Clinical and Structural Biological Studies of Central Nervous System Inflammatory Demyelinating Diseases Related to COVID-19 Vaccines (preprint)

Various vaccines have been developed in response to the SARS-CoV-2 pandemic, and the safety of vaccines has become an important issue. COVID-19 vaccines-related central nervous system inflammatory demyelinating diseases (CNS IDDs) have been reported recently. We present one case of AstraZeneca vaccine-related myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease and literature review another 78 patients published from January 2020 to October 2022. Patients were divided into three vaccine groups (viral vector, mRNA and inactivated vaccines) for further analyses. Among 79 patients with COVID-19 vaccines-related CNS IDDs, 49 (62%) cases received viral vector vaccines, 20 (25.3%) received mRNA vaccines and 10 (12.7%) received inactivated vaccines. Twenty-seven cases (34.2%) were confirmed with autoantibodies, including 15 patients (19%) with anti-MOG, 11 (13.9%) with anti-aquaporin 4 (AQP4), and one (1.3%) with both antibodies. Significantly, more males developed CNS IDDs post viral vector vaccines compared to mRNA and inactivated vaccines. Patients receiving mRNA vaccines were older than other groups. Furthermore, mRNA and inactivated vaccines correlated more with anti-AQP4 antibodies, while viral vector vaccines showed higher MOG positivity. The research suggests potential associations between COVID-19 vaccines-related CNS IDDs and gender, age, and autoantibodies, contingent on vaccine types. Protein sequence analysis implies similarities between the S protein and AQP4/MOG. Further studies may elucidate the mechanisms of CNS IDDs, aiding vaccine selection for specific groups.

Integrating local and neighboring area influences into vulnerability modeling of infectious diseases in Singapore

Infectious disease spreading is a spatial interaction process. Assessing community vulnerability to infectious diseases thus requires not only information on local demographic and built environmental conditions, but also insights into human activity interactions with neighboring areas that can lead to the transition of vulnerability from locations to locations. This study presented an analytical framework based on the Particle Swarm Optimization model to estimate the weights of the factors for vulnerability modeling, and a local proportional parameter for use in the integration of the local and neighboring area risks. A country model and five cross-region validation models were developed for the case study of Singapore to assess the vulnerability to COVID-19. The results showed that the identified weights for the factors were robust throughout the optimization process and across various models. The local proportional parameter could be set slightly higher in between 0.6 and 0.8 (out of 1), signifying that the local effect was higher than the neighboring effect. Computation of the weights from the optimal solutions for the integrated vulnerability index showed that the factors of human activity intensity and accessibility to amenities had much higher weights, at 0.5 and 0.3, respectively. Conversely, the weights of population density, elderly population, social economic status and land use diversity were much lower. These findings underscored the importance of considering non-equal weights for factors and incorporating spatial interactions between local and neighboring areas for vulnerability modeling, to provide to a more comprehensive assessment of vulnerability to infectious diseases.

Effect of Multimedia E-Book Use on the Information Literacy of Nursing Students and Health Communication in Student-Led Large- and Small-Group Community Health Education Sessions

The integration of digital technology into healthcare is critical for health communication. This study analyzed a group of nursing students who applied multimedia health education e-books to different groups of varying sizes to explore the efficiency of implementing health communication and nursing information literacy in the nursing industry. If medical personnel can make appropriate use of technology, combine medical operations with information systems, and disseminate the purpose of health to groups of different sizes properly, the quality of patient care will improve. Thirty-two junior nursing students at the college level were divided into three groups, each subject to a 3-week internship. After the internship, a questionnaire survey was conducted. Additionally, nine nursing students were interviewed in a 45-min semistructured format. Regarding the effectiveness of nursing students using multimedia e-books to implement health communication and the development of nursing information literacy, the statistical analysis results demonstrated no significant differences between large groups and small groups. However, their 5-point Likert scale average values were all greater than 4, indicating that regardless of group size, their feedback on using e-books was positive. This means multimedia e-books can effectively help nursing students practice health communication application effectiveness and develop nursing information literacy.

Physical Therapy for Adults with Heart Failure.

