Metamaterial enhanced novel plasmonic biosensor for specific detection of SARS-CoV-2 spike protein

In this study, we theoretically propose a surface plasmon resonance (SPR) biosensor composed of a plasmonic gold film, double negative (DNG) metamaterial, graphene-MoS2-COOH Van der Waals heterostructures and gold nanoparticles (Au NPs). We use a novel scheme of Goos-Hanchen (GH) shift to study the biosensing performances of our proposed plasmonic biosensor. The calculation results show that, both an extreme low reflectivity of 8.52x10(-10) and significantly enhanced GH sensitivity of 2.1530x10(7) mu m/RIU can be obtained, corresponding to the optimal configuration: 32 nm Au film/120 nm metamaterial/4-layer graphene/4-layer MoS2-COOH. In addition, there is a theoretically excellent linear response between the concentration of target analytes (SARS-CoV-2 and S protein) and the change in differential GH shift. Our proposed biosensor promises to be a useful tool for performing the novel coronavirus detection.

Dr.'s Eye: The Design and Evaluation of a Video Conferencing System to Support Doctor Appointments in Home Settings

The spread of COVID-19 has encouraged the practice of using video conferencing for family doctor appointments. Existing applications and off-the-shelf devices face challenges in dealing with capturing the correct view of patients' bodies and supporting ease of use. We created Dr.'s Eye, a video conferencing prototype to support varying types of body exams in home settings. With our prototype, we conducted a study with participants using mock appointments to understand the simultaneous use of the camera and display and to get insights into the issues that might arise in real doctor appointments. Results show the benefits of providing more flexibility with a decoupled camera and display, and privacy protection by limiting the camera view. Yet, challenges remain in maneuvering two devices, presenting feedback for the camera view, coordinating camera work between the participant and the examiner, and reluctance towards showing private body regions. This inspires future research on how to design a video system for doctor appointments. © 2023 ACM.

Computer-Aided System for COVID-19 Using Semi-supervised-based Ensemble Learning and Reinforcement Learning

Coronavirus Disease 2019(COVID-19) has shocked the world with its rapid spread and enormous threat to life and has continued up to the present. In this paper, a computer-aided system is proposed to detect infections and predict the disease progression of COVID-19. A high-quality CT scan database labeled with time-stamps and clinicopathologic variables is constructed to provide data support. To our knowledge, it is the only database with time relevance in the community. An object detection model is then trained to annotate infected regions. Using those regions, we detect the infections using a model with semi-supervised-based ensemble learning and predict the disease progression depending on reinforcement learning. We achieve an mAP of 0.92 for object detection. The accuracy for detecting infections is 98.46%, with a sensitivity of 97.68%, a specificity of 99.24%, and an AUC of 0.987. Significantly, the accuracy of predicting disease progression is 90.32% according to the timeline. It is a state-of-the-art result and can be used for clinical usage. © 2022 IEEE.

Resilience Improvement and Risk Management of Multimodal Transport Logistics in the Post–COVID-19 Era: The Case of TIR-Based Sea–Road Multimodal Transport Logistics

The COVID-19 pandemic has severely impacted international economics and trade, including cargo transportation. As a result, enhancing the resilience of transport and logistics in the post–COVID-19 era has become a general trend. Multimodal transport, with its advantages of speed, large volume and multiple modes, has increasingly gained attention from countries worldwide. However, multimodal transport logistics is a complex and systematic process. Its smooth flow depends not only on the transport itself, but also on the efficient supervision of customs and other government departments at ports. This study employs the theory and method of a super-network to establish a model of multimodal transport logistics, which includes TIR-based sea–road multimodal transport and customs supervision relationships. Structural and resilience-related characteristics of the super-network are analyzed, and performance parameters of the super-network are proposed. A simulation analysis is conducted, and based on the results, countermeasures to improve the resilience and promote risk management of multimodal transport logistics in the post–COVID-19 era are suggested. The findings of this study provide an exploration of more effective ways to ensure the smoothness of multimodal transport logistics and improve system resilience. The study concludes with theoretical and managerial implications. © 2023 by the authors.

