Review of analytical performance of COVID-19 detection methods

SARS-CoV-2 detection in COVID-19 patients' sample using Wooden quoit conformation structural aptamer (WQCSA)-Based electronic bio-sensing system

The COVID-19 epidemic and its continuous spread pose a serious threat to public health. Coronavirus strains known as SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) variants have undergone genomic changes. The severity of the symptoms, the efficiency of vaccinations, and the transmission capacity of the virus can be impacted by these alterations. Point-of-care diagnostic assays can identify particular genetic or protein sequences that are exclusive to each variety. Currently, ultrafast, responsive, and accurate antibody detection faces several challenges. Here, we outline the fabrication, implementation, and sensing performance benchmarking of an ultrafast (5 s) and inexpensive (0.15 USD) assay with label-free sensing of SARS-CoV-2 S (Spike)/N (Nucleocapsid) protein and other variants in real patient samples. A label-free DNA aptameric capacitive bio-sensing device was used to detect SARS-CoV-2 variants. Our novel, cutting-edge bio-sensing device contains a Wooden quoits conformation structural aptamer (WQCSA)-based inter-digitated capacitor electronic (WQCSA-IDCE) system. WQCSA-aptamer was used as a switch-turn on response to achieve ultrasensitivity in the variable area of the SARS-CoV-2. The molecular beacon (MB) method was also used to measure the fluorescently colored SARS-CoV-2 S/N protein. These sensors can be used with several types of label-free DNA aptamers to act as rapid, affordable, and label-free biosensors for a variety of critical acute respiratory virus syndrome disorders.

Plasmonic nanoparticle sensors: current progress, challenges, and future prospects

Plasmonic nanoparticles (NPs) have played a significant role in the evolution of modern nanoscience and nanotechnology in terms of colloidal synthesis, general understanding of nanocrystal growth mechanisms, and their impact in a wide range of applications. They exhibit strong visible colors due to localized surface plasmon resonance (LSPR) that depends on their size, shape, composition, and the surrounding dielectric environment. Under resonant excitation, the LSPR of plasmonic NPs leads to a strong field enhancement near their surfaces and thus enhances various light-matter interactions. These unique optical properties of plasmonic NPs have been used to design chemical and biological sensors. Over the last few decades, colloidal plasmonic NPs have been greatly exploited in sensing applications through LSPR shifts (colorimetry), surface-enhanced Raman scattering, surface-enhanced fluorescence, and chiroptical activity. Although colloidal plasmonic NPs have emerged at the forefront of nanobiosensors, there are still several important challenges to be addressed for the realization of plasmonic NP-based sensor kits for routine use in daily life. In this comprehensive review, researchers of different disciplines (colloidal and analytical chemistry, biology, physics, and medicine) have joined together to summarize the past, present, and future of plasmonic NP-based sensors in terms of different sensing platforms, understanding of the sensing mechanisms, different chemical and biological analytes, and the expected future technologies. This review is expected to guide the researchers currently working in this field and inspire future generations of scientists to join this compelling research field and its branches.

An account of the current status of point-of-care lateral flow tests for kidney biomarker detection

Globally, the primary causes of mortality and morbidity related to kidney ailments can be classified as Acute Kidney Injury (AKI) and Chronic Kidney Disease (CKD). Biomarker detection can have great potential to improve survival, lower mortality, and reduce the cost of treatment of kidney diseases. Considering the chronic nature of CKD, non-invasive identification and monitoring have proven to be useful. Biosensors and more specifically lateral flow test strips (LFTs) are regarded as the most desirable point-of-care instruments which have shown promise in elevating the healthcare industry to a new level. The major aspects of an ideal point-of-care (POC) lateral flow test include its cost effectiveness, high sensitivity and specificity, ease of use, quick result delivery, and quality control. This review provides a detailed account of recent developments, challenges, and opportunities in renal biomarker detection using LFTs including various approaches for sensitivity enhancement along with potential future advancements in POC and LFT kits.

RNA extraction-free reduced graphene oxide-based RT-LAMP fluorescence assay for highly sensitive SARS-CoV-2 detection

Infectious diseases have always been a seriously endanger for human life and health. A rapid, accurate and ultra-sensitive virus nucleic acid detection is still a challenge to deal with infectious diseases. Here, a RNA extraction-free reduced graphene oxide-based reverse transcription-loop-mediated isothermal amplification (EF-G-RT-LAMP) fluorescence assay was developed to achieve high-throughput, rapid and ultra-sensitive SARS-CoV-2 RNA detection. The whole detection process only took ∼36 min. The EF-G-RT-LAMP assay achieves a detection limit of 0.6 copies μL-1 with a wide dynamic range of aM-pM. A large number (up to 384) of samples can be detected simultaneously. Simulated detection of the COVID-19 pseudovirus and clinical samples in nasopharyngeal swabs demonstrated a high-throughput, rapid and ultra-sensitive practical detection capability of the EF-G-RT-LAMP assay. The results proved that the assay would be used as a rapid, easy-to-implement approach for epidemiologic diagnosis and could be extended to other nucleic acid detections.

A proactive/reactive mass screening approach with uncertain symptomatic cases

We study the problem of mass screening of heterogeneous populations under limited testing budget. Mass screening is an essential tool that arises in various settings, e.g., the COVID-19 pandemic. The objective of mass screening is to classify the entire population as positive or negative for a disease as efficiently and accurately as possible. Under limited budget, testing facilities need to allocate a portion of the budget to target sub-populations (i.e., proactive screening) while reserving the remaining budget to screen for symptomatic cases (i.e., reactive screening). This paper addresses this decision problem by taking advantage of accessible population-level risk information to identify the optimal set of sub-populations for proactive/reactive screening. The framework also incorporates two widely used testing schemes: Individual and Dorfman group testing. By leveraging the special structure of the resulting bilinear optimization problem, we identify key structural properties, which in turn enable us to develop efficient solution schemes. Furthermore, we extend the model to accommodate customized testing schemes across different sub-populations and introduce a highly efficient heuristic solution algorithm for the generalized model. We conduct a comprehensive case study on COVID-19 in the US, utilizing geographically-based data. Numerical results demonstrate a significant improvement of up to 52% in total misclassifications compared to conventional screening strategies. In addition, our case study offers valuable managerial insights regarding the allocation of proactive/reactive measures and budget across diverse geographic regions.

Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey

The unpredictable pandemic came to light at the end of December 2019, known as the novel coronavirus, also termed COVID-19, identified by the World Health Organization (WHO). The virus first originated in Wuhan (China) and rapidly affected most of the world's population. This outbreak's impact is experienced worldwide because it causes high mortality risk, many cases, and economic falls. Around the globe, the total number of cases and deaths reported till November 12, 2022, were >600 million and 6.6 million, respectively. During the period of COVID-19, several diverse diagnostic techniques have been proposed. This work presents a systematic review of COVID-19 diagnostic techniques in response to such acts. Initially, these techniques are classified into different categories based on their working principle and detection modalities, i.e. chest X-ray imaging, cough sound or respiratory patterns, RT-PCR, antigen testing, and antibody testing. After that, a comparative analysis is performed to evaluate these techniques' efficacy which may help to determine an optimum solution for a particular scenario. The findings of the proposed work show that Artificial Intelligence plays a vital role in developing COVID-19 diagnostic techniques which support the healthcare system. The related work can be a footprint for all the researchers, available under a single umbrella. Additionally, all the techniques are long-lasting and can be used for future pandemics.

Biomedical Data Mining and Machine Learning for Disease Diagnosis and Health Informatics

Powered by biomedical data mining and machine learning technologies, smart healthcare uses cutting-edge medical innovative tools to facilitate the development of sophisticated decision support systems for disease diagnosis and health informatics [...].