Heart failure (HF) is a complex clinical syndrome caused by structural and/or functional abnormalities that results in significant disease burdens not only to the patients and their families but also to the society. Common symptoms/signs of HF include dyspnea, fatigue, and exercise intolerance, which significantly reduce the quality of life of individuals. Since the coronavirus disease 2019 (COVID-19) pandemic in 2019, it has been found that individuals with cardiovascular disease are more vulnerable to COVID-19-related cardiac sequelae including HF. In this article, we review the updated diagnosis, classifications, and interventional guidelines of HF. We also discuss the link between COVID-19 and HF. The latest evidence about physical therapy for patients with HF in both the stable chronic phase and acute cardiac decompensation phase is reviewed. Physical therapy for HF patients with circulatory support devices is also described.

Long-term risk of herpes zoster following COVID-19: A retrospective cohort study of 2 442 686 patients.

The long-term risk of herpes zoster (HZ) after recovery from a SARS-CoV-2 infection is unclear. This retrospective cohort study assessed the risk of HZ in patients following a COVID-19 diagnosis. This retrospective, propensity score-matched cohort study was based on the multi-institutional research network TriNetX. The risk of incident HZ in patients with COVID-19 was compared with that of those not infected with SARS-CoV-2 during a 1-year follow-up period. Hazard ratios (HRs) and 95% confidence intervals (CIs) of HZ and its subtypes were calculated. This study identified 1 221 343 patients with and without COVID-19 diagnoses with matched baseline characteristics. During the 1-year follow-up period, patients with COVID-19 had a higher risk of HZ compared with those without COVID-19 (HR: 1.59; 95% CI: 1.49-1.69). In addition, compared with the control group patients, those with COVID-19 had a higher risk of HZ ophthalmicus (HR: 1.31; 95% CI: 1.01-1.71), disseminated zoster (HR: 2.80; 95% CI: 1.37-5.74), zoster with other complications (HR: 1.46; 95% CI: 1.18-1.79), and zoster without complications (HR: 1.66; 95% CI: 1.55-1.77). Kaplan-Meier curve analysis (log-rank p < 0.05) results indicated that the risk of HZ remained significantly higher in patients with COVID-19 compared with those without COVID-19. Finally, the higher risk of HZ in the COVID-19 cohort compared with that in the non-COVID-19 cohort remained consistent across subgroup analyses regardless of vaccine status, age, or sex. The risk of HZ within a 12-month follow-up period was significantly higher in patients who had recovered from COVID-19 compared with that in the control group. This result highlights the importance of carefully monitoring HZ in this population and suggests the potential benefit of the HZ vaccine for patients with COVID-19.

Proxalutamide for the treatment of COVID-19 rebound following Paxlovid treatment: Report of four cases and review of the literature.

BACKGROUND: The pandemic the coronavirus disease 2019 (COVID-19) has created a global health crisis. Although Paxlovid is recommended for the early-stage treatment of mild-to-moderate COVID-19 in patients at increased risk of progression to severe COVID-19, more and more cases are reported a COVID-19 rebound after Paxlovid treatment. Currently, information on the additional treatment for COVID-19 rebound following Paxlovid treatment is limited. CASE REPORT: Here, we present four cases with COVID-19 who were mild on admission. All cases experienced a COVID-19 rebound and progressed to severe COVID-19, following treatment with Paxlovid (300 mg of nirmatrelvir with 100 mg ritonavir, twice daily for 5 days). After being treated with proxalutamide (300 mg/day), all cases finally turned real-time reverse transcription polymerase chain reaction (RT-PCR) negative. CONCLUSION: Our cases suggested that proxalutamide might be an effective remedial treatment option for patients experiencing a COVID-19 rebound after Paxlovid treatment.

Pre-existing humoral immunity and CD4+ T cell response correlate with cross-reactivity against SARS-CoV-2 Omicron subvariants after heterologous prime-boost vaccination.

