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.

Association studies between COVID-19 and SSc-ILD

Severe COVID-19 patients may develop pulmonary fibrosis, similar to SSc-ILD disease, suggesting a potential link between the two diseases. However, there are limited treatment options for SSc-ILD-type diseases. Therefore, investigating pathological markers of the two diseases can provide valuable insights for treating related conditions. RNA sequencing technology offers high throughput and precision. However, the bimodal nature of RNA-Seq data cannot be accurately captured by commonly used algorithms such as DESeq2. To address this issue, the Beta-Poisson model has been developed to identify differentially expressed genes. Unlike the classical DESeq2 algorithm, the Beta-Poisson model introduces a Beta distribution to construct a new hybrid distribution in place of the Gamma distribution of the Gamma-Poisson distribution, effectively characterizing the bimodal features of RNA-Seq data. The transcriptomes of SARS-CoV infection and SSc-ILD disease in the lung epithelial cell dataset were analyzed to identify common differentially expressed genes of SARS-CoV and SSc-ILD disease. Gene function and signaling pathway enrichment analysis and protein-protein interaction (PPI) network were used to identify common pathways and drug targets for SSc-ILD with COVID-19 infection. The results show that there are 50 differentially expressed genes in common between COVID-19 and SSC-ILD. The functions of these genes are mainly enriched in immune system response, interferon signaling pathway and other related signaling pathways, and enriched in biological processes such as cell defense response to virus and interferon regulation. Based on the detection of hub genes based on PPIs network, it is predicted that STAT1, ISG15, IRF7, MX1, EIF2AK2, DDX58, OAS1, OAS2, IFIT1 and IFIT3 are the key genes involved in the pathological phenotype of the two diseases. Based on the key genes, the interaction of transcription factor (TF) and miRNA with common differentially expressed genes is also identified. The possible pathological markers of the two diseases and related molecular regulatory mechanisms of disease treatment are revealed to provide theoretical basis for the treatment of the two diseases. © 2023 Editorial Office of Journal of Shenzhen University. All rights reserved.

The impact of dynamic adaptive teaching model on surgical education.

Objective To investigate the impact of dynamic adaptive teaching model on surgical education. Methods Due to the COVID-19 pandemic in 2020, we adopted dynamic adaptive teaching model in the Department of Breast Surgery, Peking Union Medical College Hospital, which divided the whole curriculum into several individual modules and recombined different modules to accommodate to student's levels and schedules. Meanwhile, adaptive strategy also increased the proportion of online teaching and fully utilized electronic medical resources. The present study included quantitative teaching score (QTS) recorded from January 2020 to June 2020, and used the corresponding data from 2019 as control. The main endpoint was to explore the impact of dynamic adaptive teaching model on overall QTS and its interaction effect with trainer's experience and student category. Results Totally, 20 trainers and 181 trainees were enrolled in the present study. With implementation of dynamic adaptive strategy, the overall QTS decreased dramatically (1.76+/-0.84 vs. 4.91+/-1.15, t=4.85, P=0.005). The impact was consistent irrespective of trainers' experience (high experience trainers: 0.85+/-0.40 vs. 2.12+/-0.44, t=4.98, P=0.004;medium experience trainers: 0.85+/-0.29 vs. 2.06+/-0.53, t=4.51, P=0.006;and low experience trainers: 0.10+/-0.16 vs. 0.44+/-0.22, t=2.62, P=0.047). For resident (including graduate) and undergraduate student teaching, both QTS was lower with dynamic strategy (residents: 0.18+/-0.34 vs. 0.97+/-0.14, t=4.35, P=0.007;undergraduate students 1.57+/-0.55 vs. 3.77+/-1.24, t=3.62, P=0.015), but dynamic strategy was effective for post-doc student subgroup and reached comparable QTS as traditional model (0.00+/-0.00 vs. 0.17+/-0.41, t=1.00, P=0.363). Conclusions Dynamic adaptive teaching strategy could be a useful alternative to traditional teaching model for post-doc students. It could be a novel effective solution for saving teaching resources and providing individualized surgical teaching modality.Copyright © 2023, Peking Union Medical College Hospital. All rights reserved.

