Recent advances and challenges of RT-PCR tests for the diagnosis of COVID-19

CRISPR-Cas based diagnostic tools: Bringing diagnosis out of labs

Timely detection is important for the effective management of infectious diseases. Reverse Transcription Polymerase Chain Reaction (RT-PCR) stands as the prime nucleic acid based test that is employed for the detection of infectious diseases. The method ensures sensitivity and specificity. However, RT-PCR is a relatively expensive technique due to the requirement of costly equipment and reagents. Further, it requires skilled personnel and established laboratories that are usually inaccessible in underdeveloped areas. On the other hand, rapid antigen based techniques are cost effective and easily accessible, but are less effective in terms of sensitivity and specificity. CRISPR-Cas systems are advanced diagnostic tools that combine the advantages of both PCR and antigen based detection techniques, and allows the rapid detection with high sensitivity/specificity. The present review aims to discuss the applicability of CRISPR-Cas based diagnostic tools for the infectious disease detection. The review further attempts to highlight the current limitations and future research directions to improve the CRISPR based diagnostic tools for rapid and effective disease detection.

A novel ACE2-Based electrochemical biosensor for sensitive detection of SARS-CoV-2

SARS-CoV-2 emerged in late 2019 and quickly spread globally, resulting in significant morbidity, mortality, and socio-economic disruptions. As of now, collaborative global efforts in vaccination and the advent of novel diagnostic tools have considerably curbed the spread and impact of the virus in many regions. Despite this progress, the demand remains for low-cost, accurate, rapid and scalable diagnostic tools to reduce the influence of SARS-CoV-2. Herein, the angiotensin-converting enzyme 2 (ACE2), a receptor for SARS-CoV-2, was immobilized on two types of electrodes, a screen-printed gold electrode (SPGE) and a screen-printed carbon electrode (SPCE), to develop electrochemical biosensors for detecting SARS-CoV-2 with high sensitivity and selectivity. This was achieved by using 1H, 1H, 2H, 2H-perfluorodecanethiol (PFDT) and aryl diazonium salt serving as linkers for SPGEs and SPCEs, respectively. Once SARS-CoV-2 was anchored onto the ACE2, the interaction of the virus with the redox probe was analyzed using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Aryl diazonium salt was observed as a superior linker compared to PFDT due to its consistent performance in the modification of the SPCEs and effective ACE2 enzyme immobilization. A distinct pair of redox peaks in the cyclic voltammogram of the biosensor modified with aryl diazonium salt highlighted the redox reaction between the functional groups of SARS-CoV-2 and the redox probe. The sensor presented a linear relationship between the redox response and the logarithm of SARS-CoV-2 concentration, with a detection limit of 1.02 × 106 TCID50/mL (50% tissue culture infectious dose). Furthermore, the biosensor showed remarkable selectivity towards SARS-CoV-2 over H1N1virus.

Effectiveness of a standardized quality control management procedure for COVID-19 RT-PCR testing: a large-scale diagnostic accuracy study in China

BACKGROUND

The study aimed to construct a standardized quality control management procedure (QCMP) and access its accuracy in the quality control of COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR).

METHODS

Considering the initial RT-PCR results without applying QCMP as the gold standard, a large-scale diagnostic accuracy study including 4,385,925 participants at three COVID-19 RT-PCR testing sites in China, Foshan (as a pilot test), Guangzhou and Shenyang (as validation sites), was conducted from May 21, 2021, to December 15, 2022.

RESULTS

In the pilot test, the RT-PCR with QCMP had a high accuracy of 99.18% with 100% specificity, 100% positive predictive value (PPV), and 99.17% negative predictive value (NPV). The rate of retesting was reduced from 1.98% to 1.16%. Its accuracy was then consistently validated in Guangzhou and Shenyang.

CONCLUSIONS

The RT-PCR with QCMP showed excellent accuracy in identifying true negative COVID-19 and relieved the labor and time spent on retesting.

Molecular Interactions Leading to Advancements in the Techniques for COVID-19 Detection: A Review

Since 2019 the world has been in a combat with the highly contagious disease COVID-19 which is caused by the rapid transmission of the SARS-CoV-2 virus (severe acute respiratory syndrome coronavirus 2). Detection of this disease in an early stage helps to control its spread and management. To combat this epidemic with one-time effective medication, improved quick analytical procedures must be developed and validated. The requirement for accurate and precise analytical methods for the diagnosis of the virus and antibodies in infected patients has been a matter of concern. The global impact of this virus has motivated scientists and researchers to investigate and develop various analytical diagnostic techniques. This review includes the study of standard methods which are reliable and accredited for the analytical recognition of the said virus. For early detection of SARS-CoV-2 RNA, RT-PCR (Real-time reverse transcriptase-polymerase chain reaction) is an accurate method among other methods and, thus, considered as the "gold standard" technique. Here, we outline the most extensively used analytical methods for diagnosing COVID-19, along with a brief description of each technique and its analytical aspects/perspective.

Investigation of IL-6 serum level in COVID-19 patients with positive COVID-19 IgG/IgM antibody titers to check inflammation and disease progression

OBJECTIVE

The SARS-CoV-2, the cause of coronavirus disease 2019 (COVID-19), leads to severe pathogenicity and high mortality among different communities around the world. Therefore, it is important to understand the mechanisms of virus pathogenesis and the immune system's response to prevent the further spread of this virus. This study was aimed to evaluate the relationship between the serum level of interleukin 6 and positive IgG and IgM antibody levels in patients with COVID-19 to investigate inflammation and disease progression.

METHODS & MATERIALS

In this study, 10 ml of EDTA blood samples were taken from 414 COVID-19 patients. Then, the plasma was separated and the levels of IgM and IgG antibodies and interleukin 6 cytokine were evaluated by ELISA and chemiluminescence methods, respectively. All data were analyzed by SPSS 22 and GraphPad prism 9 software at the significance level of P < 0.05.

RESULTS

The results of this study showed that there was no significant difference in the expression of IgM and IgG antibodies between men and women. Also, a significant increase in the mean expression of IL-6 was observed only in the high concentration range (100-〉1000 pg/ml) in men compared to women (P < 0.001). In addition, in the female population, all three concentration ranges (negative, medium, and high) of IL-6 have the highest correlation with high titers (>10 U/ml) of IgM and IgG antibodies. While, in men, all three concentration ranges of IL-6 had the highest correlation with > 10 U/ml IgM antibody titers, but in the case of IgG, the highest correlation between different concentrations of IL-6 was observed with the negative or moderate titers of this antibody and there was an inverse relationship with the high titers of IgG (>10 U/ml).

CONCLUSION

As a result, the relationship between different serum levels of cytokine IL-6 with different titers of IgM and IgG antibodies was observed in both male and female populations. In general, it can be concluded that the correlation between different concentrations of IL-6 with different IgM titers was similar in both men and women, but in the case of different IgG titers, this correlation was higher in women than men.

From Detection to Protection: Antibodies and Their Crucial Role in Diagnosing and Combatting SARS-CoV-2

Understanding the antibody response to SARS-CoV-2, the virus responsible for COVID-19, is crucial to comprehending disease progression and the significance of vaccine and therapeutic development. The emergence of highly contagious variants poses a significant challenge to humoral immunity, underscoring the necessity of grasping the intricacies of specific antibodies. This review emphasizes the pivotal role of antibodies in shaping immune responses and their implications for diagnosing, preventing, and treating SARS-CoV-2 infection. It delves into the kinetics and characteristics of the antibody response to SARS-CoV-2 and explores current antibody-based diagnostics, discussing their strengths, clinical utility, and limitations. Furthermore, we underscore the therapeutic potential of SARS-CoV-2-specific antibodies, discussing various antibody-based therapies such as monoclonal antibodies, polyclonal antibodies, anti-cytokines, convalescent plasma, and hyperimmunoglobulin-based therapies. Moreover, we offer insights into antibody responses to SARS-CoV-2 vaccines, emphasizing the significance of neutralizing antibodies in order to confer immunity to SARS-CoV-2, along with emerging variants of concern (VOCs) and circulating Omicron subvariants. We also highlight challenges in the field, such as the risks of antibody-dependent enhancement (ADE) for SARS-CoV-2 antibodies, and shed light on the challenges associated with the original antigenic sin (OAS) effect and long COVID. Overall, this review intends to provide valuable insights, which are crucial to advancing sensitive diagnostic tools, identifying efficient antibody-based therapeutics, and developing effective vaccines to combat the evolving threat of SARS-CoV-2 variants on a global scale.

