Background
Accurate rapid diagnostic tests for SARS‐CoV‐2 infection could contribute to clinical and public health strategies to manage the COVID‐19 pandemic. Point‐of‐care antigen and molecular tests to detect current infection could increase access to testing and early confirmation of cases, and expediate clinical and public health management decisions that may reduce transmission.

Objectives
To assess the diagnostic accuracy of point‐of‐care antigen and molecular‐based tests for diagnosis of SARS‐CoV‐2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups.

Search methods
Electronic searches of the Cochrane COVID‐19 Study Register and the COVID‐19 Living Evidence Database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) were undertaken on 30 Sept 2020. We checked repositories of COVID‐19 publications and included independent evaluations from national reference laboratories, the Foundation for Innovative New Diagnostics and the Diagnostics Global Health website to 16 Nov 2020. We did not apply language restrictions.

Selection criteria
We included studies of people with either suspected SARS‐CoV‐2 infection, known SARS‐CoV‐2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen or molecular tests suitable for a point‐of‐care setting (minimal equipment, sample preparation, and biosafety requirements, with results within two hours of sample collection). We included all reference standards that define the presence or absence of SARS‐CoV‐2 (including reverse transcription polymerase chain reaction (RT‐PCR) tests and established diagnostic criteria).

Data collection and analysis
Studies were screened independently in duplicate with disagreements resolved by discussion with a third author. Study characteristics were extracted by one author and checked by a second; extraction of study results and assessments of risk of bias and applicability (made using the QUADAS‐2 tool) were undertaken independently in duplicate. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and pooled data using the bivariate model separately for antigen and molecular‐based tests. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status.

Main results
Seventy‐eight study cohorts were included (described in 64 study reports, including 20 pre‐prints), reporting results for 24,087 samples (7,415 with confirmed SARS‐CoV‐2). Studies were mainly from Europe (n = 39) or North America (n = 20), and evaluated 16 antigen and five molecular assays.

We considered risk of bias to be high in 29 (37%) studies because of participant selection; in 66 (85%) because of weaknesses in the reference standard for absence of infection; and in 29 (37%) for participant flow and timing. Studies of antigen tests were of a higher methodological quality compared to studies of molecular tests, particularly regarding the risk of bias for participant selection and the index test. Characteristics of participants in 35 (45%) studies differed from those in whom the test was intended to be used and the delivery of the index test in 39 (50%) studies differed from the way in which the test was intended to be used. Nearly all studies (97%) defined the presence or absence of SARS‐CoV‐2 based on a single RT‐PCR result, and none included participants meeting case definitions for probable COVID‐19.

Antigen tests

Forty‐eight studies reported 58 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies. There were differences between symptomatic (72.0%, 95% CI 63.7% to 79.0%; 37 evaluations; 15530 samples, 4410 cases) and asymptomatic participants (58.1%, 95% CI 40.2% to 74.1%; 12 evaluations; 1581 samples, 295 cases). Average sensitivity was higher in the first week after symptom onset (78.3%, 95% CI 71.1% to 84.1%; 26 evaluations; 5769 samples, 2320 cases) than in the second week of symptoms (51.0%, 95% CI 40.8% to 61.0%; 22 evaluations; 935 samples, 692 cases). Sensitivity was high in those with cycle threshold (Ct) values on PCR ≤25 (94.5%, 95% CI 91.0% to 96.7%; 36 evaluations; 2613 cases) compared to those with Ct values >25 (40.7%, 95% CI 31.8% to 50.3%; 36 evaluations; 2632 cases). Sensitivity varied between brands. Using data from instructions for use (IFU) compliant evaluations in symptomatic participants, summary sensitivities ranged from 34.1% (95% CI 29.7% to 38.8%; Coris Bioconcept) to 88.1% (95% CI 84.2% to 91.1%; SD Biosensor STANDARD Q). Average specificities were high in symptomatic and asymptomatic participants, and for most brands (overall summary specificity 99.6%, 95% CI 99.0% to 99.8%).

At 5% prevalence using data for the most sensitive assays in symptomatic people (SD Biosensor STANDARD Q and Abbott Panbio), positive predictive values (PPVs) of 84% to 90% mean that between 1 in 10 and 1 in 6 positive results will be a false positive, and between 1 in 4 and 1 in 8 cases will be missed. At 0.5% prevalence applying the same tests in asymptomatic people would result in PPVs of 11% to 28% meaning that between 7 in 10 and 9 in 10 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed.

No studies assessed the accuracy of repeated lateral flow testing or self‐testing.

Rapid molecular assays

Thirty studies reported 33 evaluations of five different rapid molecular tests. Sensitivities varied according to test brand. Most of the data relate to the ID NOW and Xpert Xpress assays. Using data from evaluations following the manufacturer’s instructions for use, the average sensitivity of ID NOW was 73.0% (95% CI 66.8% to 78.4%) and average specificity 99.7% (95% CI 98.7% to 99.9%; 4 evaluations; 812 samples, 222 cases). For Xpert Xpress, the average sensitivity was 100% (95% CI 88.1% to 100%) and average specificity 97.2% (95% CI 89.4% to 99.3%; 2 evaluations; 100 samples, 29 cases). Insufficient data were available to investigate the effect of symptom status or time after symptom onset.