A Hybrid Model of Deep Learning Features and Clinical Features for Severe Cases Predication of COVID-19

COVID-19 has spread around the world since 2019. Approximately 6.5% of COVID-19 a risk of developing severe disease with high mortality rate. To reduce the mortality rate and provide appropriate treatment, this research established an integrated models with to predict the clinical outcome of COVID-19 patients with clinical, deep learning and radiomics features. To obtain the optimal feature combination for prediction, 9 clinical features combination was selected from all available clinical factors after using LASSO, 18 deep learning features from U-Net architecture, and 9 radiomics features from segmentation result. A total of 213 COVID-19 patients and 335 non-COVID-19 patients from 5 hospitals were enrolled and used as training and test sample in this research. The proposed model obtained an accuracy, precision, recall, specificity, F1-score and ROC curve of 0.971, 0.943, 0.937, 0.974, 0.941 and 0.979, respectively, which exceeds the related work using only clinical, deep learning or radiomics factors. © 2023 SPIE.

Organic Electrochemical Transistors functionalized with Protein Minibinders for Sensitive and Specific Detection of SARS-CoV-2

There is a need for rapid, sensitive, specific, and low-cost virus sensors. Recent work has demonstrated that organic electrochemical transistors (OECTs) can detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Here, a simple and low-cost approach to the fabrication of OECT devices with excellent stability and unprecedented sensitivity and specificity for the detection of SARS-CoV-2 virus is demonstrated. The devices rely on the engineered protein minibinder LCB1, which binds strongly to SARS-CoV-2. The resulting devices exhibit excellent sensitivity for the detection of SARS-CoV-2 virus and SARS-CoV-2 spike protein receptor binding domain (RBD). These results demonstrate a simple, effective, and low-cost biomolecular sensor applicable to the real-time detection of SARS-CoV-2 virus and a general strategy for OECT device design that can be applied for the detection of other pathogenic viruses.

Researching China During the COVID-19 Pandemic

For scholars based in North America who study various topics in China, the global spread of COVID-19 and resulting travel restrictions imposed by governments and research institutions have erected new barriers to field sites and local contacts. New disease-related travel restrictions are overlaid upon constrained political conditions for some research activities and a general climate of mistrust between the governments of the United States and China observed in recent years. How have scholars responded to these conditions? What research tools do scholars have at their disposal to see their research through? How has COVID-19 compelled or inspired scholars to reconsider their methods, their research subjects, and the ethics of interacting with people in new ways? This chapter assembles insights from a diverse group of scholars working in North American institutions who are re-tooling their China-related research during these times of great uncertainty. They discuss new methods to allow for continued engagement and note the limitations and possibilities that the pause in fieldwork presents for generating new knowledge. The overall picture is a frank assessment of a research landscape characterized by unprecedented constraints and new types of risks which may persist well into the future. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

COVID-19 Impact on the Italian Community-based System of Mental Health Care: Reflections and Lessons Learned for the Future

Surface longwave downward radiation (LWDR) is a key factor affecting the surface energy balance. The daily LWDR and the diurnal variations of LWDR are of great significance for studies of climate change and surface processes. How to obtain LWDR at an averaged temporal scale from instantaneous LWDR is one of the longstanding problems in the field of radiation budget from remote sensing. In this paper, two temporal upscaling methods are introduced, namely, a method based on the diurnal variations of LWDR (diurnal variation based, DVB) and a method based on random forest regression (RFR). The results reveal that: (1) The DVB method has a global hourly and daily LWDR root-mean-square error (RMSE) of less than 21 W/m2 and 15 W/m2, respectively, and the RMSE of the daily LWDR based on RFR is less than 7 W/m2;(2) When compared with four existing statistical interpolation methods, the DVB method can not only ensure the accuracy, but also can overcome the problem of missing samples and/or an abnormal samples during upscaling;(3) Except for directly predict daily LWDR, the DVB methods can also obtain more accurate LWDR diurnal variations such as hourly, half-hourly etc. The RFR method enables high-efficiency and accurate estimation of daily averaged LWDR from instantaneous measurements. Compared with existing methods and products, the proposed methods are not only efficient, but also have a superior applicability and reliable accuracy. The proposed strategies provide new ideas for the community in estimating LWDR at continuous temporal scales from remotely sensed measurements.