Potential of a Bead-Based Multiplex Assay for SARS-CoV-2 Antibody Detection

Serological assays for SARS-CoV-2 play a pivotal role in the definition of whether patients are infected, the understanding of viral epidemiology, the screening of convalescent sera for therapeutic and prophylactic purposes, and in obtaining a better understanding of the immune response towards the virus. The aim of this study was to investigate the performance of a bead-based multiplex assay. This assay allowed for the simultaneous testing of IgG antibodies against SARS-CoV-2 spike, S1, S2, RBD, and nucleocapsid moieties and S1 of seasonal coronaviruses hCoV-22E, hCoV-HKU1, hCoV-NL63, and hCoV-OC43, as well as MERS and SARS-CoV. We compared the bead-based multiplex assay with commercial ELISA tests. We tested the sera of 27 SARS-CoV-2 PCR-positive individuals who were previously tested with different ELISA assays. Additionally, we investigated the reproducibility of the results by means of multiple testing of the same sera. Finally, the results were correlated with neutralising assays. In summary, the concordance of the qualitative results ranged between 78% and 96% depending on the ELISA assay and the specific antigen. Repeated freezing-thawing cycles resulted in reduced mean fluorescence intensity, while the storage period had no influence in this respect. In our test cohort, we detected up to 36% of sera positive for the development of neutralising antibodies, which is in concordance with the bead-based multiplex and IgG ELISA.

Using SCENTinel® to predict SARS-CoV-2 infection: insights from a community sample during dominance of Delta and Omicron variants

Introduction

Based on a large body of previous research suggesting that smell loss was a predictor of COVID-19, we investigated the ability of SCENTinel®, a newly validated rapid olfactory test that assesses odor detection, intensity, and identification, to predict SARS-CoV-2 infection in a community sample.

Methods

Between April 5, 2021, and July 5, 2022, 1,979 individuals took one SCENTinel® test, completed at least one physician-ordered SARS-CoV-2 PCR test, and endorsed a list of self-reported symptoms.

Results

Among the of SCENTinel® subtests, the self-rated odor intensity score, especially when dichotomized using a previously established threshold, was the strongest predictor of SARS-CoV-2 infection. SCENTinel® had high specificity and negative predictive value, indicating that those who passed SCENTinel® likely did not have a SARS-CoV-2 infection. Predictability of the SCENTinel® performance was stronger when the SARS-CoV-2 Delta variant was dominant rather than when the SARS-CoV-2 Omicron variant was dominant. Additionally, SCENTinel® predicted SARS-CoV-2 positivity better than using a self-reported symptom checklist alone.

Discussion

These results indicate that SCENTinel® is a rapid assessment tool that can be used for population-level screening to monitor abrupt changes in olfactory function, and to evaluate spread of viral infections like SARS-CoV-2 that often have smell loss as a symptom.

Cost-effective in-house COVID-19 reverse transcription-polymerase chain reaction testing with yeast-derived Taq polymerase

BACKGROUND

Despite the decline of the COVID-19 pandemic, there continues to be a persistent requirement for reliable testing methods that can be adapted to future outbreaks and areas with limited resources. While the standard approach of using reverse transcription-polymerase chain reaction (RT-PCR) with Taq polymerase is effective, it faces challenges such as limited access to high-quality enzymes and the presence of bacterial DNA contamination in commercial kits, which can impact the accuracy of test results.

METHODS

This study investigates the production of recombinant Taq polymerase in yeast cells and assesses its crude lysate in a multiplex RT-PCR assay for detecting the SARS-CoV-2 RNA-dependent RNA polymerase (RdRP) and N genes, with human Ribonuclease P serving as an internal control.

RESULTS

The unpurified yeast Taq polymerase demonstrates sensitivity comparable to commercially purified bacterial Taq polymerase and unpurified bacterial counterparts in detecting the RdRP and N genes. It exhibits the highest specificity, with 100% accuracy, for the N gene. The specificity for the RdRP gene closely aligns with that of commercially purified bacterial Taq polymerase and unpurified bacterial Taq polymerase.

CONCLUSIONS

The use of unpurified recombinant yeast Taq polymerase shows promise as a cost-effective approach for conducting in-house COVID-19 RT-PCR testing. By eliminating the need for chromatography purification steps, the production of RT-PCR kits can be streamlined, potentially improving accessibility and scalability, especially in resource-limited settings and future pandemics.

Development and Optimization of a Multiplex Real-Time RT-PCR to Detect SARS-CoV-2 in Human Samples

PCR and its variants (RT-PCR and qRT-PCR) are valuable and innovative molecular techniques for studying nucleic acids. qPCR has proven to be highly sensitive, efficient, and reproducible, generating reliable results that are easy to analyze. During the COVID-19 pandemic, qPCR became the gold standard technique for detecting the SARS-CoV-2 virus that allowed to confirm the infection event, and those asymptomatic ones, and thus save millions of lives. In-house multiplex qPCR tests were developed worldwide to detect different viral targets and ensure results, follow the infections, and favor the containment of a pandemic. Here, we present the detailed fundamentals of the qPCR technique based on fluorogenic probes and processes to develop and optimize a successful multiplex RT-qPCR test for detecting SARS-CoV-2 that could be used to diagnose COVID-19 accurately.

CODENET: A deep learning model for COVID-19 detection

Conventional COVID-19 testing methods have some flaws: they are expensive and time-consuming. Chest X-ray (CXR) diagnostic approaches can alleviate these flaws to some extent. However, there is no accurate and practical automatic diagnostic framework with good interpretability. The application of artificial intelligence (AI) technology to medical radiography can help to accurately detect the disease, reduce the burden on healthcare organizations, and provide good interpretability. Therefore, this study proposes a new deep neural network (CNN) based on CXR for COVID-19 diagnosis - CodeNet. This method uses contrastive learning to make full use of latent image data to enhance the model's ability to extract features and generalize across different data domains. On the evaluation dataset, the proposed method achieves an accuracy as high as 94.20%, outperforming several other existing methods used for comparison. Ablation studies validate the efficacy of the proposed method, while interpretability analysis shows that the method can effectively guide clinical professionals. This work demonstrates the superior detection performance of a CNN using contrastive learning techniques on CXR images, paving the way for computer vision and artificial intelligence technologies to leverage massive medical data for disease diagnosis.

Evaluation of diagnostic performance of SARS-CoV-2 infection using digital droplet polymerase chain reaction in individuals with or without COVID-19 symptoms

BACKGROUND

Reverse transcription-quantitative PCR (RT-qPCR) is commonly used to diagnose SARS-CoV-2, but it has limited sensitivity in detecting the virus in asymptomatic close contacts and convalescent patients. In this study, we propose the use of reverse transcription-digital droplet PCR (RT-ddPCR) to detect SARS-CoV-2 in clinical samples.

METHODS

The clinical performance of RT-ddPCR targeting of ORF1ab and N genes was evaluated in parallel with RT-qPCR using 200 respiratory samples collected from close contacts and patients at different phases of infection.

RESULTS

The limits of detection (LODs) for RT-ddPCR assays were determined using six dilutions of ACCUPLEX SARS-Cov-2 reference material. The LODs of ORF1ab and N genes were 3.7 copies/reaction and 2.2 copies/reaction, respectively. Compared to RT-qPCR, RT-ddPCR increased the positive rate by 12.0% in 142 samples from SARS-CoV-2-infected patients. Additionally, RT-ddPCR detected SARS-CoV-2 in three of 26 specimens from close contacts that tested negative by RT-qPCR, and infection was confirmed using follow-up samples. Finally, RT-ddPCR improved the equivocal results from RT-qPCR in 56.3% (9/16) of convalescent patient samples.

CONCLUSIONS

Detecting SARS-CoV-2 in samples with low viral loads using RT-qPCR can be challenging. However, our study suggests that RT-ddPCR, with its higher sensitivity and accuracy, is better suited for detecting low viral copies in samples, particularly those from close contacts and convalescent patients.

Associated Factors and Outcomes of Acute Kidney Injury in COVID-19 Patients in Kenya

Background

Corona Virus Disease 2019 (COVID-19), an infection caused by the SARS-CoV-2 virus, has been the largest global pandemic since the turn of the 21st century. With emerging research on this novel virus, studies from the African continent have been few. Corona Virus Disease 2019 has been shown to affect various organs including the lungs, gut, nervous system, and the kidneys. Acute kidney injury (AKI) is an independent risk factor for mortality and increases the health care burden for patients with persistent kidney dysfunction and maintenance dialysis. Sub-Saharan Africa has a high number of poorly controlled chronic illnesses, economic inequalities, and health system strains that may contribute to higher cases of kidney injury in patients with COVID-19 disease.

Objectives

The objective of this study was to determine the incidence, associated factors, and outcomes of AKI in patients hospitalized with COVID-19 in Kenya.