BACKGROUND: Information regarding the heterologous prime-boost COVID vaccination has been fully elucidated. The study aimed to evaluate both humoral, cellular immunity and cross-reactivity against variants after heterologous vaccination. METHODS: We recruited healthcare workers previously primed with Oxford/AstraZeneca ChAdOx1-S vaccines and boosted with Moderna mRNA-1273 vaccine boost to evaluate the immunological response. Assay used: anti-spike RBD antibody, surrogate virus neutralizing antibody and interferon-γ release assay. RESULTS: All participants exhibited higher humoral and cellular immune response after the booster regardless of prior antibody level, but those with higher antibody level demonstrated stronger booster response, especially against omicron BA.1 and BA.2 variants. The pre-booster IFN-γ release by CD4+ T cells correlates with post-booster neutralizing antibody against BA.1 and BA.2 variant after adjustment with age and gender. CONCLUSIONS: A heterologous mRNA boost is highly immunogenic. The pre-existing neutralizing antibody level and CD4+ T cells response correlates with post-booster neutralization reactivity against the Omicron variant.

Deep Reinforcement Learning-Based Approach for Efficient and Reliable Droplet Routing on MEDA Biochips

The micro-electrode-dot-array (MEDA) architecture provides precise droplet control and real-time sensing in digital microfluidic biochips. Previous work has shown that trapped charge under microelectrodes (MCs) leads to droplets being stuck and failures in fluidic operations. A recent approach utilizes real-time sensing of MC health status, and attempts to avoid degraded electrodes during droplet routing. However, the problem with this solution is that the computational complexity is unacceptable for MEDA biochips of realistic size. Consequently, in this work, we introduce a deep reinforcement learning (DRL)-based approach to bypass degraded electrodes and enhance the reliability of routing. The DRL model utilizes the information of health sensing in real time to proactively reduce the likelihood of charge trapping and avoid using degraded MCs. Simulation results show that our approach provides effective routing strategies for COVID-19 testing protocols. We also validate our DRL-based approach using fabricated prototype biochips. Experimental results show that the developed DRL model completed the routing tasks using a fewer number of clock cycles and shorter total execution time, compared with a baseline routing method. Moreover, our DRL-based approach provides reliable routing strategies even in the presence of degraded electrodes. Our experimental results show that the proposed DRL-based routing is robust to occurrences of electrode faults, as well as increases the lifetime and usability of microfluidic biochips compared to existing strategies.

Design and Implementation of a Recommendation System for Buying Fresh Foods Online Based on Web Crawling

As shopping patterns have gradually shifted from offline to online mode, and with recent lockdowns during the coronavirus disease 2019 (COVID-19) pandemic restricting foreign trade and accelerating the growth of the domestic economy, digital transformation has become a major strategy for many retailers to support and expand their businesses. With the pandemic becoming a turning point, the business of major e-commerce companies in Taiwan in the retail of dry goods has grown significantly, and it has driven the online sales of fresh products as well. In this era of fierce competition, it is especially important to find a way that enables consumers to quickly find ideal fresh products on multiple platforms, shortens the time for price comparison, and improves the efficiency of online shopping. This study uses the Python programming language to write a web crawler program that captures product information from fresh food e-commerce platforms, including product introduction, price, origin, and sales volume, and then defines the relevant status of the product, such as product popularity. Accordingly, through Chinese text segmentation and term-frequency calculation, it aims to classify the product names and introductions into frequently occurring words and use them as product-related labels. Finally, the program combines the product information processing results and product-related labels to construct an online fresh food recommendation system. The results of the proposed system show that it reduces the time and energy spent comparing prices. It can also guide consumers to browse products that may be of interest using relevant tags and increase consumption efficiency by helping them find the ideal item when shopping.

Detection of Feline Coronavirus in Feline Effusions by Immunofluorescence Staining and Reverse Transcription Polymerase Chain Reaction.