A comprehensive review on immunogen and immune-response proteins of SARS-CoV-2 and their applications in prevention, diagnosis, and treatment of COVID-19

Exposure to severe acute respiratory syndrome-corona virus-2 (SARS-CoV-2) prompts humoral immune responses in the human body. As the auxiliary diagnosis of a current infection, the existence of viral proteins can be checked from specific antibodies (Abs) induced by immunogenic viral proteins. For people with a weakened immune system, Ab treatment can help neutralize viral antigens to resist and treat the disease. On the other hand, highly immunogenic viral proteins can serve as effective markers for detecting prior infections. Additionally, the identification of viral particles or the presence of antibodies may help establish an immune defense against the virus. These immunogenic proteins rather than SARS-CoV-2 can be given to uninfected people as a vaccination to improve their coping ability against COVID-19 through the generation of memory plasma cells. In this work, we review immunogenic and immune-response proteins derived from SARS-CoV-2 with regard to their classification, origin, and diverse applications (e.g., prevention (vaccine development), diagnostic testing, and treatment (via neutralizing Abs)). Finally, advanced immunization strategies against COVID-19 are discussed along with the contemporary circumstances and future challenges.

The Potential Mechanisms Behind Adverse Effect of Coronavirus Disease-19 on Heart and Liver Damage: A Review

Background

Coronaviruses (CoVs) belong to the RNA viruses family. The viruses in this family are known to cause mild respiratory disease in humans. The origin of the novel SARS-COV2 virus that caused the coronavirus-19 disease (COVID-19) is the Wuhan city in China from where it disseminated to cause a global pandemic. Although lungs are the predominant target organ for Coronavirus Disease-19 (COVID-19), since its outbreak, the disease is known to affect heart, blood vessels, kidney, intestine, liver and brain. This review aimed to summarize the catastrophic impacts of Coronavirus disease-19 on heart and liver along with its mechanisms of pathogenesis.

Methods

The information used in this review was obtained from relevant articles published on PubMed, Google Scholar, Google, WHO website, CDC and other sources. Key searching statements and phrases related to COVID-19 were used to retrieve information. Original research articles, review papers, research letters and case reports were used as a source of information.

Results

Besides causing severe lung injury, COVID-19 has also been reported to affect and cause dysfunction of many other organs. COVID-19 infection can affect people by downregulating membrane-bound active angiotensin-converting enzyme (ACE). People who have deficient ACE2 expression are more vulnerable to COVID-19 infection. The patients' pre-existing co-morbidities are major risk factors that predispose individuals to severe COVID-19.

Conclusion

The disease severity and its broad spectrum phenotype is a result of combined direct and indirect pathogenic factors. Therefore, protocols that harmonize many therapeutic preferences should be the best alternatives to de-escalate the disease and obviate deaths caused as a result of multiple organ damage and dysfunction induced by the disease.

Carbon Nanostructured Immunosensing of Anti-SARS-CoV-2 S-Protein Antibodies

The rampant spread and death rate of the recent coronavirus pandemic related to the SARS-CoV-2 respiratory virus have underscored the critical need for affordable, portable virus diagnostics, particularly in resource-limited settings. Moreover, efficient and timely monitoring of vaccine efficacy is needed to prevent future widespread infections. Electrochemical immunosensing poses an effective alternative to conventional molecular spectroscopic approaches, offering rapid, cost-effective, sensitive, and portable electroanalysis of disease biomarkers and antibodies; however, efforts to improve binding efficiency and sensitivity are still being investigated. Graphene quantum dots (GQDs) in particular have shown promise in improving device sensitivity. This study reports the development of a GQD-functionalized point-of-contamination device leveraging the selective interactions between SARS-CoV-2-specific Spike (S) Protein receptor binding domain (RBD) antigens and IgG anti-SARS-CoV-2-specific S-protein antibodies at screen-printed carbon electrode (SPCE) surfaces. The immunocomplexes formed at the GQD surfaces result in the interruption of the redox reactions that take place in the presence of a redox probe, decreasing the current response. Increased active surface area, conductivity, and binding via EDC/NHS chemistry were achieved due to the nanomaterial inclusion, with 5 nm, blue luminescent GQDs offering the best results. GQD concentration, EDC/NHS ratio, and RBD S-protein incubation time and concentration were optimized for the biosensor, and inter- and intra-screen-printed carbon electrode detection was investigated by calibration studies on multiple and single electrodes. The single electrode used for the entire calibration provided the best results. The label-free immunosensor was able to selectively detect anti-SARS-CoV-2 IgG antibodies between 0.5 and 100 ng/mL in the presence of IgM and other coronavirus antibodies with an excellent regression of 0.9599. A LOD of 2.028 ng/mL was found, offering comparable findings to the literature-reported values. The detection sensitivity of the sensor is further compared to non-specific IgM antibodies. The developed GQD immunosensor was compared to other low-oxygen content carbon nanomaterials, namely (i) carbon quantum dot (CQD), (ii) electrochemically reduced graphene oxide, and (iii) carbon black-functionalized devices. The findings suggest that improved electron transfer kinetics and increased active surface area of the CNs, along with surface oxygen content, aid in the detection of anti-SARS-CoV-2 IgG antibodies. The novel immunosensor suggests a possible application toward monitoring of IgG antibody production in SARS-CoV-2-vaccinated patients to study immune responses, vaccine efficacy, and lifetime to meet the demands for POC analysis in resource-limited settings.

Developing magnetic barcode bead fluorescence assay for high throughput analyzing humoral responses against multiple SARS-CoV-2 variants

The continuous mutation of SARS-CoV-2 highlights the need for rapid, cost-effective, and high-throughput detection methods. To better analyze the antibody levels against SARS-CoV-2 and its variants in vaccinated or infected subjects, we developed a multiplex detection named Barcode Bead Fluorescence (BBF) assay. These barcode beads were magnetic, characterized by 2-dimensional edges, highly multiplexed, and could be decrypted with visible light. We conjugated 12 magnetic barcode beads with corresponding nine spike proteins (wild-type, alpha, beta, gamma, delta, and current omicrons), two nucleocapsid proteins (wild-type and omicron), and one negative control. First, the conjugated beads underwent serial quality controls via fluorescence labeling, e.g., reproducibility (R square = 0.99) and detection limits (119 pg via anti-spike antibody). Next, we investigated serums from vaccinated subjects and COVID-19 patients for clinical applications. A significant reduction of antibody levels against all variant beads was observed in both vaccinated and COVID-19 studies. Subjects with two doses of mRNA-1273 exhibited the highest level of antibodies against all spike variants compared to two doses of AZD1222 and unvaccinated. We also found that COVID-19 patients showed higher antibody levels against spike beads from wild-type, alpha, beta, and delta. Finally, the nucleocapsid beads served as markers to distinguish infections from vaccinated subjects. Overall, this study developed the BBF assay for analyzing humoral immune responses, which has the advantages of robustness, automation, scalability, and cost-effectiveness.

Obtaining a high titer of polyclonal antibodies from rats to the SARS-CoV-2 nucleocapsid protein and its N- and C-terminal domains for diagnostic test development

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is an enveloped, plus-stranded RNA virus responsible for the Coronavirus Disease 2019 (COVID-19). Patients infected with COVID-19 may be asymptomatic or have symptoms ranging from mild manifestations to severe cases of the disease that could lead to death. The SARS-CoV-2 genome encodes 4 structural proteins, including the Spike protein (S), the Nucleocapsid protein (N), Membrane protein (M) and, the Envelope protein (E). The N protein forms a major component of the ribonucleoprotein complex within the virus particle and play a vital role in its transcription and replication. Nevertheless, the S protein was the most important protein in the development of vaccines against COVID-19. However, the decrease in number of registered immunizations against the disease and the rapid drop in neutralizing antibody titers together with looser preventive measures for virus transmission, favored the rapid appearance of new variants of concerns (VOCs) that primarily show mutations in the S protein. This fact makes the N protein a good candidate for the development of diagnostic tests, due to its stability, amino acid conservation, high immunogenicity, and the smaller likelihood of mutation. With the aim of developing a new diagnostic kit based on the N protein, we evaluated the humoral response in female Wistar rats against this target. Three constructions of the N protein were used to inoculate the animals: the full-length protein (Cfull), the N- (NTD), and the C-terminal (CTD) portion of the protein. The immunizations induced the animal's immune response, with specific polyclonal IgG antibodies against the Cfull protein and its fragments. There were not non-specific bind to the protein used as negative control. Anti-Cfull antibodies demonstrated high efficiency in binding to the NTD protein and the antibodies present in the anti-CTD and anti-NTD sera have recognized the Cfull protein, but they were not able to recognize the NTD and CTD proteins, respectively. Our results indicate an efficient protocol for obtaining high antibody titers against the N recombinant protein of SARS-CoV-2 and its fragments highlighting the Cfull protein, which can be used in the development of new diagnostic kits.

