Molecular diagnostic technologies for COVID-19: Limitations and challenges

Accurate and reliable surface-enhanced Raman spectroscopy assay for early detection of SARS-CoV-2 RNA with exceptional sensitivity

This research proposes a highly sensitive and simple surface-enhanced Raman spectroscopy (SERS) assay for the detection of SARS-CoV-2 RNA using suitably designed probes specific for RdRp and N viral genes attached to a Raman marker. The sensitivity of the assay was optimized through precise adjustments to the conditions of immobilization and hybridization processes of the target RNA, including modifications to factors such as time and temperature. The assay achieved a remarkable sensitivity down to 58.39 copies/mL, comparable to or lower than the sensitivities reported for commercial fluorescent polymerase chain reaction (PCR) based methods. It has good selectivity in discriminating SARS-CoV-2 RNA against other respiratory viruses, respiratory syncytial virus (RSV), and influenza A virus. The reliability of the assay was validated by testing 24 clinical samples, including 12 positive samples with varying cycle threshold (Ct) values and 12 negative samples previously tested using real-time PCR. The assay consistently predicted true results that were in line with the PCR results for all samples. Furthermore, the assay demonstrated a notable limit of detection (LOD) of Ct (38 for RdRp gene and 37.5 for N-gene), indicating its capability to detect low concentrations of the target analyte and potentially facilitating early detection of the pathogen.

Development of a reverse transcription loop-mediated isothermal amplification assay with novel quantitative pH biosensor readout method for SARS-CoV-2 detection

Reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a molecular amplification method that can detect SARS-CoV-2 in a shorter time than the current gold-standard molecular diagnostic reverse transcription-polymerase chain reaction (RT-PCR). However, previously developed RT-LAMP assays have mostly relied on highly subjective visual colorimetric interpretation. In this study, an RT-LAMP assay was developed with quantitative measurement of reaction pH using a novel portable pH biosensor compared to qualitative colorimetric interpretation and gel electrophoresis, with 57 clinical COVID-19 samples used for validation of the test. The LoD of the assay is 103 copies/μL. The highest sensitivity was found in the qualitative methods (93.75%), while the highest specificity and likelihood ratio was found in the pH sensor (87.5% and 6.72). On the sensor measurement, a significant difference (p < 0.0001) was observed between the average pH of the RT-PCR (+) COVID-19 (6.15 ± 0.27), while the average pH of the RT-PCR (-) samples (6.72 ± 0.22). Correlation analysis revealed a strong correlation (r = 0.78, p < 0.0001) between the Ct values obtained from RT-PCR with the biosensor pH readout. RT-LAMP with the quantitative pH sensor readout method has the potential to be further developed as an objective molecular assay for rapid and simple detection of SARS-CoV-2.

Addressing label noise for electronic health records: insights from computer vision for tabular data

The analysis of extensive electronic health records (EHR) datasets often calls for automated solutions, with machine learning (ML) techniques, including deep learning (DL), taking a lead role. One common task involves categorizing EHR data into predefined groups. However, the vulnerability of EHRs to noise and errors stemming from data collection processes, as well as potential human labeling errors, poses a significant risk. This risk is particularly prominent during the training of DL models, where the possibility of overfitting to noisy labels can have serious repercussions in healthcare. Despite the well-documented existence of label noise in EHR data, few studies have tackled this challenge within the EHR domain. Our work addresses this gap by adapting computer vision (CV) algorithms to mitigate the impact of label noise in DL models trained on EHR data. Notably, it remains uncertain whether CV methods, when applied to the EHR domain, will prove effective, given the substantial divergence between the two domains. We present empirical evidence demonstrating that these methods, whether used individually or in combination, can substantially enhance model performance when applied to EHR data, especially in the presence of noisy/incorrect labels. We validate our methods and underscore their practical utility in real-world EHR data, specifically in the context of COVID-19 diagnosis. Our study highlights the effectiveness of CV methods in the EHR domain, making a valuable contribution to the advancement of healthcare analytics and research.

COVID-19: Post infection implications in different age groups, mechanism, diagnosis, effective prevention, treatment, and recommendations

SARS-CoV-2 is a highly contagious pathogen that predominantly caused the COVID-19 pandemic. The persistent effects of COVID-19 are defined as an inflammatory or host response to the virus that begins four weeks after initial infection and persists for an undetermined length of time. Chronic effects are more harmful than acute ones thus, this review explored the long-term effects of the virus on various human organs, including the pulmonary, cardiovascular, and neurological, reproductive, gastrointestinal, musculoskeletal, endocrine, and lymphoid systems and found that SARS-CoV-2 adversely affects these organs of older adults. Regarding diagnosis, the RT-PCR is a gold standard method of diagnosing COVID-19; however, it requires specialized equipment and personnel for performing assays and a long time for results production. Therefore, to overcome these limitations, artificial intelligence employed in imaging and microfluidics technologies is the most promising in diagnosing COVID-19. Pharmacological and non-pharmacological strategies are the most effective treatment for reducing the persistent impacts of COVID-19 by providing immunity to post-COVID-19 patients by reducing cytokine release syndrome, improving the T cell response, and increasing the circulation of activated natural killer and CD8 T cells in blood and tissues, which ultimately reduces fever, nausea, fatigue, and muscle weakness and pain. Vaccines such as inactivated viral, live attenuated viral, protein subunit, viral vectored, mRNA, DNA, or nanoparticle vaccines significantly reduce the adverse long-term virus effects in post-COVID-19 patients; however, no vaccine was reported to provide lifetime protection against COVID-19; consequently, protective measures such as physical separation, mask use, and hand cleansing are promising strategies. This review provides a comprehensive knowledge of the persistent effects of COVID-19 on people of varying ages, as well as diagnosis, treatment, vaccination, and future preventative measures against the spread of SARS-CoV-2.

A Portable Fluorescent Lateral Flow Immunoassay Platform for Rapid Detection of FluA

The spread of the FluA virus poses significant public health concerns worldwide. Fluorescent lateral flow immunoassay (LFIA) test strips have emerged as vital tools for the early detection and monitoring of influenza infections. However, existing quantitative virus-detection methods, particularly those utilizing smartphone-based sensing platforms, encounter accessibility challenges in resource-limited areas and among the elderly population. Despite their advantages in speed and portability, these platforms often lack user-friendliness for these demographics, impeding their widespread utilization. To address these challenges, this study proposes leveraging the optical pick-up unit (OPU) sourced from commercial optical drives as a readily available fluorescence excitation module for the quantitative detection of antibodies labeled with quantum-dot fluorescent microspheres. Additionally, we utilize miniaturized and high-performance optical components and 3D-printed parts, along with a customized control system, to develop an affordable point-of-care testing (POCT) device. Within the system, a stepping motor scans the test strip from the T-line to the C-line, enabling the calculation of the fluorescence-intensity ratio between the two lines. This simple yet effective design facilitates rapid and straightforward field or at-home testing for FluA. The proposed prototype platform demonstrates promising performance, achieving a limit of detection (LOD) of 2.91 ng/mL, a total detection time of no more than 15 min, and dimensions of 151 mm × 11.2 mm × 10.8 mm3. We believe that the proposed approach holds great potential for improving access to an accurate influenza diagnosis.

Multiplex detection of bacterial pathogens by PCR/SERS assay

Bacterial infections are a leading cause of death globally. The detection of DNA sequences correlated to the causative pathogen has become a vital tool in medical diagnostics. In practice, PCR-based assays for the simultaneous detection of multiple pathogens currently rely on probe-based quantitative strategies that require expensive equipment but have limited sensitivity or multiplexing capabilities. Hence, novel approaches to address the limitations of the current gold standard methods are still in high demand. In this study, we propose a simple multiplex PCR/SERS assay for the simultaneous detection of four bacterial pathogens, namely P. aeruginosa, S. aureus, S. epidermidis, and M. smegmatis. Wherein, specific primers for amplifying each target gDNA were applied, followed by applying SERS nanotags functionalized with complementary DNA probes and Raman reporters for specific identification of the target bacterial pathogens. The PCR/SERS assay showed high specificity and sensitivity for genotyping bacterial pathogen gDNA, whereby as few as 100 copies of the target gDNA could be detected. With high sensitivity and the convenience of standard PCR amplification, the proposed assay shows great potential for the sensitive detection of multiple pathogen infections to aid clinical decision-making.