Methods

This retrospective cohort study included 1366 patients with confirmed COVID-19 illness hospitalized at the Aga Khan University Hospital in Nairobi, Kenya, between April 1, 2020 and October 31, 2021. Data were collected on age, sex, the severity of COVID-19 illness, existing pregnancy and comorbid conditions including human immunodeficiency virus (HIV), diabetes mellitus, hypertension, and functioning kidney transplant patients. Univariate analysis was carried out to determine the association of clinical and demographic factors with AKI. To determine independent associations with AKI incidence, a logistic regression model was used and the relationship was reported as odds ratios (ORs) with a 95% confidence interval (CI). The outcomes of AKI including the in-hospital mortality rate, renal recovery rate at hospital discharge, and the duration of hospital stay were reported and stratified based on the stage of AKI.

Results

The median age of study patients was 56 years (interquartile range [IQR] = 45-68 years), with 67% of them being male (914 of 1366). The AKI incidence rate was 21.6% (n = 295). Patients with AKI were older (median age = 64 years vs 54 years; P < .001), majority male (79% of men with AKI vs 63.6% without AKI; P < .001), and likely to have a critical COVID-19 (OR = 8.03, 95% CI = 5.56-11.60; P < .001). Diabetes and hypertension, with an adjusted OR of 1.75 (95% CI = 1.34-2.30; P < .001) and 1.68 (95% CI = 1.27-2.23; P < .001), respectively, were associated with AKI occurrence in COVID-19. Human immunodeficiency virus, pregnancy, and a history of renal transplant were not significantly associated with increased AKI risk in this study. Patients with AKI had significantly higher odds of mortality, and this effect was proportional to the stage of AKI (OR = 11.35, 95% CI = 7.56-17.03; P < .001). 95% of patients with stage 1 AKI had complete renal recovery vs 33% of patients with stage 3 AKI. Of the patients with stage 3 AKI (n = 64), 10 underwent hemodialysis, with 1 recovery in renal function and 3 patients requiring ongoing dialysis after discharge.

Conclusions

This study was conducted at a single private tertiary-level health care facility in Kenya and only up to the time of hospital discharge. It is one of the first large studies from sub-Saharan Africa looking at the associated factors and outcomes of AKI in COVID-19 and forms a foundation for further analysis on the long-term consequences of COVID-19 on the kidneys. A major limitation of the study is the lack of baseline pre-admission creatinine values for most patients; thus, the impact of chronic kidney disease/baseline creatinine values on the incidence of AKI could not be established.

Label-Free and Colorimetric Detection of Influenza A Virus via Receptor-Mediated Viral Fusion with Plasmonic Vesicles

The rapid transmission and numerous re-emerging human influenza virus variants that spread via the respiratory system have led to severe global damage, emphasizing the need for detection tools that can recognize active and intact virions with infectivity. Here, this work presents a plasmonic vesicle-mediated fusogenic immunoassay (PVFIA) comprising gold nanoparticle (GNP) encapsulating fusogenic polymeric vesicles (plasmonic vesicles; PVs) for the label-free and colorimetric detection of influenza A virus (IAV). The PVFIA combines two sequential assays: a biochip-based immunoassay for target-specific capture and a PV-induced fusion assay for color change upon the IAV-PV fusion complex formation. The PVFIA demonstrates excellent specificity in capturing the target IAV, while the fusion conditions and GNP induce a significant color change, enabling visual detection. The integration of two consecutive assays results in a low detection limit (100.7919 EID50 mL-1 ) and good reliability (0.9901), indicating sensitivity that is 104.208 times higher than conventional immunoassay. Leveraging the PV viral membrane fusion activity renders the PVFIA promising for point-of-care diagnostics through colorimetric detection. The innovative approach addresses the critical need for detecting active and intact virions with infectivity, providing a valuable tool with which to combat the spread of the virus.

Photodynamic Inactivation of Bovine Coronavirus with the Photosensitizer Toluidine Blue O

Coronaviruses (CoVs) belong to the group of enveloped positive-sense single-strand RNA viruses and are causative agents of respiratory, gastro-intestinal, and central nervous systems diseases in many host species, i.e., birds, mammals, and humans. Beta-CoVs revealed a great potential to cross the barrier between species by causing three epidemics/pandemics among humans in the 21st century. Considering the urgent need for powerful antiviral agents for decontamination, prevention, and treatment of BCoV infections, we turned our attention to the possibility of photodynamic inactivation with photosensitizers in combination with light irradiation. In the present study, we evaluated, for the first time, the antiviral activity of toluidine blue O (TBO) against Beta-coronavirus 1 (BCoV) in comparison to methylene blue (MB). First, we determined the in vitro cytotoxicity of MB and TBO on the Madin-Darby bovine kidney (MDBK) cell line with ISO10993-5/Annex C. Thereafter, BCoV was propagated in MDBK cells, and the virus titer was measured with digital droplet PCR, TCID50 assay and plaque assay. The antiviral activity of non-toxic concentrations of TBO was estimated using the direct inactivation approach. All effects were calculated in MAPLE 15® mathematical software by developing programs for non-linear modeling and response surface analysis. The median inhibitory concentration (IC50) of TBO after 72 h of incubation in MDBK cells was 0.85 µM. The antiviral activity of TBO after the direct inactivation of BCoV (MOI = 1) was significantly stronger than that of MB. The median effective concentration (EC50) of TBO was 0.005 µM. The cytopathic effect decreased in a concentration-dependent manner, from 0.0025 to 0.01 µM, and disappeared fully at concentrations between 0.02 and 0.3 µM of TBO. The number of virus particles also decreased, depending on the concentration applied, as proven by ddPCR analysis. In conclusion, TBO exhibits significant potential for direct inactivation of BCoV in vitro, with a very high selectivity index, and should be subjected to further investigation, aiming at its application in veterinary and/or human medical practice.

Characteristics of hematological parameters on admission in COVID-19 Omicron variant infected in Chinese population: a large-scale retrospective study

BACKGROUND

The Omicron variant of SARS-CoV-2, currently the most prevalent strain, has rapidly spread in Jingzhou, China, due to changes in the country's epidemic prevention policy, resulting in an unprecedented increase in cases. Previous studies reported hematological parameters' predictive value in COVID-19 severity and prognosis, but their relevance for early diagnosis in patients infected by the Omicron variant, particularly in high-risk pneumonia cases, remains unclear. Our study aimed to evaluate these parameters as early warning indicators for Omicron-infected patients in fever clinics and those with pulmonary infections (PI).

METHODS

A total of 2,021 COVID-19 patients admitted to the fever clinic and infectious disease department of Jingzhou Hospital Affiliated to Yangtze University from November 1, 2022, to December 31, 2022, were retrospectively recruited. Demographic and hematological parameters were obtained from the electronic medical records of eligible patients. These hematological parameters were analyzed by receiver operating characteristic (ROC) curves to determine whether they can be used for early diagnosis of COVID-19 patients in fever clinics and the presence of PI in COVID-19 patients.

RESULTS

Statistical differences in hematological parameters were observed between COVID-19 patients with fever and PI and control groups (P < 0.01). The ROC curve further demonstrated that lymphocyte (LYM) counts, neutrophil (NEU) counts, monocyte-to-lymphocyte ratios (MLR), platelet-to-lymphocyte ratios (PLR), white blood cell counts (WBC), and mean corpuscular hemoglobin concentration (MCHC) were the top 6 indicators in diagnosing Omicron infection with fever, with area under the curve (AUC) values of 0.738, 0.718, 0.713, 0.702, 0.700, and 0.687, respectively (P < 0.01). Furthermore, the mean platelet volume (MPV) with an AUC of 0.764, red blood cell count (RBC) with 0.753, hematocrit (HCT) with 0.698, MLR with 0.694, mean corpuscular hemoglobin (MCH) with 0.676, and systemic inflammation response indexes (SIRI) with 0.673 were the top 6 indicators for the diagnosis of COVID-19 patients with PI (P < 0.01).

CONCLUSIONS

LYM, NEU, MLR, PLR, WBC, and MCHC can serve as potential prescreening indicators for Omicron infection in fever clinics. Additionally, MPV, RBC, HCT, MLR, MCH, and SIRI can predict the presence of PI in COVID-19 patients infected by the Omicron variant.

Interrater Reliability of the Spanish (Colombia) Version of the Post-COVID-19 Functional Status Scale

Background

COVID-19 has been one of the most critical public health challenges of recent decades. This disease develops severely in one in five patients, and approximately 5% require admission to a critical care unit. Due to the impact of the sequelae, the Post-COVID-19 Functional Status Scale (PCFS) was developed. This study is aimed at determining the interrater reliability of the Spanish (Colombia) version of the PCFS in adult patients with post-COVID-19 infection.