Feline coronavirus (FCoV), the pathogen for feline infectious peritonitis, is a lethal infectious agent that can cause effusions in the pleural and abdominal cavities in domestic cats. To study the epidemiology of FCoV in Taiwan, 81 FIP-suspected sick cats with effusive specimens were recruited to test for FCoV infection using immunofluorescence staining and reverse transcription-polymerase chain reaction as detection methods, and viral RNAs were recovered from the specimens to conduct genotyping and phylogenetic analysis based on the spike (S) protein gene. The results revealed that a total of 47 (47/81, 58%) of the sick cats were positive for FCoV in the effusion samples, of which 39 were successfully sequenced and comprised of 21 type I strains, 9 type II strains, and 9 co-infections. The signalment analysis of these sick cats revealed that only the sex of cats showed a significant association (odds ratio = 2.74, 95% confidence interval = 1.06-7.07, p = 0.03) with the infection of FCoV, while age and breed showed no association. FCoV-positive cats demonstrated a significantly lower albumin to globulin ratio than negative individuals (p = 0.0004). The partial S gene-based phylogenetic analysis revealed that the type I strains demonstrated genetic diversity forming several clades, while the type II strains were more conserved. This study demonstrates the latest epidemiological status of FCoV infection in the northern part of Taiwan among sick cats and presents comparisons of Taiwan and other countries.

Immunogenicity of a spike protein subunit-based COVID-19 vaccine with broad protection against various SARS-CoV-2 variants in animal studies.

SARS-CoV-2 pandemic has profound impacts on human life and global economy since the outbreak in 2019. With the new variants continue to emerge with greater immune escaping capability, the protectivity of the available vaccines is compromised. Therefore, development a vaccine that is capable of inducing immunity against variants including omicron strains is in urgent need. In this study, we developed a protein-based vaccine BCVax that is consisted of antigen delta strain spike protein and QS21-based adjuvant AB801 in nanoparticle immune stimulation complex format (AB801-ISCOM). Results from animal studies showed that high level of anti-S protein IgG was induced after two doses of BCVax and the IgG was capable of neutralizing multiple variants of pseudovirus including omicron BA.1 or BA.2 strains. In addition, strong Th1 response was stimulated after BCVax immunization. Furthermore, BCvax with AB801-ISCOM as the adjuvant showed significant stronger immunity compared with the vaccine using aluminum hydroxide plus CpG 1018 as the adjuvant. BCVax was also evaluated as a booster after two prior vaccinations, the IgG titers and pseudovirus neutralization activities against BA.2 or BA.4/BA.5 were further enhanced suggesting BCVax is a promising candidate as booster. Taken together, the pre-clinical data warrant BCVax for further development in clinic.

A Visual Modeling Method for Spatiotemporal and Multidimensional Features in Epidemiological Analysis: Applied COVID-19 Aggregated Datasets (preprint)

The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological analysis. However, most epidemiology visualizations do not support the combined analysis of objective factors that might influence the transmission situation, resulting in a lack of quantitative and qualitative evidence. To address this issue, we have developed a portrait-based visual modeling method called +msRNAer. This method considers the spatiotemporal features of virus transmission patterns and the multidimensional features of objective risk factors in communities, enabling portrait-based exploration and comparison in epidemiological analysis. We applied +msRNAer to aggregate COVID-19-related datasets in New South Wales, Australia, which combined COVID-19 case number trends, geo-information, intervention events, and expert-supervised risk factors extracted from LGA-based censuses. We perfected the +msRNAer workflow with collaborative views and evaluated its feasibility, effectiveness, and usefulness through one user study and three subject-driven case studies. Positive feedback from experts indicates that +msRNAer provides a general understanding of analyzing comprehension that not only compares relationships between cases in time-varying and risk factors through portraits but also supports navigation in fundamental geographical, timeline, and other factor comparisons. By adopting interactions, experts discovered functional and practical implications for potential patterns of long-standing community factors against the vulnerability faced by the pandemic. Experts confirmed that +msRNAer is expected to deliver visual modeling benefits with spatiotemporal and multidimensional features in other epidemiological analysis scenarios.

The Omicron variant wave: Where are we now and what are the prospects?

