Efficiency of flipped classroom with online-based teaching under COVID-19

Due to the spread of COVID-19 worldwide, a large number of universities had to close their campuses. To maintain teaching and learning during this disruption to the traditional teaching, most universities have adopted online teaching model. The current study aimed at investigating the efficacy of various online teaching modes as well as comparing a proposed combined model of online and flipped learning to other online and traditional models. The Learning under COVID-19questionnaire was designed and administered to undergraduate engineering students at Chengdu University of Information Technology (CUIT). The questionnaire included five parts: demographic questions, frequencies of online courses, types of online courses, the communication and Q&A in online classes and the effect of online classes, as well as the effect of combined model learning. The results of the study showed that, students were dissatisfied with online learning in general, and they were especially dissatisfied with the communication and Q&A modes. In addition, the combined model of online teaching with the flipped learning improved students' learning, attention, and evaluation of courses. [ABSTRACT FROM AUTHOR] Copyright of Interactive Learning Environments is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Limits of epidemic prediction using SIR models.

The Susceptible-Infectious-Recovered (SIR) equations and their extensions comprise a commonly utilized set of models for understanding and predicting the course of an epidemic. In practice, it is of substantial interest to estimate the model parameters based on noisy observations early in the outbreak, well before the epidemic reaches its peak. This allows prediction of the subsequent course of the epidemic and design of appropriate interventions. However, accurately inferring SIR model parameters in such scenarios is problematic. This article provides novel, theoretical insight on this issue of practical identifiability of the SIR model. Our theory provides new understanding of the inferential limits of routinely used epidemic models and provides a valuable addition to current simulate-and-check methods. We illustrate some practical implications through application to a real-world epidemic data set.

Exosomal Vaccine Loading T Cell Epitope Peptides of SARS-CoV-2 Induces Robust CD8+ T Cell Response in HLA-A Transgenic Mice.

Purpose: Current vaccines for the SARS-CoV-2 virus mainly induce neutralizing antibodies but overlook the T cell responses. This study aims to generate an exosomal vaccine carrying T cell epitope peptides of SARS-CoV-2 for the induction of CD8+ T cell response. Methods: Thirty-one peptides presented by HLA-A0201 molecule were conjugated to the DMPE-PEG-NHS molecules, and mixed with DSPE-PEG to form the peptide-PEG-lipid micelles, then fused with exosomes to generate the exosomal vaccine, followed by purification using size-exclusion chromatography and validation by Western blotting, liquid nuclear magnetic resonance (NMR) test and transmission electron microscopy. Furthermore, the exosomal vaccine was mixed with Poly (I:C) adjuvant and subcutaneously administered for three times into the hybrid mice of HLA-A0201/DR1 transgenic mice with wild-type mice. Then, the epitope-specific T cell responses were detected by ex vivo ELISPOT assay and intracellular cytokine staining. Results: The exosomal vaccine was purified from the Peak 2 fraction of FPLC and injected into the hybrid mice for three times. The IFN-γ spot forming units and the frequencies of IFN-γ+/CD8+ T cells were 10-82-fold and 13-65-fold, respectively, higher in the exosomal vaccine group compared to the Poly (I:C) control group, without visible organ toxicity. In comparison with the peptides cocktail vaccine generated in our recent work, the exosomal vaccine induced significantly stronger T cell response. Conclusion: Exosomal vaccine loading T cell epitope peptides of SARS-CoV-2 virus was initially generated without pre-modification for both peptides and exosomes, and elicited robust CD8+ T cell response in HLA-A transgenic mice.

Clinical data mining reveals Gancao-Banxia as a potential herbal pair against moderate COVID-19 by dual binding to IL-6/STAT3.