Path analysis method in an epidemic model and stability analysis

In this paper, a new method for obtaining the basic reproduction number is proposed, called the path analysis method. Compared with the traditional next-generation method, this method is more convenient and less error-prone. We develop a general model that includes most of the epidemiological characteristics and enumerate all disease transmission paths. The path analysis method is derived by combining the next-generation method and the disease transmission paths. Three typical examples verify the effectiveness and convenience of the method. It is important to note that the path analysis method is only applicable to epidemic models with bilinear incidence rates. The Volterra-type Lyapunov function is given to prove the global stability of the system. The simulations prove the correctness of our conclusions.

One-step and wash-free multiplexed immunoassay platform based on bioinspired photonic barcodes

Multiplex, rapid and accurate virus quantification plays a great value in biomedical detection. Here, a novel one step, wash-free immunoassay platform based bioinspired PhC barcodes for multiplexed virus quantification was explored. PhC barcodes were decorated with PDA by self-polymerization of DA, thus this nanocomposite hybridized PhC barcodes facilitated the adsorption of FITC labelled antibodies and quenched itself photoluminescent, allowing a fast responsive composite platform. In the presence of target analyte, the FITC-labelled detection antibody was released from the surface of PDA decorated microcarrier to specifically bind to the target analyte, thus recovered the photoluminescence. In addition, the PhC microcarrier was enabled to carry out various color barcode for different targets detection though tuning internal periodic structures. Based on these excellent performances of the nanocomposite barcode, this method can not only capture H1N1, H5N1, SARS-CoV-2 simultaneously with rapid, accuracy but also accomplish multiplex quantification detection with high-sensitivity. Furthermore, our developed platform was also achieved with high-sensitivity and high-specificity through the verification of clinical samples, thus laying out a new avenue for multiplex virus detection in clinical diagnosis. © 2023

The design and implementation of the all-in-one machine for killing and sorting in the small and medium-sized logistics center

To stop the COVID-19 spread, artificial intelligence and new technologies are also actively participating in the battle. For fighting against the virus, disinfection is one of the effective ways to block the spread of the virus. According to the preliminary market research, only in the large distribution centers is the operator-controlled machine disinfection, at present most of the small and medium-sized express logistics stations are through human resources to carry out disinfection, and sorting of express packages, so the dependence on human costs, medical resources can be imagined. To this end, we designed ultrasonic atomization disinfection, sorting, and whole load notification integrated machine based on deep learning [1] and Internet of Things [2] technology to cope with the trend of normalization and recurrence of the epidemic. After testing logistics with different labels, the experimental results show that the system can effectively distinguish different labels and carry out a series of operations such as disinfection, sorting, and notification of full load, which can be put into production and contribute to epidemic prevention work. © 2023 IEEE.

Coronavirus disease 2019 vaccination in solid organ transplant recipients.

Solid organ transplant (SOT) recipients are a high-risk population for coronavirus disease 2019 (COVID-19), and the safety and efficacy of COVID-19 vaccines in this population is of great concern. At present, the published studies on COVID-19 vaccines for SOT recipients are mainly about mRNA vaccines and there are a few cases reports on recombinant adenovirus vector-based vaccines. These results show that the COVID-19 vaccines are safe for the SOT recipients, but the immune response rates are lower and the incidence of vaccine breakthrough infections is higher than that in the general population. Based on the results of the current studies, SOT recipients can start to be vaccinated with COVID-19 vaccines 1 to 3 months after organ transplantation. Prevention of COVID-19 after vaccination is still necessary to avoid vaccine breakthrough infections.Copyright © 2021 by the Chinese Medical Association.