Influence of storage solution, temperature, assay time and concentration on RT-qPCR nucleic acid detection for SARS-CoV-2 detection of SARS-CoV-2 by the RT-qPCR

Real-time reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) is an important method for the early diagnosis of coronavirus disease 2019 (COVID-19). This study investigated the effects of storage solution, temperature and detection time on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid detection by RT-qPCR. Various concentrations of SARS-CoV-2 were added to inactive and non-inactive storage solution and the viral suspensions were stored at various temperatures (room temperature, 4, -20 and -80 °C). Then, at five different detection time points, the Ct values were determined by RT-qPCR. Active and inactive storage solutions and storage temperature have a great impact on the detection of N gene of SARS-CoV-2 at different concentration corridors but have little impact on the ORF gene. The storage time has a greater impact on the N gene and ORF gene at high concentrations but has no effect on the two genes at low concentrations. In conclusion, storage temperature, storage time and storage status (inactivated, non-inactivated) have no effect on the nucleic acid detection of SARS-CoV-2 at the same concentration. For different concentrations of SARS-CoV-2, the detection of N gene is mainly affected.

Long Term Impact of Adeno-tonsillectomy on Immunity Against Respiratory Viral Infections; Evidence Deduced During COVID-19 Pandemic

OBJECTIVES

To evaluate the risk of acquiring COVID-19 infection in patients who have undergone adeno-tonsillectomy (AT) as compared to their siblings.

METHODS

In this bidirectional cohort control study, 36 cohorts, younger than 18 y, who underwent AT, and 27 controls (siblings of the enrolled cohorts, younger than 18 y) were recruited. Incidence of COVID-19 was analyzed by symptoms suggestive of COVID-19 infection, COVID-19 testing, and SARS-CoV-2 specific antibody measurement.

RESULTS

In the cohort group, the overall COVID-19 positivity rate was 80.5% (n = 29/36) and symptomatic COVID-19 positivity rate was 68.9% (n = 20/29). Among the controls, the overall COVID-19 positivity rate was 44% (n = 12/27) and symptomatic COVID-19 positivity rate was 16% (n = 2/12). The cohorts had 1.8 times higher risk of contracting COVID-19 infection and the relative risk of symptomatic COVID-19 infections as compared to controls was 4.14.

CONCLUSIONS

This pilot study indicates that adeno-tonsillectomy poses children at a significantly higher risk of COVID-19 infections and likely other viral upper respiratory tract infections.

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.

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients

Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effectively curb the spread of the disease. Therefore, the present study was conducted within a controlled clinical environment to determine eventual detectable variations in the voice of COVID-19 patients, recovered and healthy subjects, and also to determine whether machine learning-based voice assessment (MLVA) can accurately discriminate between them, thus potentially serving as a more effective mass-screening tool. Three different subpopulations were consecutively recruited: positive COVID-19 patients, recovered COVID-19 patients and healthy individuals as controls. Positive patients were recruited within 10 days from nasal swab positivity. Recovery from COVID-19 was established clinically, virologically and radiologically. Healthy individuals reported no COVID-19 symptoms and yielded negative results at serological testing. All study participants provided three trials for multiple vocal tasks (sustained vowel phonation, speech, cough). All recordings were initially divided into three different binary classifications with a feature selection, ranking and cross-validated RBF-SVM pipeline. This brough a mean accuracy of 90.24%, a mean sensitivity of 91.15%, a mean specificity of 89.13% and a mean AUC of 0.94 across all tasks and all comparisons, and outlined the sustained vowel as the most effective vocal task for COVID discrimination. Moreover, a three-way classification was carried out on an external test set comprised of 30 subjects, 10 per class, with a mean accuracy of 80% and an accuracy of 100% for the detection of positive subjects. Within this assessment, recovered individuals proved to be the most difficult class to identify, and all the misclassified subjects were declared positive; this might be related to mid and short-term vocal traces of COVID-19, even after the clinical resolution of the infection. In conclusion, MLVA may accurately discriminate between positive COVID-19 patients, recovered COVID-19 patients and healthy individuals. Further studies should test MLVA among larger populations and asymptomatic positive COVID-19 patients to validate this novel screening technology and test its potential application as a potentially more effective surveillance strategy for COVID-19.

Rapid and sensitive point-of-care diagnosis of human cytomegalovirus infection using RPA-CRISPR technology

Background

Human cytomegalovirus (HCMV) is a common herpesvirus that can cause a range of symptoms, from mild conditions such as fevers to severe illnesses like pneumonia. Early and accurate diagnosis of HCMV infection is crucial, particularly for vulnerable populations with limited medical care. However, current diagnostic methods are often expensive, time-consuming, and require skilled technicians.

Materials and methods

We developed an HCMV-RPA-CRISPR diagnosis platform for the rapid and cost-effective detection of HCMV infection. This method utilizes recombinase polymerase amplification (RPA) to amplify the HCMV target gene isothermally without the need for thermal cycling equipment. The platform integrates the CRISPR/Cas12a system, significantly enhancing specificity and sensitivity. A total of 13 clinical blood samples were tested to evaluate the platform's effectiveness and accuracy. Additionally, a lateral flow assay (LFA) and fluorescence detection were incorporated for straightforward and rapid visual interpretation of the results.

Results

The assay effectively detected concentrations as low as a single copy of the positive control plasmid per microliter in under 1 h, without requiring specialized equipment or training. In clinical sample evaluations, both the fluorescence readout and LFA exhibited 100% sensitivity and specificity, identifying four HCMV-positive and nine HCMV-negative samples.

Conclusion

The HCMV-RPA-CRISPR diagnosis platform is comparably effective to qPCR for HCMV diagnosis. Its applicability in common clinical laboratories, clinics, and point-of-care settings, particularly in resource-limited environments, makes it a valuable tool for widespread HCMV screening and diagnosis.

A photocontrolled one-pot isothermal amplification and CRISPR-Cas12a assay for rapid detection of SARS-CoV-2 Omicron variants

CRISPR-Cas technology has widely been applied to detect single-nucleotide mutation and is considered as the next generation of molecular diagnostics. We previously reported the combination of nucleic acid amplification (NAA) and CRISPR-Cas12a system to distinguish major severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. However, the mixture of NAA and CRISPR-Cas12a reagents in one tube could interfere with the efficiency of NAA and CRISPR-Cas12a cleavage, which in turn affects the detection sensitivity. In the current study, we employed a novel photoactivated CRISPR-Cas12a strategy integrated with recombinase polymerase amplification (RPA) to develop one-pot RPA/CRISPR-Cas12a genotyping assay for detecting SARS-CoV-2 Omicron sub-lineages. The new system overcomes the potential inhibition of RPA due to early CRISPR-Cas12a activation and cleavage of the target template in traditional one-pot assay using photocleavable p-RNA, a complementary single-stranded RNA to specifically bind crRNA and precisely block Cas12a activation. The detection can be finished in one tube at 39℃ within 1 h and exhibits a low limit of detection of 30 copies per reaction. Our results demonstrated that the photocontrolled one-pot RPA/CRISPR-Cas12a assay could effectively identify three signature mutations in the spike gene of SARS-CoV-2 Omicron variant, namely, R346T, F486V, and 49X, and distinguish Omicron BA.1, BA.5.2, and BF.7 sub-lineages. Furthermore, the assay achieved a sensitivity of 97.3% and a specificity of 100.0% and showed a concordance of 98.3% with Sanger sequencing results.IMPORTANCEWe successfully developed one-pot recombinase polymerase amplification/CRISPR-Cas12a genotyping assay by adapting photocontrolled CRISPR-Cas technology to optimize the conditions of nucleic acid amplification and CRISPR-Cas12a-mediated detection. This innovative approach was able to quickly distinguish severe acute respiratory syndrome coronavirus 2 Omicron variants and can be readily modified for detecting any nucleic acid mutations. The assay system demonstrates excellent clinical performance, including rapid detection, user-friendly operations, and minimized risk of contamination, which highlights its promising potential as a point-of-care testing for wide applications in resource-limiting settings.