Disposable and eco-friendly electrochemical immunosensor for rapid detection of SARS-CoV-2

This study describes the development of a simple, disposable, and eco-friendly electrochemical immunosensor for rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Electrochemical devices were manufactured by stencil-printing using low-cost materials such as polyester sheets, graphite flakes, and natural resin. The immunosensor comprises gold nanoparticles stabilized with cysteamine, glutaraldehyde, anti-SARS-CoV-2 S protein monoclonal antibody (Ab1) as the biological receptor, and bovine serum albumin as a protective layer. The COVID-19 diagnostic was based on rapid square wave voltammetry measurements (15 min) using [Fe(CN)6]3-/4- as a redox probe. The method presented a linear response in the concentration range from 250 pg mL-1 to 20 μg mL-1 S protein, with a limit of detection of 36.3 pg mL-1. The proposed immunosensor was stable for up to two weeks when stored at 4 °C and it demonstrated excellent clinical performance in diagnosing COVID-19 when applied to a panel of 44 undiluted swab samples collected from symptomatic patients. In comparison with results obtained through the quantitative reverse transcription polymerase chain reaction method, the proposed immunosensor offered 100 % accuracy, thus emerging as a powerful alternative candidate for routine and decentralized testing, which can be helpful in controlling the COVID-19 outbreak.

Development and application of proficiency testing (PT) to evaluate the diagnostic capacity of SARS-CoV-2 by RT-qPCR - A practical and metrological approach

It is necessary to use quality tools to evaluate the diagnostic capacity of laboratories, such as implementing a proficiency testing (PT) program. The goal of this work is to develop and apply a PT protocol to assess the diagnostic capacity of SARS-CoV-2 through the RT-PCR method, based on appropriate metrological tools. A 5-item test panel containing items with different dilutions of SARS-CoV-2, including negative controls, was developed to perform this PT with the application of different performance assessment tools to score and differentiate performance between laboratories, according to Table 2. Based on the participants' total qualitative result, 95% of the negative samples and 73% of the positive samples were correctly identified by the laboratories. The results obtained were compared e validate the systematics of the PT developed, so that it can be implemented and used to monitor and improve the diagnostic capacity of SARS-CoV-2, also helping to improve the quality of these results.

Two-Dimensional (2D) materials in the detection of SARS-CoV-2

The SARS-CoV-2 pandemic has resulted in a devastating effect on human health in the last three years. While tremendous effort has been devoted to the development of effective treatment and vaccines against SARS-CoV-2 and controlling the spread of it, collective health challenges have been encountered along with the concurrent serious economic impacts. Since the beginning of the pandemic, various detection methods like PCR-based methods, isothermal nucleic acid amplification-based (INAA) methods, serological methods or antibody tests, and evaluation of X-ray chest results have been exploited to diagnose SARS-CoV-2. PCR-based detection methods in these are considered gold standards in the current stage despite their drawbacks, including being high-cost and time-consuming procedures. Furthermore, the results obtained from the PCR tests are susceptible to sample collection methods and time. When the sample is not collected properly, obtaining a false result may be likely. The use of specialized lab equipment and the need for trained people for the experiments pose additional challenges in PCR-based testing methods. Also, similar problems are observed in other molecular and serological methods. Therefore, biosensor technologies are becoming advantageous with their quick response, high specificity and precision, and low-cost characteristics for SARS-CoV-2 detection. In this paper, we critically review the advances in the development of sensors for the detection of SARS-CoV-2 using two-dimensional (2D) materials. Since 2D materials including graphene and graphene-related materials, transition metal carbides, carbonitrides, and nitrides (MXenes), and transition metal dichalcogenides (TMDs) play key roles in the development of novel and high-performance electrochemical (bio)sensors, this review pushes the sensor technologies against SARS-CoV-2 detection forward and highlights the current trends. First, the basics of SARS-CoV-2 detection are described. Then the structure and the physicochemical properties of the 2D materials are explained, which is followed by the development of SARS-CoV-2 sensors by exploiting the exceptional properties of the 2D materials. This critical review covers most of the published papers in detail from the beginning of the outbreak.

Associations between an international COVID-19 job exposure matrix and SARS-CoV-2 infection among 2 million workers in Denmark

OBJECTIVES

This study investigates the associations between the Danish version of a job exposure matrix for COVID-19 (COVID-19-JEM) and Danish register-based SARS-CoV-2 infection information across three waves of the pandemic. The COVID-19-JEM consists of four dimensions on transmission: two on mitigation measures, and two on precarious work characteristics.

METHODS

The study comprised 2 021 309 persons from the Danish working population between 26 February 2020 and 15 December 2021. Logistic regression models were applied to assess the associations between the JEM dimensions and overall score and SARS-CoV-2 infection across three infection waves, with peaks in March-April 2020, December-January 2021, and February-March 2022. Sex, age, household income, country of birth, wave, residential region and during wave 3 vaccination status were accounted for.

RESULTS

Higher risk scores within the transmission and mitigation dimensions and the overall JEM score resulted in higher odds ratios (OR) of a SARS-CoV-2 infection. OR attenuated across the three waves with ranges of 1.08-5.09 in wave 1, 1.06-1.60 in wave 2, and 1.05-1.45 in those not (fully) vaccinated in wave 3. In wave 3, no associations were found for those fully vaccinated. In all waves, the two precarious work dimensions showed weaker or inversed associations.

CONCLUSIONS

The COVID-19-JEM is a promising tool for assessing occupational exposure to SARS-CoV-2 and other airborne infectious agents that mainly spread between people who are in close contact with each other. However, its usefulness depends on applied restrictions and the vaccination status in the population of interest.

Simultaneous Detection of SARS-CoV-2 Nucleoprotein and Receptor Binding Domain by a Multi-Area Reflectance Spectroscopy Sensor

The COVID-19 pandemic has emphasized the urgent need for point-of-care methods suitable for the rapid and reliable diagnosis of viral infections. To address this demand, we report the rapid, label-free simultaneous determination of two SARS-CoV-2 proteins, namely, the nucleoprotein and the receptor binding domain peptide of S1 protein, by implementing a bioanalytical device based on Multi Area Reflectance Spectroscopy. Simultaneous detection of these two proteins is achieved by using silicon chips with adjacent areas of different silicon dioxide thickness on top, each of which is modified with an antibody specific to either the nucleoprotein or the receptor binding domain of SARS-CoV-2. Both areas were illuminated by a single probe that also collected the reflected light, directing it to a spectrometer. The online conversion of the combined reflection spectra from the two silicon dioxide areas into the respective adlayer thickness enabled real-time monitoring of immunoreactions taking place on the two areas. Several antibodies have been tested to define the pair, providing the higher specific signal following a non-competitive immunoassay format. Biotinylated secondary antibodies and streptavidin were used to enhance the specific signal. Both proteins were detected in less than 12 min, with detection limits of 1.0 ng/mL. The assays demonstrated high repeatability with intra- and inter-assay coefficients of variation lower than 10%. Moreover, the recovery of both proteins from spiked samples prepared in extraction buffer from a commercial self-test kit for SARS-CoV-2 collection from nasopharyngeal swabs ranged from 90.0 to 110%. The short assay duration in combination with the excellent analytical performance and the compact instrument size render the proposed device and assay suitable for point-of-care applications.

