Linear spot Raman detector for the bi-channel immunochromatographic assay to simultaneously detect respiratory viruses

The rapid and accurate measurement of Raman signals on the test line (T-line) of surface-enhanced Raman scattering immunochromatography assay (SERS-ICA) strip is necessary for on-site detection based on SERS. Here, a novel linear spot Raman detector which can directly collect the SERS signals of the whole T-line on the dual-diagnostic SERS-ICA strip is developed for detection of multiple respiratory viruses via two magnetic SERS tags within 26min. The tags modified with two Raman reporter molecules can specifically recognize two viruses, thus enabling the simultaneous detection of both viruses on one T-line. Measured by the linear Raman detector, the limits of detection of the proposed dual-diagnostic SERS-ICA strip is as low as 870 and 263 copies/mL for severe acute respiratory syndrome coronavirus 2 and H1N1, respectively. The dual-diagnostic strip combined with the novel Raman detector herein are of great importance in the differential diagnosis of respiratory pathogens and show potential in the rapid and accurate diagnosis and control of emerging acute respiratory diseases.

CFD Simulations of Ventilation and Interunit Dispersion in Dormitory Complex: A Case Study of Epidemic Outbreak in Shanghai.

Since the beginning of March 2022, a new round of COVID-19 outbreaks in Shanghai has led to a sharp increase in the number of infected people. It is important to identify possible pollutant transmission routes and predict potential infection risks for infectious diseases. Therefore, this study investigated the cross-diffusion of pollutants caused by natural ventilation, including external windows and indoor ventilation windows, under three wind directions in a densely populated building environment with the CFD method. In this study, CFD building models were developed based on an actual dormitory complex and surrounding buildings under realistic wind conditions to reproduce the airflow fields and transmission paths of pollutants. This paper adopted the Wells-Riley model to assess the risk of cross-infection. The biggest risk of infection was when a source room was located on the windward side, and the risk of infection in other rooms on the same side as the source room was large in the windward direction. When pollutants were released from room 8, north wind resulted in the highest concentration of pollutants in room 28, reaching 37.8%. This paper summarizes the transmission risks related to the indoor and outdoor environments of compact buildings.

Simultaneously ultrasensitive and quantitative detection of influenza A virus, SARS-CoV-2, and respiratory syncytial virus via multichannel magnetic SERS-based lateral flow immunoassay.

Respiratory viruses usually induced similar clinical symptoms at early infection. Herein, we presented a multichannel surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-based LFA) using high-performance magnetic SERS tags for the simultaneous ultrasensitive detection of respiratory viruses, namely influenza A virus (H1N1), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and respiratory syncytial virus (RSV) in biological samples. As-prepared magnetic SERS tags can directly enrich and capture target viruses without pretreatment of samples, avoiding the interference of impurities in the samples as well as improving the sensitivity. With the capture-detection method, the detection limits of the proposed assay reached 85 copies mL-1, 8 pg mL-1, and 8 pg mL-1 for H1N1, SARS-CoV-2 and RSV, respectively. Moreover, the detection properties of the proposed method for target viruses in throat swab samples were verified, suggesting its remarkable potential for the early and rapid differential diagnosis of respiratory viruses.

Identification of source location in a single-sided building with natural ventilation: Case of interunit pollutant dispersion

A sudden outbreak of COVID-19 occurred in December 2019 and its rapid spread over the last two years caused a global pandemic. A special airborne transmission via aerosols called interunit dispersion is risky in a high-density urban environment, which needs more attention. In order to identify the source location of pollutants or viruses under the interunit transmission condition with natural ventilation, this study adopted the inverse Computational Fluid Dynamics (CFD) simulation with the adjoint probability method. The detailed process of the inverse modeling was presented. Also, the possible interunit transmission routes of the pollutants or viruses were analyzed. A three-story building model with single-sided openings was built. Six different combinations of fixed sensor locations were tested, and it was determined that setting sensors in the four corner regions of the building was the optimist strategy. A total of 25 cases with five different wind directions (0°, 45°, 90°, 135°, and 180°) were tested to verify the accuracy of the source location with inverse modeling. The results showed that 67%–78% of the rooms in the building can be identified with a limited number of pollutant sensors and all rooms can be identified with one additional sensor in the downstream room of the building under different wind direction. This research revealed that the inverse modeling method could be used to identify the pollutant source in the coupled indoor and outdoor environment. Further, this work can provide guidance for the pollutant monitor positions in the applications.

Correlation of Seizure Increase and COVID-19 Outbreak in Adult Patients with Epilepsy: Findings and Suggestions from a Nationwide Multi-centre Survey in China.

OBJECTIVES: To investigate the impact of the COVID-19 outbreak on the behaviours, mental health and seizure control of adult patients with epilepsy (PWE) and to identify the correlation of seizure increase and the COVID-19 outbreak to guide the medical care of individuals with epilepsy during a public health crisis. METHODS: This study was conducted at 28 centres from February 2020 to April 2020. Participants filled out a 62-item online survey including sociodemographic, COVID-19-related, epilepsy-related and psychological variables and were divided into two groups based on whether their seizure frequency increased during the COVID-19 pandemic. Chi-square tests and t-tests were used to test differences in significant characteristics. Multiple logistic regression analyses were used to identify risk factors for seizure worsening. RESULTS: A total of 1,237 adult PWE were enrolled for analysis. Of this sample, 31 (8.33%) patients experienced an increase in seizures during the pandemic. Multivariate logistic regression suggested that feeling nervous about the pandemic (P < 0.05), poor quality of life (P = 0.001), drug reduction/withdrawal (P = 0.032), moderate anxiety during the COVID-19 outbreak (P = 0.046) and non-seizure free before the COVID-19 outbreak (P < 0.05) were independently related to seizure increase during the pandemic. CONCLUSIONS: During the COVID-19 pandemic, PWE with poor quality of life and mental status, as well as AED reduction/withdrawal, were more likely to experience seizure increase. This observation highlights the importance of early identification of the population at high risk of seizure worsening and implementation of preventive strategies during the pandemic.