Rapid screening of benzyl dodecyl dimethyl ammonium bromide co-metabolic degrading bacteria based on NIR hyperspectral imaging technology.

As a typical disinfectant, the use of benzyl dodecyl dimethyl ammonium bromide (BDAB) has dramatically increased since the emergence of SARS-CoV-2, posing a threat to environmental balance and human health. Screening BDAB co-metabolic degrading bacteria is required for efficient microbial degradation. Conventional methods for screening co-metabolic degrading bacteria are laborious and time-consuming, especially when the number of strains is large. This study aimed to develop a novel method for the rapid screening of BDAB co-metabolic degrading bacteria from the cultured solid medium using near-infrared hyperspectral imaging (NIR-HSI) technology. Based on NIR spectra, the concentration of BDAB in the solid medium can be well predicted by partial least squares regression (PLSR) models, non-destructively and rapidly, with Rc2 > 0.872 and Rcv2 > 0.870. The results show that the predicted BDAB concentrations decrease after degrading bacteria utilization, comparing with the regions where no degrading bacteria grew. The proposed method was applied to directly identify the BDAB co-metabolic degrading bacteria cultured on the solid medium, and two kinds of co-metabolic degrading bacteria RQR-1 and BDAB-1 were correctly identified. This method provides a high-efficiency method for screening BDAB co-metabolic degrading bacteria from a large number of bacteria.

Development of Website for COVID-19 Detection on Chest X-Ray Images

Control of the spread of COVID-19 must be encouraged, even though this is a new normal era. Rapid screening for COVID-19 detection must be carried out to control the spread of COVID-19. This research develops a website for COVID-19 detection based on chest X-Ray images and compares the CNN-BiLSTM model. This study divides X-ray images of the chest into three categories: COVID-19, Normal, and Viral Pneumonia. When compared to other models, the Resnet50-BiLSTM model produces the highest accuracy. The accuracy of the Resnet50-BiLSTM model was 98.51%. Then, in order, the following models were used: Resnet50, VGG19-BiLSTM, VGG19, AlexNet-BiLSTM, and AlexNet. The comparison of Precision, Recall, and F1-Measure findings also demonstrate that Resnet50-BiLSTM has the highest score when compared to other approaches. The website was also developed using the Flask framework for automatic COVID-19 detection. © 2022 IEEE.

Experts proposal and frequently asked questions of rapid screening and prevention of novel coronavirus pneumonia in children.

The outbreak of novel coronavirus pneumonia (NCP) has become the most severe public health issue at the moment, threatening people's lives. Pediatricians in Shanghai have recently launched a discussion on the focused questions of NCP, including the incidence situation, epidemiological features, essentials of early screening, treatment and nosocomial infection prevention of children's novel coronavirus infection (2019-nCoV), and further put forward the experts proposal upon the patterns of disease occurrence, development, diagnosis and control, for the reference of frontline pediatricians.Copyright © 2020 by the Chinese Medical Association.

Investigating public awareness, prevailing attitudes and perceptions towards domestic violence and abuse in the United Kingdom: a qualitative study.

BACKGROUND: Reported cases of Domestic Violence and Abuse (DVA) have increased since the advent of the COVID-19 pandemic and ensuing lockdowns. Understanding the general public's view about DVA is vital, as it would help develop targeted interventions and effective public policies to tackle this rising problem in society. Our qualitative study investigated the public awareness, attitudes and perceptions towards DVA, and explored mechanisms to tackle DVA in the community setting in the UK. METHODS: The research team conducted personal interviews with 29 community dwelling adults who responded to study invitations and adverts on social media. We used a topic guide to ensure consistency across the interviews, which were audio-recorded, transcribed and analysed thematically to detect emergent themes concerning DVA. RESULTS: All respondents were aware of the concept of abuse. Thirty-eight percent declared either having experienced DVA directly or that they knew someone close to being abused. More than half of the respondents were not aware of existing DVA supportive services in the UK. Overarching themes generated from the contextual analysis included contributing factors for DVA, challenges and barriers facing victims and proposals for future interventions. CONCLUSIONS: Community dwelling adults have a good understanding of the impacts of DVA, but many fail to recognise specific instances or events in their daily lives contributing to DVA. Raising public awareness, particularly in children through the school curriculum, highlighting existing support services and introducing the routine use of short screening tools for DVA in health and social care settings can increase awareness, early identification and signposting to effective interventions. Sustained, multi-level community facing interventions are recommended to reduce stigma and fear associated with DVA.