A lightweight CORONA-NET for COVID-19 detection in X-ray images

Since December 2019, COVID-19 has posed the most serious threat to living beings. With the advancement of vaccination programs around the globe, the need to quickly diagnose COVID-19 in general with little logistics is fore important. As a consequence, the fastest diagnostic option to stop COVID-19 from spreading, especially among senior patients, should be the development of an automated detection system. This study aims to provide a lightweight deep learning method that incorporates a convolutional neural network (CNN), discrete wavelet transform (DWT), and a long short-term memory (LSTM), called CORONA-NET for diagnosing COVID-19 from chest X-ray images. In this system, deep feature extraction is performed by CNN, the feature vector is reduced yet strengthened by DWT, and the extracted feature is detected by LSTM for prediction. The dataset included 3000 X-rays, 1000 of which were COVID-19 obtained locally. Within minutes of the test, the proposed test platform's prototype can accurately detect COVID-19 patients. The proposed method achieves state-of-the-art performance in comparison with the existing deep learning methods. We hope that the suggested method will hasten clinical diagnosis and may be used for patients in remote areas where clinical labs are not easily accessible due to a lack of resources, location, or other factors.

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detection. In this study, we explore the realistic development of DL-driven COVID-19 detection methods and focus on the fully automatic framework using available resources, which can effectively investigate various coronavirus variants through modalities. We conducted an exploration and comparison of several diagnostic techniques that are widely used and globally validated for the detection of COVID-19. Furthermore, we explore review-based studies that provide detailed information on synergistic medicine combinations for the treatment of COVID-19. We recommend DL methods that effectively reduce time, cost, and complexity, providing valuable guidance for utilizing available synergistic combinations in clinical and research settings. This study also highlights the implication of innovative diagnostic technical and instrumental strategies, exploring public datasets, and investigating synergistic medicines using optimised DL rules. By summarizing these findings, we aim to assist future researchers in their endeavours by providing a comprehensive overview of the implication of DL techniques in COVID-19 detection and treatment. Integrating DL methods with various diagnostic approaches holds great promise in improving the accuracy and efficiency of COVID-19 diagnostics, thus contributing to effective control and management of the ongoing pandemic.

An Automated Deep Learning Approach for Spine Segmentation and Vertebrae Recognition Using Computed Tomography Images

Spine image analysis is based on the accurate segmentation and vertebrae recognition of the spine. Several deep learning models have been proposed for spine segmentation and vertebrae recognition, but they are very computationally demanding. In this research, a novel deep learning model is introduced for spine segmentation and vertebrae recognition using CT images. The proposed model works in two steps: (1) A cascaded hierarchical atrous spatial pyramid pooling residual attention U-Net (CHASPPRAU-Net), which is a modified version of U-Net, is used for the segmentation of the spine. Cascaded spatial pyramid pooling layers, along with residual blocks, are used for feature extraction, while the attention module is used for focusing on regions of interest. (2) A 3D mobile residual U-Net (MRU-Net) is used for vertebrae recognition. MobileNetv2 includes residual and attention modules to accurately extract features from the axial, sagittal, and coronal views of 3D spine images. The features from these three views are concatenated to form a 3D feature map. After that, a 3D deep learning model is used for vertebrae recognition. The VerSe 20 and VerSe 19 datasets were used to validate the proposed model. The model achieved more accurate results in spine segmentation and vertebrae recognition than the state-of-the-art methods.

Outcomes of hip fracture surgery during the COVID-19 pandemic

PURPOSE

To investigate if changes to hospital operational models during the COVID-19 pandemic negatively impacted overall time to surgery (TtS) as well as morbidity and mortality rates of hip fractures (HFx).

METHODS

416 patients treated for OTA 31 fractures at a single institution between January 2019 and November 2020 were reviewed. TtS as well as morbidity and mortality rates were obtained from pre-pandemic and pandemic groups.

RESULTS

263 patients were treated pre-pandemic and 153 were treated during the pandemic. There were no significant differences in median TtS, readmission rates (p = 0.134), reoperation rates (p = 0.052), 30-day (p = 0.095) and 90-day (p = 0.22) mortality rates.

CONCLUSION

Reallocation of hospital resources in response to the COVID-19 pandemic did not negatively impact surgical timing or complications. TtS for HFx remains a challenge and often requires multidisciplinary care, which is complicated by a pandemic. However, this study demonstrates HFx standard of care can be maintained despite COVID-19 obstacles to treatment efficiency and efficacy.

Patterns of testing in the extensive Danish national SARS-CoV-2 test set-up

BACKGROUND

The Danish national SARS-CoV-2 mass test system was among the most ambitious worldwide. We describe its set-up and analyse differences in patterns of testing per demography and time period in relation to the three waves of SARS-CoV-2 transmission in Denmark.

METHODS

We included all reported PCR- and rapid antigen-tests performed between 27 February 2020 and 10 March 2022 among all residents aged 2 years or above. Descriptive statistics and Poisson regression models were used to analyse characteristics of individuals tested for SARS-CoV-2 using a national cohort study design.

RESULTS

A total of 63.7 million PCR-tests and 60.0 million rapid antigen-tests were performed in the study period, testing 90.9% and 78.8% of the Danish population at least once by PCR or antigen, respectively. Female sex, younger age, Danish heritage and living in the capital area were all factors positively associated with the frequency of PCR-testing. The association between COVID-19 vaccination and PCR-testing changed from negative to positive over time.

CONCLUSION

We provide details of the widely available, free-of-charge, national SARS-CoV-2 test system, which served to identify infected individuals, assist isolation of infectious individuals and contact tracing, and thereby mitigating the spread of SARS-CoV-2 in the Danish population. The test system was utilized by nearly the entire population at least once, and widely accepted across different demographic groups. However, demographic differences in the test uptake did exist and should be considered in order not to cause biases in studies related to SARS-CoV-2, e.g., studies of transmission and vaccine effectiveness.

Artificial intelligence enabled COVID-19 detection: techniques, challenges and use cases

Deep Learning and Machine Learning are becoming more and more popular as their algorithms get progressively better, and their use is expected to have the large effect on improving the health care system. Also, the pandemic was a chance to show how adding AI to healthcare infrastructure could help, since infrastructures around the world are overworked and falling apart. These new technologies can be used to fight COVID-19 because they are flexible and can be changed. Based on these facts, we looked at how the ML and DL-based models can be used to deal with the COVID-19 pandemic problem and what the pros and cons of each are. This paper gives a full look at the different ways to find COVID-19. We looked at the COVID-19 issues in a systematic way and then rated the methods and techniques for finding it based on their availability, ease of use, accuracy, and cost. We have also shown in pictures how well each of the detection techniques works. We did a comparison of different detection models based on the above factors. This helps researchers understand the different methods and the pros and cons of using them as the basis for their research. In the last part, we talk about the open challenges and research questions that come with putting these techniques together with other detection methods.

The critical role of engineering in the rapid development of COVID-19 diagnostics: Lessons from the RADx Tech Test Verification Core

Engineering plays a critical role in the development of medical devices, and this has been magnified since 2020 as severe acute respiratory syndrome coronavirus 2 swept over the globe. In response to the coronavirus disease 2019, the National Institutes of Health launched the Rapid Acceleration of Diagnostics (RADx) initiative to help meet the testing needs of the United States and effectively manage the pandemic. As the Engineering and Human Factors team for the RADx Tech Test Verification Core, we directly assessed more than 30 technologies that ultimately contributed to an increase of the country's total testing capacity by 1.7 billion tests to date. In this review, we present central lessons learned from this "apples-to-apples" comparison of novel, rapidly developed diagnostic devices. Overall, the evaluation framework and lessons learned presented in this review may serve as a blueprint for engineers developing point-of-care diagnostics, leaving us better prepared to respond to the next global public health crisis rapidly and effectively.