Low-Cost Arduino Reverse Transcriptase Loop-Mediated Isothermal Amplification (RT-LAMP) for Sensitive Nucleic Acid Detection

This work presents a low-cost transcription loop-mediated isothermal amplification (RT-LAMP) instrument for nucleic acid detection, employing an Arduino Nano microcontroller. The cooling system includes customized printed circuit boards (PCBs) that serve as electrical resistors and incorporate fans. An aluminum block is designed to accommodate eight vials. The system also includes two PCB heaters-one for sample heating and the other for vial lid heating to prevent condensation. The color detection system comprises a TCS3200 color 8-sensor array coupled to one side of the aluminum heater body and a white 8-LED array coupled to the other side, controlled by two Multiplexer/Demultiplexer devices. LED light passes through the sample, reaching the color sensor and conveying color information crucial for detection. The top board is maintained at 110 ± 2 °C, while the bottom board is held at 65 ± 0.5 °C throughout the RT-LAMP assay. Validation tests successfully demonstrated the efficacy of the colorimetric RT-LAMP reactions using SARS-CoV-2 RNA amplification as a sample viability test, achieving 100% sensitivity and 97.3% specificity with 66 clinical samples. Our instrument offers a cost-effective (USD 100) solution with automated result interpretation and superior sensitivity compared to visual inspection. While the prototype was tested with SARS-CoV-2 RNA samples, its versatility extends to detecting other pathogens using alternative primers, showcasing its potential for broader applications in biosensing.

Research on accurate pipetting complementation model for high-throughput molecular detection platform

The incidence of infectious diseases has risen in recent years, leading to a significant surge in the demand for medical molecular detection. High-throughput molecular detection platforms play a crucial role in facilitating rapid and efficient molecular detection. Among the various techniques employed in high-throughput molecular detection, microliquid transfer stands out as one of the most frequently utilized methods. However, ensuring the accuracy of liquid transfer poses a challenge due to variations in the physical and chemical properties of different samples and reagents. In this study, a pipetting complementation model was developed specifically for the serum, paraffin oil, and throat swabs. The aim was to enhance the transfer accuracy of diverse liquids in the context of high-throughput molecular detection, ultimately ensuring detection reliability and stability. The experimental findings revealed notable improvements in pipetting accuracy after compensating for the three liquids. In particular, the pipetting error rates decreased by 52.5, 96, and 71.4% for serum, paraffin oil, and throat swabs, respectively. These results underscore the model's effectiveness in providing reliable support for the precise transfer of liquids on the high-throughput molecular detection platform.

Antivirals for Broader Coverage against Human Coronaviruses

Coronaviruses (CoVs) are enveloped positive-sense single-stranded RNA viruses with a genome that is 27-31 kbases in length. Critical genes include the spike (S), envelope (E), membrane (M), nucleocapsid (N) and nine accessory open reading frames encoding for non-structural proteins (NSPs) that have multiple roles in the replication cycle and immune evasion (1). There are seven known human CoVs that most likely appeared after zoonotic transfer, the most recent being SARS-CoV-2, responsible for the COVID-19 pandemic. Antivirals that have been approved by the FDA for use against COVID-19 such as Paxlovid can target and successfully inhibit the main protease (MPro) activity of multiple human CoVs; however, alternative proteomes encoded by CoV genomes have a closer genetic similarity to each other, suggesting that antivirals could be developed now that target future CoVs. New zoonotic introductions of CoVs to humans are inevitable and unpredictable. Therefore, new antivirals are required to control not only the next human CoV outbreak but also the four common human CoVs (229E, OC43, NL63, HKU1) that circulate frequently and to contain sporadic outbreaks of the severe human CoVs (SARS-CoV, MERS and SARS-CoV-2). The current study found that emerging antiviral drugs, such as Paxlovid, could target other CoVs, but only SARS-CoV-2 is known to be targeted in vivo. Other drugs which have the potential to target other human CoVs are still within clinical trials and are not yet available for public use. Monoclonal antibody (mAb) treatment and vaccines for SARS-CoV-2 can reduce mortality and hospitalisation rates; however, they target the Spike protein whose sequence mutates frequently and drifts. Spike is also not applicable for targeting other HCoVs as these are not well-conserved sequences among human CoVs. Thus, there is a need for readily available treatments globally that target all seven human CoVs and improve the preparedness for inevitable future outbreaks. Here, we discuss antiviral research, contributing to the control of common and severe CoV replication and transmission, including the current SARS-CoV-2 outbreak. The aim was to identify common features of CoVs for antivirals, biologics and vaccines that could reduce the scientific, political, economic and public health strain caused by CoV outbreaks now and in the future.

Immunoglobulin A response to SARS-CoV-2 infection and immunity

The novel coronavirus disease (COVID-19) and its infamous "Variants" of the etiological agent termed Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) has proven to be a global health concern. The three antibodies, IgA, IgM, and IgG, perform their dedicated role as main workhorses of the host adaptive immune system in virus neutralization. Immunoglobulin-A (IgA), also known as "Mucosal Immunoglobulin", has been under keen interest throughout the viral infection cycle. Its importance lies because IgA is predominant mucosal antibody and SARS family viruses primarily infect the mucosal surfaces of human respiratory tract. Therefore, IgA can be considered a diagnostic and prognostic marker and an active infection biomarker for SARS CoV-2 infection. Along with molecular analyses, serological tests, including IgA detection tests, are gaining ground in application as an early detectable marker and as a minimally invasive detection strategy. In the current review, it was emphasized the role of IgA response in diagnosis, host defense strategies, treatment, and prevention of SARS-CoV-2 infection. The data analysis was performed through almost 100 published peer-reviewed research reports and comprehended the importance of IgA in antiviral immunity against SARS-CoV-2 and other related respiratory viruses. Taken together, it is concluded that secretory IgA- Abs can serve as a promising detection tool for respiratory viral diagnosis and treatment parallel to IgG-based therapeutics and diagnostics. Vaccine candidates that target and trigger mucosal immune response may also be employed in future dimensions of research against other respiratory viruses.

Advances in nanobiosensors during the COVID-19 pandemic and future perspectives for the post-COVID era

The unprecedented threat of the highly contagious virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes exponentially increased infections of coronavirus disease 2019 (COVID-19), highlights the weak spots of the current diagnostic toolbox. In the midst of catastrophe, nanobiosensors offer a new opportunity as an alternative tool to fill a gap among molecular tests, rapid antigen tests, and serological tests. Nanobiosensors surpass the potential of antigen tests because of their enhanced sensitivity, thus enabling us to see antigens as stable and easy-to-access targets. During the first three years of the COVID-19 pandemic, a substantial number of studies have reported nanobiosensors for the detection of SARS-CoV-2 antigens. The number of articles on nanobiosensors and SARS-CoV-2 exceeds the amount of nanobiosensor research on detecting previous infectious diseases, from influenza to SARS-CoV and MERS-CoV. This unprecedented publishing pace also implies the significance of SARS-CoV-2 and the present pandemic. In this review, 158 studies reporting nanobiosensors for detecting SARS-CoV-2 antigens are collected to discuss the current challenges of nanobiosensors using the criteria of point-of-care (POC) diagnostics along with COVID-specific issues. These advances and lessons during the pandemic pave the way for preparing for the post-COVID era and potential upcoming infectious diseases.

A SYBR Green I-based aptasensor for the label-free, fluorometric, and anti-interference detection of MeHg. Anal Bioanal Chem 2024;416:299-311. [PMID: 37932512 DOI: 10.1007/s00216-023-05018-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Methylmercury (MeHg+) is a common form of organic mercury that is substantially more toxic than inorganic mercury and is more likely to accumulate in organisms through biological enrichment. Therefore, developing a method to enable the specific and rapid detection of MeHg+ in seafood is important and remains challenging to accomplish. Herein, a rapid, label-free fluorescence detection method for MeHg+ determination was developed based on SYBR Green I. The detection system implemented "add and measure" detection mode can be completed in 10 min. Under optimal assay conditions, the detection platform showed a linear relationship with the concentration of MeHg+ within 1-50 nM (Y = 8.573x + 42.89, R2 = 0.9928), with a detection limit of 0.3218 nM. The results obtained for competitive substances, such as inorganic mercury ions and anions, show a high specificity of the method. In addition, this method successfully detected MeHg+ in seawater and marine products, with an accompanying spike recovery rate of 96.45-105.1%.

