Deep Learning Methods for Interpretation of Pulmonary CT and X-ray Images in Patients with COVID-19-Related Lung Involvement: A Systematic Review.

SARS-CoV-2 is a novel virus that has been affecting the global population by spreading rapidly and causing severe complications, which require prompt and elaborate emergency treatment. Automatic tools to diagnose COVID-19 could potentially be an important and useful aid. Radiologists and clinicians could potentially rely on interpretable AI technologies to address the diagnosis and monitoring of COVID-19 patients. This paper aims to provide a comprehensive analysis of the state-of-the-art deep learning techniques for COVID-19 classification. The previous studies are methodically evaluated, and a summary of the proposed convolutional neural network (CNN)-based classification approaches is presented. The reviewed papers have presented a variety of CNN models and architectures that were developed to provide an accurate and quick automatic tool to diagnose the COVID-19 virus based on presented CT scan or X-ray images. In this systematic review, we focused on the critical components of the deep learning approach, such as network architecture, model complexity, parameter optimization, explainability, and dataset/code availability. The literature search yielded a large number of studies over the past period of the virus spread, and we summarized their past efforts. State-of-the-art CNN architectures, with their strengths and weaknesses, are discussed with respect to diverse technical and clinical evaluation metrics to safely implement current AI studies in medical practice.

Ultrasensitive and amplification-free detection of SARS-CoV-2 RNA using an electrochemical biosensor powered by CRISPR/Cas13a.

This study proposed a CRISPR/Cas13a-powered electrochemical multiplexed biosensor for detecting SARS-CoV-2 RNA strands. Current SARS-CoV-2 diagnostic methods, such as reverse transcription PCR (RT-PCR), are primarily based on nucleic acid amplification (NAA) and reverse transcription (RT) processes, which have been linked to significant issues such as cross-contamination and long turnaround times. Using a CRISPR/Cas13a system integrated onto an electrochemical biosensor, we present a multiplexed and NAA-free strategy for detecting SARS-CoV-2 RNA fragments. SARS-CoV-2 S and Orf1ab genes were detected in both synthetic and clinical samples. The CRISPR/Cas13a-powered biosensor achieved low detection limits of 2.5 and 4.5 ag/µL for the S and Orf1ab genes, respectively, successfully meeting the sensitivity requirement. Furthermore, the biosensor's specificity, simplicity, and universality may position it as a potential rival to RT-PCR.

Preclinical assessment and randomized Phase I study of CT-P63, a broadly neutralizing antibody targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in significant morbidity and mortality worldwide. Despite a successful vaccination programme, the emergence of mutated variants that can escape current levels of immunity mean infections continue. Herein, we report the development of CT-P63, a broad-spectrum neutralizing monoclonal antibody. In vitro studies demonstrated potent neutralizing activity against the most prevalent variants, including Delta and the BA.1 and BA.2 sub-lineages of Omicron. In a transgenic mouse model, prophylactic CT-P63 significantly reduced wild-type viral titres in the respiratory tract and CT-P63 treatment proved efficacious against infection with Beta, Delta, and Omicron variants of SARS-CoV-2 with no detectable infectious virus in the lungs of treated animals. A randomized, double-blind, parallel-group, placebo-controlled, Phase I, single ascending dose study in healthy volunteers (NCT05017168) confirmed the safety, tolerability, and pharmacokinetics of CT-P63. Twenty-four participants were randomized and received the planned dose of CT-P63 or placebo. The safety and tolerability of CT-P63 were evaluated as primary objectives. Eight participants (33.3%) experienced a treatment-emergent adverse event (TEAE), including one grade ≥3 (blood creatine phosphokinase increased). There were no deaths, treatment-emergent serious adverse events, TEAEs of special interest, or TEAEs leading to study drug discontinuation in the CT-P63 groups. Serum CT-P63 concentrations rapidly peaked before declining in a biphasic manner and systemic exposure was dose proportional. Overall, CT-P63 was clinically safe and showed broad-spectrum neutralizing activity against SARS-CoV-2 variants in vitro and in vivo.

Comparative effectiveness of N95, surgical or medical, and non-medical facemasks in protection against respiratory virus infection: A systematic review and network meta-analysis.