COVID-19 Detection Using Raw Chest X-Ray Images

COVID-19 has had a lasting effect on the human population around the globe. originating from Wuhan, China, in December 2019, the virus managed to spread worldwide in a short time. Huge waiting time between the detection of symptoms and clinical confirmation of the virus being present in the body has made the virus more fatal;thus, rapid screening of large numbers of suspected patients is essential. Due to inefficiency in pathological testing, alternate ways must be devised to combat these issues. Due to advancements in CAD, integrating radiological images with Artificial Intelligence (AI) can detect the disease accurately. This study proposes a deep learning model for automatic COVID-19 detection using raw Chest X-ray (CXR) images. With 17 convolutional layers, the proposed model is trained to diagnose COVID-19 with an 96.67% accuracy. The model can be used to help the world in numerous ways. © 2022 IEEE.

Development of multiplex S-gene-targeted RT-PCR for rapid identification of SARS-CoV-2 variants by extended S-gene target failure.

BACKGROUND: Tracking SARS-CoV-2 variants of concern (VOC) by genomic sequencing is time-consuming. The rapid screening of VOCs is necessary for clinical laboratories. In this study, we developed a rapid screening method based on multiplex RT-PCR by extended S-gene target failure (eSGTF), a false negative result caused by S-gene mutations. METHODS: Three S-gene target (SGT) regions (SGT1, codons 65-72; SGT2, codons 152-159; and SGT3, codons 370-377) and an N-gene region (for internal control) were detected in single-tube. Four types of VOC (Alpha, Delta, Omicron BA.1, and Omicron BA.2) are classified by positive/negative patterns of 3 S-gene regions (eSGTF pattern). RESULTS: The eSGTF patterns of VOCs were as follows (SGT1, SGT2, SGT3; P, positive; N, negative): Alpha, NPP; Delta, PNP; Omicron BA.1, NPN pattern; and Omicron BA.2, PPN. As compared with the S-gene sequencing, eSGTF patterns were identical to the specific VOCs (concordance rate = 96.7%, N = 206/213). Seven samples with discordant results had a minor mutation in the probe binding region. The epidemics of VOCs estimated by eSGTF patterns were similar to those in Japan. CONCLUSIONS: Multiplex RT-PCR and eSGTF patterns enable high-throughput screening of VOCs. It will be useful for the rapid determination of VOCs in clinical laboratories.

How Significant Are Xpert Xpress SARS-CoV-2 Test Findings When Only an N2 Gene Is Detected?

The rapid identification of patients infected with COVID-19 during the SARS-CoV-2 pandemic is critical to operating emergency rooms effectively. Xpert Xpress SARS-CoV-2 (Xpert) assays are increasingly being used in the rapid screening of COVID-19. We evaluated the clinical performance of Xpert by comparing findings with those of qRT-PCR evaluations and included the clinical features of patients visiting the emergency department. Positive results with Xpert testing (n = 370) were compared with qRT-PCR findings, demonstrating a 91.9% intertest agreement. We reviewed the subsequent COVID-19 test results and SARS-CoV-2 infection histories for individuals showing discrepancies in Xpert and qRT-PCR testing and determined whether the findings were true-positive or false-positive. The true-positive rate for Xpert testing was 95.4% (353/370); the remaining 17 samples (4.6%) were false-positive. All false-positive data for Xpert testing showed N2 signals amplified to Ct values of ≥40 with no E gene signals. Rapid Xpert testing is highly sensitive and shows a good performance overall in challenging situations, such as an emergency room. However, we considered the possibility of false-positive Xpert results given an N2 gene signal only, especially given high Ct values. We recommend interpreting test data with caution and considering retesting over time.

Tracking SARS-CoV-2 Variants Using a Rapid Typification Strategy: A Key Tool for Early Detection and Spread Investigation of Omicron in Argentina.

SARS-CoV-2 variants of concern (VOC) and interest (VOI) present mutations in reference to the original virus, being more transmissible. We implemented a rapid strategy for the screening of SARS-CoV-2 VOC/VOIs using real time RT-PCR and performed monitoring and surveillance of the variants in our region. Consecutive real-time RT-PCRs for detection of the relevant mutations/deletions present in the Spike protein in VOC/VOIs (TaqMan™ SARS-CoV-2 Mutation Panel, Applied Biosystems) were implemented. A total of 6,640 SARS-CoV-2 RNA samples (Cts < 30) from infected individuals in Central Argentina during 2021 were analyzed using different algorithms that were gradually adapted to the changing scenarios of local variant circulation. The strategy developed allowed the early detection and the identification of VOC/VOIs that circulated through the year, with a 100% of concordance with the WGS. The analyses of the samples showed introductions of VOCs Alpha and Gamma in February and March 2021, respectively. Gamma showed an exponential increase, with a peak of detection in July (72%), being responsible of the second wave of COVID19 in Argentina. Since VOC Delta entered into the region, it increased gradually, together with VOI Lambda, replacing VOC Gamma, until being the main variant (84.9%) on November. By December, these variants were replaced by the emergent VOC Omicron in a term of 2 weeks, producing the third wave. We report a useful tool for VOC/VOI detection, capable to quickly and cost-effectively monitor currently recognized variants in resource-limited settings, which allowed to track the recent expansion of Omicron in our region, and contributed to the implementation of public health measures to control the disease spread.