Review of Transfer Learning Applied to Diagnosis of COVID-19

Since the outbreak of the coronavirus disease 2019 (COVID-19) epidemic, the number of infections and deaths caused by the epidemic has continued to increase due to its highly contagious nature. The best way to prevent outbreaks of COVID-19 in society is to detect it early in infection through methods such as reverse transcriptionpolymerase chain reaction (RT-PCR) test and manual examination. However, such laboratory procedures are inefficient, and radiologists'diagnosis of X-ray and CT images is time-consuming and prone to diagnostic errors. Researchers have proposed computer-aided diagnostic algorithms based on transfer learning, which can minimize the problems arising from traditional diagnostic methods. But there are few reviews on the application of transfer learning in the imaging of COVID-19. Therefore, this paper summarizes and analyzes the current research results on the diagnosis of COVID-19 based on transfer learning techniques at home and abroad. The model types are categorized and discussed, and six perspectives of dataset sources, data preprocessing methods, transfer learning based diagnostic models, model visualization, evaluation metrics, and model performance are analyzed and compared, respectively. The current challenges and future development directions are also pointed out, laying foundation for further research in the future. © 2023, Journal of Computer Engineering and Applications Beijing Co., Ltd.;Science Press. All rights reserved.

Sensitivity enhanced tunable plasmonic biosensor using two-dimensional twisted bilayer graphene superlattice

This study theoretically demonstrated an insight for designing a novel tunable plasmonic biosensor, which was created by simply stacking a twisted bilayer graphene (TBG) superlattice onto a plasmonic gold thin film. To achieve ultrasensitive biosensing, the plasmonic biosensor was modulated by Goos-Hänchen (GH) shift. Interestingly, our proposed biosensor exhibited tunable biosensing ability, largely depending on the twisted angle. When the relative twisted angle was optimized to be 55.3°, such a configuration: 44 nm Au film/1-TBG superlattice could produce an ultralow reflectivity of 2.2038 × 10-9and ultra-large GH shift of 4.4785 × 104μm. For a small refractive index (RI) increment of 0.0012 RIU (refractive index unit) in sensing interface, the optimal configuration could offer an ultra-high GH shift detection sensitivity of 3.9570 × 107μm/RIU. More importantly, the optimal plasmonic configuration demonstrated a theoretical possibility of quantitatively monitoring severe acute respiratory syndrome coronavirus (SARS-CoV-2) and human hemoglobin. Considering an extremely small RI change as little as 3 × 10-7RIU, a good linear response between detection concentration of SARS-CoV-2 and changes in differential GH shift was studied. For SARS-CoV-2, a linear detection interval was obtained from 0 to 2 nM. For human hemoglobin, a linear detection range was achieved from 0 to 0.002 g/L. Our work will be important to develop novel TBG-enhanced biosensors for quantitatively detecting microorganisms and biomolecules in biomedical application. © 2023 the author(s), published by De Gruyter, Berlin/Boston 2023.

Metamaterial enhanced novel plasmonic biosensor for specific detection of SARS-CoV-2 spike protein

In this study, we theoretically propose a surface plasmon resonance (SPR) biosensor composed of a plasmonic gold film, double negative (DNG) metamaterial, graphene-MoS2-COOH Van der Waals heterostructures and gold nanoparticles (Au NPs). We use a novel scheme of Goos-Hanchen (GH) shift to study the biosensing performances of our proposed plasmonic biosensor. The calculation results show that, both an extreme low reflectivity of 8.52×10-10 and significantly enhanced GH sensitivity of 2.1530×107 μm/RIU can be obtained, corresponding to the optimal configuration: 32 nm Au film/120 nm metamaterial/4-layer graphene/4-layer MoS2-COOH. In addition, there is a theoretically excellent linear response between the concentration of target analytes (SARS-CoV-2 and S protein) and the change in differential GH shift. Our proposed biosensor promises to be a useful tool for performing the novel coronavirus detection. © 2023 SPIE.

