T2Candida Assay in the Diagnosis of Intraabdominal Candidiasis: A Prospective Multicenter Study

The T2Candida magnetic resonance assay is a direct-from-blood pathogen detection assay that delivers a result within 3–5 h, targeting the most clinically relevant Candida species. Between February 2019 and March 2021, the study included consecutive patients aged >18 years admitted to an intensive care unit or surgical high-dependency unit due to gastrointestinal surgery or necrotizing pancreatitis and from whom diagnostic blood cultures were obtained. Blood samples were tested in parallel with T2Candida and 1,3-β-D-glucan. Of 134 evaluable patients, 13 (10%) were classified as having proven intraabdominal candidiasis (IAC) according to the EORTC/MSG criteria. Two of the thirteen patients (15%) had concurrent candidemia. The sensitivity, specificity, positive predictive value, and negative predictive value, respectively, were 46%, 97%, 61%, and 94% for T2Candida and 85%, 83%, 36%, and 98% for 1,3-β-D-glucan. All positive T2Candida results were consistent with the culture results at the species level, except for one case of dual infection. The performance of T2Candida was comparable with that of 1,3-β-D-glucan for candidemic IAC but had a lower sensitivity for non-candidemic IAC (36% vs. 82%). In conclusion, T2Candida may be a valuable complement to 1,3-β-D-glucan in the clinical management of high-risk surgical patients because of its rapid results and ease of use.

Citrus Stubborn Disease: Current Insights on an Enigmatic Problem Prevailing in Citrus Orchards

Citrus stubborn was initially observed in California in 1915 and was later proven as a graft-transmissible disease in 1942. In the field, diseased citrus trees have compressed and stunted appearances, and yield poor-quality fruits with little market value. The disease is caused by Spiroplasma citri, a phloem-restricted pathogenic mollicute, which belongs to the Spiroplasmataceae family (Mollicutes). S. citri has the largest genome of any Mollicutes investigated, with a genome size of roughly 1780 Kbp. It is a helical, motile mollicute that lacks a cell wall and peptidoglycan. Several quick and sensitive molecular-based and immuno-enzymatic pathogen detection technologies are available. Infected weeds are the primary source of transmission to citrus, with only a minor percentage of transmission from infected citrus to citrus. Several phloem-feeding leafhopper species (Cicadellidae, Hemiptera) support the natural spread of S. citri in a persistent, propagative manner. S. citri-free buds are used in new orchard plantings and bud certification, and indexing initiatives have been launched. Further, a quarantine system for newly introduced types has been implemented to limit citrus stubborn disease (CSD). The present state of knowledge about CSD around the world is summarized in this overview, where recent advances in S. citri detection, characterization, control and eradication were highlighted to prevent or limit disease spread through the adoption of best practices.

Factors influencing environmental sampling recovery of healthcare pathogens from non-porous surfaces with cellulose sponges

Results from sampling healthcare surfaces for pathogens are difficult to interpret without understanding the factors that influence pathogen detection. We investigated the recovery of four healthcare-associated pathogens from three common surface materials, and how a body fluid simulant (artificial test soil, ATS), deposition method, and contamination levels influence the percent of organisms recovered (%R). Known quantities of carbapenemase-producing KPC+ Klebsiella pneumoniae (KPC), Acinetobacter baumannii, vancomycin-resistant Enterococcus faecalis, and Clostridioides difficile spores (CD) were suspended in Butterfield’s buffer or ATS, deposited on 323cm2 steel, plastic, and laminate surfaces, allowed to dry 1h, then sampled with a cellulose sponge wipe. Bacteria were eluted, cultured, CFU counted and %R determined relative to the inoculum. The %R varied by organism, from <1% (KPC) to almost 60% (CD) and was more dependent upon the organism’s characteristics and presence of ATS than on surface type. KPC persistence as determined by culture also declined by >1 log10 within the 60 min drying time. For all organisms, the %R was significantly greater if suspended in ATS than if suspended in Butterfield’s buffer (p<0.05), and for most organisms the %R was not significantly different when sampled from any of the three surfaces. Organisms deposited in multiple droplets were recovered at equal or higher %R than if spread evenly on the surface. This work assists in interpreting data collected while investigating a healthcare infection outbreak or while conducting infection intervention studies.

A Recombinase Polymerase Amplification-Coupled Cas12a Mutant-Based Module for Efficient Detection of Streptomycin-Resistant Mutations in Mycobacterium tuberculosis

Drug-resistant tuberculosis (TB) is a serious public health problem and threat to global TB prevention and control. Streptomycin (STR) is the earliest and classical anti-TB drug, and it is the earliest drug that generated resistance to anti-TB treatment, which limits its use in treating TB and impedes TB control efforts. The rapid, economical, and highly sensitive detection of STR-resistant TB may help reduce disease transmission and morbimortality. CRISPR/CRISPR-associated protein (Cas) is a new-generation pathogen detection method that can detect single-nucleotide polymorphisms with high sensitivity and good specificity. In this study, a Cas12a RR detection system that can recognize more non-traditional protospacer-adjacent motif-targeting sequences was developed based on Cas12a combined with recombinase polymerase amplification technology. This system detects 0.1% of the target substance, and the entire detection process can be completed within 60 min. Its sensitivity and specificity for detecting clinical STR-resistant Mycobacterium tuberculosis were both 100%. Overall, the Cas12 RR detection system provides a novel alternative for the rapid, simple, sensitive, and specific detection of STR-resistant TB, which may contribute to the prompt treatment and prevention of disease transmission in STR-resistant TB.