Methods

This is an observational study performed with patients diagnosed with COVID-19. Two evaluators repeated the test-retest of the PCFS scale with knowledge and clinical experience in the care of patients with COVID-19 and had previously applied the test. The PCFS assesses functional limitations at discharge and can be used at 4 and 8 weeks to evaluate practical consequences and determine the degree of disability these patients may have. For interrater reliability, Cronbach's alpha was applied with its respective confidence interval and the Bland-Altman method. A 95% confidence interval (CI) was taken as the basis for the interpretation of the Intraclass Correlation Coefficient (ICC).

Results

A total of 112 adult patients participated in the study, aged 51.46 ± 15.94 years. It was evidenced that the survival, constant care, and activities of daily living questions have an ICC of one (1.000) with an ICC (1.000-1.000), demonstrating excellent reliability, while those close to one were instrumental activities, role participation, symptoms, and final score with an ICC 0.918 to 0.984 and an ICC (0.881-0.989). Thus, a homogeneous distribution of the interrater data was evident.

Conclusions

Excellent interobserver reliability of the Spanish (Colombia) version of the PCFS in patients with different degrees of functional status was reported.

Rapid and sensitive one-tube detection of mpox virus using RPA-coupled CRISPR-Cas12 assay

Mpox is caused by a zoonotic virus belonging to the Orthopoxvirus genus and the Poxviridae family. In this study, we develop a recombinase polymerase amplification (RPA)-coupled CRISPR-Cas12a detection assay for the mpox virus. We design and test a series of CRISPR-derived RNAs(crRNAs) targeting the conserved D6R and E9L genes for orthopoxvirus and the unique N3R and N4R genes for mpox viruses. D6R crRNA-1 exhibits the most robust activity in detecting orthopoxviruses, and N4R crRNA-2 is able to distinguish the mpox virus from other orthopoxviruses. The Cas12a/crRNA assay alone presents a detection limit of 108 copies of viral DNA, whereas coupling RPA increases the detection limit to 1-10 copies. The one-tube RPA-Cas12a assay can, therefore, detect viral DNA as low as 1 copy within 30 min and holds the promise of providing point-of-care detection for mpox viral infection.

CRISPR-Based Precision Molecular Diagnostics for Disease Detection and Surveillance

Sensitive, rapid, and portable molecular diagnostics is the future of disease surveillance, containment, and therapy. The recent SARS-CoV-2 pandemic has reminded us of the vulnerability of lives from ever-evolving pathogens. At the same time, it has provided opportunities to bridge the gap by translating basic molecular biology into therapeutic tools. One such molecular biology technique is CRISPR (clustered regularly interspaced short palindromic repeat) which has revolutionized the field of molecular diagnostics at the need of the hour. The use of CRISPR-Cas systems has been widespread in biology research due to the ease of performing genetic manipulations. In 2012, CRISPR-Cas systems were, for the first time, shown to be reprogrammable, i.e., capable of performing sequence-specific gene editing. This discovery catapulted the field of CRISPR-Cas research and opened many unexplored avenues in the field of gene editing, from basic research to therapeutics. One such field that benefitted greatly from this discovery was molecular diagnostics, as using CRISPR-Cas technologies enabled existing diagnostic methods to become more sensitive, accurate, and portable, a necessity in disease control. This Review aims to capture some of the trajectories and advances made in this arena and provides a comprehensive understanding of the methods and their potential use as point-of-care diagnostics.

Emergent Molecular Techniques Applied to the Detection of Porcine Viruses

Molecular diagnostic tests have evolved very rapidly in the field of human health, especially with the arrival of the recent pandemic caused by the SARS-CoV-2 virus. However, the animal sector is constantly neglected, even though accurate detection by molecular tools could represent economic advantages by preventing the spread of viruses. In this regard, the swine industry is of great interest. The main viruses that affect the swine industry are described in this review, including African swine fever virus (ASFV), porcine reproductive and respiratory syndrome virus (PRRSV), porcine epidemic diarrhea virus (PEDV), and porcine circovirus (PCV), which have been effectively detected by different molecular tools in recent times. Here, we describe the rationale of molecular techniques such as multiplex PCR, isothermal methods (LAMP, NASBA, RPA, and PSR) and novel methods such as CRISPR-Cas and microfluidics platforms. Successful molecular diagnostic developments are presented by highlighting their most important findings. Finally, we describe the barriers that hinder the large-scale development of affordable, accessible, rapid, and easy-to-use molecular diagnostic tests. The evolution of diagnostic techniques is critical to prevent the spread of viruses and the development of viral reservoirs in the swine industry that impact the possible development of future pandemics and the world economy.

FP-CNN: Fuzzy pooling-based convolutional neural network for lung ultrasound image classification with explainable AI

The COVID-19 pandemic wreaks havoc on healthcare systems all across the world. In pandemic scenarios like COVID-19, the applicability of diagnostic modalities is crucial in medical diagnosis, where non-invasive ultrasound imaging has the potential to be a useful biomarker. This research develops a computer-assisted intelligent methodology for ultrasound lung image classification by utilizing a fuzzy pooling-based convolutional neural network FP-CNN with underlying evidence of particular decisions. The fuzzy-pooling method finds better representative features for ultrasound image classification. The FPCNN model categorizes ultrasound images into one of three classes: covid, disease-free (normal), and pneumonia. Explanations of diagnostic decisions are crucial to ensure the fairness of an intelligent system. This research has used Shapley Additive Explanation (SHAP) to explain the prediction of the FP-CNN models. The prediction of the black-box model is illustrated using the SHAP explanation of the intermediate layers of the black-box model. To determine the most effective model, we have tested different state-of-the-art convolutional neural network architectures with various training strategies, including fine-tuned models, single-layer fuzzy pooling models, and fuzzy pooling at all pooling layers. Among different architectures, the Xception model with all pooling layers having fuzzy pooling achieves the best classification results of 97.2% accuracy. We hope our proposed method will be helpful for the clinical diagnosis of covid-19 from lung ultrasound (LUS) images.

Diagnostic Performance Between Chest CT Severity Score and Initial Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Cycle Values in COVID-19 Patients and Their Relation With the Clinical Status of Patients

INTRODUCTION

Reverse transcription-polymerase chain reaction (RT-PCR) is used as a standard test for the diagnosis of SARS-CoV-2 viral RNA from nasopharyngeal aspirates. However, this method lacks sensitivity and cannot assess disease severity. A CT scan of the thorax provides a CT severity score (CT-SS), which depicts lung involvement and disease severity. This study aims to investigate the diagnostic value of chest CT compared with RT-PCR cycle threshold (Ct) values in COVID-19 and relate it clinically with the disease severity of patients.

METHODS

This retrospective observational study was conducted in a tertiary center from April 2021 to March 2022. We included 511 patients who had tested RT-PCR positive for COVID-19, were hospitalized, and had undergone high-resolution CT (HRCT) thorax. Data was collected from patient records regarding name, age, sex, admission data, baseline investigations including Ct value, management, and outcome. HRCT was reviewed to assess lung involvement and calculate CT-SS. Data was analyzed using SPSS Statistics version 25 (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.).

RESULT

The mean age of patients was 50.4 ± 13.7 years, and the majority (67.5%) were male. Gender-wise, there was no difference in RT-PCR cycle threshold (Ct) values; however, CT-SS was significantly higher in males (17.5 ± 4.8 vs.10.5 ± 6.6, t=-13.6, p<0.0001). ICU admission was needed for 34.8% of patients, and they had a significantly lower Ct value (21.7 ± 3.3 vs. 22.8 ± 3.7, t=21.10, p<0.0001) and higher CT-SS (16.3 ± 4.5 vs. 6.7 ± 5.1, t=-3.32, p=0.001).

CONCLUSION

Ct values could not differentiate between moderate and severe patients. CT-SS was not related to the viral load at admission. Patients who succumbed had significantly lower Ct values and higher CT-SS.

Streamlined Specimen Purification for Rapid COVID-19 Diagnosis Using Positively Charged Polymer Thin Film-Coated Surfaces and Chamber Digital PCR

The ongoing coronavirus disease 2019 (COVID-19) pandemic demands rapid and straightforward diagnostic tools to prevent early-stage viral transmission. Although nasopharyngeal swabs are a widely used patient sample collection method for diagnosing COVID-19, using these samples for diagnosis without RNA extraction increases the risk of obtaining false-positive and -negative results. Thus, multiple purification steps are necessary, which are time-consuming, generate significant waste, and result in substantial sample loss. To address these issues, we developed surface-modified polymerase chain reaction (PCR) tubes using the tertiary aminated polymer poly(2-dimethylaminomethylstyrene) (pDMAMS) via initiated chemical vapor deposition. Introducing the clinical samples into the pDMAMS-coated tubes resulted in approximately 100% RNA capture efficiency within 25 min, which occurred through electrostatic interactions between the positively charged pDMAMS surface and the negatively charged RNA. The captured RNA is then detected via chamber digital PCR, enabling a sensitive, accurate, and rapid diagnosis. Our platform provides a simple and efficient RNA extraction and detection strategy that allows detection from 22 nasopharyngeal swabs and 21 saliva specimens with 0% false negatives. The proposed method can facilitate the diagnosis of COVID-19 and contribute to the prevention of early-stage transmission.