Short-Term Mindfulness Intervention on Adolescents' Negative Emotion under Global Pandemic

Objective: In this research, we tried to explore how short-term mindfulness (STM) intervention affects adoles-cents' anxiety, depression, and negative and positive emotion during the COVID-19 pandemic. Design: 10 classes were divided into experiment groups (5 classes;n = 238) and control (5 classes;n = 244) randomly. Hospital Anxiety and Depression Scale (HADS) and Positive and Negative Affect Schedule (PANAS) were used to measure par-ticipants' dependent variables. In the experiment group, we conducted STM practice interventions every morning in their first class from March to November 2020. No interventions were conducted in the control group. Methods: Paired-sample t-tests were used to identify if a significant difference exists between every time point of the experimental and control groups. Repeated ANOVA and Growth Mixture Model (GMM) were used to analyze the tendency of positive and negative emotions, anxiety, and depression in the experimental group. Results and Conclusions: (1) With the intervention of STM, there was a significant decrease in negative emotions and an increase in positive emotions in the experimental group, whereas there were non-significant differences in the control group. (2) To explore the heterogeneity trajectories of dependent variables, we built a GMM and found there were two latent growth classes in the trajectories. (3) The results of the models showed their trajectories were downward, which meant that the levels of anxiety, depression, and negative emotions of participants decreased during the STM training period. Nonetheless, the score of positive affect showed upward in three loops of intervention, which indicated that the level of the participants' positive affect increased through the STM inter-vention. (4) This research indicated that STM should be given increasing consideration to enhance mental health during the worldwide outbreak of COVID-19. © 2023, Tech Science Press. All rights reserved.

Airborne infection risk in classrooms based on environment and occupant behavior measurement under COVID-19 epidemic

The changes of indoor environment and occupant behavior (OB) are two main causes for the gap between predicted and actual airborne infection risk. To improve the accuracy of COVID-19 airborne infection risk assessment, the environment (CO2 concentration) and OBs (occupant area per person (OA) and activity level (AL)) in three typical classrooms of a primary school in Tianjin, China was selected to conduct the on-site measurement. Based on the measured data, a modified Wells-Riley model was proposed to predict the infection risk, and a risk-controlled ventilation strategy was developed to calculate the ventilation demand. Results indicated that classrooms in the breaking time (B-T) showed a lower indoor CO2 concentration (C in), larger OA, and higher AL than in the teaching time (T-T). The variation tendency of the calculated infection risk increment in T-T was consistent with C in while in B-T was significantly affected by OA and AL, and the maximum fluctuation extent in B-T was two times of that in T-T. Moreover, to avoid the risk spreading in classrooms, a feasible solution of dynamic ventilation control based on the real-time infection risk was proposed, thus facilitating to provide a healthy and sustainable environment for students in classrooms. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

[Efficacy and safety of inactivated novel coronavirus vaccine inoculation in patients with chronic hepatitis B].

Objective: To explore the safety of inactivated novel coronavirus vaccine inoculation and the fluctuating neutralizing antibody in patients with chronic hepatitis B (CHB). Methods: Retrospective and prospective epidemiological research methods were employed. 153 CHB patients who visited the Department of Infectious Diseases at the First Hospital of Shanxi Medical University from September 2021 to February 2022 were selected as the research subjects. Information on vaccination-related adverse reactions was collected. Colloidal gold immunochromatography was used to identify neutralizing antibodies in the body after 3-6 months of vaccination. Statistical analysis was performed using the χ2-test or Fisher's exact test. Results: The positive rates of neutralizing antibodies after inactivated novel coronavirus vaccine inoculation in 153 patients with CHB were 45.50%, 44.70%, 40.00% and 16.20%, respectively, at 3, 4, 5, and 6 months. The neutralizing antibody concentrations were 10.00 (2.95, 30.01) U/ml, 6.08 (3.41, 24.50) U/ml, 5.90 (3.93, 14.68) U/ml, and 1.25 (0.92, 3.75) U/ml, respectively. The difference was not statistically significant (P>0.05) when the neutralizing antibody positivity rates in hepatitis B virus (HBV) DNA-negative and positive patients and HBeAg-negative and positive patients at different time points were compared. The overall incidence of adverse reactions following vaccination was 18.30%. Pain at the site of inoculation and fatigue were the main presentations, and no serious adverse reactions occurred. Conclusion: CHB patients, when inoculated with an inactivated novel coronavirus vaccine, can produce neutralizing antibodies, which can stay at certain levels for 3, 4, and 5 months. However, the neutralizing antibody level gradually decreases over time, and the decrease is remarkable at 6 months. So, it is recommended to boost vaccinations at an appropriate time. Additionally, the results of the study suggest that HBV replication status has little effect on the production of neutralizing antibodies in CHB patients with relatively stable liver function, which means the inactivated novel coronavirus vaccine has a good safety profile.

