Feasibility of Rapid Diagnostic Technology for SARS-CoV-2 Virus Using a Trace Amount of Saliva

Containment of SARS-CoV-2 has become an urgent global issue. To overcome the problems of conventional quantitative polymerase chain reaction (qPCR) tests, we verified the usefulness of a mobile qPCR device that utilizes mouthwash to obtain a saliva sample with the aim of developing a rapid diagnostic method for SARS-CoV-2. First, we examined whether anyone could easily operate this device. Then, we examined whether RNA in the mouthwash could be detected in a short time. In addition, we investigated whether it was possible to diagnose SARS-CoV-2 infection using mouthwash obtained from COVID-19 patients undergoing hospitalization. The results revealed that all subjects were able to complete the operation properly without error. In addition, RNase P was detected in the mouthwash without pretreatment. The average detection time was 18 min, which is significantly shorter than conventional qPCR devices. Furthermore, this device detected SARS-CoV-2 in the mouthwash of a COVID-19 patient undergoing hospitalization. The above findings verified the efficacy of this diagnostic method, which had a low risk of infection, was technically simple, and provided stable results. Therefore, this method is useful for the rapid detection of SARS-CoV-2.

A simple and rapid diagnostic method for 13 types of high-risk human papillomavirus (HR-HPV) detection using CRISPR-Cas12a technology

Cervical carcinoma is the second most common cancer in women worldwide with greater than 99% of the cases caused by human papillomaviruses (HPVs). Early detection of HPVs especially the high risk types (HR-HPVs) are essential to prevent the disease progression. The existing methods for HPV detection, such as qPCR are of high sensitivity and specificity, but the need for expensive machinery and well-trained personnel slow down the disease detection. The emerging Cas12a-based method presents a new technique for nucleic acid detection. However, it is time-consuming and labor-intensive when used for HPV detection, as several reactions are required in order to identify multiple HPV infections. We herein present a non-genotyping method for 13 types of HR-HPV detection in a single reaction by combining the isothermal recombinase polymerase amplification (RPA) method with CRISPR-Cas12a technology. The result could be achieved in 35 min with high sensitivity (500 copies per reaction). This assay represents great advances for the application of RPA-Cas12a system and holds a great potential to address the key challenges facing the HPV diagnostics.

A simple and rapid diagnostic method for 13 types of High risk human papillomavirus (HR-HPVs) detection using CRISPR-Cas12a technology

Cervical carcinoma is the second most common cancer in women worldwide with greater than 99% of the cases caused by human papillomaviruses (HPVs). Early detection of HPVs especially the high risk types (HR-HPVs) are essential to prevent the disease progression. The existing methods for HPV detection, such as qPCR are of high sensitivity and specificity, but the need for expensive machinery and well-trained personnel slow down the disease detection. The emerging Cas12a-based method presents a new technique for nucleic acid detection. However, it is time-consuming and labor-intensive when used for HPV detection, as several reactions are required in order to identify multiple HPV infections. We herein present a non-genotyping method for 13 types of HR-HPV detection in a single reaction by combining the isothermal recombinase polymerase amplification (RPA) method with CRISPR-Cas12a technology. The result could be achieved in 30 minutes with high sensitivity (500 copies per reaction). This assay reprsents great advances for the application of RPA-Cas12a system and holds a great potential to address the key challenges facing the HPV diagnostics.

Influenza, malaria parasitemia, and typhoid fever coinfection in children: Seroepidemiological investigation in four Health-care Centers in Lagos, Nigeria

Objectives: There are similarities in the presentation of influenza-A infection, malaria, and typhoid fever which include their overlapping clinical symptoms such as fever and myalgia. Coinfection may be easily missed and may lead to more severe associated morbidity. This study, therefore, investigated the prevalence of coinfection of influenza A, malaria, and typhoid fever in children in four locations in Lagos and determined their age, gender, and location-related prevalence. Materials and Methods: A cross-sectional hospital-based study was conducted between March and October 2018. Children less than 15 years attending four health centers in Festac, Amuwo, Ojo, and Shibiri were recruited consecutively. Demographic and epidemiological data were obtained using structured questionnaires, to ascertain children with influenza-like symptoms. Their blood samples were then tested with rapid diagnostic method for malaria and typhoid fever. The children were further screened for influenza-A-specific IgM using ELISA method. Descriptive statistics were reported while p-values were determined for comparable parameters using Chi-square. Results: There were 364 children aged <1–14 years including 207 (56.9%) males. Of the 364 children tested, 76/364 (20.9%) were seropositive for influenza-A virus out of which 47/76 (61.8%) had malaria parasitemia, 42/76 (55.3%) had typhoid fever, and 21/76 (27.6%) were coinfected with both malaria parasites and Salmonella enteric Typhi. Children coinfected with influenza-A and malaria were found with a higher frequency of chest pain and cold/chill symptom respectively compared to children having influenza alone (P = 0.0001). Seropositivity for influenza was recorded in all the months studied with the month of March recording the highest influenza-A seropositivity of 20/76 (26.3%) (P = 0.02). Conclusion: This study detected 27.6% trio coinfection seroprevalence of influenza Type-A, malaria, and typhoid fever among children population. The finding is unique being the first of such report, to the best of our knowledge. Children coinfected with influenza-A and malaria had greater morbidity.