Interlaboratory comparison using inactivated SARS-CoV-2 variants as a feasible tool for quality control in COVID-19 wastewater monitoring

Wastewater-based SARS-CoV-2 epidemiology (WBE) has proven as an excellent tool to monitor pandemic dynamics supporting individual testing strategies. WBE can also be used as an early warning system for monitoring the emergence of novel pathogens or viral variants. However, for a timely transmission of results, sophisticated sample logistics and analytics performed in decentralized laboratories close to the sampling sites are required. Since multiple decentralized laboratories commonly use custom in-house workflows for sample purification and PCR-analysis, comparative quality control of the analytical procedures is essential to report reliable and comparable results. In this study, we performed an interlaboratory comparison at laboratories specialized for PCR and high-throughput-sequencing (HTS)-based WBE analysis. Frozen reserve samples from low COVID-19 incidence periods were spiked with different inactivated authentic SARS-CoV-2 variants in graduated concentrations and ratios. Samples were sent to the participating laboratories for analysis using laboratory specific methods and the reported viral genome copy numbers and the detection of viral variants were compared with the expected values. All PCR-laboratories reported SARS-CoV-2 genome copy equivalents (GCE) for all spiked samples with a mean intra- and inter-laboratory variability of 19 % and 104 %, respectively, largely reproducing the spike-in scheme. PCR-based genotyping was, in dependence of the underlying PCR-assay performance, able to predict the relative amount of variant specific substitutions even in samples with low spike-in amount. The identification of variants by HTS, however, required >100 copies/ml wastewater and had limited predictive value when analyzing at a genome coverage below 60 %. This interlaboratory test demonstrates that despite highly heterogeneous isolation and analysis procedures, overall SARS-CoV-2 GCE and mutations were determined accurately. Hence, decentralized SARS-CoV-2 wastewater monitoring is feasible to generate comparable analysis results. However, since not all assays detected the correct variant, prior evaluation of PCR and sequencing workflows as well as sustained quality control such as interlaboratory comparisons are mandatory for correct variant detection.

COVID-19 infection analysis framework using novel boosted CNNs and radiological images

COVID-19, a novel pathogen that emerged in late 2019, has the potential to cause pneumonia with unique variants upon infection. Hence, the development of efficient diagnostic systems is crucial in accurately identifying infected patients and effectively mitigating the spread of the disease. However, the system poses several challenges because of the limited availability of labeled data, distortion, and complexity in image representation, as well as variations in contrast and texture. Therefore, a novel two-phase analysis framework has been developed to scrutinize the subtle irregularities associated with COVID-19 contamination. A new Convolutional Neural Network-based STM-BRNet is developed, which integrates the Split-Transform-Merge (STM) block and Feature map enrichment (FME) techniques in the first phase. The STM block captures boundary and regional-specific features essential for detecting COVID-19 infectious CT slices. Additionally, by incorporating the FME and Transfer Learning (TL) concept into the STM blocks, multiple enhanced channels are generated to effectively capture minute variations in illumination and texture specific to COVID-19-infected images. Additionally, residual multipath learning is used to improve the learning capacity of STM-BRNet and progressively increase the feature representation by boosting at a high level through TL. In the second phase of the analysis, the COVID-19 CT scans are processed using the newly developed SA-CB-BRSeg segmentation CNN to accurately delineate infection in the images. The SA-CB-BRSeg method utilizes a unique approach that combines smooth and heterogeneous processes in both the encoder and decoder. These operations are structured to effectively capture COVID-19 patterns, including region-homogenous, texture variation, and border. By incorporating these techniques, the SA-CB-BRSeg method demonstrates its ability to accurately analyze and segment COVID-19 related data. Furthermore, the SA-CB-BRSeg model incorporates the novel concept of CB in the decoder, where additional channels are combined using TL to enhance the learning of low contrast regions. The developed STM-BRNet and SA-CB-BRSeg models achieve impressive results, with an accuracy of 98.01%, recall of 98.12%, F-score of 98.11%, Dice Similarity of 96.396%, and IOU of 98.85%. The proposed framework will alleviate the workload and enhance the radiologist's decision-making capacity in identifying the infected region of COVID-19 and evaluating the severity stages of the disease.

One-plasmid double-expression system for preparation of MS2 virus-like particles packaging SARS-CoV-2 RNA

COVID-19 is a disease caused by a virus named SARS-CoV-2. SARS-CoV-2 is a single-stranded positive-sense RNA virus. Reverse transcription quantitative PCR (RT-qPCR) assays are the gold standard molecular test for detection of RNA viruses. The aim of this study was to construct an RNA-positive control based on MS2 phage-like particles (MS2 VLPs) to detect SARS-CoV-2 RNA. pCDFDuet-1 was used as a one-plasmid double-expression system to construct MS2 VLPs containing ssRNA of SARS-CoV-2. The sequence encoding one copy of maturase, His-tag and coat protein dimer was cloned and inserted into MCS1 of the plasmid; the fragment encoding protein N and ORF1ab from SARS-CoV-2 was cloned and inserted into MCS2. The prepared plasmid was transformed into Escherichia coli strain BL2 (DE3), and expression of the construct was induced by 1 mM isopropyl-L-thio-D-galactopyranoside (IPTG) at 30°C for 12 hours. MS2 VLPs were purified and collected with Ni-NTA affinity chromatography columns. The size and shape of the MS2 VLPs were verified by transmission electron microscopy, and the stability of MS2 VLP packaged RNA was evaluated by treatment with RNase A. Effects of storage temperature and buffer on MS2 VLP stability were also investigated. The results showed that SARS-CoV-2 MS2 VLPs could be successfully produced by this one-plasmid double-expression system. MS2 VLPs showed high stability and may be used as a positive control in molecular diagnosis of COVID-19.

Development of a one-step reverse transcription-quantitative polymerase chain reaction assay for the detection of porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome (PRRS) caused by PRRS virus (PRRSV) is an important disease that severely affects the swine industry and, therefore, warrants rapid and accurate diagnosis for its control. Despite the progress in developing diagnostic tools, including polymerase chain reaction (PCR)-based methods such as reverse transcription quantitative PCR (RT-qPCR) to diagnose PRRSV infection, its diagnosis at the genetic level is challenging because of its high genetic variability. Nevertheless, RT-qPCR is the easiest and fastest method for diagnosing PRRSV. Therefore, this study aimed to develop an RT-qPCR assay for rapid and accurate diagnosis of PRRSV by encompassing all publicly available PRRSV sequences. The developed assay using highly specific primers and probes could detect up to 10 copies of PRRSV-1 and -2 subtypes. Furthermore, a comparison of the performance of the developed assay with those of two commercial kits widely used in South Korea demonstrated the higher efficiency of the developed assay in detecting PRRSV infections in field samples. For PRRSV-1 detection, the developed assay showed a diagnostic agreement of 97.7% with the results of ORF5 sequencing, while for commercial kits, it showed 95.3% and 72.1% agreement. For PRRSV-2, the developed assay showed a diagnostic agreement of 97.7%, whereas the commercial kits showed 93% and 90.7% agreement. In conclusion, we developed an assay with higher accuracy than those of the tested commercial kits, which will contribute markedly to global PRRSV control.

Advances in Cas12a-Based Amplification-Free Nucleic Acid Detection

In biomedicine, rapid and sensitive nucleic acid detection technology plays an important role in the early detection of infectious diseases. However, most traditional nucleic acid detection methods require the amplification of nucleic acids, resulting in problems such as long detection time, complex operation, and false-positive results. In recent years, clustered regularly interspaced short palindromic repeats (CRISPR) systems have been widely used in nucleic acid detection, especially the CRISPR-Cas12a system, which can trans cleave single-stranded DNA and can realize the detection of DNA targets. But, amplification of nucleic acids is still required to further improve detection sensitivity, which makes Cas12a-based amplification-free nucleic acid detection methods a great challenge. This article reviews the recent progress of Cas12a-based amplification-free detection methods for nucleic acids. These detection methods apply electrochemical detection methods, fluorescence detection methods, noble metal nanomaterial detection methods, and lateral flow assay. Under various optimization strategies, unamplified nucleic acids have the same sensitivity as amplified nucleic acids. At the same time, the article discusses the advantages and disadvantages of each method and further discusses the current challenges such as off-target effects and the ability to achieve high-throughput detection. Amplification-free nucleic acid detection technology based on CRISPR-Cas12a has great potential in the biomedical field.