The Omicron variant BA.2 is the dominant form of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in many countries, including those that have already implemented the strictest quarantine mandates that effectively contained the spread of the previous variants. Although many individuals were partially or fully vaccinated, confirmed Omicron infections have far surpassed all other variants combined in just a couple of months since the Omicron variant emerged. The ChAdOx1-S (AstraZeneca), BNT162b2 (Pfizer-BioNTech), and mRNA-1273 (Moderna) vaccines offer protection against the severe illness of SARS-CoV-2 infection; however, these currently available vaccines are less effective in terms of preventing Omicron infections. As a result, a booster dose of BNT162b2 or mRNA-1273 is recommended for individuals >12 years old who had received their second dose of the approved vaccines for >5 months. Herein, we review the studies that assessed the clinical benefits of the booster dose of vaccines against Omicron infections. We also analyzed public data to address whether early booster vaccination effectively prevented the surge of the Omicron infections. Finally, we discuss the consideration of a fourth dose of vaccine as a way to prevent possible upcoming infections.

The paradigm and future value of the metaverse for the intervention of cognitive decline

Cognitive decline is a gradual neurodegenerative process that is affected by genetic and environmental factors. The doctor-patient relationship in the healthcare for cognitive decline is in a “shallow” medical world. With the development of data science, virtual reality, artificial intelligence, and digital twin, the introduction of the concept of the metaverse in medicine has brought alternative and complementary strategies in the intervention of cognitive decline. This article technically analyzes the application scenarios and paradigms of the metaverse in medicine in the field of mental health, such as hospital management, diagnosis, prediction, prevention, rehabilitation, progression delay, assisting life, companionship, and supervision. The metaverse in medicine has made primary progress in education, immersive consultation, dental disease, and Parkinson's disease, bringing revolutionary prospects for non-pharmacological complementary treatment of cognitive decline and other mental problems. In particular, with the demand for non-face-to-face communication generated by the global COVID-19 epidemic, the needs for uncontactable healthcare service for the elderly have increased. The paradigm of self-monitoring, self-healing, and healthcare experienced by the elderly through the metaverse in medicine, especially from meta-platform, meta-community, and meta-hospital, will be generated, which will reconstruct the service modes for the elderly people. The future map of the metaverse in medicine is huge, which depends on the co-construction of community partners.

Research progress of origin traceability technology for food and drug homologous products

The idea of 'food and drug homology' plays a very important role in Chinese history. Especially, in the COVID-19 epidemic situation, 'food and drug homology' products improved health as medicated diet, thus promoting traditional Chinese drugs industry becomingmoreinternational. However, the quality of food and drug homology products were uneven, intermingled quality products and fake ones happen occasionally. In recent years, traceability technology for food and drug homologous products has gradually become a research hotspot due to the complex and diverse means of adulteration of food and drug homologous products. The aim of the development of origin traceability technology is to protect the 'genuineness' and 'distinctiveness' of food and drug homologous products. At the same time, it protects the rights and interests of consumersand protects the authenticity of food and drug homologous products and the healthy development of the food and drug homologous industry. Based on the basic data of journals and master's and doctoral dissertations collected from CNKI, Web of Sciences and Pud Med till June 2021, this paper analyzed the development trend of traceability technology in the application of global food and drug homologous products. The source, classification, origin traceability technology and application progress in food and drug homologous products were summarized in order to provide a theoretical basis for future research on origin traceability technology for food and drug homologous products.

Respiratory surveillance wards as a strategy to reduce nosocomial transmission of COVID-19 through early detection: The experience of a tertiary-care hospital in Singapore.

OBJECTIVES: Patients with COVID-19 may present with respiratory syndromes indistinguishable from those caused by common viruses. Early isolation and containment is challenging. Although screening all patients with respiratory symptoms for COVID-19 has been recommended, the practicality of such an effort has yet to be assessed. METHODS: Over a 6-week period during a SARS-CoV-2 outbreak, our institution introduced a "respiratory surveillance ward" (RSW) to segregate all patients with respiratory symptoms in designated areas, where appropriate personal protective equipment (PPE) could be utilized until SARS-CoV-2 testing was done. Patients could be transferred when SARS-CoV-2 tests were negative on 2 consecutive occasions, 24 hours apart. RESULTS: Over the study period, 1,178 patients were admitted to the RSWs. The mean length-of-stay (LOS) was 1.89 days (SD, 1.23). Among confirmed cases of pneumonia admitted to the RSW, 5 of 310 patients (1.61%) tested positive for SARS-CoV-2. This finding was comparable to the pickup rate from our isolation ward. In total, 126 HCWs were potentially exposed to these cases; however, only 3 (2.38%) required quarantine because most used appropriate PPE. In addition, 13 inpatients overlapped with the index cases during their stay in the RSW; of these 13 exposed inpatients, 1 patient subsequently developed COVID-19 after exposure. No patient-HCW transmission was detected despite intensive surveillance. CONCLUSIONS: Our institution successfully utilized the strategy of an RSW over a 6-week period to contain a cluster of COVID-19 cases and to prevent patient-HCW transmission. However, this method was resource-intensive in terms of testing and bed capacity.