Description of a One-Year Succession of Variants of Interest and Concern of SARS-CoV-2 in Venezuela.

Some of the lineages of SARS-CoV-2, the new coronavirus responsible for COVID-19, exhibit higher transmissibility or partial resistance to antibody-mediated neutralization and were designated by WHO as Variants of Interests (VOIs) or Concern (VOCs). The aim of this study was to monitor the dissemination of VOIs and VOCs in Venezuela from March 2021 to February 2022. A 614 nt genomic fragment was sequenced for the detection of some relevant mutations of these variants. Their presence was confirmed by complete genome sequencing, with a correlation higher than 99% between both methodologies. After the introduction of the Gamma VOC since the beginning of the year 2021, the variants Alpha VOC and Lambda VOI were detected as early as March 2021, at a very low frequency. In contrast, the Mu VOI, detected in May 2021, was able to circulate throughout the country. After the detection of the Delta VOC in June 2021, it became the predominant circulating variant. With the arrival of the Omicron VOC in December, this variant was able to displace the Delta one in less than one month.

Detection of the Omicron variant of SARS-CoV-2 by restriction analysis targeting the mutations K417N and N440K of the spike protein

By the end of 2021, the Omicron variant of concern (VOC) emerges in South Africa. This variant caused immediate concern, due to the explosive increase in cases associated with it and the large number of mutations it exhibits. In this study, the restriction sites that allow detecting the mutations K417N and N440K in the Spike gene are described. This analysis al-lows us to propose a rapid method for the identification of cases infected with the Omicron variant. We show that the proposed methodology can contribute to provide more information on the prevalence and rapid detection of cases of this new VOC. © 2022, Instituto de Investigaciones Clinicas. All rights reserved.

Investigating the Robustness of Deep Neural Network Based COVID-19 Detection Models Against Universal Adversarial Attacks

Corona viruses are a type of virus with a large family which can cause several terrible and devastating infectious diseases like middle east respiratory syndrome and severe acute respiratory syndrome. The first task of the authority is to screen as many people as possible to detect COVID-19 patients which arises the challenge of rapid screening. Although polymerase chain reaction(PCR) tests are primarily used for the COVID-19 test but because of it's high false negative results and need of experts leading to an alternative diagnostic system based on radiological images like chest X-ray. Moreover, computer aided diagnosis systems from radiography images has significantly been advanced during the last decade with promising efficiency which can overcome the need of both time and experts. In this case, machine learning(ML) and deep learning(DL) based screening techniques can provide automated, fast and reliable results. Therefore, many researchers have proposed several deep neural network(DNN) models for rapid screening of COVID-19 using chest X-ray images. Nevertheless, the vulnerability issue DNN models are overlooked or poorly evaluated in the COVID-19 screening. DNN models are remarkably vulnerable to perturbation which is addressed universal adversarial perturbation (UAP). UAP can falsely influence a DNN model and can eventually lead to going wrong in most of the classification problems. Here, we experimented and evaluated the performance of several DNN based automated COVID-19 diagnostic models, and investigated the robustness of these models against two types of adversarial attack:non targeted and targeted. We showed that DNN based COVID-19 detection models are highly vulnerable to adversarial attack and it is substantially important to be aware of the risk factors of DNN models before deploying for real life applications. © 2021 IEEE.

Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study.

BACKGROUND: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. METHODS: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. RESULTS: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95-100) to 100% and specificity from 99% (95% CI 97-100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76-87) to 94% (95% CI 89-98) and specificity ranging from 76% (95% CI 70-82) to 92% (95% CI 88-96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. CONCLUSIONS: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people.Trial Registration NCT04509713 (clinicaltrials.gov).

Tracking the Initial Diffusion of SARS-CoV-2 Omicron Variant in Italy by RT-PCR and Comparison with Alpha and Delta Variants Spreading.

