FEN1-aided recombinase polymerase amplification (FARPA) for one-pot and multiplex detection of nucleic acids with an ultra-high specificity and sensitivity.

Recombinase polymerase amplification (RPA) running at 37-42 °C is fast, efficient and less-implemented; however, the existing technologies of nucleic acid testing based on RPA have some limitations in specificity of single-base recognition and multiplexing capability. Herein, we report a highly specific and multiplex RPA-based nucleic acid detection platform by combining flap endonuclease 1 (FEN1)-catalysed invasive reactions with RPA, termed as FEN1-aided RPA (FARPA). The optimal conditions enable RPA and FEN1-based fluorescence detection to occur automatically and sequentially within a 25-min turnaround time and FARPA exhibits sensitivity to 5 target molecules. Due to the ability of invasive reactions in discriminating single-base variation, this one-pot FARPA is much more specific than the Exo probe-based or CRISPR-based RPA methods. Using a universal primer pair derived from tags in reverse transcription primers, multiplex FARPA was successfully demonstrated by the 3-plex assay for the detection of SARS-CoV-2 pathogen (the ORF1ab, the N gene, and the human RNase P gene as the internal control), the 2-plex assay for the discrimination of SARS-CoV-2 wild-type from variants (Alpha, Beta, Epsilon, Delta, or Omicrons), and the 4-plex assay for the screening of arboviruses (zika virus, tick-borne encephalitis virus, yellow fever virus, and chikungunya virus). We have validated multiplex FARPA with 103 nasopharyngeal swabs for SARS-CoV-2 detection. The results showed a 100% agreement with RT-qPCR assays. Moreover, a hand-held FARPA analyser was constructed for the visualized FARPA due to the switch-like endpoint read-out. This FARPA is very suitable for pathogen screening and discrimination of viral variants, greatly facilitating point-of-care diagnostics.

Convolutional neural network optimized by differential evolution for electrocardiogram classification

The Coronavirus disease 2019, or COVID-19, has shifted the medical paradigm from face-to-face to telehealth. Telehealth has become a vital resource to contain the virus spread and ensure the continued care of patients. In terms of preventing cardiovascular diseases, automating electrocardiogram (ECG) classification is a promising telehealth intervention. The healthcare service ensures that patient care is appropriate, comfortable, and accessible. Convolutional neural networks (CNNs) have demonstrated promising results in ECG categorization, which require high accuracy and short training time to ensure healthcare quality. This study proposes a one-dimensional-CNN (1D-CNN) arrhythmia classification based on the differential evolution (DE) algorithm to optimize the accuracy of ECG classification and training time. The performance of 1D-CNNs of different activation functions are optimized based on the standard DE algorithm. Finally, based on MIT-BIH and SCDH arrhythmia databases, the performances of optimized and unoptimized 1D-CNN are compared and analysed. Results show that the 1D-CNN optimized by the DE has higher accuracy in heartbeats classification. The optimized 1D-CNN improves from 97.6% to 99.5% on MIT-BIH and from 80.2% to 88.5% on SCDH. Therefore, the optimized 1D-CNN shows improvements of 1.9% and 8.3% in the two datasets, respectively. In addition, compared with the unoptimized 1D-CNN based on the same parameter settings, the optimized 1D-CNN has less training time. Under the conditions of ReLU function and 10 epochs, the training takes 9.22 s on MIT-BIH and 10.35 s on SCDH, reducing training time by 67.2% and 64.2%, respectively.

Constructing Selenium Nanoparticles with Enhanced Storage Stability and Antioxidant Activities via Conformational Transition of Curdlan.

Selenium nanoparticles (SeNPs) are among the emerging selenium supplements because of their high bioactivity and low toxicity. However, bare SeNPs are prone to activity loss caused by aggregation and sedimentation. This study aims to stabilize SeNPs with curdlan (CUR), a polysaccharide, to maintain or even enhance their biological activity. Herein, the stable SeNPs were constructed via the unique conformational transition of CUR induced by alkali-neutralization (AN) pretreatment. The physicochemical properties and structures of the prepared SeNPs were characterized by dynamic light scattering (DLS), UV-visible spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), transmission electron microscopy (TEM), and free-radical-scavenging activity assays. The results show that most SeNPs are stabilized within the triple helix of CUR that has been pretreated with high-intensity AN treatment. These amorphous, small-sized (average size was 53.6 ± 17.7 nm), and stabilized SeNPs have significantly enhanced free-radical-scavenging ability compared to the control and can be well-stabilized for at least 240 days at 4 °C. This work indicates that CUR, as a food additive, can be used to well-stabilize SeNPs by AN pretreatment and provides a facile method to prepare and enhance the stability and bioactivity of SeNPs via triple-helix conformational transition.

Optimal diagnostic fever thresholds using non-contact infrared thermometers under COVID-19.

