standard molecular approach (RT-PCR) using 170 nasopharyngeal swabs demonstrated 98% estimated sensitivity (95% CI, 89.35-99.95%) and 100% specificity (95% CI, 96.38-100%). The positive and negative predictive values were reported to be 100% and 99%, respectively, with an accuracy of 99.3%. With high viral load samples (Ct value ≤25, n = 47), the system demonstrated 100% detection sensitivity and specificity. The proposed technique provides a valuable platform for potential use in rapid screening, particularly during pandemics, where diagnostic capacity and mass screening are crucial.

Special Issue "Molecular and Genetic Aspects of SARS-CoV-2 Infection and COVID-19 Disease"

We are pleased to present the first and second editions of this Special Issue, titled "Molecular and Genetic Aspects of SARS-CoV-2 Infection and COVID-19 Disease", of the International Journal of Molecular Sciences [...].

COVID-19 Detection and Diagnosis Model on CT Scans Based on AI Techniques

The end of 2019 could be mounted in a rudimentary framing of a new medical problem, which globally introduces into the discussion a fulminant outbreak of coronavirus, consequently spreading COVID-19 that conducted long-lived and persistent repercussions. Hence, the theme proposed to be solved arises from the field of medical imaging, where a pulmonary CT-based standardized reporting system could be addressed as a solution. The core of it focuses on certain impediments such as the overworking of doctors, aiming essentially to solve a classification problem using deep learning techniques, namely, if a patient suffers from COVID-19, viral pneumonia, or is healthy from a pulmonary point of view. The methodology's approach was a meticulous one, denoting an empirical character in which the initial stage, given using data processing, performs an extraction of the lung cavity from the CT scans, which is a less explored approach, followed by data augmentation. The next step is comprehended by developing a CNN in two scenarios, one in which there is a binary classification (COVID and non-COVID patients), and the other one is represented by a three-class classification. Moreover, viral pneumonia is addressed. To obtain an efficient version, architectural changes were gradually made, involving four databases during this process. Furthermore, given the availability of pre-trained models, the transfer learning technique was employed by incorporating the linear classifier from our own convolutional network into an existing model, with the result being much more promising. The experimentation encompassed several models including MobileNetV1, ResNet50, DenseNet201, VGG16, and VGG19. Through a more in-depth analysis, using the CAM technique, MobilneNetV1 differentiated itself via the detection accuracy of possible pulmonary anomalies. Interestingly, this model stood out as not being among the most used in the literature. As a result, the following values of evaluation metrics were reached: loss (0.0751), accuracy (0.9744), precision (0.9758), recall (0.9742), AUC (0.9902), and F1 score (0.9750), from 1161 samples allocated for each of the three individual classes.

Development of a High-Throughput Mass Spectrometry-Based SARS-CoV-2 Immunoassay

The serious impact of the Covid-19 pandemic underscores the need for rapid, reliable, and high-throughput diagnosis methods for infection. Current analytical methods, either point-of-care or centralized detection, are not able to satisfy the requirements of patient-friendly testing, high demand, and reliability of results. Here, we propose a two-point separation on-demand diagnostic strategy that uses laser desorption/ionization time-of-flight mass spectrometry (LDI-TOF MS) and adopts a stable yet cleavable ionic probe as a mass reporter. The use of this reporter enables ultrasensitive, interruptible, storable, restorable, and high-throughput on-demand detection. We describe a demonstration of the concept whereby we (i) design and synthesize a laser-cleavable reporter (DTPA), (ii) conjugate the reporter onto an antibody and verify the function of the conjugate, (iii) detect with good turnaround and high sensitivity the conjugated reporter, (iv) analyze quantitatively by using a laser-cleavable internal standard, and (v) identify negative and positive samples containing the spike protein. The protocol has excellent sensitivity (amol for the SARS-CoV-2 Spike S1 subunit antibody) without any amplification. This strategy is also applicable for the detection of other disease antigens besides SARS-CoV-2.

The Suitability of RNA from Positive SARS-CoV-2 Rapid Antigen Tests for Whole Virus Genome Sequencing and Variant Identification to Maintain Genomic Surveillance

The COVID-19 pandemic has transformed laboratory management, with a surge in demand for diagnostic tests prompting the adoption of new diagnostic assays and the spread of variant surveillance tools. Rapid antigen tests (RATs) were initially used only for screening and later as suitable infection assessment tools. This study explores the feasibility of sequencing the SARS-CoV-2 genome from the residue of the nasopharyngeal swab extraction buffers of rapid antigen tests (RATs) to identify different COVID-19 lineages and sub-lineages.