Rapid, tunable, and multiplexed detection of RNA using convective array PCR

Detection of RNA targets is typically achieved through RT-qPCR or RNAseq. RT-qPCR is rapid but limited in number and complexity of targets detected, while RNAseq is high-throughput but takes multiple days. We demonstrate simultaneous amplification and detection of 28 distinct RNA targets from a single unsplit purified RNA sample in under 40 minutes using our convective array PCR (caPCR) technology. We integrate tunable strand displacement probes into caPCR to allow detection of RNA species with programmable sequence selectivity for either a single, perfectly matched target sequence or for targets with up to 2 single-nucleotide variants within the probe-binding regions. Tunable probes allow for robust detection of desired RNA species against high homology background sequences and robust detection of RNA species with significant sequence diversity due to community-acquired mutations. As a proof-of-concept, we experimentally demonstrated detection of 7 human coronaviruses and 7 key variants of concern of SARS-CoV-2 in a single assay.

An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern

As the COVID-19 pandemic winds down, it leaves behind the serious concern that future, even more disruptive pandemics may eventually surface. One of the crucial steps in handling the SARS-CoV-2 pandemic was being able to detect the presence of the virus in an accurate and timely manner, to then develop policies counteracting the spread. Nevertheless, as the pandemic evolved, new variants with potentially dangerous mutations appeared. Faced by these developments, it becomes clear that there is a need for fast and reliable techniques to create highly specific molecular tests, able to uniquely identify VOCs. Using an automated pipeline built around evolutionary algorithms, we designed primer sets for SARS-CoV-2 (main lineage) and for VOC, B.1.1.7 (Alpha) and B.1.1.529 (Omicron). Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for the main lineage and each variant in a matter of hours. Preliminary in-silico validation showed that the sequences in the primer sets featured high accuracy. A pilot test in a laboratory setting confirmed the results: the developed primers were favorably compared against existing commercial versions for the main lineage, and the specific versions for the VOCs B.1.1.7 and B.1.1.529 were clinically tested successfully.

Analysis of altered level of blood-based biomarkers in prognosis of COVID-19 patients

INTRODUCTION

Immune and inflammatory responses developed by the patients with Coronavirus Disease 2019 (COVID-19) during rapid disease progression result in an altered level of biomarkers. Therefore, this study aimed to analyze levels of blood-based biomarkers that are significantly altered in patients with COVID-19.

METHODS

A cross-sectional study was conducted among COVID-19 diagnosed patients admitted to the tertiary care hospital. Several biomarkers-biochemical, hematological, inflammatory, cardiac, and coagulatory-were analyzed and subsequently tested for statistical significance at P<0.01 by using SPSS version 17.0.

RESULTS

A total of 1,780 samples were analyzed from 1,232 COVID-19 patients (median age 45 years [IQR 33-57]; 788 [63.96%] male). The COVID-19 patients had significantly (99% Confidence Interval, P<0.01) elevated levels of glucose, urea, alanine transaminase (ALT), aspartate aminotransaminase (AST), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), white blood cell (WBC), C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), ferritin, D-Dimer, and creatinine phosphokinase-MB (CPK-MB) compared to the control group. However, the levels of total protein, albumin, and platelets were significantly (P<0.01) lowered in COVID-19 patients compared to the control group. The elevated levels of glucose, urea, WBC, CRP, D-Dimer, and LDH were significantly (P<0.01) associated with in-hospital mortality in COVID-19 patients.

CONCLUSIONS

Assessing and monitoring the elevated levels of glucose, urea, ALT, AST, ALP, WBC, CRP, PCT, IL-6, ferritin, LDH, D-Dimer, and CPK-MB and the lowered levels of total protein, albumin, and platelet could provide a basis for evaluation of improved prognosis and effective treatment in patients with COVID-19.

Aptamer-Based Strategies to Address Challenges in COVID-19 Diagnosis and Treatments

Coronavirus disease (COVID-19), a highly contagious and rapidly spreading disease with significant fatality in the elderly population, has swept across the world since 2019. Since its first appearance, the causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has undergone multiple mutations, with Omicron as the predominant circulating variant of concern at the moment. The gold standard for diagnosis of COVID-19 by real-time polymerase chain reaction (RT-PCR) to detect the virus is laborious and requires well-trained personnel to perform sophisticated procedures. Also, the genetic variants of SARS-CoV-2 that arise regularly could result in false-negative detection. Meanwhile, the current COVID-19 treatments such as conventional medicine, complementary and alternative medicine, passive antibody therapy, and respiratory therapy are associated with adverse effects. Thus, there is an urgent need to discover novel diagnostic and therapeutic approaches against SARS-CoV-2 and its variants. Over the past 30 years, nucleic acid-based aptamers have gained increasing attention and serve as a promising alternative to the antibodies in the diagnostic and therapeutic fields with their uniqueness of being small, nonimmunogenicity, and thermally stable. Aptamer targeting the SARS-CoV-2 structural proteins or the host receptor proteins represent a powerful tool to control COVID-19 infection. In this review, challenges faced by currently available diagnostic and therapeutic tools for COVID-19 are underscored, along with how aptamers can shed a light on the current COVID-19 pandemic, focusing on the critical factors affecting the discovery of high-affinity aptamers and their potential applications to control COVID-19 infection.

Rapid On-Site Detection of SARS-CoV-2 Using RT-LAMP Assay with a Portable Low-Cost Device

Emerging infectious diseases pose a serious threat to human health and affect social stability. In recent years, the epidemic situation of emerging infectious diseases is very serious; among these infectious diseases, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected many countries and regions in a short time. The prevention and treatment of these diseases require rapid on-site detection methods. However, the common detection method, RT-PCR, requires expensive instruments, complex operations, and professional operators. Here, we developed a portable low-cost assay for rapid on-site detection of viral nucleic acid using reverse transcription-loop-mediated isothermal amplification (RT-LAMP). The SARS-CoV-2 RNA can be successfully amplified within 15 min in a thermos, and the detection result is read rapidly in a portable low-cost device with a sensitivity of 10⁰ copies/µL. The portable low-cost device consists of a black box, a laser or LED and a filter, costing only a few cents. The rapid on-site detection method can provide strong support for the control of biological threats such as infectious diseases. It is also an emergency detection method for low-resource settings, relieving the huge pressure on health care.

A Machine Learning Approach to COVID-19 Detection via Graphene Field-Effect-Transistor (GFET)

In the wake of the COVID-19 pandemic, there has been a need for reliable diagnostic testing. However, state-of-the-art detection methods rely on laboratory tests and also vary in accuracy. We evaluate that the usage of a graphene field-effect-transistor (GFET) coupled with machine learning can be a promising alternate diagnostic testing method. We processed the current-voltage data gathered from the GFET sensors to assess information about the presence of COVID-19 in biosamples. We perform binary classification using the following machine learning algorithms: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM) with the Radial Basis Function (RBF) kernel, and K-Nearest Neighbors (KNN) in conjunction with Principal Component Analysis (PCA). We find that LDA and SVM with RBF proved to be the most accurate in identifying positive and negative samples, with accuracies of 99% and 98.5%, respectively. Based on these results, there is promise to develop a bioelectronic diagnostic method for COVID-19 detection by combining GFET technology with machine learning.

Sample Treatment with Trypsin for RT-LAMP COVID-19 Diagnosis

The SARS-CoV-2 coronavirus is responsible for the COVID-19 pandemic resulting in a global health emergency. Given its rapid spread and high number of infected individuals, a diagnostic tool for a rapid, simple, and cost-effective detection was essential. In this work, we developed a COVID-19 diagnostic test, that incorporates a human internal control, based on the Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP). When working with synthetic SARS-CoV-2 RNA, the optimized RT-LAMP assay has a sensitivity of 10 viral copies and can be detected by fluorescence in less than 15 min or by the naked eye in 25 min using colorimetric RT-LAMP. To avoid the RNA extraction step, a pre-treatment of the sample was optimized. Subsequently, a validation was performed on 268 trypsin treated samples (including nasopharyngeal, buccal, and nasal exudates) and amplified with colorimetric RT-LAMP to evaluate its sensitivity and specificity in comparison with RT-qPCR of extracted samples. The validation results showed a sensitivity and specificity of 100% for samples with Ct ≤ 30. The rapid, simple, and inexpensive RT-LAMP SARS-CoV-2 extraction-free procedure developed may be an alternative test that could be applied for the detection of SARS-CoV-2 or adapted to detect other viruses present in saliva or nasopharyngeal samples with higher sensitivity and specificity of the antibody test.