Unraveling implicit human behavioral effects on dynamic characteristics of Covid-19 daily infection rates in Taiwan (preprint)

We study Covid-19 spreading dynamics underlying 84 curves of daily Covid-19 infection rates pertaining to 84 districts belonging to the largest seven cities in Taiwan during her pristine surge period. Our computational developments begin with selecting and extracting 18 features from each smoothed district-specific curve. This step of computing effort allows unstructured data to be converted into structured data, with which we then demonstrate asymmetric growth and decline dynamics among all involved curves. Specifically, based on Theoretical Information measurements of conditional entropy and mutual information, we compute major factors of order-1 and order-2 that reveal significant effects on affecting the curves' peak value and curvature at peak, which are two essential features characterizing all the curves. Further, we investigate and demonstrate major factors determining the geographic and social-economic induced behavioral effects by encoding each of these 84 districts with two binary characteristics: North-vs-South and Unban-vs-suburban. Furthermore, based on this data-driven knowledge on the district scale, we go on to study fine-scale behavioral effects on infectious disease spreading through similarity among 96 age-group-specific curves of daily infection rate within 12 urban districts of Taipei and 12 suburban districts of New Taipei City, which counts for almost one-quarter of the island nation's total population. We conclude that human living, traveling, and working behaviors do implicitly affect the spreading dynamics of Covid-19 across Taiwan profoundly.

Case report: Vaccine-induced immune thrombotic thrombocytopenia complicated by acute cerebral venous thrombosis and hemorrhage after AstraZeneca vaccines followed by Moderna COVID-19 vaccine booster and surgery

Vaccine-induced thrombotic thrombocytopenia (VITT) is a well-known complication of adenoviral vector COVID-19 vaccines including ChAdOx1 nCoV-19 (AstraZeneca) and Ad26. COV2.S (Janssen, Johnson & Johnson). To date, only a few cases of mRNA COVID-19 vaccine such as mRNA-1273 (Moderna) or BNT162b2 (Pfizer-BioNTech)-induced VITT have been reported. We report a case of VITT with acute cerebral venous thrombosis and hemorrhage after a booster of mRNA-1273 (Moderna) vaccine in a patient previously vaccinated with two doses of the AstraZeneca vaccine. A 42-year-old woman presented with sudden onset of weakness of the right upper limb with focal seizure. She had received two doses of AstraZeneca vaccines and a booster with Moderna vaccine 32 days before presentation. She had also undergone a laparoscopic myomectomy 12 days previously. Laboratory examinations revealed anemia (9.5 g/dl), thrombocytopenia (31 × 103/μl), and markedly elevated d-dimer (>20.0 mg/L;reference value < 0.5 mg/L). The initial brain computed tomography (CT) was normal, but a repeated scan 10 h later revealed hemorrhage at the left cerebrum. Before the results of the blood smear were received, on suspicion of thrombotic microangiopathy with thrombocytopenia and thrombosis, plasmapheresis and pulse steroid therapy were initiated, followed by intravenous immunoglobulin (1 g/kg/day for two consecutive days) due to refractory thrombocytopenia. VITT was confirmed by positive anti-PF4 antibody and both heparin-induced and PF4-induced platelet activation testing. Clinicians should be aware that mRNA-1273 Moderna, an mRNA-based vaccine, may be associated with VITT with catastrophic complications. Additionally, prior exposure to the AstraZeneca vaccine and surgical procedure could also have precipitated or aggravated autoimmune heparin-induced thrombocytopenia/VITT-like presentation.