Authors' conclusions
Antigen tests vary in sensitivity. In people with signs and symptoms of COVID‐19, sensitivities are highest in the first week of illness when viral loads are higher. The assays shown to meet appropriate criteria, such as WHO's priority target product profiles for COVID‐19 diagnostics (‘acceptable’ sensitivity ≥ 80% and specificity ≥ 97%), can be considered as a replacement for laboratory‐based RT‐PCR when immediate decisions about patient care must be made, or where RT‐PCR cannot be delivered in a timely manner. Positive predictive values suggest that confirmatory testing of those with positive results may be considered in low prevalence settings. Due to the variable sensitivity of antigen tests, people who test negative may still be infected.

Evidence for testing in asymptomatic cohorts was limited. Test accuracy studies cannot adequately assess the ability of antigen tests to differentiate those who are infectious and require isolation from those who pose no risk, as there is no reference standard for infectiousness. A small number of molecular tests showed high accuracy and may be suitable alternatives to RT‐PCR. However, further evaluations of the tests in settings as they are intended to be used are required to fully establish performance in practice.

Several important studies in asymptomatic individuals have been reported since the close of our search and will be incorporated at the next update of this review. Comparative studies of antigen tests in their intended use settings and according to test operator (including self‐testing) are required.

/pdf/rapid-point-of-care-antigen-and-molecular-based-tests-for-2a2qjx1fq9.pdf

Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection.

Antibiotics, disinfectants and bacteria resistant to them have been detected in environmental compartments such as waste water, surface water, ground water, sediments and soils. Antibiotics are released into the environment after their use in medicine, veterinary medicine and their employment as growth promoters in animal husbandry, fish farming and other fields. There is increasing concern about the growing resistance of pathogenic bacteria in the environment, and their ecotoxic effects. Increasingly, antibiotic resistance is seen as an ecological problem. This includes both the ecology of resistance genes and that of the resistant bacteria themselves. Little is known about the effects of subinhibitory concentrations of antibiotics and disinfectants on environmental bacteria, especially with respect to resistance. According to the present state of our knowledge, the impact on the frequency of resistance transfer by antibacterials present in the environment is questionable. The input of resistant bacteria into the environment seems to be an important source of resistance in the environment. The possible impact of resistant bacteria on the environment is not yet known. Further research into these issues is warranted.

Resistance in the Environment

The cyanine platforms including cyanine, hemicyanine, and squaraine are good candidates for developing chemosensors because of their excellent photophysical properties, outstanding biocompatibility, and low toxicity to living systems. A huge amount of research work involving chemosensors based on the cyanine platforms has emerged in recent years. This review focuses on the development from 2000 to 2015, in which cyanine, hemicyanine, and squaraine sensors will be separately summarized. In each section, a systematization according to the type of detection mechanism is established. The basic principles about the design of the chemosensors and their applications as bioimaging agents are clearly discussed. In addition, we emphasize the advances that have been made in improving the detection performance through incorporation of the chemosensors into nanoparticles.

Recent Development of Chemosensors Based on Cyanine Platforms

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection. Objectives To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys. Search methods We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020. Selection criteria We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria). Data collection and analysis We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs). Main results We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands. Authors' conclusions The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.

Antibody tests for identification of current and past infection with SARS‐CoV‐2

Surgical resection of solid tumors is currently the gold standard and preferred therapeutic strategy for cancer. Chemotherapy drugs also make a significant contribution by inhibiting the rapid growth of tumor cells and these two approaches are often combined to enhance treatment efficacy. However, surgery and chemotherapy inevitably lead to severe side effects and high systemic toxicity, which in turn results in poor prognosis. Precision medicine has promoted the development of treatment modalities that are developed to specifically target and kill tumor cells. Advances in in vivo medical imaging for visualizing tumor lesions can aid diagnosis, facilitate surgical resection, investigate therapeutic efficacy, and improve prognosis. In particular, the modality of fluorescence imaging has high specificity and sensitivity and has been utilized for medical imaging. Therefore, there are great opportunities for chemists and physicians to conceive, synthesize, and exploit new chemical probes that can image tumors and release chemotherapy drugs in vivo. This review focuses on small molecular ligand-targeted fluorescent imaging probes and fluorescent theranostics, including their design strategies and applications in clinical tumor treatment. The progress in chemical probes described here suggests that fluorescence imaging is a vital and rapidly developing field for interventional surgical imaging, as well as tumor diagnosis and therapy.