Imaging features of COVID-19: a series of 56 cases.

Objective: To evaluate the imaging features of CT scan in patients with COVID-19. Method(s): Clinical data of 56 patients with COVID-19 from January 17 to 19, 2020 admitted to Wenzhou Central Hospital and the Second Affiliated Hospital of Wenzhou Medical University were retrospectively reviewed. The clinical manifestations, lung imaging characteristics and treatment outcomes of patients with different severity were analyzed with SAS software. Result(s): Fever (92.8%, 52/56), dry cough (75.0%, 42/56) and asthenia (58.9%, 33/56) were the first symptoms in most of the patients;some patients also had shortness of breath (25.0%, 14/56) and pharyngeal pain (10.7%, 6/56). Chest high-resolution CT scan showed that in 42 moderate patients, ground glass-like high-density shadows in the lung were observed in 30 cases (71.4%);localized plaque consolidation shadows and bronchial inflation signs were observed in 10 cases (23.8%). In 12 severe patients, 11 had high-density patches involving multiple lung lobes (>=3). In 2 critically ill patients the patches and stripes involving the entire lung were observed;and cord-like high-density shadow, local consolidation and fibrosis were also shown. Conclusion(s): The multiple ground-glass changes outside the lungs are early imaging manifestations of COVID-19 patients. The increase in pulmonary lobe consolidation and fibrosis may indicate the disease progression, and the degree of lung consolidation and fibrosis is closely related to the disease severity.Copyright © 2020 by the Chinese Medical Association.

Students' Engagement in Virtual Learning of Heritage Building During the Pandemic

The COVID-19 outbreak has caused a significant impact on the higher education system unprecedented in modern history. Learning institutions were closed, tight regulations enforced to encourage social and physical distancing and switched classes from face-to-face to online delivery (ODL). As a result, e-learning tools and platforms were explored to keep students engaged in learning during this pandemic. Although this virtual teaching–learning adaptation is not by choice and challenging for both educators and students, modern technology has encouraged us to explore a new interactive way of delivering knowledge and continue students' learning engagement. This paper focuses on the alternative teaching methods that have been conducted in Architecture Measured Drawing, which traditionally relies on physical interactions and interaction in the form of collaborative work in-studio learning and field trips. A case study of one (1) private university conducted the Architecture Measured course online in response to the pandemic has been investigated. This paper aims to identify the teaching and learning methods of this course during the pandemic and to analyze the level of students' engagement throughout the course. A survey was distributed to students enrolled in the module to gain feedback on their experience. Findings proved that the alternative method adopted has shown that students have experienced different types of engagement with each stage in the course. Students' engagement was maintained at a high level despite the shift and completed the course successfully. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Strategies for general surgery related issues in the treatment of critically ill patients diagnosed with COVID-19.

In order to improve the cure rate of critically ill patients in Wuhan epidemic area and reduce the fatality rate, the state have dispatched medical staffs from the whole country to support Wuhan and treat critically ill patients in dedicated facilities. A medical team from the First Affiliated Hospital of Xi'an Jiaotong University, consisting of 133 medical staffs major in critical care medicine, respiralogy, infection, cardiology, and general surgery, entirely took over the critical care unit of the East Hospital of the Renmin Hospital of Wuhan University, and formed a multidisciplinary collaboration team with local medical staffs to treat patients together. Up to March 13th in 2020, the author's medical team has admitted a total of 109 patients, of which 48 had been discharged up on recovery. Critically ill patients with Corona Virus Disease 2019 mainly have elder age, comorbidities, complicated conditions, and difficult diagnosis and treatment. The author and the author's team combined with clinical practice, share experience and strategies of general surgery related issues in the treatment of critically ill patients, providing reference for collegues in general surgery.Copyright © 2020 by the Chinese Medical Association.