Development and Analytical Evaluation of a Point-of-Care Electrochemical Biosensor for Rapid and Accurate SARS-CoV-2 Detection

The COVID-19 pandemic has underscored the critical need for rapid and accurate screening and diagnostic methods for potential respiratory viruses. Existing COVID-19 diagnostic approaches face limitations either in terms of turnaround time or accuracy. In this study, we present an electrochemical biosensor that offers nearly instantaneous and precise SARS-CoV-2 detection, suitable for point-of-care and environmental monitoring applications. The biosensor employs a stapled hACE-2 N-terminal alpha helix peptide to functionalize an in situ grown polypyrrole conductive polymer on a nitrocellulose membrane backbone through a chemical process. We assessed the biosensor's analytical performance using heat-inactivated omicron and delta variants of the SARS-CoV-2 virus in artificial saliva (AS) and nasal swab (NS) samples diluted in a strong ionic solution, as well as clinical specimens with known Ct values. Virus identification was achieved through electrochemical impedance spectroscopy (EIS) and frequency analyses. The assay demonstrated a limit of detection (LoD) of 40 TCID50/mL, with 95% sensitivity and 100% specificity. Notably, the biosensor exhibited no cross-reactivity when tested against the influenza virus. The entire testing process using the biosensor takes less than a minute. In summary, our biosensor exhibits promising potential in the battle against pandemic respiratory viruses, offering a platform for the development of rapid, compact, portable, and point-of-care devices capable of multiplexing various viruses. The biosensor has the capacity to significantly bolster our readiness and response to future viral outbreaks.

Integrated point-of-care RT-PCR methods during and after COVID-19 pandemic

The COVID-19 pandemic has taken the world by surprise and people and organisations worldwide worked in some way or the other to combat the spread; isolate from the infected and get back to normal life, as it was before the pandemic hit. In this regard, the diagnosis of COVID-19 was at the centre of control and prevention and have seen a vehement change in every aspect, especially development of point-of-care testing for better and quick diagnosis. Among different types of techniques developed, the most important was the RT-PCR method of detection which detects nucleic acid of the virus in samples. RT-PCR is a laboratory-based method requiring trained professionals and precise steps for accurate testing. With the advent and spread of the pandemic, number of RT-PCR diagnostic centres rose significantly, and the detection process became less cumbersome, easy to use, ability to handle large volume of samples, more accurate, less time-consuming, and cost-effective. Different industries developed RT-PCR kits, reducing the efforts to prepare laboratory samples. Machines were employed for labour-driven tasks in PCR testing. In addition, new age technologies such as artificial intelligence, IoT, digital systems were combined with RT-PCR for accurate and easy testing. In this review, point-of-care RT-PCR methods, when the COVID-19 started, and the methods now, has been compared on the basis of technological advancements.

Microparticle-Based Detection of Viruses

Surveillance of viral pathogens in both point-of-care and clinical settings is imperative to preventing the widespread propagation of disease-undetected viral outbreaks can pose dire health risks on a large scale. Thus, portable, accessible, and reliable biosensors are necessary for proactive measures. Polymeric microparticles have recently gained popularity for their size, surface area, and versatility, which make them ideal biosensing tools. This review cataloged recent investigations on polymeric microparticle-based detection platforms across eight virus families. These microparticles were used as labels for detection (often with fluorescent microparticles) and for capturing viruses for isolation or purification (often with magnetic microparticles). We also categorized all methods by the characteristics, materials, conjugated receptors, and size of microparticles. Current approaches were compared, addressing strengths and weaknesses in the context of virus detection. In-depth analyses were conducted for each virus family, categorizing whether the polymeric microparticles were used as labels, for capturing, or both. We also summarized the types of receptors conjugated to polymeric microparticles for each virus family.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

A Miniaturized System for Rapid, Isothermal Detection of SARS-CoV-2 in Human and Environmental Samples

We report a small-footprint cost-effective isothermal rapid DNA amplification system, with integrated microfluidics for automated sample analysis and detection of SARS-CoV-2 in human and environmental samples. Our system measures low-level fluorescent signals in real-time during amplification, while maintaining the desired assay temperature on a low power, portable system footprint. A unique soft microfluidic chip design was implemented to mitigate thermocapillary effects and facilitate optical alignment for automated image capture and signal analysis. The system-on-board prototype, coupled with the LAMP primers designed by BioCoS, was sensitive enough to detect large variations in viral loads of SARS-CoV-2 corresponding to a threshold cycle range of 16 to 39. Furthermore, tested samples consisted of a broad range of viral strains and lineages identified in Canada during 2021-2022. Clinical specimens were collected and tested at the Kingston Health Science Centre using a clinically validated PCR assay, and variants were determined using whole genome sequencing.

Optical Biosensors for the Diagnosis of COVID-19 and Other Viruses-A Review

The sudden outbreak of the COVID-19 pandemic led to a huge concern globally because of the astounding increase in mortality rates worldwide. The medical imaging computed tomography technique, whole-genome sequencing, and electron microscopy are the methods generally used for the screening and identification of the SARS-CoV-2 virus. The main aim of this review is to emphasize the capabilities of various optical techniques to facilitate not only the timely and effective diagnosis of the virus but also to apply its potential toward therapy in the field of virology. This review paper categorizes the potential optical biosensors into the three main categories, spectroscopic-, nanomaterial-, and interferometry-based approaches, used for detecting various types of viruses, including SARS-CoV-2. Various classifications of spectroscopic techniques such as Raman spectroscopy, near-infrared spectroscopy, and fluorescence spectroscopy are discussed in the first part. The second aspect highlights advances related to nanomaterial-based optical biosensors, while the third part describes various optical interferometric biosensors used for the detection of viruses. The tremendous progress made by lab-on-a-chip technology in conjunction with smartphones for improving the point-of-care and portability features of the optical biosensors is also discussed. Finally, the review discusses the emergence of artificial intelligence and its applications in the field of bio-photonics and medical imaging for the diagnosis of COVID-19. The review concludes by providing insights into the future perspectives of optical techniques in the effective diagnosis of viruses.

Point-of-Care Testing for Infectious Diseases Based on Class 2 CRISPR/Cas Technology

The early detection of infectious diseases and microorganisms is critical for effective disease treatment, control, and prevention. Currently, nucleic acid testing and antigen-antibody serum reaction are the two methods most commonly used for the detection of infectious diseases. The former is highly accurate, specific, and sensitive, but it is time-consuming, expensive, and has special technician and instrument requirements. The latter is rapid and economical, but it may not be accurate and sensitive enough. Therefore, it is necessary to develop a quick and on-site diagnostic test for point-of-care testing (POCT) to enable the clinical detection of infectious diseases that is accurate, sensitive, convenient, cheap, and portable. Here, CRISPR/Cas-based detection methods are detailed and discussed in depth. The powerful capacity of these methods will facilitate the development of diagnostic tools for POCT, though they still have some limitations. This review explores and highlights POCT based on the class 2 CRISPR/Cas assay, such as Cas12 and Cas13 proteins, for the detection of infectious diseases. We also provide an outlook on perspectives, multi-application scenarios, clinical applications, and limitations for POCT based on class 2 CRISPR/Cas technology.

Severe Acute Respiratory Syndrome Associated Infections

Viral infections are some of the most common sources of respiratory illness in pediatric and adult populations worldwide. Influenza and coronaviruses are viral pathogens that could lead to severe respiratory illness and death. More recently, respiratory illness from coronaviruses, accounts for more than 1 million deaths in the United States alone. This article will explore the epidemiology, pathogenesis, diagnosis, treatment, and prevention of severe acute respiratory syndrome caused by coronavirus-2, and Middle Eastern respiratory syndrome.