Deep-Learning-Based COVID-19 Diagnosis and Implementation in Embedded Edge-Computing Device

The rapid spread of coronavirus disease 2019 (COVID-19) has posed enormous challenges to the global public health system. To deal with the COVID-19 pandemic crisis, the more accurate and convenient diagnosis of patients needs to be developed. This paper proposes a deep-learning-based COVID-19 detection method and evaluates its performance on embedded edge-computing devices. By adding an attention module and mixed loss into the original VGG19 model, the method can effectively reduce the parameters of the model and increase the classification accuracy. The improved model was first trained and tested on the PC X86 GPU platform using a large dataset (COVIDx CT-2A) and a medium dataset (integrated CT scan); the weight parameters of the model were reduced by around six times compared to the original model, but it still approximately achieved 98.80%and 97.84% accuracy, outperforming most existing methods. The trained model was subsequently transferred to embedded NVIDIA Jetson devices (TX2, Nano), where it achieved 97% accuracy at a 0.6−1 FPS inference speed using the NVIDIA TensorRT engine. The experimental results demonstrate that the proposed method is practicable and convenient; it can be used on a low-cost medical edge-computing terminal. The source code is available on GitHub for researchers.

COVID-19 in early 2023: Structure, replication mechanism, variants of SARS-CoV-2, diagnostic tests, and vaccine & drug development studies

Coronavirus Disease-19 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome-coronaviruses-2 (SARS-CoV-2), a highly pathogenic and transmissible coronavirus. Most cases of COVID-19 have mild to moderate symptoms, including cough, fever, myalgias, and headache. On the other hand, this coronavirus can lead to severe complications and death in some cases. Therefore, vaccination is the most effective tool to prevent and eradicate COVID-19 disease. Also, rapid and effective diagnostic tests are critical in identifying cases of COVID-19. The COVID-19 pandemic has a dynamic structure on the agenda and contains up-to-date developments. This article has comprehensively discussed the most up-to-date pandemic situation since it first appeared. For the first time, not only the structure, replication mechanism, and variants of SARS-CoV-2 (Alpha, Beta, Gamma, Omicron, Delta, Epsilon, Kappa, Mu, Eta, Zeta, Theta, lota, Lambda) but also all the details of the pandemic, such as how it came out, how it spread, current cases, what precautions should be taken, prevention strategies, the vaccines produced, the tests developed, and the drugs used are reviewed in every aspect. Herein, the comparison of diagnostic tests for SARS-CoV-2 in terms of procedure, accuracy, cost, and time has been presented. The mechanism, safety, efficacy, and effectiveness of COVID-19 vaccines against SARS-CoV-2 variants have been evaluated. Drug studies, therapeutic targets, various immunomodulators, and antiviral molecules applied to patients with COVID-19 have been reviewed.

Rapid, Sensitive, Label-Free Electrical Detection of SARS-CoV-2 in Nasal Swab Samples

Rapid diagnosis of coronavirus disease 2019 (COVID-19) is key for the long-term control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) amid renewed threats of mutated SARS-CoV-2 around the world. Here, we report on an electrical label-free detection of SARS-CoV-2 in nasopharyngeal swab samples directly collected from outpatients or in saliva-relevant conditions by using a remote floating-gate field-effect transistor (RFGFET) with a 2-dimensional reduced graphene oxide (rGO) sensing membrane. RFGFET sensors demonstrate rapid detection (<5 min), a 90.6% accuracy from 8 nasal swab samples measured by 4 different devices for each sample, and a coefficient of variation (CV) < 6%. Also, RFGFET sensors display a limit of detection (LOD) of pseudo-SARS-CoV-2 that is 10 000-fold lower than enzyme-linked immunosorbent assays, with a comparable LOD to that of reverse transcription-polymerase chain reaction (RT-PCR) for patient samples. To achieve this, comprehensive systematic studies were performed regarding interactions between SARS-CoV-2 and spike proteins, neutralizing antibodies, and angiotensin-converting enzyme 2, as either a biomarker (detection target) or a sensing probe (receptor) functionalized on the rGO sensing membrane. Taken together, this work may have an immense effect on positioning FET bioelectronics for rapid SARS-CoV-2 diagnostics.

CRISPR-Cas-Driven Single Micromotor (Cas-DSM) Enables Direct Detection of Nucleic Acid Biomarkers at the Single-Molecule Level

The target-dependent endonuclease activity (also known as the trans-cleavage activity) of CRISPR-Cas systems has stimulated great interest in the development of nascent sensing strategies for nucleic acid diagnostics. Despite many attempts, the majority of the sensitive CRISPR-Cas diagnostics strategies mainly rely on nucleic acid preamplification, which generally needs complex probes/primers designs, multiple experimental steps, and a longer testing time, as well as introducing the risk of false-positive results. In this work, we propose the CRISPR-Cas-Driven Single Micromotor (Cas-DSM), which can directly detect the nucleic acid targets at a single-molecule level with high specificity. We have demonstrated that the Cas-DSM is a reliable and practical method for the quantitative detection of DNA/RNA in various complex clinical samples as well as in individual cells without any preamplification processes. Due to the excellent features of the CRISPR/Cas system, including constant temperature, simple design, high specificity, and flexible programmability, the Cas-DSM could serve as a simple and universal platform for nucleic acid detection. More importantly, this work will provide a breakthrough for the development of next-generation amplification-free CRISPR/Cas sensing toolboxes.

Adsorption-Free Self-Priming Direct Digital Dual-crRNA CRISPR/Cas12a-Assisted Chip for Ultrasensitive Detection of Pathogens

Rapid and sensitive pathogen detection methods are critical for disease diagnosis and treatment. RPA-CRISPR/Cas12 systems have displayed remarkable potential in pathogen detection. A self-priming digital PCR chip is a powerful and attractive tool for nucleic detection. However, the application of the RPA-CRISPR/Cas12 system to the self-priming chip still has great challenges due to the problems of protein adsorption and two-step detection mode of RPA-CRISPR/Cas12. In this study, an adsorption-free self-priming digital chip was developed and a direct digital dual-crRNAs (3D) assay was established based on the chip for ultrasensitive detection of pathogens. This 3D assay combined the advantages of rapid amplification of RPA, specific cleavage of Cas12a, accurate quantification of digital PCR, and point-of-care testing (POCT) of microfluidics, enabling accurate and reliable digital absolute quantification of Salmonella in POCT. Our method can provide a good linear relationship of Salmonella detection in the range from 2.58 × 10¹ to 2.58 × 10⁴ cells/mL with a limit of detection ∼0.2 cells/mL within 30 min in a digital chip by targeting the invA gene of Salmonella. Moreover, the assay could directly detect Salmonella in milk without nucleic acid extraction. Therefore, the 3D assay has the significant potential to provide accurate and rapid pathogen detection in POCT. This study provides a powerful nucleic detection platform and facilitates the application of CRISPR/Cas-assisted detection and microfluidic chips.

Application of microfluidic technologies on COVID-19 diagnosis and drug discovery

The ongoing coronavirus disease 2019 (COVID-19) pandemic has boosted the development of antiviral research. Microfluidic technologies offer powerful platforms for diagnosis and drug discovery for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis and drug discovery. In this review, we introduce the structure of SARS-CoV-2 and the basic knowledge of microfluidic design. We discuss the application of microfluidic devices in SARS-CoV-2 diagnosis based on detecting viral nucleic acid, antibodies, and antigens. We highlight the contribution of lab-on-a-chip to manufacturing point-of-care equipment of accurate, sensitive, low-cost, and user-friendly virus-detection devices. We then investigate the efforts in organ-on-a-chip and lipid nanoparticles (LNPs) synthesizing chips in antiviral drug screening and mRNA vaccine preparation. Microfluidic technologies contribute to the ongoing SARS-CoV-2 research efforts and provide tools for future viral outbreaks.