METHODS

Viral RNA was extracted from the residue of the nasopharyngeal swab extraction buffers of RATs and, after a confirmation of positivity through a reaction of RT-PCR, viral genome sequencing was performed.

RESULTS

Overall, the quality of the sequences obtained from the RNA extracted from the residue of the nasopharyngeal swab extraction buffers of RATs was adequate and allowed us to identify the SARS-CoV-2 variants' circulation and distribution in a period when the use of molecular swabs had been drastically reduced.

CONCLUSIONS

This study demonstrates the potential for genomic surveillance by sequencing SARS-CoV-2 from the residue of the nasopharyngeal swab extraction buffers of RATs, highlighting alternative possibilities for tracking variants.

Impact of Cancerous Pulmonary Involvement on Outcomes in COVID-19 Patients

BACKGROUND

SARS-CoV2 is a highly contagious virus causing COVID-19 (Corona virus disease 2019), which has resulted in more than 6 million deaths worldwide as of June 2022. Mortality in COVID-19 has mainly been attributed to respiratory failure. Previous studies showed that the presence of cancer did not adversely affect the outcome of COVID-19. However, in our clinical practice, it was noted that in cancer patients with pulmonary involvement, COVID-19-related morbidity, and morbidity were high. Therefore, this study was designed to assess the impact of cancerous pulmonary involvement on COVID-19 outcomes and to compare clinical outcomes of COVID-19 in cancer and non-cancer population, with further discretion between cancers with and without pulmonary involvement.

METHODS

We performed a retrospective study from April 2020 until June 2020 with a sample size of 117 patients with a confirmed diagnosis of SARS-CoV2 on nasal swab PCR. Data was extracted from HIS (Hospital Information System). Hospitalization, supplemental oxygen, ventilatory support, and death were compared between non-cancer and cancer patients with a particular focus on pulmonary involvement.

RESULTS

Admissions, supplemental oxygen requirement, and mortality were significantly higher in cancer patients with pulmonary involvement (63.3%, 36.4%, and 45%, respectively) compared to cancer patients without pulmonary involvement (22.1%, 14.7%, and 8.8% respectively) (p-values: 0.00003, 0.003, and 0.00003 respectively). In the non-cancer group, there was no mortality, only 2% required admission, and none needed supplemental oxygen.

CONCLUSION

We conclude that the cancer patient with pulmonary involvement was significantly at higher risk of complications and death from COVID when compared with the non-pulmonary cancer group and the general population.

Visual diagnosis of COVID-19 disease based on serum metabolites using a paper-based electronic tongue

This study aims to use a paper-based sensor array for point-of-care detection of COVID-19 diseases. Various chemical compounds such as nanoparticles, organic dyes and metal ion complexes were employed as sensing elements in the array fabrication, capturing the metabolites of human serum samples. The viral infection caused the type and concentration of serum compositions to change, resulting in different color responses for the infected and control samples. For this purpose, 118 serum samples of COVID-19 patients and non-COVID controls both men and women with the age range of 14–88 years were collected. The serum samples were initially subjected to the sensor, followed by monitoring the variation in the color of sensing elements for 5 min using a scanner. By taking into consideration the statistical information, this method was capable of discriminating COVID-19 patients and control samples with 83.0% accuracy. The variation of age did not influence the colorimetric patterns. The desirable correlation was observed between the sensor responses and viral load values calculated by the PCR test, proposing a rapid and facile way to estimate the disease severity. Compared to other rapid detection methods, the developed assay is cost-effective and user-friendly, allowing for screening COVID-19 diseases reliably.

Piezoelectric point-of-care biosensor for the detection of SARS-COV-2 (COVID-19) antibodies