BACKGROUND: Coronavirus disease 2019 (COVID-19) keeps spreading globally. Chinese medicine (CM) exerts a critical role for the prevention or therapy of COVID-19 in an integrative and holistic way. However, mining and development of early, efficient, multisite binding CMs that inhibit the cytokine storm are imminent. METHODS: The formulae were extracted retrospectively from clinical records in Hunan Province. Clinical data mining analysis and association rule analysis were employed for mining the high-frequency herbal pairs and groups from formulae. Network pharmacology methods were applied to initially explore the most critical pair's hub targets, active ingredients, and potential mechanisms. The binding power of active ingredients to the hub targets was verified by molecular docking. RESULTS: Eight hundred sixty-two prescriptions were obtained from 320 moderate COVID-19 through the Hunan Provincial Health Commission. Glycyrrhizae Radix et Rhizoma (Gancao) and Pinelliae Rhizoma (Banxia) were used with the highest frequency and support. There were 49 potential genes associated with Gancao-Banxia pair against moderate COVID-19 patients. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that Gancao-Banxia might act via inflammatory response, viral defense, and immune responses signaling pathways. IL-6 and STAT3 were the two most hub targets in the protein-protein interaction (PPI) network. The binding of five active ingredients originated from Gancao-Banxia to IL-6-STAT3 was verified by molecular docking, namely quercetin, coniferin, licochalcone a, Licoagrocarpin and (3S,6S)-3-(benzyl)-6-(4-hydroxybenzyl)piperazine-2,5-quinone, maximizing therapeutic efficacy. CONCLUSIONS: This work provided some potential candidate Chinese medicine formulas for moderate COVID-19. Among them, Gancao-Banxia was considered the most potential herbal pair. Bioinformatic data demonstrated that Gancao-Banxia pair may achieve dual inhibition of IL-6-STAT3 via directly interacting with IL-6 and STAT3, suppressing the IL-6 amplifier. SARS-CoV-2 models will be needed to validate this possibility in the future.

Comparative studies on the high-performance compression of SARS-CoV-2 genome collections.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is fast mutating worldwide. The mutated strains have been timely sequenced by worldwide labs, accumulating a huge amount of viral genome sequences open to public for biomedicine research such as mRNA vaccine design and drug recommendation. It is inefficient to transmit the millions of genome sequences without compression. In this study, we benchmark the performance of reference-free and reference-based compression algorithms on SARS-CoV-2 genome collections extracted from NCBI. Experimental results show that reference-based two-level compression is the most suitable approach to the compression, achieving the best compression ratio 1019.33-fold for compressing 132 372 genomes and 949.73-fold for compressing 416 238 genomes. This enormous file size reduction and efficient decompression have enabled a 5-min download and decompression of $10^5$ SARS-CoV-2 genomes. As compression on datasets containing such big numbers of genomes has been explored seldom before, our comparative analysis of the state-of-the-art compression algorithms provides practical guidance for the selection of compression tools and their parameters such as reference genomes to compress viral genome databases with similar characteristics. We also suggested a genome clustering approach using multiple references for a better compression. It is anticipated that the increased availability of SARS-CoV-2 genome datasets will make biomedicine research more productive.

Field-effect at electrical contacts to two-dimensional materials.

The inferior electrical contact to two-dimensional (2D) materials is a critical challenge for their application in post-silicon very large-scale integrated circuits. Electrical contacts were generally related to their resistive effect, quantified as contact resistance. With a systematic investigation, this work demonstrates a capacitive metal-insulator-semiconductor (MIS) field-effect at the electrical contacts to 2D materials: The field-effect depletes or accumulates charge carriers, redistributes the voltage potential, and gives rise to abnormal current saturation and nonlinearity. On one hand, the current saturation hinders the devices' driving ability, which can be eliminated with carefully engineered contact configurations. On the other hand, by introducing the nonlinearity to monolithic analog artificial neural network circuits, the circuits' perception ability can be significantly enhanced, as evidenced using a coronavirus disease 2019 (COVID-19) critical illness prediction model. This work provides a comprehension of the field-effect at the electrical contacts to 2D materials, which is fundamental to the design, simulation, and fabrication of electronics based on 2D materials. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material (results of the simulation and SEM) is available in the online version of this article at 10.1007/s12274-021-3670-y.

Machine learning algorithm improves accuracy of ortho-K lens fitting in vision shaping treatment.