The emergence of the Omicron SARS-CoV-2 variant caused public health concerns worldwide, raising the need for the improvement of rapid monitoring strategies. The present manuscript aimed at providing evidence of the utility of a diagnostic kit for the routine testing of SARS-CoV-2 infection as a cost-effective method for tracking the Omicron variant in Italy. The study was conducted on patients' naso-oropharyngeal-swab-derived RNA samples. These samples were subjected to RT-PCR using the TaqPath COVID-19 RT PCR CE IVD kit. Nonparametric testing and polynomial models fitting were used to compare the spreading of Alpha, Delta and Omicron variants. The samples of interest were correctly amplified and displayed the presence of S gene-target failure, suggesting that these patients carry the Omicron variant. The trend of diffusion was found to be significantly different and more rapid compared with that of the Alpha and Delta variants in our cohorts. Overall, these results highlight that the S gene target failure was a very useful tool for the immediate and inexpensive tracking of Omicron variant in the three weeks from the first detection. Thus, our approach could be used as a first-line screening to reduce the time and costs of monitoring strategies, facilitating the management of preventive and counteracting measures against COVID-19.

Prompt successful response to a COVID-19 outbreak: Performance of community-based rapid screening station.

An outbreak occurred in Wanhua District of Taipei City. It was traced to a cluster infection originating from a teahouse. To prevent further large-scaled community spread, the Taipei City Government established the first community rapid test screening station. This report describes the station's strategy and performance and key factors that contributed to its operation. The project involves collaboration among various departments of Taipei City Government, including the health, environmental, police, transportation, and fire departments. The station provides rapid screening, polymerase chain reaction (PCR) testing, and immediate isolation and follow-up medical services upon the detection of a positive case. These services are accessible to local residents and are intended to ease hospitals' burdens. In 36 days, a total of 8532 people were tested, and 419 confirmed cases were identified. Over the same period, the weekly number of positive cases in Wanhua District decreased from 356 to 40, and the PCR positive rate decreased from 21.7% to 1.2%. The policy of establishing rapid screening station, contact tracing and mask wearing policy are key strategies for interrupting chains of transmission of COVID-19. This intervention has become a model for preventing the spread of the epidemic and establishing community rapid screening stations in Taiwan.

A simple method for detection of mutations in amino acid 452 of the Spike protein of SARS-CoV-2 using restriction enzyme analysis

Variants of Concern or Interest of SARS-CoV-2 (VOC or VOI), the coronavirus responsible for COVID-19, have emerged in several countries. Mutations in the amino acid 452 of the Spike protein are particularly important and associated with some of these variants: L452R, present in Delta VOC, and L452Q, present in Lambda VOI. These mutations have been associated with both increased infectivity and evasion of protective immune response. A search on GISAID to detect the number of sequences harboring the L452R mutation and the frequency of Delta VOC among them, showed that since August 2021, most of these sequences belong to the Delta VOC. Restriction enzyme analysis is proposed as a rapid method to detect L452R. A small amplicon from the Spike gene was digested with MspI. A 100% concordance was observed between digestion and sequencing results. The mutation L452Q can also be detected by restriction analysis, allowing the identification of putative Lambda VOIs. The proposed methodology, which allows screening of a great number of samples, could provide a faster information on the prevalence of Delta VOC cases.

Rapid screening for SARS-CoV-2 VOC-Alpha (202012/01, B.1.1.7) using the Allplex™ SARS-CoV-2/FluA/FluB/RSV Assay.

BACKGROUND: The emergence of SARS-CoV-2 variants of concern (VOCs) for increased transmissibility and being potentially capable of immune-escape mandates for epidemiological surveillance. Genomic alterations present in VOCs can affect the results of RT-qPCR assays for routine diagnostic purposes, leading to peculiar profiles that can be used for rapid screening of variants. This study reports a peculiar profile observed with the Allplex™ SARS-CoV-2/FluA/FluB/RSV assay and VOC-Alpha (202012/01, lineage B.1.1.7, also named VOC-UK), which was the first identified SARS-CoV-2 VOC. METHODS: Samples were analyzed by two RT-qPCR assays: the Allplex™ SARS-CoV-2/FluA/FluB/RSV assay (ASFR, Seegene Technologies Inc; Seoul, South Korea) and the TaqPath COVID-19 RT-PCR (Thermo Fisher Scientific, USA). Definition of the SARS-CoV-2 variant was carried out by Sanger sequencing of the relevant S-gene regions and, in some cases, by whole genome sequencing (WGS) using the ARTIC-nCoV workflow on a MiniION (Oxford Nanopore Technologies, Oxford, UK) or a Illumina MiSeq platform (San Diego, California, USA). RESULTS: Of the 173 SARS-CoV-2-positive specimens, all those of lineage B.1.1.7 (N=71) showed an average Cq difference between the N and S genes of +11±2 (range, +8/+15). None of the other specimens, including several different lineages (Wild-type for the analyzed regions, N=22; Gamma, N=63; Delta, N=9; B.1.258Δ, N=3; B.1.160, N=3; B.1.177.7, N=1; B.1.1.420, N=1), exhibited a similar difference in Cq values. CONCLUSIONS: The peculiar pattern of delayed N gene positivity could constitute a convenient method for VOC-Alpha screening, simultaneous to viral detection, when using the Allplex™ SARS-CoV-2/FluA/FluB/RSV assay.