Fever screening is an effective method to detect infectors associated with different variants of coronavirus disease 2019 (COVID-19) based on the fact that most infectors with COVID-19 have fever symptoms. Non-contact infrared thermometers (NCITs) are widely used in fever screening. Nevertheless, authoritative data is lacking in defining "fever" at different body surface sites when using NCITs. The purpose of this study was to determine the optimal diagnostic threshold for fever screening using NICTs at different body surface sites, to improve the accuracy of fever screening and provide theoretical reference for healthcare policy. Participants (n = 1860) who were outpatients or emergency patients at Chengdu Women's and Children's Central Hospital were recruited for this prospective investigation from March 1 to June 30, 2021. NCITs and mercury axillary thermometers were used to measure neck, temple, forehead and wrist temperatures of all participants. Receiver operating characteristic curves were used to reflect the accuracy of NCITs. Linear correlation analysis was used to show the effect of age on body temperature. Multilinear regression analysis was used to explore the association between non-febrile participant's covariates and neck temperature. The mean age of participants was 3.45 ± 2.85 years for children and 28.56 ± 7.25 years for adults. In addition 1,304 (70.1%) participants were children (≤12), and 683 (36.7%) were male. The neck temperature exhibited the highest accuracy among the four sites. Further the optimal fever diagnostic thresholds of NCITs at the four body surface measurement sites were neck (36.75 °C, sensitivity: 0.993, specificity: 0.858); temple (36.55 °C, sensitivity: 0.974, specificity: 0.874); forehead (36.45 °C, sensitivity: 0.961, specificity: 0.813); and wrist (36.15 °C, sensitivity: 0.951, specificity: 0.434). Based on the findings of our study, we recommend 36.15, 36.45, 36.55, and 36.75 °C as the diagnostic thresholds of fever at the wrist, forehead, temple and neck, respectively. Among the four surface sites, neck temperature exhibited the highest accuracy.

The Influence of Personality and Demographic Characteristics on Aggressive Driving Behaviors in Eastern Chinese Drivers.

PURPOSE: Road safety research is important due to the large number of road traffic fatalities globally. This study investigated the influences of age, driving experience and other covariates on aggressive driving behavior. METHODS: A cross-sectional survey was conducted in Yixing City, Wuxi City, Jiangsu Province, China. Regression analysis was applied to explore the influences of age and driving experience and their interactions with other covariates on aggressive driving behavior. Two analyses methodologies were used to assess the simple effect of the interactions. Firstly, the Jamovi automatic analysis classification program was used to calculate the simple slope test. Second, the SPSS macro program was also used to calculate the simple slope test also. RESULTS: A total of 570 drivers (247 males, 282 females) participated in the survey. A negative correlation was found between age and aggressive driving behaviors, and a positive correlation was found between neuroticism and aggressive driving behaviors in the multiple regression analysis. Significant associations were also found between age, driving experience, and depression, as well as age, driving experience, and neuroticism. Simple slope tests showed that depressive symptoms could increase aggressive behaviors in the elderly and experienced drivers. When experiencing neuroticism, individuals with higher driving experience were more aggressive in driving than shorter experienced drivers. CONCLUSION: Age and neuroticism influenced aggressive driving behaviors. Veteran drivers could be aggressive drivers when experiencing depressive symptoms or neuroticism. Mobile intervention could be sent to the potentially risky drivers, which would be safe and broadly feasible to prevent aggressive driving behavior in the background of COVID-19.

Health QR Code Application in the Novel Containment Strategy and Healthcare Plan for Pregnant Women and Children Under Quarantine During the Summer Outbreak of SARS-CoV-2 Delta Variant in Chengdu, China: An Observational Study.

PURPOSE: To report the experience of health QR code application in Chengdu's anti-epidemic measures including circle-layer management, hospital triage system and healthcare plan for quarantined pregnant women and children during the summer outbreak of SARS-CoV-2 Delta strain in 2021 and to evaluate these measures. METHODS: We comprehensively summarized Chengdu's health code application in the circle-layer management (a set of stringent confinement measures of places confirmed cases and close contacts have recently been to and less strict quarantine measures of surrounding areas), hospital triage system, and healthcare plan for quarantined pregnant women and children. We also assessed the effectiveness or efficiency of these measures by analyzing the number of different cases with confirmed COVID-19 infections or epidemiological history, the attitude of quarantined pregnant women toward the summer outbreak and healthcare services, as well as the time needed for obtaining epidemiological history and accuracy of health-code-based hospital triage system. RESULTS: The circle-layer management lasted 15 days and ended with no community or nosocomial transmission happened. Approximately 70 pregnant women and 600 children below 6-year-old were quarantined. Four home visits and two patient transfers were performed. Online survey indicated that about 80% of quarantined women felt satisfactory about the healthcare service. The novel triage system identified 137/221 (61.99%) patients with epidemiological history from patients with yellow health code, and 71/4504 (1.57%) patients from patients with green health code in our hospital (p < 0.001). The health QR code markedly outperformed the traditional methods in the efficiency experiment of obtaining epidemiological history (3.52 ± 0.98 vs 78.91 ± 23.18 seconds, P < 0.001). CONCLUSION: The circle-layer management has successfully and precisely prevented the spread of the summer outbreak of COVID-19 in Chengdu. The health-code-based triage system showed great effectiveness and efficiency in triaging patients with epidemiological history. The healthcare services for quarantined pregnant women has basically met their needs.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.