Comparative Study of Newer and Established Methods of Diagnosing Coccidioidal Meningitis

Meningitis is the most devastating form of coccidioidomycosis. A convenient, rapid diagnostic method could result in early treatment and avoid many meningitis complications. We studied cerebrospinal fluid (CSF) samples in patients with documented coccidioidal meningitis, and controls, with complement fixation (CF), immunodiffusion (ID) (the “classical” assays), lateral flow assays (LFA; one-strip and two-strip), and two enzyme immunoassays (EIA). The two-strip LFA and EIAs not only enabled separate testing for IgG and IgM antibodies separately, but also could aggregate results for each method. CF with ID or the aggregate use of IgG and IgM tests were considered optimal test uses. LFAs and EIAs were evaluated at 1:21 and 1:441 dilutions of specimens. All assays were compared to true patient status. With 49 patient specimens and 40 controls, this is the largest comparative study of CSF coccidioidal diagnostics. Sensitivity of these tests ranged from 71–95% and specificity 90–100%. IgM assays were less sensitive. Assays at 1:441 were similarly specific but less sensitive, suggesting that serial dilutions of samples could result in assays yielding titers. Agreement of positive results on cases was 87–100%. When kits are available, hospital laboratories in endemic areas can perform testing. LFA assays do not require a laboratory, are simple to use, and give rapid results, potentially even at the bedside.

Establishment of rapid diagnostic method for the identification of Staphylococcus aureus in bacterial conjunctivitis

Staphylococcus aureus is the most frequent cause of conjunctivitis and may lead to severe visual impairment. However, the tools available for the diagnosis, such as bacterial culture and cytology, are often inadequate. Therefore, the goal of the present work was to establish a rapid detection method for S. aureus in the secretions of the conjunctival sac to provide a basis for the early diagnosis of acute bacterial conjunctivitis. The study included 32 patients with acute bacterial conjunctivitis, 30 patients with viral conjunctivitis, and 28 control subjects. Extracted DNA was analyzed by conventional PCR and RT-PCR using primers specific for S. aureus DNA and two antibiotic resistance genes, mecA and femB. By this technique, S. aureus was found in 37.5% of patients with bacterial conjunctivitis, 20% of patients with viral conjunctivitis, and in 7.1% normal control subjects. Except for the control group in which the femB gene was not found, in most other cases S. aureus carried mecA and femB genes. The developed molecular biology approach is faster and more sensitive than the methods requiring bacterial cultures and is uniquely suited for the detection of an S. aureus infection in the eye.

Screening and Diagnosis of Chronic Pharyngitis Based on Deep Learning

Chronic pharyngitis is a common disease, which has a long duration and a wide range of onset. It is easy to misdiagnose by mistaking it with other diseases, such as chronic tonsillitis, by using common diagnostic methods. In order to reduce costs and avoid misdiagnosis, the search for an affordable and rapid diagnostic method is becoming more and more important for chronic pharyngitis research. Speech disorder is one of the typical symptoms of patients with chronic pharyngitis. This paper introduces a convolutional neural network model for diagnosis based on the typical symptom of speech disorder. First of all, the voice data is converted into a speech spectrogram, which can better output the speech characteristic information and lay a foundation for computer diagnosis and discrimination. Second, we construct a deep convolutional neural network for the diagnosis of chronic pharyngitis through the design of the structure, the design of the network layer, and the description of the function. Finally, we perform a parameter optimization experiment on the convolutional neural network and judge the recognition efficiency of chronic pharyngitis. The results show that the convolutional neural network has a high recognition rate for patients with chronic pharyngitis and has a good diagnostic effect.