Alternative platform for COVID-19 diagnosis based on AuNP-modified lab-on-paper

COVID-19 has caused global health problems, and so rapid diagnosis is crucial to slow spread of the disease. Herein, a novel lab-on-paper screening method for SARS-CoV-2 Omicron BA.2 variant was developed using a gold nanoparticle-based colorimetric biosensor along with sensitive detection of SARS-CoV-2 antigen using laser desorption ionization-mass spectrometry (LDI-MS). As a result of antigen-antibody interaction, in the presence of SARS-CoV-2 antigen the gold nanoparticles undergo aggregation and change color from red to light purple, allowing for rapid determination of SARS-CoV-2 antigen with the naked eye. Furthermore, the lab-on-paper method can be directly applied as a substrate for sensitive quantitation of SARS-CoV-2 antigen in saliva using LDI-MS without the use of a conventional organic matrix and sample preparation. LDI-MS offers early diagnosis with high sensitivity, rapidity without sample preparation and lower cost per test compared with reverse transcriptase-PCR, which is crucial for preventing mortality in patients with underlying conditions. This method showed linearity over 0.01-1 μg mL^-1 covering the cut-off value of 0.048 μg mL^-1 for COVID-19 detection in human saliva. Moreover, a colorimetric sensor for urea was also fabricated in-parallel, for prediction of COVID-19 severity in patients with chronic kidney disease. The color change upon increasing urea concentration directly reflected kidney damage, which is related to increasing risk of mortality among patients with COVID-19. Hence, this platform might be a potential device for non-invasive diagnosis of SARS-CoV-2 Omicron BA.2 variant, which is the variant of most concern because it is transmitted more rapidly than the original SARS-CoV-2 virus and the Delta variant.

The Impact of the COVID-19 Pandemic on the Management of Mental Health Services for Hospitalized Patients in Sibiu County-Central Region, Romania

INTRODUCTION

The COVID-19 pandemic brought a burden and represented a challenge for the Romanian medical system. This study explored the consequences that COVID epidemiological measures had on the quality of the mental health care provided to hospitalized patients in a regional psychiatric hospital in Romania.

MATERIALS AND METHODS

Both patient-level and hospital-level indicators were considered for this comparative retrospective study. On the one hand, we extracted patient-level indicators, such as sociodemographics, diagnosis, admission, and discharge dates for 7026 hospitalized patients (3701 women, average age = 55.14) from hospital records. On the other hand, for the hospital-level indicators, we included indicators referring to the aggregated concept of mental health services, such as case mix index, length of stay, bed occupancy rate and patients' degree of satisfaction. Data extracted covered a period of two years (1 March 2019-28 February 2021) before and during the first year of the COVID-19 pandemic.

RESULTS

We found that, compared to the pre-pandemic period, the pandemic period was marked by a drastic decrease in hospitalized patient admissions, coupled with an increase in emergency-based admissions. Other management indicators, such as the case mix index, the number of cases contracted/performed, and the degree of patient satisfaction, decreased. In contrast, the average length of stay and bed occupancy rate increased.

CONCLUSIONS

The COVID-19 pandemic, especially in the first year, raised multiple difficult issues for the management of psychiatric hospitals. It imposed an application of strict measures designed to face these new and unprecedented challenges. Our findings offer a detailed snapshot of the first year of the COVID-19 pandemic in terms of its impact on mental health services and suggest some future directions. Implications for hospital management are discussed.

A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19

In this paper, we present a systematic review and meta-analysis that aims to evaluate the reliability of coronavirus disease diagnostic tests in 2019 (COVID-19). This article seeks to describe the scientific discoveries made because of diagnostic tests conducted in recent years during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Between 2020 and 2021, searches for published papers on the COVID-19 diagnostic were made in the PubMed database. Ninety-nine scientific articles that satisfied the requirements were analyzed and included in the meta-analysis, and the specificity and sensitivity of the diagnostic accuracy were assessed. When compared to serological tests such as the enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay (CLIA), lateral flow immunoassay (LFIA), and chemiluminescent microparticle immunoassay (CMIA), molecular tests such as reverse transcription polymerase chain reaction (RT-PCR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR) performed better in terms of sensitivity and specificity. Additionally, the area under the curve restricted to the false-positive rates (AUC_FPR) of 0.984 obtained by the antiviral neutralization bioassay (ANB) diagnostic test revealed significant potential for the identification of COVID-19. It has been established that the various diagnostic tests have been effectively adapted for the detection of SARS-CoV-2; nevertheless, their performance still must be enhanced to contain potential COVID-19 outbreaks, which will also help contain potential infectious agent outbreaks in the future.

Evaluation of ten (10) SARS-CoV-2 rapid serological tests in comparison with WANTAI SARS-CoV-2 ab ELISA in Burkina Faso, West Africa

BACKGROUND

The aim of this study was to evaluate the performance of ten (10) SARS-CoV-2 serological rapid diagnostic tests in comparison with the WANTAI SARS-CoV-2 Ab ELISA test in a laboratory setting.

MATERIALS AND METHODS

Ten (10) SARS-CoV-2 serological rapid diagnostic tests (RDTs) for SARS-CoV-2 IgG/IgM were evaluated with two (2) groups of plasma tested positive for one and negative for the other with the WANTAI SARS-CoV-2 Ab ELISA. The diagnostic performance of the SARS-CoV-2 serological RDTs and their agreement with the reference test were calculated with their 95% confidence intervals.

RESULTS

The sensitivity of serological RDTs ranged from 27.39 to 61.67% and the specificity from 93.33 to 100% compared to WANTAI SARS-CoV-2 Ab ELISA test. Of all the tests, two tests (STANDARD Q COVID-19 IgM/IgG Combo SD BIOSENSOR and COVID-19 IgG/IgM Rapid Test (Zhejiang Orient Gene Biotech Co., Ltd)) had a sensitivity greater than 50%. In addition, all ten tests had specificity greater than or equal to 93.33% each. The concordance between RDTs and WANTAI SARS-CoV-2 Ab ELISA test ranged from 0.25 to 0.61.

CONCLUSION

The SARS-CoV-2 serological RDTs evaluated show low and variable sensitivities compared to the WANTAI SARS-CoV-2 Ab ELISA test, with however a good specificity. These finding may have implications for the interpretation and comparison of COVID-19 seroprevalence studies depending on the type of test used.

PCR-like performance of rapid test with permselective tunable nanotrap

Highly sensitive rapid testing for COVID-19 is essential for minimizing virus transmission, especially before the onset of symptoms and in asymptomatic cases. Here, we report bioengineered enrichment tools for lateral flow assays (LFAs) with enhanced sensitivity and specificity (BEETLES²), achieving enrichment of SARS-CoV-2 viruses, nucleocapsid (N) proteins and immunoglobulin G (IgG) with 3-minute operation. The limit of detection is improved up to 20-fold. We apply this method to clinical samples, including 83% with either intermediate (35%) or low viral loads (48%), collected from 62 individuals (n = 42 for positive and n = 20 for healthy controls). We observe diagnostic sensitivity, specificity, and accuracy of 88.1%, 100%, and 91.9%, respectively, compared with commercial LFAs alone achieving 14.29%, 100%, and 41.94%, respectively. BEETLES², with permselectivity and tunability, can enrich the SARS-CoV-2 virus, N proteins, and IgG in the nasopharyngeal/oropharyngeal swab, saliva, and blood serum, enabling reliable and sensitive point-of-care testing, facilitating fast early diagnosis.

Multiplexed Ultrasensitive Sample-to-Answer RT-LAMP Chip for the Identification of SARS-CoV-2 and Influenza Viruses

Prompt on-site diagnosis of SARS-CoV-2 with other respiratory infections will have minimized the global impact of the COVID-19 pandemic through rapid, effective management. However, no such multiplex point-of-care (POC) chip has satisfied a suitable sensitivity of gold-standard nucleic acid amplification tests (NAATs). Here, a rapid multiplexed ultrasensitive sample-to-answer loop-mediated isothermal amplification (MUSAL) chip operated by simple LED-driven photothermal amplification to detect six targets from single-swab sampling is presented. First, the MUSAL chip allows ultrafast on-chip sample preparation with ≈500-fold preconcentration at a rate of 1.2 mL min^-1 . Second, the chip enables contamination-free amplification using autonomous target elution into on-chip reagents by photothermal activation. Finally, the chip accomplishes multiplexed on-chip diagnostics of SARS-CoV-2 and influenza viruses with a limit of detection (LoD) of 0.5 copies µL^-1 . The rapid, ultrasensitive, cost-effective sample-to-answer chip with a multiplex capability will allow timely management of various pandemics situations that may be faced shortly.