The aim of this systematic review and network meta-analysis is to evaluate the comparative effectiveness of N95, surgical/medical and non-medical facemasks as personal protective equipment against respiratory virus infection. The study incorporated 35 published and unpublished randomized controlled trials and observational studies investigating specific mask effectiveness against influenza virus, SARS-CoV, MERS-CoV and SARS-CoV-2. We searched PubMed, Google Scholar and medRxiv databases for studies published up to 5 February 2021 (PROSPERO registration: CRD42020214729). The primary outcome of interest was the rate of respiratory viral infection. The quality of evidence was estimated using the GRADE approach. High compliance to mask-wearing conferred a significantly better protection (odds ratio [OR], 0.43; 95% confidence interval [CI], 0.23-0.82) than low compliance. N95 or equivalent masks were the most effective in providing protection against coronavirus infections (OR, 0.30; CI, 0.20-0.44) consistently across subgroup analyses of causative viruses and clinical settings. Evidence supporting the use of medical or surgical masks against influenza or coronavirus infections (SARS, MERS and COVID-19) was weak. Our study confirmed that the use of facemasks provides protection against respiratory viral infections in general; however, the effectiveness may vary according to the type of facemask used. Our findings encourage the use of N95 respirators or their equivalents (e.g., P2) for best personal protection in healthcare settings until more evidence on surgical and medical masks is accrued. This study highlights a substantial lack of evidence on the comparative effectiveness of mask types in community settings.

Computational Method-Based Optimization of Carbon Nanotube Thin-Film Immunosensor for Rapid Detection of SARS-CoV-2 Virus.

The recent global spread of COVID-19 stresses the importance of developing diagnostic testing that is rapid and does not require specialized laboratories. In this regard, nanomaterial thin-film-based immunosensors fabricated via solution processing are promising, potentially due to their mass manufacturability, on-site detection, and high sensitivity that enable direct detection of virus without the need for molecular amplification. However, thus far, thin-film-based biosensors have been fabricated without properly analyzing how the thin-film properties are correlated with the biosensor performance, limiting the understanding of property-performance relationships and the optimization process. Herein, the correlations between various thin-film properties and the sensitivity of carbon nanotube thin-film-based immunosensors are systematically analyzed, through which optimal sensitivity is attained. Sensitivities toward SARS-CoV-2 nucleocapsid protein in buffer solution and in the lysed virus are 0.024 [fg/mL]-1 and 0.048 [copies/mL]-1, respectively, which are sufficient for diagnosing patients in the early stages of COVID-19. The technique, therefore, can potentially elucidate complex relationships between properties and performance of biosensors, thereby enabling systematic optimization to further advance the applicability of biosensors for accurate and rapid point-of-care (POC) diagnosis.

Autoimmune inflammatory rheumatic diseases and COVID-19 outcomes in South Korea: a nationwide cohort study.

BACKGROUND: Real-world evidence on the association between autoimmune inflammatory rheumatic diseases, therapies related to these diseases, and COVID-19 outcomes are inconsistent. We aimed to investigate the potential association between autoimmune inflammatory rheumatic diseases and COVID-19 early in the COVID-19 pandemic. METHODS: We did an exposure-driven, propensity score-matched study using a South Korean nationwide cohort linked to general health examination records. We analysed all South Korean patients aged older than 20 years who underwent SARS-CoV-2 RT-PCR testing between Jan 1 and May 30, 2020, and received general health examination results from the Korean National Health Insurance Service. We defined autoimmune inflammatory rheumatic diseases (inflammatory arthritis and connective tissue diseases) based on the relevant ICD-10 codes, with at least two claims (outpatient or inpatient) within 1 year. The outcomes were positive SARS-CoV-2 RT-PCR test, severe COVID-19 (requirement of oxygen therapy, intensive care unit admission, application of invasive ventilation, or death), and COVID-19-related death. Adjusted odds ratios (ORs) with 95% CIs were estimated after adjusting for the potential confounders. FINDINGS: Between Jan 1 and May 30, 2020, 133 609 patients (70 050 [52·4%] female and 63 559 [47·6%] male) completed the general health examination and were tested for SARS-CoV-2; 4365 (3·3%) were positive for SARS-CoV-2, and 8297 (6·2%) were diagnosed with autoimmune inflammatory rheumatic diseases. After matching, patients with an autoimmune inflammatory rheumatic disease showed an increased likelihood of testing positive for SARS-CoV-2 (adjusted OR 1·19, 95% CI 1·03-1·40; p=0·026), severe COVID-19 outcomes (1·26, 1·02-1·59; p=0·041), and COVID-19-related death (1·69, 1·01-2·84; p=0·046). Similar results were observed in patients with connective tissue disease and inflammatory arthritis. Treatment with any dose of systemic corticosteroids or disease-modifying antirheumatic drugs (DMARDs) were not associated with COVID-19-related outcomes, but those receiving high dose (≥10 mg per day) of systemic corticosteroids had an increased likelihood of a positive SARS-CoV-2 test (adjusted OR 1·47, 95% CI 1·05-2·03; p=0·022), severe COVID-19 outcomes (1·76, 1·06-2·96; p=0·031), and COVID-19-related death (3·34, 1·23-8·90; p=0·017). INTERPRETATION: Early in the COVID-19 pandemic, autoimmune inflammatory rheumatic diseases were associated with an increased likelihood of a positive SARS-CoV-2 PCR test, worse clinical outcomes of COVID-19, and COVID-19-related deaths in South Korea. A high dose of systemic corticosteroid, but not DMARDs, showed an adverse effect on SARS-CoV-2 infection and COVID-19-related clinical outcomes. FUNDING: National Research Foundation of Korea.