Rapid screening for COVID-19 by applying artificial intelligence to chest computed tomography images: A feasibility study.

Aim: The aim of the study was to present the results and impact of the application of artificial intelligence (AI) in the rapid diagnosis of COVID-19 by telemedicine in public health in Paraguay. Methods: This is a descriptive, multi-centered, observational design feasibility study based on an AI tool for the rapid detection of COVID-19 in chest computed tomography (CT) images of patients with respiratory difficulties attending the country's public hospitals. The patients' digital CT images were transmitted to the AI diagnostic platform, and after a few minutes, radiologists and pneumologists specialized in COVID-19 downloaded the images for evaluation, confirmation of diagnosis, and comparison with the genetic diagnosis (reverse transcription polymerase chain reaction (RT-PCR)). It was also determined the percentage of agreement between two similar AI systems applied in parallel to study the viability of using it as an alternative method of screening patients with COVID-19 through telemedicine. Results: Between March and August 2020, 911 rapid diagnostic tests were carried out on patients with respiratory disorders to rule out COVID-19 in 14 hospitals nationwide. The average age of patients was 50.7 years, 62.6% were male and 37.4% female. Most of the diagnosed respiratory conditions corresponded to the age group of 27-59 years (252 studies), the second most frequent corresponded to the group over 60 years, and the third to the group of 19-26 years. The most frequent findings of the radiologists/pneumologists were severe pneumonia, bilateral pneumonia with pleural effusion, bilateral pulmonary emphysema, diffuse ground glass opacity, hemidiaphragmatic paresis, calcified granuloma in the lower right lobe, bilateral pleural effusion, sequelae of tuberculosis, bilateral emphysema, and fibrotic changes, among others. Overall, an average of 86% agreement and 14% diagnostic discordance was determined between the two AI systems. The sensitivity of the AI system was 93% and the specificity 80% compared with RT-PCR. Conclusion: Paraguay has an AI-based telemedicine screening system for the rapid stratified detection of COVID-19 from chest CT images of patients with respiratory conditions. This application strengthens the integrated network of health services, rationalizing the use of specialized human resources, equipment, and inputs for laboratory diagnosis.

Yeungnam University type drive-through (YU-Thru) coronavirus disease 2019 (COVID-19) screening system: a rapid and safe screening system.

Active and prompt scale-up screening tests are essential to efficiently control the coronavirus disease 2019 (COVID-19) outbreak. The goal of this work was to identify shortcomings in the conventional screening system (CSS) implemented in the beginning of the outbreak. To overcome these shortcomings, we then introduced a novel, independently developed system called the Yeungnam University type drive-through (YU-Thru), and distributed it nationwide in Korea. This system is similar to the drive-throughs utilized by fast food restaurants. YU-Thru system has shortened the time taken to test a single person to 2-4 minutes, by completely eliminating the time required to clean and ventilate the specimen collection room. This time requirement was a major drawback of the CSS. YU-Thru system also reduced the risk of subjects and medical staff infecting one another by using a separate and closed examination system. On average, 50 to 60 tests were conducted per day when using the CSS, while now up to 350 tests per day are conducted with the YU-Thru system. We believe that the YU-Thru system has made an important contribution to the rapid detection of COVID-19 in Daegu, South Korea. Here, we will describe the YU-Thru system in detail so that other countries experiencing COVID-19 outbreaks can take advantage of this system.

Experts proposal and frequently asked questions of rapid screening and prevention of novel coronavirus pneumonia in children / 中华实用儿科临床杂志

The outbreak of novel coronavirus pneumonia (NCP) has become the most severe public health issue at the moment, threatening people′s lives. Pediatricians in Shanghai have recently launched a discussion on the focused questions of NCP, including the incidence situation, epidemiological features, essentials of early screening, treatment and nosocomial infection prevention of children′s novel coronavirus infection (2019-nCoV), and further put forward the experts proposal upon the patterns of disease occurrence, development, diagnosis and control, for the reference of frontline pediatricians.