SARS-CoV-2: Next Generation Sequencing and Analysis

Sars-cov-2 is the causative agent responsible for the global pandemic of COVID-19. Bioinformatics tools are used to sequence the viral genome, identify SARS-CoV-2 from all host genomes, and detect its variants. There is no all-in-one tool that can automatically analyse complete sequences, so different bioinformatics resources are needed to work together for detection and characterisation. This paper discusses the use of next-generation sequencing for virus definition and characterization. © 2022 SPIE. All rights reserved.

Identification of a red cell hemostatic mechanism causing COVID-19 microvascular obstruction

Background: Severe COVID-19 infection is associated with a wide spectrum of clinical manifestations, leading to systemic thromboinflammation and multiorgan dysfunction. The primary cause of multiorgan damage is widespread endothelial injury, leading to microangiopathy and organ ischemia. The molecular mechanisms by which ischemic endothelial cells causes microvascular obstruction remains ill defined. Aim(s): Identification of distinct microvascular occlusion mechanisms in COVID-19. Method(s): The microvasculature of multiple organs from patients dying from COVID-19, myocardial infarction or stroke were analyzed by H&E, immunohistochemistry, SEM and CLEM. Animal models of gut ischemia and stroke were also examined. Intravital confocal microscopy examined endothelial injury and microvascular obstruction mechanisms mediated by platelets, red cells and fibrin. Result(s): We demonstrate the existence of a distinct microvascular hemostatic mechanism mediated by hemolyzed red blood cells (RBC), independent of platelets and fibrin. Extensive RBC hemolysis was apparent in the microvasculature of COVID-19 patients and in humans with major organ ischemia, leading to widespread microvascular obstruction. This RBC hemostatic mechanism was triggered by organ ischemia and associated with localized accumulation of hemolyzed RBCs at sites of endothelial necroptosis. RBC hemolysis was impaired in animals lacking the necroptosis mediator, MLKL or the C9 component of complement, indicating the involvement of cell intrinsic and extrinsic membrane lytic processes. Intravital microscopy revealed that the RBC hemostatic mechanism was triggered by the fragmentation of lyzed RBCs and the deposition of RBC membranes on the surface of dying endothelial cells, forming an endovascular sealant that prevents interstitial bleeding. Conclusion(s): Our studies demonstrate the existence of a previously unidentified microvascular hemostatic mechanism mediated by hemolyzed RBCs. Dysregulation of this hemostatic mechanism is linked to microvascular obstruction and bleeding in COVID-19 and ischemic diseases.

Phase Ib study of AVB-S6-500 (axl inhibition) in combination with durvalumab (MEDI4736) in patients with platinum-resistant, recurrent epithelial ovarian cancer (NCT04019288) (320)

Objectives: Immune checkpoint blockade (ICB) has demonstrated efficacy in a small fraction of patients with platinum-resistant ovarian cancer (PROC), some with durable responses. The receptor tyrosine kinase AXL and its sole ligand, GAS6, are possible mediators of T cell exclusion and an attractive target due to the expected synergy between AXL inhibition and immune targeting agents. The recommended phase II dose (RP2D), safety, and efficacy of the combination of AXL inhibition via AVB-S6-500 with durvalumab (MEDI4736) were evaluated in patients with PROC. Methods: In this open-label Phase Ib open-label study, patients with PROC received AVB-S6-500 and durvalumab therapy in escalating dosing regimens guided by a Bayesian optimal interval (BOIN) design: durvalumab (1500 mg Q4W) and AVB-S6-500 (10mg/kg Q2W, 15mg/kg Q2W, 20mg/kg Q2W) with durvalumab infused prior to AVB-S6-500. The response was evaluated using modified RECIST v1.1. Pharmacokinetic/pharmacodynamic (PK/PD) studies were collected, and PD-L1 status and tumor/tumor microenvironment AXL and GAS6 staining pre and on-treatment were assessed. Results: Eleven patients with epithelial ovarian cancer (six clear cells [55%], four high-grade serous [36%], one endometrioid histology [1%]) received treatment per protocol. The median number of prior lines of therapy was 3 (range: 1-5);73% (8/11) of patients had received prior bevacizumab. There were no DLTs noted over the 6-week period and no grade ≥3 adverse events attributed to study drugs. Five patients experienced an immune-related AE, most commonly liver enzyme elevations (36%). Infusion reaction with AVB-S6- 500 was noted in the first two subjects, prompting the institution of a premedication regimen, after which only one of the nine additional patients experienced an infusion reaction. Dose delays greater than one week occurred in six (55%) patients;three patients experienced delays for cancer-related complications (small bowel obstruction, pneumonia, severe fatigue), while three patients experienced delays for non-medical causes (COVID/travel, weather). Patients received therapy for a median of two cycles (range: 1-6), and there were no responses noted across all dosing levels. One patient had stable disease, with a duration of response of three months. Only two patients had strong (2+) AXLstaining on pretreatment biopsy, both with high-grade serous histology. The majority of serum AXL levels were within previously demonstrated ranges (range: 5.6-112ng/mL), though two patients had comparatively high levels (102, 112ng/mL). PK/PD analysis revealed expected AVB-S6-500 levels at initial postdose (C1D1), but low levels at trough (C2D1 predose) when compared to prior AVB-S6-500 data [1]. Conclusions: The combination of AVB-S6-500 and durvalumab was tolerable in this PROC patient population at all dosing levels tested. Exploratory studies to correlate lack of response to AXL-GAS6 pathway alterations, tumor microenvironment, and clinical characteristics, such as prior treatment, dosing delays, burden of disease, and ascites, are ongoing.