/pdf/fluorescent-chemical-probes-for-accurate-tumor-diagnosis-and-3j5p8i5h85.pdf

Fluorescent chemical probes for accurate tumor diagnosis and targeting therapy

The recent outbreak of novel coronavirus (SARS-CoV-2) causing COVID-19 disease spreads rapidly in the world. Rapid and early detection of SARS-CoV-2 facilitates early intervention and prevents the disease spread. Here, we present an All-In-One Dual CRISPR-Cas12a (AIOD-CRISPR) assay for one-pot, ultrasensitive, and visual SARS-CoV-2 detection. By targeting SARS-CoV-2's nucleoprotein gene, two CRISPR RNAs without protospacer adjacent motif (PAM) site limitation are introduced to develop the AIOD-CRISPR assay and detect the nucleic acids with a sensitivity of few copies. We validate the assay by using COVID-19 clinical swab samples and obtain consistent results with RT-PCR assay. Furthermore, a low-cost hand warmer (~$0.3) is used as an incubator of the AIOD-CRISPR assay to detect clinical samples within 20 min, enabling an instrument-free, visual SARS-CoV-2 detection at the point of care. Thus, our method has the significant potential to provide a rapid, sensitive, one-pot point-of-care assay for SARS-CoV-2.

/pdf/ultrasensitive-and-visual-detection-of-sars-cov-2-using-all-40peni3fhp.pdf

Ultrasensitive and visual detection of SARS-CoV-2 using all-in-one dual CRISPR-Cas12a assay.

Microorganism remediation strategies towards heavy metals.

Bisphenol A (BPA) is an important monomer in the manufacture of polycarbonate plastics, food cans, and other daily used chemicals. Daily and worldwide usage of BPA and BPA-contained products led to its ubiquitous distribution in water, sediment/soil, and atmosphere. Moreover, BPA has been identified as an environmental endocrine disruptor for its estrogenic and genotoxic activity. Thus, BPA contamination in the environment is an increasingly worldwide concern, and methods to efficiently remove BPA from the environment are urgently recommended. Although many factors affect the fate of BPA in the environment, BPA degradation is mainly depended on the metabolism of bacteria. Many BPA-degrading bacteria have been identified from water, sediment/soil, and wastewater treatment plants. Metabolic pathways of BPA degradation in specific bacterial strains were proposed, based on the metabolic intermediates detected during the degradation process. In this review, the BPA-degrading bacteria were summarized, and the (proposed) BPA degradation pathway mediated by bacteria were referred.

http://ir.yic.ac.cn/bitstream/133337/6978/2/Bacteria-mediated%20bisphenol%20A%20degradation.pdf

Bacteria-mediated bisphenol A degradation.

A recent outbreak of novel coronavirus (SARS-CoV-2), the causative agent of COVID-19, has spread rapidly all over the world. Human immunodeficiency virus (HIV) is another deadly virus and causes acquired immunodeficiency syndrome (AIDS). Rapid and early detection of these viruses will facilitate early intervention and reduce disease transmission risk. Here, we present an All-In-One Dual CRISPR-Cas12a (termed "AIOD-CRISPR") assay method for simple, rapid, ultrasensitive, one-pot, and visual detection of coronavirus SARS-CoV-2 and HIV virus. In our AIOD CRISPR assay, a pair of crRNAs was introduced to initiate dual CRISPR-Cas12a detection and improve detection sensitivity. The AIOD-CRISPR assay system was successfully utilized to detect nucleic acids (DNA and RNA) of SARS-CoV-2 and HIV with a sensitivity of few copies. Also, it was evaluated by detecting HIV-1 RNA extracted from human plasma samples, achieving a comparable sensitivity with real-time RT-PCR method. Thus, our method has a great potential for developing next-generation point-of-care molecular diagnostics.

/pdf/all-in-one-dual-crispr-cas12a-aiod-crispr-assay-a-case-for-36l2bxtuc7.pdf

All-in-One Dual CRISPR-Cas12a (AIOD-CRISPR) Assay: A Case for Rapid, Ultrasensitive and Visual Detection of Novel Coronavirus SARS-CoV-2 and HIV virus

http://ir.yic.ac.cn/bitstream/133337/13808/4/A%20near-infrared%20ratiometric%20fluorescent%20probe%20for%20cysteine%20detection%20over%20glutathione%20indicating%20mitochondrial%20oxidative%20stress%20in%20vivo.pdf

Kun Yin

Papers

Ultrasensitive and visual detection of SARS-CoV-2 using all-in-one dual CRISPR-Cas12a assay.

Microorganism remediation strategies towards heavy metals.

Bacteria-mediated bisphenol A degradation.

All-in-One Dual CRISPR-Cas12a (AIOD-CRISPR) Assay: A Case for Rapid, Ultrasensitive and Visual Detection of Novel Coronavirus SARS-CoV-2 and HIV virus

A near-infrared ratiometric fluorescent probe for cysteine detection over glutathione indicating mitochondrial oxidative stress in vivo