Optimizing SARS-CoV-2 Pooled Testing Strategies Through Differentiated Pooling for Distinct Groups

Pooled testing has been successfully used to expand SARS-CoV-2 testing, especially in settings requiring high volumes of screening of lower-risk individuals, but efficiency of pooling declines as prevalence rises. We propose a differentiated pooling strategy that independently optimizes pool sizes for distinct groups with different probabilities of infection to further improve the efficiency of pooled testing. We compared the efficiency (results obtained per test kit used) of the differentiated strategy with a traditional pooling strategy in which all samples are processed using uniform pool sizes under a range of scenarios. For most scenarios, differentiated pooling is more efficient than traditional pooling. In scenarios examined here, an improvement in efficiency of up to 3.94 results per test kit could be obtained through differentiated versus traditional pooling, with more likely scenarios resulting in 0.12 to 0.61 additional results per kit. Under circumstances similar to those observed in a university setting, implementation of our strategy could result in an improvement in efficiency between 0.03 to 3.21 results per test kit. Our results can help identify settings, such as universities and workplaces, where differentiated pooling can conserve critical testing resources.

Breath Analysis of COVID-19 Patients in a Tertiary UK Hospital by Optical Spectrometry: The E-Nose CoVal Study

Throughout the SARS-CoV-2 pandemic, diagnostic technology played a crucial role in managing outbreaks on a national and global level. One diagnostic modality that has shown promise is breath analysis, due to its non-invasive nature and ability to give a rapid result. In this study, a portable FTIR (Fourier Transform Infra-Red) spectrometer was used to detect chemical components in the breath from Covid positive symptomatic and asymptomatic patients versus a control cohort of Covid negative patients. Eighty-five patients who had a nasopharyngeal polymerase chain reaction (PCR) test for the detection of SARS-CoV-2 within the last 5 days were recruited to the study (36 symptomatic PCR positive, 23 asymptomatic PCR positive and 26 asymptomatic PCR negative). Data analysis indicated significant difference between the groups, with SARS-CoV-2 present on PCR versus the negative PCR control group producing an area under the curve (AUC) of 0.87. Similar results were obtained comparing symptomatic versus control and asymptomatic versus control. The asymptomatic results were higher than the symptomatic (0.88 vs. 0.80 AUC). When analysing individual chemicals, we found ethanol, methanol and acetaldehyde were the most important, with higher concentrations in the COVID-19 group, with symptomatic patients being higher than asymptomatic patients. This study has shown that breath analysis can provide significant results that distinguish patients with or without COVID-19 disease/carriage.

Screening and confirmation tests for SARS-CoV-2: benefits and drawbacks

Background

Coronavirus disease 2019 is a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that emerged in late 2019 and has activated an ongoing international public health emergency. SARS-CoV-2 was discovered in Wuhan, China, in December 2019 and rapidly spread to other cities and countries. Currently, SARS-CoV-2 diagnostic tests have relied heavily on detecting viral genes, antigens, and human antibodies. Hence, this review discusses and analyses the existing screening and confirmation tests for SARS-CoV-2, including the real-time reverse transcriptase polymerase chain reaction (RT-PCR), lateral flow immunoassay (LFIA), and enzyme-linked immunosorbent assay (ELISA).

Main body

The illustrations of each testing were presented to provide the readers with an understanding of the scientific principles behind the testing methods. The comparison was made by highlighting the advantages and disadvantages of each testing. ELISA is ideal for performing the maximum population screening to determine immunological capacity, although its inability to provide reliable results on the status of the infection. Recently, LFIA has been approved as a quicker way of determining whether a patient is infected at the analysis time without using particular instruments and non-laboratory settings. RT-PCR is the gold-standard approach in terms of sensitivity and specificity.

Conclusion

However, the combination of LFIA or ELISA with RT-PCR is also proposed in this review to obtain an adequate level of sensitivity and specificity.

Graphic Abstract

Electrochemical Capillary Driven Immunoassay for Detection of SARS-CoV-2

The COVID-19 pandemic focused attention on a pressing need for fast, accurate, and low-cost diagnostic tests. This work presents an electrochemical capillary driven immunoassay (eCaDI) developed to detect SARS-CoV-2 nucleocapsid (N) protein. The low-cost flow device is made of polyethylene terephthalate (PET) and adhesive films. Upon addition of a sample, reagents and washes are sequentially delivered to an integrated screen-printed carbon electrode for detection, thus automating a full sandwich immunoassay with a single end-user step. The modified electrodes are sensitive and selective for SARS-CoV-2 N protein and stable for over 7 weeks. The eCaDI was tested with influenza A and Sindbis virus and proved to be selective. The eCaDI was also successfully applied to detect nine different SARS-CoV-2 variants, including Omicron.

Can the nucleic acid Ct value of discharged patients infected with SARS-CoV-2 Omicron variant be 35?--A retrospective study on fluctuation of nucleic acid Ct values in SNIEC mobile cabin hospital

Objective

To explore the meaning of cycle threshold (Ct) value fluctuation and the appropriateness of setting the discharge Ct value to 35, which is the current standard in Chinese guidelines.

Method

A retrospective study was conducted on 95 patients with Ct value fluctuation (Ct value below 35 on day 3; group A) and 97 patients with a normal discharge process (control; group B). Their clinical characteristics and follow-up data were collected.

Results

(1) There was no significant difference between the groups in age, gender distribution, number of vaccinations, initial ORF-Ct value, and initial N-Ct value. The proportion of patients complicated with chronic internal disorders, respiratory symptoms, and abnormal chest radiology in group A was significantly higher than that in group B. (2) Between the two groups, there was no significant difference in the ORF-Ct or N-Ct value on day 1, but the ORF-Ct and N-Ct values of group B on days 2 to 4 were significantly higher than those of group A. (3) There was no significant difference between the groups in the ORF-Ct value at discharge, but there was a significant difference in the N-Ct value at discharge. Seven days after discharge, almost 100% of the patients had been cured. The mean negative conversion interval of nucleic acid of the patients in group A was 14.5 ± 4.6 days, which was longer than that of the patients in group B (11.8 ± 4 days). (4) Logistic regression analysis showed that the ORF-Ct value on day 2 was the key factor influencing the Ct value fluctuation.

Conclusion

The fluctuation of Ct value is only a normal phenomenon in the recovery period of the disease, and there is no need for excessive intervention. It is reasonable to set the Ct value of the discharge standard to 35 and retest the nucleic acid on the 10^th day after discharge for patients with underlying diseases or symptoms.

The SHERLOCK Platform: An Insight into Advances in Viral Disease Diagnosis

Persistence and prevalence of microbial diseases (pandemics, epidemics) is the most alarming threats to the human resulting in huge health and economic losses. Rapid detection and understanding of the disease dynamics by molecular biotechnology tools allow for robust reporting, treatment and control of diseases. As per WHO, the optimal diagnostic approach should be quick, specific, sensitive, without a stringed instrument, and low cost. The drawbacks of traditional detection techniques promote the use of CRISPR-mediated nucleic acid detection methods such as SHERLOCK as detection method. It takes advantage of the unexpected in vitro features of CRISPR-Cas system to develop field-deployable sensitive detection tools. Previously, CRISPR-mediated diagnostic methods have extensively been reviewed particularly for SARS-COV-2 detection, but it fails to provide the insight into advances of this technique. This study is the first attempt to review the advances of SHERLOCK approach as diagnostic tool for viral diseases detection. Variations of SHERLOCK mechanism for improved efficiency are discussed. Particularly integrated SHERLOCK approaches in terms of extraction-free assay and Bluetooth-enabled detection are reviewed to access their feasibility for the development of simpler and cost-effective diagnostic toolkits. Insight in to perks and limitations of diagnostic methods indicates its potential as ultimate diagnostic instrument for disease management.