Activity Trajectory Generation via Modeling Spatiotemporal Dynamics

Human daily activities, such as working, eating out, and traveling, play an essential role in contact tracing and modeling the diffusion patterns of the COVID-19 pandemic. However, individual-level activity data collected from real scenarios are highly limited due to privacy issues and commercial concerns. In this paper, we present a novel framework based on generative adversarial imitation learning, to generate artificial activity trajectories that retain both the fidelity and utility of the real-world data. To tackle the inherent randomness and sparsity of irregular-sampled activities, we innovatively capture the spatiotemporal dynamics underlying trajectories by leveraging neural differential equations. We incorporate the dynamics of continuous flow between consecutive activities and instantaneous updates at observed activity points in temporal evolution and spatial transformation. Extensive experiments on two real-world datasets show that our proposed framework achieves superior performance over state-of-the-art baselines in terms of improving the data fidelity and data utility in facilitating practical applications. Moreover, we apply the synthetic data to model the COVID-19 spreading, and it achieves better performance by reducing the simulation MAPE over the baseline by more than 50%. The source code is available online: https://github.com/tsinghua-fib-lab/Activity-Trajectory-Generation. © 2022 ACM.

Watts-level ultraviolet-C LED integrated light sources for efficient surface and air sterilization

With the epidemic of the coronavirus disease (COVID-19) infection, AlGaN-based ultraviolet-C light emitting diodes (UVC-LEDs) have attracted widespread attention for their sterilization application. However, the sterilization characters of high power integrated light sources (ILSs) haven't been widely investigated before utilizing in public sanitary security. In this work, by integrating up to 195 UVC-LED chips, high power UVC-LED ILSs with a light output power (LOP) of 1.88 W were demonstrated. The UVC-LED ILSs were verified to have efficient and rapid sterilization capability, which have achieved more than 99.9% inactivation rate of several common pathogenic microorganisms within 1 s. In addition, the corresponding air sterilization module based on them was also demonstrated to kill more than 97% of Staphylococcus albus in the air of 20 m(3) confined room within 30 min. This work demonstrates excellent sterilization ability of UVC-LED ILSs with high LOP, revealing great potential of UVC-LEDs in sterilization applications in the future.

Mindfulness Intervention on Adolescents’ Emotional Intelligence and Psychological Capital during the COVID-19 Pandemic: A Randomized Controlled Trial

Background: Since the outbreak of COVID-19 caused adults suffer from mental disorders, it would be an essential for psychologist to help individuals overcome mental disorders. Objective: This study aim to explore whether the intervention of mindfulness is an efficient method to enhance adolescents’ emotional intelligence (EI) and psychological capital (PC) to provide a theoretical basis and future directions for both targeted crisis intervention and psychological trauma recovery plans. Design: This research was designed as randomized controlled trial and total of 798 students were evaluated statistically. Methods: We used paired-sample t-tests and repeated measures ANOVA to compare every factor defined above by time and group. Then, we used Mplus to build LGCM to examine the trajectory of changes in EI and PC in the experimental group. Results and Conclusions: (1) The EI and PC scores had significantly different time points in the experimental group but not in the control group. (2) EI and PC tended to increase with intervention, and there were significant individual differences in the initial level and development speed. (3) Individuals’ EI could promote the growth of PC. This research indicated that mindfulness should be given increasing consideration to enhance mental health during the worldwide outbreak of COVID-19. © 2022, Tech Science Press. All rights reserved.