Hardware-Efficient Stochastic Binary CNN Architectures for Near-Sensor Computing

With recent advances in the field of artificial intelligence (AI) such as binarized neural networks (BNNs), a wide variety of vision applications with energy-optimized implementations have become possible at the edge. Such networks have the first layer implemented with high precision, which poses a challenge in deploying a uniform hardware mapping for the network implementation. Stochastic computing can allow conversion of such high-precision computations to a sequence of binarized operations while maintaining equivalent accuracy. In this work, we propose a fully binarized hardware-friendly computation engine based on stochastic computing as a proof of concept for vision applications involving multi-channel inputs. Stochastic sampling is performed by sampling from a non-uniform (normal) distribution based on analog hardware sources. We first validate the benefits of the proposed pipeline on the CIFAR-10 dataset. To further demonstrate its application for real-world scenarios, we present a case-study of microscopy image diagnostics for pathogen detection. We then evaluate benefits of implementing such a pipeline using OxRAM-based circuits for stochastic sampling as well as in-memory computing-based binarized multiplication. The proposed implementation is about 1,000 times more energy efficient compared to conventional floating-precision-based digital implementations, with memory savings of a factor of 45.

Clinical Characteristics of Pediatric Respiratory Tract Infection and Respiratory Pathogen Isolation During the Coronavirus Disease 2019 Pandemic

Objective: We sought to compare the clinical characteristics of pediatric respiratory tract infection and respiratory pathogen isolations during the coronavirus disease (COVID-19) pandemic to those of cases in 2018 and 2019.Methods: Our study included all children from 28 days to 15 years old with respiratory tract infections who were admitted to the Department of Respiration, in the Children's Hospital of Soochow University, between January 2018 and December 2020. Human rhinovirus (HRV) and human metapneumovirus (hMPV) were detected by reverse transcription polymerase chain reaction (RT-PCR). Mycoplasma pneumoniae (MP) and human bocavirus (HBoV) were detected by real-time fluorescence quantitative polymerase chain reaction (qPCR); In parallel, Mycoplasma pneumoniae was detected by enzyme-linked immunosorbent assays, and bacteria were detected by culture in blood, bronchoalveolar lavage specimen, and pleural fluid.Results: Compared to 2018 and 2019, the pathogen detection rate was significantly lower in 2020. With regard to infections caused by single pathogens, in 2020, the detection rates of MP were the lowest and those of HRV were the highest when compared to those in 2018 and 2019. Meanwhile, the positive rates of respiratory syncytial virus (RSV) and hMPV reported in 2020 were less than those recorded in 2018 but similar to those recorded in 2019. Also, the 2020 rate of adenovirus (ADV) was lower than that recorded in 2019, but similar to that recorded in 2018. There were no statistical differences in the positive rates of HBoV and PIV III over the 3 years surveyed. Infections in infants were significantly less common in 2020, but no significant difference was found among children aged 1 to 3 years. The detection rate of pathogens in children old than 5 years in 2020 was significantly lower than those recorded in the previous 2 years. Notably, the pathogen detection rates in the first and second quarters of 2020 were similar to those recorded in the previous 2 years; however, the rates were reduced in the third and fourth quarters of 2020. As for co-infections, the positive rate was at its lowest in 2020. In the previous 2 years, viral–MP was the most common type of mixed infection. By contrast, in 2020, viral–viral infections were the most common combination.Conclusion: The pathogen detection rate was significantly reduced in Suzhou City during the COVID-19 pandemic. Public interventions may help to prevent respiratory pathogen infections in children.

Effects of Planted Pollinator Habitat On Bee Health And Interspecific Pathogen Detection

Shared resources can instigate pathogen spread due to large congregations of individuals in both natural and human modified resources. Of concern is the addition of pollinator habitat in conservation efforts as it attracts bees of various species, potentially instigating interspecific sharing of pathogens. Common pathogens have been documented across a wide variety of pollinators with shared floral resources instigating their spread in some, but not all, cases. To evaluate the impact of augmented pollinator habitat on bee health, we screened samples from eight bee species across three families against a panel of 9 pathogens using RT-qPCR. While we found that some habitat characteristics influenced pathogen detection, we found no evidence that pathogen detection in one bee species was correlated with pathogen detection in another. These findings suggest factors other than the habitat itself may be more critical in the dissemination of diseases among bee species. However, we found high levels of gut parasites in some bee species which may be of concern, such as Bombus pensylvanicus. Future monitoring of bee health at augmented pollinator habitat is needed to ensure pathogens do not build up over time to then spread within their communities.

A Low-Cost, 3D-Printed Biosensor for Rapid Detection of Escherichia coli

Detection of bacterial pathogens is significant in the fields of food safety, medicine, public health, etc. If bacterial pathogens are not treated promptly, antimicrobial resistance is possible and can lead to morbidity and mortality. Current bacterial detection methodologies rely on laboratory-based techniques that pose limitations such as long turnaround detection times, expensive costs, in-adequate accuracy, and required trained specialists. Here, we describe a cost-effective and port-able 3D-printed electrochemical biosensor that facilitates rapid detection of certain Escherichia coli (E. coli) strains (DH5α, BL21, TOP10, and JM109) within 15 minutes using 500 μL of sample and costs $2.50 per test. The sensor displayed an excellent limit of detection (LOD) of 53 CFU, limit of quantification (LOQ) of 270 CFU, and showed cross-reactivity with strains BL21 and JM109 due to shared epitopes. This advantageous diagnostic device is a potential candidate for high-frequency testing at the point of care as well as applicable to various fields where pathogen detection is of interest.

Recent Developments towards Portable Point-of-Care Diagnostic Devices for Pathogen Detection

The rapid development of accurate and quick diagnostic tools for infectious diseases has made a massive impact in global health. POC devices for pathogen detection have primarily contributed to clinical...