The immunomodulatory effects of Qushi Jianpi Hewei Decoction (QJHD) for patients with COVID-19 by metagenomics and transcriptomic sequencing

Ethnopharmacological relevance: Several studies have confirmed that intestinal microflora dysbiosis correlates with the severity of COVID-19 patients. Clinical meta-analysis and our data show that the circulating miRNAs like miRNA-146 and the levels of serum cytokines in the peripheral blood are closely related to mild to moderate COVID-19 patients. Despite the widespread use of traditional herbal medicine for COVID-19 in China, the mechanisms remain largely uncovered. Aim of the study: We conducted an observational case-control study to verify the efficacy and safety of traditional Chinese herbal medicine Qushi Jianpi Hewei Decoction (QJHD) for mild to moderate COVID-19 patients, and investigated the potential biomolecular mechanisms through metagenomics and transcriptomic sequencing methods. Material(s) and Method(s): QJHD was given orally twice a day individually for 14 to 28 days. A total of 10 patients were enrolled in the study and given QJHD. We observed advantages in clinical cure time rate, and the relief of gastrointestinal symptoms as compared with reports in the literature. The metagenomics sequencing data of fecal microflora and transcriptomic sequencing data of blood cell in patients with SARS-Cov-2 infection patients were selected compared to the healthy control donors. Result(s): No serious adverse events were reported. Meanwhile, the transcriptome analysis showed a decrease of the hsa-miR-21-5p expression in peripheral blood without QJHD. The species composition analysis showed an increase in the expression of Faecalibacterium prausnitzii in the intestinal tract;The interleukin-10 (IL-10) expression also in COVID-19 patient decreased in peripheral blood compared with healthy control donors. And we found an improvement in these parameters in patients taking QJHD. Conclusion(s): Our findings show that QJHD could improve clinical outcomes of mild to moderate COVID-19 patients, probably through beneficial immunomodulatory effects by regulating Faecalibacterium prausnitzii in the intestinal tract and hsa-miR-21 and IL-10 expression in peripheral blood. (chictr.org.cn, ChiCTR2000030305)Copyright © 2022 The Author(s)

Risk factors for fatal outcome in patients with severe COVID-19: an analysis of 107 cases in Wuhan.

Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.

Risk factors for fatal outcome in patients with severe COVID-19: an analysis of 107 cases in Wuhan.

Objective: To analyze the risk factors of fatal outcome in patients with severe COVID-19. Method(s): The clinical characteristics of 107 patients with severe COVID-19 admitted in Renmin Hospital of Wuhan University from February 12 to March 12, 2020 were retrospectively analyzed. During the hospitalization 49 patients died (fatal group) and 58 patients survived (survival group). The clinical characteristics, baseline laboratory findings were analyzed using R and Python statistical software. The risk factors of fatal outcome in patients with severe COVID-19 were analyzed with multivariate logistic regression. Result(s): Univariate analysis showed that the two groups had statistically significant differences in age, clinical classification, dry cough, dyspnea and laboratory test indicators (P<0.05 or <0.01). The random forest model was used to rank the significance of the statistically significant variables in the univariate analysis, and the selected variables were included in the binary logistic regression model. After stepwise regression analysis, the patient's clinical type, age, neutrophil count, and the proportion of CD3 cells are independent risk factors for death in severe COVID-19 patients. Dry cough is an independent protective factor for the death of severe COVID-19 patients. Conclusion(s): COVID-19 patients with fatal outcome are more likely to have suppressed immune function, secondary infection and inflammatory factor storm. These factors may work together in severe patients, leading to intractable hypoxemia and multiple organ dysfunction and resulting in fatal outcome of patients. The study indicates that timely intervention and treatment measures against above factors may be effective to save the lives of patients with severe COVID-19.Copyright © 2020 by the Chinese Medical Association.