Rapid Conductometric Detection of SARS-CoV-2 Proteins and Its Variants Using Molecularly Imprinted Polymer Nanoparticles

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) biosensors have captured more attention than the conventional methodologies for SARS-CoV-2 detection due to having cost-effective platforms and fast detection. However, these reported SARS-CoV-2 biosensors suffer from drawbacks including issues in detection sensitivity, degradation of biomaterials on the sensor's surface, and incapability to reuse the biosensors. To overcome these shortcomings, molecularly imprinted polymer nanoparticles (nanoMIPs) incorporated conductometric biosensor for highly accurate, rapid, and selective detection of two model SARS-CoV-2 proteins: (i) receptor binding domain (RBD) of the spike (S) glycoprotein and (ii) full length trimeric spike protein are introduced. In addition, these biosensors successfully responded to several other SARS-CoV-2 RBD spike protein variants including Alpha, Beta, Gamma, and Delta. Our conductometric biosensor selectively detects the two model proteins and SARS-CoV-2 RBD spike protein variant samples in real-time with sensitivity to a detection limit of 7 pg mL-1 within 10 min of sample incubation. A battery-free, wireless near-field communication (NFC) interface is incorporated with the biosensor for fast and contactless detection of SARS-CoV-2 variants. The smartphone enabled real-time detection and on-screen rapid result for SARS-CoV-2 variants can curve the outbreak due to its ability to alert the user to infection in real time.

Label-free and portable field-effect sensor for monitoring RT-LAMP products to detect SARS-CoV-2 in wastewater

The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has proven the need for developing reliable and affordable technologies to detect pathogens. Particularly, the detecting the genome in wastewater could be an indicator of the transmission rate to alert on new outbreaks. However, wastewater-based epidemiology remains a technological challenge to develop affordable technologies for sensing pathogens. In this work, we introduce a label-free and portable field-effect transistor (FET)-based sensor to detect N and ORF1ab genes of the SARS-CoV-2 genome. Our sensor integrates the reverse transcription loop-mediated isothermal amplification (RT-LAMP) reaction as a cost-effective molecular detection exhibiting high specificity. The detection relies upon pH changes, due to the RT-LAMP reaction products, which are detected through a simple, but effective, extended-gate FET sensor (EGFET). We evaluate the proposed device by measuring real wastewater samples to detect the presence of SARS-CoV-2 genome, achieving a limit of detection of 0.31 × 10⁻³ ng/μL for end-point measurement. Moreover, we find the ability of the sensor to perform real-time-like analysis, showing that the RT-LAMP reaction provides a good response after 15 min for concentrations as low as 0.37 ng/μL. Hence, we show that our EGFET sensor offers a powerful tool to detect the presence of the SARS-CoV-2 genome with a naked-eye method, in a straightforward way than the conventional molecular methods for wastewater analysis.

SARS-CoV-2-on-Chip for Long COVID Management

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a "wicked evil" in this century due to its extended progression and huge human mortalities. Although the diagnosis of SARS-CoV-2 viral infection is made simple and practical by employing reverse transcription polymerase chain reaction (RT-PCR) investigation, the process is costly, complex, time-consuming, and requires experts for testing and the constraints of a laboratory. Therefore, these challenges have raised the paradigm of on-site portable biosensors on a single chip, which reduces human resources and enables remote access to minimize the overwhelming burden on the existing global healthcare sector. This article reviews the recent advancements in biosensors for long coronavirus disease (COVID) management using a multitude of devices, such as point-of-care biosensors and lab-on-chip biosensors. Furthermore, it details the shift in the paradigm of SARS-CoV-2-on-chip biosensors from the laboratory to on-site detection with intelligent and economical operation, representing near-future diagnostic technologies for public health emergency management.

Fluorescent nanodiamond-based spin-enhanced lateral flow immunoassay for detection of SARS-CoV-2 nucleocapsid protein and spike protein from different variants

SARS-CoV-2 viruses, responsible for the COVID-19 pandemic, continues to evolve into new mutations, which poses a significant threat to public health. Current testing methods have some limitations, such as long turnaround times, high costs, and professional laboratory requirements. In this report, the novel Spin-Enhanced Lateral Flow Immunoassay (SELFIA) platform and fluorescent nanodiamond (FND) reporter were utilized for the rapid detection of SARS-CoV-2 nucleocapsid and spike antigens from different variants, including wild-type (Wuhan-1), Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529). The SARS-CoV-2 antibodies were conjugated with FND via nonspecific binding, enabling the detection of SARS-CoV-2 antigens via both direct and competitive SELFIA format. Direct SELFIA was performed by directly adding the SARS-CoV-2 antibodies-conjugated FND on the antigens-immobilized nitrocellulose (NC) membrane. Conversely, the SARS-CoV-2 antigen-containing sample was first incubated with the antibodies-conjugated FND, and then dropped on the antigen-immobilized NC membrane to carry out the competitive SELFIA. The results suggested that S44F anti-S IgG antibody can be efficiently used for the detection of wild-type, Alpha, Delta, and Omicron variants spike antigens. Findings were comparable in direct SELFIA, competitive SELFIA, and ELISA. A detection limit of 1.94, 0.77, 1.14, 1.91, and 1.68 ng/mL can be achieved for SARS-CoV-2 N protein, wild-type, Alpha, Delta, and Omicron S proteins, respectively, via competitive SELFIA assay. These results suggest that a direct SELFIA assay can be used for antibody/antigen pair screening in diagnosis development, while the competitive SELFIA assay can serve as an accurate quantitative diagnostic tool. The simplicity and rapidity of the SELFIA platform were demonstrated, which can be leveraged in the detection of other infectious diseases in the near future.

A Comparative Study of Voltammetric vs Impedimetric Immunosensor for Rapid SARS-CoV-2 Detection at the Point-of-care

Here, a novel biosensing platform for the detection of SARS-CoV-2 usable both at voltammetric and impedimetric mode is reported. The platform was constructed on a multi-walled carbon nanotubes (MWCNTs) screen-printed electrode (SPE) functionalized by methylene blue (MB), antibodies against SARS-CoV-2 spike protein (SP), a bioactive layer of chitosan (CS) and protein A (PrA). The voltammetric sensor showed superior performances both in phosphate buffer solution (PBS) and spiked-saliva samples, with LOD values of 5.0±0.1 and 30±2.1 ng/mL, compared to 20±1.8 and 50±2.5 ng/mL for the impedimetric sensor. Moreover, the voltammetric immunosensor was tested in real saliva, showing promising results.

Colorimetric Detection of the SARS-CoV-2 Virus (COVID-19) in Artificial Saliva Using Polydiacetylene Paper Strips

The spread and resurgence of the SARS-CoV-2 virus (COVID-19 disease) threatens human health and social relations. Prevention of COVID-19 disease partly relies on fabricating low-cost, point-of-care (POC) sensing technology that can rapidly and selectively detect the SARS-CoV-2 virus. We report a colorimetric, paper-based polydiacetylene (PDA) biosensor, designed to detect SARS-CoV-2 spike protein in artificial saliva. Analytical characterizations of the PDA sensor using NMR and FT-IR spectroscopy showed the correct structural elucidation of PCDA-NHS conjugation. The PDA sensor platform containing the N-Hydroxysuccinimide ester of 10, 12-pentacosadiynoic acid (PCDA-NHS) was divided into three experimental PCDA-NHS concentration groups of 10%, 20%, and 30% to optimize the performance of the sensor. The optimal PCDA-NHS molar concentration was determined to be 10%. The PDA sensor works by a color change from blue to red as its colorimetric output when the immobilized antibody binds to the SARS-CoV-2 spike protein in saliva samples. Our results showed that the PDA sensing platform was able to rapidly and qualitatively detect the SARS-CoV-2 spike protein within the concentration range of 1 to 100 ng/mL after four hours of incubation. Further investigation of pH and temperature showed minimal influence on the PDA sensor for the detection of COVID-19 disease. After exposure to the SARS-CoV-2 spike protein, smartphone images of the PDA sensor were used to assess the sensor output by using the red chromatic shift (RCS) of the signal response. These results indicate the potential and practical use of this PDA sensor design for the rapid, colorimetric detection of COVID-19 disease in developing countries with limited access to medical testing.