The Assessment of Multiplex PCR in Identifying Bacterial Infections in Patients Hospitalized with SARS-CoV-2 Infection: A Systematic Review

Bacterial infection can occur in patients hospitalized with SARS-CoV-2 in various conditions, resulting in poorer outcomes, such as a higher death rate. This current systematic review was conducted in order to assess the efficiency of multiplex PCR in detecting bacterial infections in hospitalized COVID-19 patients, as well as to analyze the most common bacterial pathogens and other factors that interfere with this diagnosis. The research was conducted using four electronic databases (PubMed, Taylor&Francis, Web of Science, and Wiley Online Library). Out of 290 studies, nine were included in the systematic review. The results supported the use of multiplex PCR in detecting bacteria, considering its high sensitivity and specificity rates. The most common bacterial pathogens found were Klebsiella pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, Streptococcus pneumoniae, and Haemophilus influenzae. The median age at admission was 61.5 years, and the majority of patients were men (70.3%), out of a total of 1553 patients. The proportion of ICU admission was very high, with a pooled proportion of 52.6% over the analyzed studies, and an average duration of hospitalization of 13 days. The mortality rate was proportionally high, as was the rate of ICU admission, with a pooled mortality of 24.9%. It was discovered that 65.2% of all patients used antibiotics before admission, with or without medical prescription. Antibiotic treatment should be considered consciously, considering the high risks of developing antibiotic resistance.

Affordable on-site COVID-19 test using non-powered preconcentrator

A simple, affordable point of care test (POCT) is necessary for on-site detection of coronavirus disease 2019 (COVID-19). The lateral flow assay (LFA) has great potential for use in POCT mainly because of factors such as low time consumption, low cost, and ease of use. However, it lacks sensitivity and limits of detection (LOD), which are essential for early diagnostics. In this study, we proposed a non-powered preconcentrator (NPP) based on nanoelectrokinetics for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Antigen (Ag) lateral flow assay. The non-powered preconcentrator is composed of glass fiber-based composite paper and ion permselective material, and it can be simply operated by force balancing gravitational, capillary, and depletion-induced forces. The proposed approach helps enrich the SARS-CoV-2 viral nucleocapsid (N) proteins based on a 10-min operation, and it improved the LOD by up to 10-fold. The corresponding virus enrichment, which was evaluated using the reverse-transcriptase polymerase chain reaction (RT-PCR), revealed an improvement in ΔCt values > 3. We successfully demonstrated the enhancement of the NPP-assisted LFA, we extended to applying it to clinical samples. Further, we demonstrated an affordable, easy-to-implement form of LFA by simply designing NPP directly on the LFA buffer tube.

Evaluation of RT-PCR assays for detection of SARS-CoV-2 variants of concern

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic has been considered with great importance on correct screening procedure. The detection efficiency of recent variants of concern were observed by comparing 5 commercial RT-PCR kits and a SYBR-green method developed and validated in our laboratory. The RNA was extracted from nasopharyngeal samples from suspected COVID-19 patients and RT-PCR assay was performed according to the instruction of the respective manufacturers. The specificity and sensitivity of Maccura kit was 81.8% and 82.5%, A*Star kit was 100% and 75.4%, Da An Gene kit was 100% and 68.4%, Sansure kit was 54.5% and 91.2% and TaqPath kit was 100% and 70.2% respectively. Our in house SYBR-Green method showed a consistent detection result with 90.9% specificity and 91.2% sensitivity. We also found that detection kits targeting more genes showed better accuracy which facilitates less false positive results (< 20%). Our study found a significant difference (p < 0.005) in Ct value reported for common target genes shared by the RT-PCR kits in relation with different variants of COVID-19 infection. Recent variants of concerns contain more than 30 mutations in the spike proteins including 2 deletion and a unique insertion mutation by which makes detection of these variants difficult and these facilitates the variants to escape from being detected.

Development and validation of a nomogram to predict failure of 14-day negative nucleic acid conversion in adults with non-severe COVID-19 during the Omicron surge: a retrospective multicenter study

BACKGROUND

With the variability in emerging data, guidance on the isolation duration for patients with coronavirus disease 2019 (COVID-19) due to the Omicron variant is controversial. This study aimed to determine the predictors of prolonged viral RNA shedding in patients with non-severe COVID-19 and construct a nomogram to predict patients at risk of 14-day PCR conversion failure.

METHODS

Adult patients with non-severe COVID-19 were enrolled from three hospitals of eastern China in Spring 2022. Viral shedding time (VST) was defined as either the day of the first positive test or the day of symptom onset, whichever was earlier, to the date of the first of two consecutively negative PCR tests. Patients from one hospital (Cohort I, n = 2033) were randomly grouped into training and internal validation sets. Predictors of 14-day PCR conversion failure were identified and a nomogram was developed by multivariable logistic regression using the training dataset. Two hospitals (Cohort II, n = 1596) were used as an external validation set to measure the performance of this nomogram.

RESULTS

Of the 2033 patients from Cohort I, the median VST was 13.0 (interquartile range: 10.0‒16.0) days; 716 (35.2%) lasted > 14 days. In the training set, increased age [per 10 years, odds ratio (OR) = 1.29, 95% confidence interval (CI): 1.15‒1.45, P < 0.001] and high Charlson comorbidity index (OR = 1.25, 95% CI: 1.08‒1.46, P = 0.004) were independent risk factors for VST > 14 days, whereas full or boosted vaccination (OR = 0.63, 95% CI: 0.42‒0.95, P = 0.028) and antiviral therapy (OR = 0.56, 95% CI: 0.31‒0.96, P = 0.040) were protective factors. These predictors were used to develop a nomogram to predict VST > 14 days, with an area under the ROC curve (AUC) of 0.73 in the training set (AUC, 0.74 in internal validation set; 0.76 in external validation set).

CONCLUSIONS

Older age, increasing comorbidities, incomplete vaccinations, and lack of antiviral therapy are risk factors for persistent infection with Omicron variant for > 14 days. A nomogram based on these predictors could be used as a prediction tool to guide treatment and isolation strategies.

The Deceptive COVID-19: Lessons from Common Molecular Diagnostics and a Novel Plan for the Prevention of the Next Pandemic

The COVID-19 pandemic took place during the years 2020-2022 and the virus, named SARS-CoV-2, seems likely to have resulted in an endemic disease. Nevertheless, widespread COVID-19 has given rise to several major molecular diagnostics' facts and concerns that have emerged during the overall management of this disease and the subsequent pandemic. These concerns and lessons are undeniably critical for the prevention and control of future infectious agents. Furthermore, most populaces were introduced to several new public health maintenance strategies, and again, some critical events arose. The purpose of this perspective is to thoroughly analyze all these issues and the concerns, such as the molecular diagnostics' terminologies, their role, as well as the quantity and quality issues with a molecular diagnostics' test result. Furthermore, it is speculated that society will be more vulnerable in the future and prone to emerging infectious diseases; thus, a novel preventive medicine's plan for the prevention and control of future (re)emerging infectious diseases is presented, so as to aid the early prevention of future epidemics and pandemics.

Analysis of Chest X-ray for COVID-19 Diagnosis as a Use Case for an HPC-Enabled Data Analysis and Machine Learning Platform for Medical Diagnosis Support

The COVID-19 pandemic shed light on the need for quick diagnosis tools in healthcare, leading to the development of several algorithmic models for disease detection. Though these models are relatively easy to build, their training requires a lot of data, storage, and resources, which may not be available for use by medical institutions or could be beyond the skillset of the people who most need these tools. This paper describes a data analysis and machine learning platform that takes advantage of high-performance computing infrastructure for medical diagnosis support applications. This platform is validated by re-training a previously published deep learning model (COVID-Net) on new data, where it is shown that the performance of the model is improved through large-scale hyperparameter optimisation that uncovered optimal training parameter combinations. The per-class accuracy of the model, especially for COVID-19 and pneumonia, is higher when using the tuned hyperparameters (healthy: 96.5%; pneumonia: 61.5%; COVID-19: 78.9%) as opposed to parameters chosen through traditional methods (healthy: 93.6%; pneumonia: 46.1%; COVID-19: 76.3%). Furthermore, training speed-up analysis shows a major decrease in training time as resources increase, from 207 min using 1 node to 54 min when distributed over 32 nodes, but highlights the presence of a cut-off point where the communication overhead begins to affect performance. The developed platform is intended to provide the medical field with a technical environment for developing novel portable artificial-intelligence-based tools for diagnosis support.