It is always challenging to diagnose a disease using a biosensor reliably, and quickly with high sensitivity and selectivity, simultaneosuly. Recently the world experienced a global pandemic caused by a novel coronavirus (COVID-19). Although the vaccines are available, COVID-19 resulted a huge threat to the entire world with high mortality rates. Irrespective of a specific disease, there is a constant need for a cheaper and faster in-vitro, lab-on-a-chip sensor with high sensitivity and selectivity. Such sensors will not only facilitate the disease detection but will expedite and vaccine development process through detection of its corresponding antibodies when developed. In this article, we present an ultrasonic guided wave sensor using 128° YX lithium niobate piezoelectric wafer, specially designed in a shape of a multi-threaded comb with cantilever beams which is equally selective and sensitive for the detection of corresponding antigen-antibody assays. As a proof of concept in this article, the diagnostic sensor is created and tested for detection of SARS-COV-2 antibodies. Sensors were functionalized with SARS-COV-2 antigens and target antibody for the same was detected. Unique and judicially tuned acoustic features are analyzed for successful detection of the right antibodies. The proposed lab-on-a-chip device utilizes a wide range of diagnostic frequencies resulting into a highly sensitive platform for the diagnostics even to the slightest biophysical changes. The proposed sensor is also believed to extend to the detection of various other antigens/antibodies of different diseases in the future.

Comparative Evaluation of Six SARS-CoV-2 Real-Time RT-PCR Diagnostic Approaches Shows Substantial Genomic Variant–Dependent Intra- and Inter-Test Variability, Poor Interchangeability of Cycle Threshold and Complementary Turn-Around Times

Several professional societies advise against using real-time Reverse-Transcription PCR (rtRT-PCR) cycle threshold (Ct) values to guide clinical decisions. We comparatively assessed the variability of Ct values generated by six diagnostic approaches by testing serial dilutions of well-characterized isolates of 10 clinically most relevant SARS-CoV-2 genomic variants: Alpha, Beta, Gamma, Delta, Eta, Iota, Omicron, A.27, B.1.258.17, and B.1 with D614G mutation. Comparison of three fully automated rtRT-PCR analyzers and a reference manual rtRT-PCR assay using RNA isolated with three different nucleic acid isolation instruments showed substantial inter-variant intra-test and intra-variant inter-test variability. Ct value differences were dependent on both the rtRT-PCR platform and SARS-CoV-2 genomic variant. Differences ranging from 2.0 to 8.4 Ct values were observed when testing equal concentrations of different SARS-CoV-2 variants. Results confirm that Ct values are an unreliable surrogate for viral load and should not be used as a proxy of infectivity and transmissibility, especially when different rtRT-PCR assays are used in parallel and multiple SARS-CoV-2 variants are circulating. A detailed turn-around time (TAT) comparative assessment showed substantially different TATs, but parallel use of different diagnostic approaches was beneficial and complementary, allowing release of results for more than 81% of non-priority samples within 8 h after admission.

Recent review of COVID-19 management: diagnosis, treatment and vaccination

The idiopathic Coronavirus disease 2019 (COVID-19) pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached global proportions; the World Health Organization (WHO) declared it as a public health emergency during the month of January 30, 2020. The major causes of the rise of new variants of SARS-CoV-2 are genetic mutations and recombination. Some of the variants with high infection and transmission rates are termed as variants of concern (VOCs) like currently Omicron variants. Pregnant women, aged people, and immunosuppressed and compromised patients constitute the most susceptible human population to the SARS-CoV-2 infection, especially to the new evolving VOCs. To effectively manage the pathological condition of infection, the focus should be directed towards prevention and prophylactic approach. In this narrative review, we aimed to analyze the current scenario of COVID-19 management and discuss the treatment and prevention strategies. We also focused on the complications prevalent during the COVID-19 and post-COVID period and to discuss the novel approaches developed for mitigation of the global pandemic. We have also emphasized on the COVID-19 management approaches for the special population including children, pregnant women, aged groups, and immunocompromised patients. We conclude that the advancements in therapeutic and pharmacological domains have provided opportunities to develop and design novel diagnosis, treatment, and prevention strategies. New advanced techniques such as RT-LAMP, RT-qPCR, High-Resolution Computed Tomography, etc., efficiently diagnose patients with SARS-CoV-2 infection. In the case of treatment options, new drugs like paxlovid, combinations of β-lactum drugs and molnupiravir are found to be effective against even the new emerging variants. In addition, vaccination is an essential approach to prevent the infection or to reduce its severity. Vaccines for against COVID-19 from Comirnaty by Pfizer-BioNTech, SpikeVax by Moderna, and Vaxzevria by Oxford-AstraZeneca are approved and used widely. Similarly, numerous vaccines have been developed with different percentages of effectiveness against VOCs. New developments like nanotechnology and AI can be beneficial in providing an efficient and reliable solution for the suppression of SARS-CoV-2. Public health concerns can be efficiently treated by a unified scientific approach, public engagement, and better diagnosis.