Capillary-Assisted Molecular Pendulum Bioanalysis

The development of robust biosensing strategies that can be easily implemented in everyday life remains a challenge for the future of modern biosensor research. While several reagentless approaches have attempted to address this challenge, they often achieve user-friendliness through sacrificing sensitivity or universality. While acceptable for certain applications, these trade-offs hinder the widespread adoption of reagentless biosensing technologies. Here, we report a novel approach to reagentless biosensing that achieves high sensitivity, rapid detection, and universality using the SARS-CoV-2 virus as a model target. Universality is achieved by using nanoscale molecular pendulums, which enables reagentless electrochemical biosensing through a variable antibody recognition element. Enhanced sensitivity and rapid detection are accomplished by incorporating the coffee-ring phenomenon into the sensing scheme, allowing for target preconcentration on a ring-shaped electrode. Using this approach, we obtained limits of detection of 1 fg/mL and 20 copies/mL for the SARS-CoV-2 nucleoproteins and viral particles, respectively. In addition, clinical sample analysis showed excellent agreement with Ct values from PCR-positive SARS-CoV-2 patients.

A survey of COVID-19 in public transportation: Transmission risk, mitigation and prevention

The COVID-19 pandemic is posing significant challenges to public transport operators by drastically reducing demand while also requiring them to implement measures that minimize risks to the health of the passengers. While the collective scientific understanding of the SARS-CoV-2 virus and COVID-19 pandemic are rapidly increasing, currently there is a lack of understanding of how the COVID-19 relates to public transport operations. This article presents a comprehensive survey of the current research on COVID-19 transmission mechanisms and how they relate to public transport. We critically assess literature through a lens of disaster management and survey the main transmission mechanisms, forecasting, risks, mitigation, and prevention mechanisms. Social distancing and control on passenger density are found to be the most effective mechanisms. Computing and digital technology can support risk control. Based on our survey, we draw guidelines for public transport operators and highlight open research challenges to establish a research roadmap for the path forward.

Improving immunoassay detection accuracy of anti-SARS-CoV-2 antibodies through dual modality validation

A novel test strategy is proposed with dual-modality detection techniques for COVID-19 antibody detection. The full-length S protein of SARS-CoV-2 was chemically immobilized on a glass surface to capture anti-SARS-CoV-2 IgG in patient serum and was detected through either Electrochemical Impedance Spectroscopy (EIS) or fluorescence imaging with labeled secondary antibodies. Gold nanoparticles conjugated with protein G were used as the probe and the bound GNP-G was detected through EIS measurements. Anti-human-IgG conjugated with the fluorescent tag Alexa Fluor 488 was used as the probe for fluorescence imaging. Clinical SARS-CoV-2 IgG positive serum and negative controls were used to validate both modalities. For fluorescence-based detection, a high sensitivity was noticed with a quantification range of 0.01-0.1 A.U.C. and a LOD of 0.004 A.U.C. This study demonstrates the possibility of utilizing different measurement techniques in conjunction for improved COVID-19 serology testing.

Designing isolation guidelines for COVID-19 patients with rapid antigen tests

Appropriate isolation guidelines for COVID-19 patients are warranted. Currently, isolating for fixed time is adopted in most countries. However, given the variability in viral dynamics between patients, some patients may no longer be infectious by the end of isolation, whereas others may still be infectious. Utilizing viral test results to determine isolation length would minimize both the risk of prematurely ending isolation of infectious patients and the unnecessary individual burden of redundant isolation of noninfectious patients. In this study, we develop a data-driven computational framework to compute the population-level risk and the burden of different isolation guidelines with rapid antigen tests (i.e., lateral flow tests). Here, we show that when the detection limit is higher than the infectiousness threshold values, additional consecutive negative results are needed to ascertain infectiousness status. Further, rapid antigen tests should be designed to have lower detection limits than infectiousness threshold values to minimize the length of prolonged isolation.

Diagnosis Methods for COVID-19: A Systematic Review

At the end of 2019, the coronavirus appeared and spread extremely rapidly, causing millions of infections and deaths worldwide, and becoming a global pandemic. For this reason, it became urgent and essential to find adequate tests for an accurate and fast diagnosis of this disease. In the present study, a systematic review was performed in order to provide an overview of the COVID-19 diagnosis methods and tests already available, as well as their evolution in recent months. For this purpose, the Science Direct, PubMed, and Scopus databases were used to collect the data and three authors independently screened the references, extracted the main information, and assessed the quality of the included studies. After the analysis of the collected data, 34 studies reporting new methods to diagnose COVID-19 were selected. Although RT-PCR is the gold-standard method for COVID-19 diagnosis, it cannot fulfill all the requirements of this pandemic, being limited by the need for highly specialized equipment and personnel to perform the assays, as well as the long time to get the test results. To fulfill the limitations of this method, other alternatives, including biological and imaging analysis methods, also became commonly reported. The comparison of the different diagnosis tests allowed to understand the importance and potential of combining different techniques, not only to improve diagnosis but also for a further understanding of the virus, the disease, and their implications in humans.

Life barcoded by DNA barcodes

The modern concept of DNA-based barcoding for cataloguing biodiversity was proposed in 2003 by first adopting an approximately 600 bp fragment of the mitochondrial COI gene to compare via nucleotide alignments with known sequences from specimens previously identified by taxonomists. Other standardized regions meeting barcoding criteria then are also evolving as DNA barcodes for fast, reliable and inexpensive assessment of species composition across all forms of life, including animals, plants, fungi, bacteria and other microorganisms. Consequently, global DNA barcoding campaigns have resulted in the formation of many online workbenches and databases, such as BOLD system, as barcode references, and facilitated the development of mini-barcodes and metabarcoding strategies as important extensions of barcode techniques. Here we intend to give an overview of the characteristics and features of these barcode markers and major reference libraries existing for barcoding the planet’s life, as well as to address the limitations and opportunities of DNA barcodes to an increasingly broader community of science and society.

Electrochemical Biosensor for SARS-CoV-2 cDNA Detection Using AuPs-Modified 3D-Printed Graphene Electrodes

A low-cost and disposable graphene polylactic (G-PLA) 3D-printed electrode modified with gold particles (AuPs) was explored to detect the cDNA of SARS-CoV-2 and creatinine, a potential biomarker for COVID-19. For that, a simple, non-enzymatic electrochemical sensor, based on a Au-modified G-PLA platform was applied. The AuPs deposited on the electrode were involved in a complexation reaction with creatinine, resulting in a decrease in the analytical response, and thus providing a fast and simple electroanalytical device. Physicochemical characterizations were performed by SEM, EIS, FTIR, and cyclic voltammetry. Square wave voltammetry was employed for the creatinine detection, and the sensor presented a linear response with a detection limit of 0.016 mmol L-1. Finally, a biosensor for the detection of SARS-CoV-2 was developed based on the immobilization of a capture sequence of the viral cDNA upon the Au-modified 3D-printed electrode. The concentration, immobilization time, and hybridization time were evaluated in presence of the DNA target, resulting in a biosensor with rapid and low-cost analysis, capable of sensing the cDNA of the virus with a good limit of detection (0.30 µmol L-1), and high sensitivity (0.583 µA µmol-1 L). Reproducible results were obtained (RSD = 1.14%, n = 3), attesting to the potentiality of 3D-printed platforms for the production of biosensors.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbour embedding (tSNE) and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.