The role of HLA genotypes in understanding the pathogenesis of severe COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has caused human tragedy through the global spread of the viral pathogen SARS-CoV-2. Although the underlying factors for the severity of COVID-19 in different people are still unknown, several gene variants can be used as predictors of disease severity, particularly variations in viral receptor genes such as angiotensin-converting enzyme 2 (ACE2) or major histocompatibility complex (MHC) genes. The reaction of the immune system, as the most important defense strategy in the case of viruses, plays a decisive role. The innate immune system is important both as a primary line of defense and as a trigger of the acquired immune response. The HLA-mediated acquired immune response is linked to the acquired immune system. In various diseases, it has been shown that genetic alterations in components of the immune system can play a crucial role in how the body responds to pathogens, especially viruses. One of the most important host genetic factors is the human leukocyte antigen (HLA) profile, which includes HLA classes I and II and may be symbolic of the diversity of immune response and genetic predisposition in disease progression. COVID-19 will have direct contact with the acquired immune system as an intracellular pathogen after exposure to the proteasome and its components through class I HLA. Therefore, it is assumed that in different genotypes of the HLA-I class, an undesirable supply causes an insufficient activation of the immune system. Insufficient binding of antigen delivered by class I HLA to host lymphocytes results in uncertain identification and insufficient activation of the acquired immune system. The absence of secretion of immune cytokines such as interferons, which play an important role in controlling viral infection in the early stages, is a complication of this event. Understanding the allelic diversity of HLA in people infected with coronavirus compared with uninfected people of one race not only allows identification of people with HLA susceptible to COVID-19 but also provides better insight into the behavior of the virus, which helps to take effective preventive and curative measures earlier.

Structural Attacks and Defenses for Flow-Based Microfluidic Biochips

Flow-based microfluidic biochips (FMBs) have seen rapid commercialization and deployment in recent years for point-of-care and clinical diagnostics. However, the outsourcing of FMB design and manufacturing makes them susceptible to susceptible to malicious physical level and intellectual property (IP)-theft attacks. This work demonstrates the first structure-based (SB) attack on representative commercial FMBs. The SB attacks maliciously decrease the heights of the FMB reaction chambers to produce false-negative results. We validate this attack experimentally using fluorescence microscopy, which showed a high correlation ( R² = 0.987) between chamber height and related fluorescence intensity of the DNA amplified by polymerase chain reaction. To detect SB attacks, we adopt two existing deep learning-based anomaly detection algorithms with  ∼ 96% validation accuracy in recognizing such deliberately introduced microstructural anomalies. To safeguard FMBs against intellectual property (IP)-theft, we propose a novel device-level watermarking scheme for FMBs using intensity-height correlation. The countermeasures can be used to proactively safeguard FMBs against SB and IP-theft attacks in the era of global pandemics and personalized medicine.

Reverse Transcription-Loop-Mediated Isothermal Amplification-CRISPR-Cas13a Technology as a Promising Diagnostic Tool for SARS-CoV-2

At the end of 2019, a new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), caused a pandemic that persists to date and has resulted in more than 6.2 million deaths. In the last couple of years, researchers have made great efforts to develop a diagnostic technique that maintains high levels of sensitivity and specificity, since an accurate and early diagnosis is required to minimize the prevalence of SARS-CoV-2 infection. In this context, CRISPR-Cas systems are proposed as promising tools for development as diagnostic techniques due to their high specificity, highlighting that Cas13 endonuclease discriminates single nucleotide changes and displays collateral activity against single-stranded RNA molecules. With the aim of improving the sensitivity of diagnosis, this technology is usually combined with isothermal preamplification reactions (SHERLOCK, DETECTR). Based on this, we developed a reverse transcription-loop-mediated isothermal amplification (RT-LAMP)-CRISPR-Cas13a method for SARS-CoV-2 virus detection in nasopharyngeal samples without using RNA extraction that exhibits 100% specificity and 83% sensitivity, as well as a positive predictive value (PPV) of 100% and negative predictive values (NPVs) of 100%, 81%, 79.1%, and 66.7% for cycle threshold (CT) values of <20, 20 to 30, >30 and overall, respectively. IMPORTANCE The coronavirus disease 2019 (COVID-19) crisis has driven the development of innovative molecular diagnosis methods, including CRISPR-Cas technology. In this work, we performed a protocol, working with RNA extraction kit-free samples and using RT-LAMP-CRISPR-Cas13a technology; our results place this method at the forefront of rapid and specific diagnostic methods for COVID-19 due to the high specificity (100%), sensitivity (83%), PPVs (100%), and NPVs (81% for high viral loads) obtained with clinical samples.

Predictive models for COVID-19 detection using routine blood tests and machine learning

The problem of accurate, fast, and inexpensive COVID-19 tests has been urgent till now. Standard COVID-19 tests need high-cost reagents and specialized laboratories with high safety requirements, are time-consuming. Data of routine blood tests as a base of SARS-CoV-2 invasion detection allows using the most practical medicine facilities. But blood tests give general information about a patient’s state, which is not directly associated with COVID-19. COVID-19-specific features should be selected from the list of standard blood characteristics, and decision-making software based on appropriate clinical data should be created. This review describes the abilities to develop predictive models for COVID-19 detection using routine blood tests and machine learning.

Machine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application

Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine learning (ML) sensors for the prompt diagnosis of COVID-19 are an important option for IoT application in healthcare and ambient assisted living (AAL). Determining a COVID-19 infected status with various diagnostic tests and imaging results is costly and time-consuming. This study provides a fast, reliable and cost-effective alternative tool for the diagnosis of COVID-19 based on the routine blood values (RBVs) measured at admission. The dataset of the study consists of a total of 5296 patients with the same number of negative and positive COVID-19 test results and 51 routine blood values. In this study, 13 popular classifier machine learning models and the LogNNet neural network model were exanimated. The most successful classifier model in terms of time and accuracy in the detection of the disease was the histogram-based gradient boosting (HGB) (accuracy: 100%, time: 6.39 sec). The HGB classifier identified the 11 most important features (LDL, cholesterol, HDL-C, MCHC, triglyceride, amylase, UA, LDH, CK-MB, ALP and MCH) to detect the disease with 100% accuracy. In addition, the importance of single, double and triple combinations of these features in the diagnosis of the disease was discussed. We propose to use these 11 features and their binary combinations as important biomarkers for ML sensors in the diagnosis of the disease, supporting edge computing on Arduino and cloud IoT service.

The Performances of Three Commercially Available Assays for the Detection of SARS-CoV-2 Antibodies at Different Time Points Following SARS-CoV-2 Infection

The aim of this study was to evaluate the performances of three commercially available antibody assays for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies at different time points following SARS-CoV-2 infection. Sera from 536 cases, including 207 SARS-CoV-2 PCR positive, were tested for SARS-CoV-2 antibodies with the Wantai receptor binding domain (RBD) total antibody assay, Liaison S1/S2 IgG assay and Alinity i nucleocapsid IgG assay and compared to a two-step reference ELISA (SARS-CoV-2 RBD IgG and SARS-CoV-2 spike IgG). Diagnostic sensitivity, specificity, predictive values and Cohen's kappa were calculated for the commercial assays. The assay's sensitivities varied greatly, from 68.7% to 95.3%, but the specificities remained high (96.9-99.1%). The three tests showed good performances in sera sampled 31 to 60 days after PCR positivity compared to the reference ELISA. The total antibody test performed better than the IgG tests the first 30 days and the nucleocapsid IgG test showed reduced sensitivity two months or more after PCR positivity. Hence, the test performances at different time points should be taken into consideration in clinical practice and epidemiological studies. Spike or RBD IgG tests are preferable in sera sampled more than two months following SARS-CoV-2 infection.

Multiple introduced lineages and the single native lineage co-driving the four waves of the COVID-19 pandemic in West Africa

Coronavirus disease 2019 (COVID-19) has become a vast burden on public health and socioeconomics in West Africa, but the epidemic situation is unclear. Therefore, we conducted a retrospective analysis of the positive rate, death rate, and diversity of SARS-CoV-2. As of March 31, 2022, a total of 894,813 cases of COVID-19 have been recorded, with 12,028 deaths, both of which were distributed in all 16 countries. There were four waves of COVID-19 during this period. Most cases were recorded in the second wave, accounting for 34.50% of total cases. These data suggest that although West Africa seems to have experienced a low and relatively slow spread of COVID-19, the epidemic was ongoing, evolving with each COVID-19 global pandemic wave. Most cases and most deaths were both recorded in Nigeria. In contrast, the fewest cases and fewest deaths were reported, respectively, in Liberia and Sierra Leone. However, high death rates were found in countries with low incidence rates. These data suggest that the pandemic in West Africa has so far been heterogeneous, which is closely related to the infrastructure of public health and socioeconomic development (e.g., extreme poverty, GDP per capita, and human development index). At least eight SARS-CoV-2 variants were found, namely, Delta, Omicron, Eta, Alpha, Beta, Kappa, Iota, and Gamma, which showed high diversity, implicating that multiple-lineages from different origins were introduced. Moreover, the Eta variant was initially identified in Nigeria and distributed widely. These data reveal that the COVID-19 pandemic in the continent was co-driven by both multiple introduced lineages and a single native lineage. We suggest enhancing the quarantine measures upon entry at the borders and implementing a genome surveillance strategy to better understand the transmission dynamics of the COVID-19 pandemic in West Africa.