Rapid, multiplexed, and nucleic acid amplification-free detection of SARS-CoV-2 RNA using an electrochemical biosensor.

Considering the worldwide health crisis associated with highly contagious severe respiratory disease of COVID-19 outbreak, the development of multiplexed, simple and rapid diagnostic platforms to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is in high demand. Here, a nucleic acid amplification-free electrochemical biosensor based on four-way junction (4-WJ) hybridization is presented for the detection of SARS-CoV-2. To form a 4-WJ structure, a Universal DNA-Hairpin (UDH) probe is hybridized with two adaptor strands and a SARS-CoV-2 RNA target. One of the adaptor strands is functionalized with a redox mediator that can be detected using an electrochemical biosensor. The biosensor could simultaneously detect 5.0 and 6.8 ag/µL of S and Orf1ab genes, respectively, within 1 h. The biosensor was evaluated with 21 clinical samples (16 positive and 5 negative). The results revealed a satisfactory agreement with qRT-PCR. In conclusion, this biosensor has the potential to be used as an on-site, real-time diagnostic test for COVID-19.

Mix-and-read, one-minute SARS-CoV-2 diagnostic assay: development of PIFE-based aptasensor.

We developed a one-minute, one-step SARS-CoV-2 antigen assay based on protein-induced fluorescence enhancement of a DNA aptamer. The system showed significant selectivity and sensitivity towards both nucleocapsid protein and SARS-CoV-2 virus lysate, but with marked improvements in speed and manufacturability. We hence propose this platform as a mix-and-read testing strategy for SARS-CoV-2 that can be applied to POC diagnostics in clinical settings, especially in low- and middle-income countries.

The in vitro and in vivo efficacy of CT-P59 against Gamma, Delta and its associated variants of SARS-CoV-2.

The SARS-CoV-2 variant is rapidly spreading across the world and causes to resurge infections. We previously reported that CT-P59 presented its in vivo potency against Beta variants, despite its reduced activity in cell experiments. Yet, it remains uncertain to exert the antiviral effect of CT-P59 on Gamma, Delta and its associated variants (L452R). To tackle this question, we carried out cell tests and animal studies. CT-P59 showed neutralization against Gamma, Delta, Epsilon, and Kappa variants in cells, with reduced susceptibility. The mouse challenge experiments with Gamma and Delta variants substantiated in vivo potency of CT-P59 showing symptom remission and virus abrogation in the respiratory tract. Collectively, cell and animal studies showed that CT-P59 is effective against Gamma and Delta variants infection, hinting that CT-P59 has therapeutic potential for patients infected with Gamma, Delta and its associated variants.

Recent advances in sensitive surface-enhanced Raman scattering-based lateral flow assay platforms for point-of-care diagnostics of infectious diseases.

This review reports the recent advances in surface-enhanced Raman scattering (SERS)-based lateral flow assay (LFA) platforms for the diagnosis of infectious diseases. As observed through the recent infection outbreaks of COVID-19 worldwide, a timely diagnosis of the disease is critical for preventing the spread of a disease and to ensure epidemic preparedness. In this regard, an innovative point-of-care diagnostic method is essential. Recently, SERS-based assay platforms have received increasing attention in medical communities owing to their high sensitivity and multiplex detection capability. In contrast, LFAs provide a user-friendly and easily accessible sensing platform. Thus, the combination of LFAs with a SERS detection system provides a new diagnostic modality for accurate and rapid diagnoses of infectious diseases. In this context, we briefly discuss the recent application of LFA platforms for the POC diagnosis of SARS-CoV-2. Thereafter, we focus on the recent advances in SERS-based LFA platforms for the early diagnosis of infectious diseases and their applicability for the rapid diagnosis of SARS-CoV-2. Finally, the key issues that need to be addressed to accelerate the clinical translation of SERS-based LFA platforms from the research laboratory to the bedside are discussed.