Application of Localized Surface Plasmon Resonance of Conjugated Gold Nanoparticles in Spectral Diagnosis of SARS-CoV-2: A Numerical Study

Severe respiratory syndrome COVID-19 (SARS-CoV-2) outbreak has became the most important global health issue, and simultaneous efforts to fast and low-cost diagnosis of this virus were performed by researchers. One of the most usual tests was colorimetric methods based on the change of color of gold nanoparticles in the presence of viral antibodies, antigens, and other biological agents. This spectral change can be due to the aggregation of the particles or the shift of localized surface plasmon resonance due to the electrical interactions of surface agents. It is known that surface agents could easily shift the absorption peak of metallic nanocolloids which is attributed to the localized surface plasmon resonance. Experimental diagnosis assays for colorimetric detection of SARS-CoV-2 using Au NPs were reviewed, and the shift of absorption peak was studied from the viewpoint of numerical analysis. Using the numerical method, the refractive index and real and imaginary parts of the effective relative permittivity of the viral biological shell around Au NPs were obtained. This model gives a quantitative description of colorimetric assays of the detection of SARS-CoV-2 using Au NPs.

SERS Signature of SARS-CoV-2 in Saliva and Nasopharyngeal Swabs: Towards Perspective COVID-19 Point-of-Care Diagnostics

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(-) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value-RMSEC and RMSECV below 0.3 and R²_cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease.

Rapid detection of intact SARS-CoV-2 using designer DNA Nets and a pocket-size smartphone-linked fluorimeter

Rapid, sensitive, and inexpensive point-of-care diagnosis is vital to controlling highly infectious diseases, including COVID-19. Here, we report the design and characterization of a compact fluorimeter called a "Virus Pod" (V-Pod) that enables sensitive self-testing of SARS-CoV-2 viral load in saliva. The rechargeable battery-operated device reads the fluorescence generated by Designer DNA Nanostructures (DDN) when they specifically interact with intact SARS-CoV-2 virions. DDNs are net-shaped self-assembling nucleic acid constructs that provide an array of highly specific aptamer-fluorescent quencher duplexes located at precise positions that match the pattern of spike proteins. The room-temperature assay is performed by mixing the test sample with DNA Net sensor in a conventional PCR tube and placing the tube into the V-Pod. Fluorescent signals are generated when multivalent aptamer-spike binding releases fluorescent quenchers, resulting in rapid (5-min) generation of dose-dependent output. The V-Pod instrument performs laser excitation, fluorescence intensity quantitation, and secure transmission of data to an App via Bluetooth™. We show that the V-Pod and DNA Net assay achieves clinically relevant detection limits of 3.92 × 103 viral-genome-copies/mL for pseudo-typed wild-type SARS-CoV-2 and 1.84 × 104, 9.69 × 104, 6.99 × 104 viral-genome-copies/mL for pathogenic Delta, Omicron, and D614G variants, representing sensitivity similar to laboratory-based PCR. The pocket-sized instrument (∼$294), inexpensive reagent-cost/test ($1.26), single-step, rapid sample-to-answer, and quantitative output represent a capability that is compatible with the needs of frequent self-testing in a consumer-friendly format that can link with medical service systems such as healthcare providers, contact tracing, and infectious disease reporting.

Single Institute Audit of Maxillofacial Trauma Cases Before and During COVID-19 Pandemic

Study Design

In the year 2020, we saw the emergence of severe acute respiratory syndrome coronavirus 2 causing COVID-19 into a full blown pandemic. This resulted in constraints on healthcare resources, and the attention was shifted to reduce cross contamination and prevent spreader events. Maxillofacial trauma care was also affected similarly, and most of the cases were managed by closed reduction whenever possible. A retrospective study was conducted to document our experience in treating maxillofacial trauma cases before and after nationwide lockdown due to COVID-19 pandemic in India.

Objective

The objective of the study was to compare the effect of pandemic in reported pattern of mandibular trauma and the result of closed reduction procedures in the management of single or multiple fractures in mandible during this time period.

Methods

The study was conducted in the Department of Oral and Maxillofacial Surgery, Maulana Azad institute of Dental Sciences, Delhi, for a period of 20 months, that is, 10 months before and after nationwide lock down which was effective from 23rd March 2020 due to COVID-19 pandemic. The cases were grouped into Group A (those reporting from 1st June 2019 to 31st March 2020) and Group B (those reporting from 1st April 2020 to 31st January 2021). Primary objectives were assessed and compared according to etiology, gender, location of the mandibular fractures, and treatment provided. Quality of life (QoL) associated with the treatment outcome by closed reduction was assessed after 2 months as a secondary objective using General Oral Health Assessment Index (GOHAI) in Group B.

Results

A total of 798 patients sought treatment for mandibular fractures and included 476 patients in Group A and 322 in Group B. The groups showed similar age and male: female ratio. Cases showed a steep fall during first wave of pandemic, and most of the cases occurred as result of RTA followed by fall and assault. The fractures due to fall and assault showed an obvious rise during the lockdown period. There were 718 (89.97%) patients having exclusive mandibular fractures and 80 (10.03%) patients having involvement of both mandible and maxilla. Single fractures of mandible constituted 110 (23.11%) and 58 (18.01%) in Group A and B, respectively. 324 patients (68.07%) and 226 patients (70.19%) had multiple fractures involving mandible in respective groups. Parasymphysis of mandible was most commonly involved (24.31%) followed closely by unilateral condyle (23.48%) then Angle and Ramus of mandible (20.71%) with coronoid being the least fractured. During the initial 6 months after lockdown, all the cases were treated successfully using closed reduction. GOHAI QoL assessment conducted in cases having exclusive mandibular fracture (210 Multiple, 48 Single) showed favorable results with significant (P < .05) difference between the single and multiple fractures.

Conclusions

After one and half years and recovering from the second wave of pandemic that hit the country, we have come to understand COVID-19 better and embraced better management protocol. The study reveals that IMF remains the gold standard for the management of most of the facial fractures in pandemic situations. It was evident from the QoL data that most of the patients were able to carry out their day-to-day functions adequately. As the country prepares for a third wave of pandemic, management of maxillofacial trauma by closed reduction will remain the norm for most unless indicated otherwise.

BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data

Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge from the datasets collected from 930 COVID-19 patients hospitalized in Italy during the first wave of COVID-19 (March-June 2020). The dataset consists of twenty-five biomarkers from electronic health record and Chest X-ray (CXR) images. It is found that the system can diagnose low- or high-risk patients with an accuracy, sensitivity, and F1-score of 89.03%, 90.44%, and 89.03%, respectively. The system exhibits 6% higher accuracy than the systems that employ either CXR images or biomarker data. In addition, the system can calculate the mortality risk of high-risk patients using multivariate logistic regression-based nomogram scoring technique. Interested physicians can use the presented system to predict the early mortality risks of COVID-19 patients using the web-link: Covid-severity-grading-AI. In this case, a physician needs to input the following information: CXR image file, Lactate Dehydrogenase (LDH), Oxygen Saturation (O2%), White Blood Cells Count, C-reactive protein, and Age. This way, this study contributes to the management of COVID-19 patients by predicting early mortality risk.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00521-023-08606-w.

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.

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.