Travel pattern variation effects on utility factor after COVID-19: An empirical case

Carbon emission is largely reduced during the COVID-19 due to the lockdown. However, the accurate impact in the personal transport sector after the epidemic is still not clear. To accurately measure the travel pattern variation effects on utility factor of plug-in hybrid electric vehicles (PHEV s) due to COVID-19, travel pattern, charging pattern, and utility factors (UF) are compared in a typical city based on actual travel data before and after the pandemic. The result shows that the number of trips and the daily vehicle kilometers travelled decreased significantly during the pandemic while the average daily travel mileage increased quickly after the pandemic and is only 9% lower than that before the pandemic. Some consumers even travel longer with personal vehicles to avoid possible health risks from public transportation. The electricity utility factor after the pandemic is 0.022 larger compared to that before the pandemic due to the variation of travel patterns, a 60-km-range PHEV has a pre-pandemic standard UF of 0.745 and a post-pandemic standard UF of 0.767. Besides, the actual UF is 15% smaller compared to the standard UF due to the actual charging frequency in reality. © 2021 IEEE.

Soluble Signals to Improve Endothelial Integrity in the Lung

Disorders in pulmonary vascular integrity are a prominent feature in many lung diseases, including acute respiratory distress syndrome (ARDS), capillary leak syndrome, and COVID19. Paracrine signals are enriched in the lung and are critically important in regulating the homeostasis of the functional pulmonary microvasculature. Here, we employed single-cell RNA-sequencing (scRNAseq) to study ligand and receptor interactions in the native human lung microvascular niche, and identified soluble factors that are critical in endothelial integrity. The scRNAseq data reveals a total of 47 cell populations consisting of five vascular endothelial subtypes in human lungs, including general capillary EC, aerocyte capillary EC (EC aCap), arterial EC, pulmonary venous EC, and systemic venous EC. Using EC aCap as a signal receiving core (Receptors) and the putative adjacent cell types (alveolar fibroblast, ATI, ATII, pericyte, plasma cell, etc.) in the EC aCap niche as senders (Ligands), we identified that SLIT2-ROBO4, ANGPT1-TIE1, ADM-RAMP2, VEGFD-KDR, and BMP5-BMPR2 are the top specific and abundant pairs in the niche. Immunostaining and ELISA assays confirmed their spatial information and secretion level. Furthermore, upon treatment with these ligands, real-time resistance recorded using an electric cell-substrate impedance sensing (ECIS) system revealed that VEGFD, ANGPT1 (angiopoietin 1), and ADM (adrenomedullin) could markedly increase the electrical resistance of human lung microvascular, arterial, and venous endothelial cells, suggesting their strong impact on the endothelial barrier function. Deciphering the cell-cell soluble signals that improve endothelial integrity in human lungs lays the foundation for uncovering the pathogenesis of pulmonary vascular disorders and the development of ex vivo functional lung vasculature.

Paradoxes of Disconnected Connection

Normal academic life is a series of gatherings. The COVID-19 outbreak in spring of 2020 disrupted these gatherings and constituted not just a health crisis but also a profound alteration of academic life. Social distancing and quarantine accelerated historic processes of distanciation, as an increasing number of social situations were lifted out of the places in which they would have occurred. Teaching, learning, mentoring, and collaborating continued to “take place” but these newly mediated connections included experiences of disconnection. Auto-ethnography conducted by six academics at various levels during the COVID pandemic explores questions of space, place, pedagogy, and scholarship, comparing and contrasting our varied vantage points on transformations of spatial routines, the learning process, the academic community, and our lives. We show how disconnected connection was experienced differently, by differently-situated social actors, each of whom appropriated certain media according to his or her wants and needs. © Oxford University Press 2021.