PURPOSE: To construct a machine learning (ML)-based model for estimating the alignment curve (AC) curvature in orthokeratology lens fitting for vision shaping treatment (VST), which can minimize the number of lens trials, improving efficiency while maintaining accuracy, with regards to its improvement over a previous calculation method. METHODS: Data were retrospectively collected from the clinical case files of 1271 myopic subjects (1271 right eyes). The AC curvatures calculated with a previously published algorithm were used as the target data sets. Four kinds of machine learning algorithms were implemented in the experimental analyses to predict the targeted AC curvatures: robust linear regression models, support vector machine (SVM) regression models with linear kernel functions, bagging decision trees, and Gaussian processes. The previously published calculation method and the novel machine learning method were then compared to assess the final parameters of ordered lenses. RESULTS: The linear SVM and Gaussian process machine learning models achieved the best performance. The input variables included sex, age, horizontal visible iris diameter (HVID), spherical refraction (SER), cylindrical refraction, eccentricity value (e value), flat K (K1) and steep K (K2) readings, anterior chamber depth (ACD), and axial length (AL). The R-squared values for the output AC1K1, AC1K2 and AC2K1 values were 0.91, 0.84, and 0.73, respectively. The previous calculation method and machine learning methods displayed excellent consistency, and the proposed methods performed best based on flat K reading and e values. CONCLUSIONS: The ML model can provide practitioners with an efficient method for estimating the AC curvatures of VST lenses and reducing the probability of cross-infection originating from trial lenses, which is especially useful during pandemics, such as that for COVID-19.

Development of a chiral HPLC method for the separation and quantification of hydroxychloroquine enantiomers.

Hydroxychloroquine (2-[[4-[(7-Chloroquinolin-4-yl) amino]pentyl](ethyl) amino]-ethanol, HCQ), an effective anti-malarial drug, has been tested in the clinics for potential treatment of severe coronavirus disease 2019 (COVID-19). Despite the controversy around the clinical benefits of HCQ, the existence of a chiral center in the molecule to possess two optical isomers suggests that there might be an enantiomeric difference on the treatment of COVID-19. Due to their poor resolution and the inability of quantification by previously reported methods for the analysis of HCQ enantiomers, it is necessary to develop an analytical method to achieve baseline separation for quantitative and accurate determination of the enantiomeric purity in order to compare the efficacy and toxicity profiles of different enantiomers. In this study, we developed and validated an accurate and reproducible normal phase chiral high-performance liquid chromatography (HPLC) method for the analysis of two enantiomers of HCQ, and the method was further evaluated with biological samples. With this newly developed method, the relative standard deviations of all analytes were lower than 5%, and the limits of quantification were 0.27 µg/ml, 0.34 µg/ml and 0.20 µg/ml for racemate, R- and S-enantiomer, respectively. The present method provides an essential analytical tool for preclinical and clinical evaluation of HCQ enantiomers for potential treatment of COVID-19.

Type A Aortic Dissection During COVID-19 Pandemic: Report From Tertiary Aortic Centers in the United States and China.

Coronavirus disease 2019 (COVID-19) has substantially disrupted many processes of care related to emergency cardiac conditions, while there has been no clinical guidance regarding the management of type A aortic dissection. A retrospective multicenter study involving 52 consecutive patients (mean age 52.3, 28.9% women) with type A aortic dissection during COVID-19 pandemic was conducted at tertiary aortic centers in Michigan, Wuhan and Changsha (China). Twenty-four (46.2%) were considered clinically suspicious for COVID-19 based on radiographic lung lesions (70.8%) followed by dyspnea (25.0%), cough (12.5%), and fever (12.5%). Overall, 47 (90.4%) underwent an operation and 5 (9.6%) managed nonoperatively. All suspected patients underwent a reverse-transcriptase-polymerase-chain-reaction at arrival, whereas 82.1% in the nonsuspected (P = 0.054). Among the 24 patients either nonoperatively managed or whose operation was delayed for >24 hours, only 1 (4.2%) died. A total of 3 (6.4%) operated patients had a positive reverse-transcriptase-polymerase-chain-reaction at various timings, including 1 nonsuspected patient preoperatively and 2 with very recent COVID-19 infection. The first patient died of respiratory failure despite uneventful surgical repair and maximal medical management. The postoperative course of both patients with recent COVID-19 was characterized by severe coagulopathy requiring massive transfusions and prolonged ICU stay. However, both survived to hospital discharge. In light of the possible dismal outcomes associated with dual diagnoses of type A aortic dissection/COVID-19 and the higher-than-expected number of asymptomatic carriers, all type A dissection patients should be immediately tested for COVID-19. Surgical interventions in patients recovered from recent COVID-19 may be safe.