Binding-Induced Folding of DNA Oligonucleotides Targeted to the Nucleocapsid Gene Enables Electrochemical Sensing of SARS-CoV-2

In the wake of the COVID-19 pandemic, millions of confirmed cases and deaths have been reported around the world. COVID-19 spread can be slowed and eventually stopped by a rapid test to diagnose positive cases of the disease on the spot. It is still important to test for COVID-19 quickly regardless of the availability of the vaccine. Using the binding-induced folding principle, we developed an electrochemical test for detecting SARS-CoV-2 with no RNA extraction or nucleic acid amplification. The test showed high sensitivity with a limit of detection of 2.5 copies/μL. An electrode mounted with a capture probe and a portable potentiostat are used to conduct the test. To target the N-gene of SARS-CoV-2, a highly specific oligo-capturing probe was used. Based on the binding-induced "folding" principle, the sensor detects binding between the oligo and RNA. When the target is absent, the capture probe tends to form a hairpin as a secondary structure, retaining the redox reporter close to the surface. This can be seen as a large anodic and cathodic peak current. When the target RNA is present, the hairpin structure will open to hybridize with its complementary sequence, causing the redox reporter to pull away from the electrode. Consequently, the anodic/cathodic peak currents are reduced, indicating the presence of the SARS-CoV-2 genetic material. Validation of the test performance was performed using 122 COVID-19 clinical samples (55 positives and 67 negatives) and benchmarked to the gold standard reverse transcription-polymerase chain reaction (RT-PCR) test. As a result of our test, the accuracy, sensitivity, and specificity have been measured at 98.4%, 98.2%, and 98.5%, respectively.

'CoviSwiftTM': A point-of-care RT-PCR device for SARS-CoV-2 and its variant detection

We present the point-of-care (POC) molecular diagnostic solution, evaluated during COVID-19 pandemic caused by SARS-CoV-2 (Dec 2021). The POC comprised of a complete platform from self-sampling to RT-PCR testing of SARS-CoV-2 and its variants on portable Compact Q Real time polymerase chain reaction system. The multiplex assay was designed to target S, ORF1, and N genes of SARS-CoV-2 genome in a single tube with RNaseP as endogenous internal control. The present POC enables high accuracy (>95%) and high-throughput testing with a turnaround time of 45 min. It provides a unique platform from self-sample collection to report generation with rapid protocol, pipette and expert-free operation, long shelf-life stability and room temperature storage which enable to increase the efficiency of molecular testing. This novel test named "CoviSwift™ COVID-19 S PLUS RAPID PCR KIT" has been approved by CDSCO, Indian National Regulatory Authority, India, and is in use for clinical settings in India.

Clinical Evaluation of an Antigen Home Test Using Surface-Enhanced Raman Spectroscopy and Stacking Pad for SARS-CoV-2 Screening with Nasal and Salivary Swab Samples

This prospective study aimed to evaluate the performance of the InstaView COVID-19 (coronavirus diseases 2019) Antigen Home Test (InstaView AHT) which detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens. In this test kit, surface-enhanced Raman spectroscopy was used, a stacking pad was inserted, and nasal swab and salivary swab samples were used simultaneously to improve performance. The clinical performance of the InstaView AHT was compared to that of RT-PCR using nasopharyngeal samples. The participants without any prior training were recruited and performed the sample collection, testing, and interpretation of the results by themselves. Of the 91 PCR-positive patients, 85 had positive InstaView AHT results. The sensitivity and specificity of the InstaView AHT were 93.4% (95% confidence interval [CI]: 86.2-97.5) and 99.4% (95% CI: 98.2-99.9). The sensitivity of the InstaView AHT was above 90% for all samples obtained from patients with Ct ≤ 20, 20 < Ct ≤ 25, and 25 < Ct ≤ 30 (100%, 95.1%, and 92.0%, respectively). The InstaView AHT can be used as an alternative to RT-PCR testing because of its relatively high sensitivity and specificity, especially when SARS-CoV-2 prevalence is high, and the availability of RT-PCR testing is limited.

Multifunctional Nanoparticle Platform for Surface Accumulative Nucleic Acid Amplification and Rapid Electrochemical Detection: An Application to Pathogenic Coronavirus

Of various molecular diagnostic assays, the real-time reverse transcription polymerase chain reaction is considered the gold standard for infection diagnosis, despite critical drawbacks that limit rapid detection and accessibility. To confront these issues, several nanoparticle-based molecular detection methods have been developed to a great extent, but still possess several challenges. In this study, a novel nucleic acid amplification method termed nanoparticle-based surface localized amplification (nSLAM) is paired with electrochemical detection (ECD) to develop a nucleic acid biosensor platform that overcomes these limitations. The system uses primer-functionalized Fe3O4-Au core-shell nanoparticles for nucleic acid amplification, which promotes the production of amplicons that accumulate on the nanoparticle surfaces, inducing significantly amplified currents during ECD that identify the presence of target genetic material. The platform, applying to the COVID-19 model, demonstrates an exceptional sensitivity of ∼1 copy/μL for 35 cycles of amplification, enabling the reduction of amplification cycles to 4 cycles (∼7 min runtime) using 1 fM complementary DNA. The nSLAM acts as an accelerator that actively promotes and participates in the nucleic acid amplification process through direct polymerization and binding of amplicons on the nanoparticle surfaces. This ultrasensitive fast-response system is a promising method for detecting emerging pathogens like the coronavirus and can be extended to detect a wider variety of biomolecules.

Capabilities of Double-Resonance LPG and SPR Methods for Hypersensitive Detection of SARS-CoV-2 Structural Proteins: A Comparative Study

The danger of the emergence of new viral diseases and their rapid spread demands apparatuses for continuous rapid monitoring in real time. This requires the creation of new bioanalytical methods that overcome the shortcomings of existing ones and are applicable for point-of-care diagnostics. For this purpose, a variety of biosensors have been developed and tested in proof-of-concept studies, but none of them have been introduced for commercial use so far. Given the importance of the problem, in this study, long-period grating (LPG) and surface plasmon resonance (SPR) biosensors, based on antibody detection, were examined, and their capabilities for SARS-CoV-2 structural proteins detection were established. Supersensitive detections of structural proteins in the order of several femtomoles were achieved by the LPG method, while the SPR method demonstrated a sensitivity of about one hundred femtomoles. The studied biosensors are compatible in sensitivity with ELISA and rapid antigen tests but, in contrast, they are quantitative, which makes them applicable for acute SARS-CoV-2 infection detection, especially during the early stages of viral replication.

Recent trends in carbon nanotube (CNT)-based biosensors for the fast and sensitive detection of human viruses: a critical review

The current COVID-19 pandemic, with its numerous variants including Omicron which is 50-70% more transmissible than the previously dominant Delta variant, demands a fast, robust, cheap, and easily deployed identification strategy to reduce the chain of transmission, for which biosensors have been shown as a feasible solution at the laboratory scale. The use of nanomaterials has significantly enhanced the performance of biosensors, and the addition of CNTs has increased detection capabilities to an unrivaled level. Among the various CNT-based detection systems, CNT-based field-effect transistors possess ultra-sensitivity and low-noise detection capacity, allowing for immediate analyte determination even in the presence of limited analyte concentrations, which would be typical of early infection stages. Recently, CNT field-effect transistor-type biosensors have been successfully used in the fast diagnosis of COVID-19, which has increased research and commercial interest in exploiting current developments of CNT field-effect transistors. Recent progress in the design and deployment of CNT-based biosensors for viral monitoring are covered in this paper, as are the remaining obstacles and prospects. This work also highlights the enormous potential for synergistic effects of CNTs used in combination with other nanomaterials for viral detection.

Malachite Green-Based Detection of SARS-CoV-2 by One-Step Reverse Transcription Loop-Mediated Isothermal Amplification

The pandemic of severe acute respiratory syndrome 2 (SARS-CoV-2) revealed the necessity of diagnosis of the infected people to prevent the prevalence infection cycle. Many commercial pathogen diagnosis methods are based on the detection of genomic materials. Isothermal amplification methods such as loop-mediated-isothermal amplification (LAMP) are the method of choice in these cases. Reverse transcription steps are efficiently coupled to LAMP for the detection of pathogens with genomic RNAs such as SARS-CoV-2. Many detection systems for LAMP include fluorescent readout systems. Although such systems result in desirable limits of detection, the need for special instrumentation is the main dispute of such systems to become real point of care assays. In contrast, colorimetric detection methods would reduce costs and improve the applicability of the system. In this study one-step reverse transcription-LAMP reaction was established that enables visual detection of the SARS-CoV-2 genome. Nasopharyngeal RNA samples were first validated by reverse transcription quantitative polymerase chain reaction and then subjected to RT-LAMP. To lower the cost associated with the readout system equipment, malachite green (MG) was used. The color change of MG to blue allowed visual detection of the virus. Firstly, experiments were set up as two-step RT-LAMP reaction to identify the best primer sets. In addition, MG concentration was optimized with the significant colorimetric signal for the positive samples. Next, a one-step colorimetric method was developed for the detection of SARS-CoV-2 based on MG color shift in 2 h.

Rapid Detection of SARS-CoV-2 RNA in Human Nasopharyngeal Specimens Using Surface-Enhanced Raman Spectroscopy and Deep Learning Algorithms

A rapid and cost-effective method to detect the infection of SARS-CoV-2 is fundamental to mitigating the current COVID-19 pandemic. Herein, a surface-enhanced Raman spectroscopy (SERS) sensor with a deep learning algorithm has been developed for the rapid detection of SARS-CoV-2 RNA in human nasopharyngeal swab (HNS) specimens. The SERS sensor was prepared using a silver nanorod array (AgNR) substrate by assembling DNA probes to capture SARS-CoV-2 RNA. The SERS spectra of HNS specimens were collected after RNA hybridization, and the corresponding SERS peaks were identified. The RNA detection range was determined to be 103-109 copies/mL in saline sodium citrate buffer. A recurrent neural network (RNN)-based deep learning model was developed to classify 40 positive and 120 negative specimens with an overall accuracy of 98.9%. For the blind test of 72 specimens, the RNN model gave a 97.2% accuracy prediction for positive specimens and a 100% accuracy for negative specimens. All the detections were performed in 25 min. These results suggest that the DNA-functionalized AgNR array SERS sensor combined with a deep learning algorithm could serve as a potential rapid point-of-care COVID-19 diagnostic platform.

A luciferase based automated assay for rapid and sensitive detection of SARS-CoV-2 antibodies

The Coronavirus disease 2019 (COVID-19) pandemic brings great challenges to the public health and social economics around the world. As the pandemic continues and the mass vaccination goes on, monitoring the antibodies is particularly important for the epidemiological survey and vaccine assessment. Here, we developed a luciferase immunoprecipitation assay combined with an automated platform to detect anti-Receptor Binding Domain (RBD) antibody, where protein A and protein G modified magnetic beads were used to capture antibodies in serum samples and SARS-CoV-2 RBD was fused with Gaussia luciferase to label the captured target antibodies. The whole detection procedure can be completed within 20 min. The developed assay has proven up to 32 times more sensitive than ELISA for the detection of RBD antibodies. Furthermore, the results of the antibody detection of sera from vaccination as well as convalescence displayed good performance. The automated platform may provide a powerful tool for the control of COVID-19 pandemic by vaccination and the research of SARS-CoV-2 seroconversion.

Outcome of Newborns with Confirmed or Possible SARS-CoV-2 Vertical Infection-A Scoping Review

Severe acute respiratory syndrome virus 2 (SARS-CoV-2), the virus that causes 2019 coronavirus disease (COVID-19), has been isolated from various tissues and body fluids, including the placenta, amniotic fluid, and umbilical cord of newborns. In the last few years, much scientific effort has been directed toward studying SARS-CoV-2, focusing on the different features of the virus, such as its structure and mechanisms of action. Moreover, much focus has been on developing accurate diagnostic tools and various drugs or vaccines to treat COVID-19. However, the available evidence is still scarce and consistent criteria should be used for diagnosing vertical transmission. Applying the PRISMA ScR guidelines, we conducted a scoping review with the primary objective of identifying the types, and examining the range, of available evidence of vertical transmission of SARS-CoV-2 from mother to newborn. We also aimed to clarify the key concepts and criteria for diagnosis of SARS-CoV-2 vertical infection in neonates and summarize the existing evidence and advance the awareness of SARS-CoV-2 vertical infection in pregnancy. Most studies we identified were case reports or case series (about 30% of poor quality and inconsistent reporting of the findings). Summarizing the existing classification criteria, we propose an algorithm for consistent diagnosis. Registration: INPLASY2022120093.

COVID-19 surveillance in wastewater: An epidemiological tool for the monitoring of SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic has prompted a lot of questions globally regarding the range of information about the virus's possible routes of transmission, diagnostics, and therapeutic tools. Worldwide studies have pointed out the importance of monitoring and early surveillance techniques based on the identification of viral RNA in wastewater. These studies indicated the presence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in human feces, which is shed via excreta including mucus, feces, saliva, and sputum. Subsequently, they get dumped into wastewater, and their presence in wastewater provides a possibility of using it as a tool to help prevent and eradicate the virus. Its monitoring is still done in many regions worldwide and serves as an early "warning signal"; however, a lot of limitations of wastewater surveillance have also been identified.

Assessing the knowledge and practices of primary healthcare workers on malaria diagnosis and related challenges in view of COVID-19 outbreak in a Nigerian Southwestern metropolis

The clinical features of COVID-19 and malaria are interrelated. Due to the similarity of symptoms between the two disease states, patients can be incorrectly diagnosed with the other ailment in areas with limited health resources. There is a dearth of knowledge of co-infection between COVID-19 and malaria from healthcare providers' perspective. Hence, this study assessed the ability of primary healthcare workers to diagnose malaria infection correctly from COVID-19 infection. A multistage sampling technique was used to select health care workers who were directly involved in malaria case management at 261 government-owned primary health facilities in Oyo State. Socio-demographic characteristics of respondents, knowledge and practices, COVID-19 differential diagnosis and challenges that healthcare workers face regarding malaria diagnosis were obtained using a standardized electronic structured questionnaire. Descriptive statistics, bivariate and multivariate analysis were conducted on data collected and significant results were interpreted at a 5% level of significance. A good percentage of the respondents (81.6%, 74.3%) had good knowledge about malaria and COVID-19. However, the knowledge gained did not translate to practice, as majority (86.2%) of respondents had poor malaria diagnosis practices. Practices relating to COVID-19 differential diagnosis in 69.7% of respondents were also poor. Most of the respondents attributed poor practices to the unavailability of Malaria Rapid Diagnostic Test (mRDT), inadequate training and continuous capacity improvement. Only 12.3% of the respondents have not had any form of training on malaria diagnosis and treatment in the last five years. Harmonization of regular trainings and continuous on-the job capacity building is essential to improve case identification, diagnosis and management of both ailments. Also, uninterrupted supplies of essential commodities such as mRDT in laboratories will reduce missed opportunities for malaria diagnosis.

Comparison of clinician diagnosis of COVID-19 with real time polymerase chain reaction in an adult-representative population in Sweden

BACKGROUND

Due to the high transmissibility of SARS-CoV-2, accurate diagnosis is essential for effective infection control, but the gold standard, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is costly, slow, and test capacity has at times been insufficient. We compared the accuracy of clinician diagnosis of COVID-19 against RT-PCR in a general adult population.

METHODS

COVID-19 diagnosis data by 30th September 2021 for participants in an ongoing population-based cohort study of adults in Western Sweden were retrieved from registers, based on positive RT-PCR and clinician diagnosis using recommended ICD-10 codes. We calculated accuracy measures of clinician diagnosis using RT-PCR as reference for all subjects and stratified by age, gender, BMI, and comorbidity collected pre-COVID-19.

RESULTS

Of 42,621 subjects, 3,936 (9.2%) and 5705 (13.4%) had had COVID-19 identified by RT-PCR and clinician diagnosis, respectively. Sensitivity and specificity of clinician diagnosis against RT-PCR were 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. Positive predictive value (PPV) was 54% (95%CI 53-55%), while negative predictive value (NPV) was 98% (95%CI 98-98%) and Youden's index 71% (95%CI 70-72%). These estimates were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while specificity, NPV, and Youden's index were similar between patients with and without chronic obstructive pulmonary disease (COPD), sensitivity was slightly higher in patients with (84% [95%CI 74-90%]) than those without (78% [95%CI 77-79%]) COPD.

CONCLUSIONS

The accuracy of clinician diagnosis for COVID-19 is adequate, regardless of gender, age, BMI, and asthma, and thus can be used for screening purposes to supplement RT-PCR.