SG-APSIC1091: Assessment of compliance to cleaning of computers by healthcare workers (HCWs) using adenosine triphosphate (ATP) measurement

Objectives: HCWs are recommended to wipe the computers with alcohol wipes before clinical use. Compliance assessment by direct observation is resource intensive. We used ATP measurement as a surrogate to assess the compliance to preutilization cleaning of computers. Methods: We conducted a pilot study to determine the median relative light unit (RLU) value reflective of preutilization cleaning of the computers. We identified values of <250, 250–500, and >500 RLU to reflect cleaned, probably cleaned, and not cleaned computers, respectively. Subsequently, we conducted a cross-sectional study of the computers in the inpatient wards in Tan Tock Seng Hospital and National Centre for Infectious Diseases. Using 3M Clean-Trace ATP swabs, we tested 5 computers in each ward: 2 computers on wheels, 2 from the nursing station, and 1 at the patients' room entrance. All analyses were conducted using STATA version 15 software. Results: Between October 4 and 10, 2021, we collected 219 samples from 219 computers. Among them, 44 (20.1%) were cleaned, 49 (22.4%) were probably cleaned, and 126 (57.5%) computers were not cleaned. Higher compliance to computer cleaning was observed in COVID-19 wards [85 ATP samples;cleaned, 37 (43.5%);probably cleaned, 26 (30.6%);not cleaned, 22 (25.9%)] compared with non–COVID-19 wards [134 ATP samples;cleaned, 7 (5.2%);probably cleaned, 23 (17.2%);not cleaned, 104 (77.6%)] (P < .01). No significant difference was observed in compliance with cleaning computers between the ICU [30 ATP samples;cleaned, 7 (23.3%);probably cleaned, 4 (13.3%);not cleaned, 19 (63.3%)] and general wards [189 ATP samples;cleaned, 37 (19.6%);probably cleaned, 45 (23.8%);not cleaned, 107 (56.6%)] (P = .47). Conclusions: ATP swab tests can be used as a surrogate marker to assess compliance to pre-utilization cleaning of computers. Enhanced awareness of environmental hygiene may explain the higher compliance to computer cleaning observed in COVID-19 wards.

Multi-user upper limb rehabilitation training system integrating social interaction.

COVID-19 causes persistent symptoms such as weakness and myasthenia in most patients. Due to the cross-infection of COVID-19, the traditional face-to-face rehabilitation services are risky for the elderly. To ensure that the elderly in urgent need of rehabilitation services receive training while minimizing the disturbance of the COVID-19 pandemic on their social activities. We have improved the existing virtual upper limb training system, and added a social factor to the system. Seniors with upper limb rehabilitation needs can use the system to compete or collaborate with others for training. In addition, a set of natural and scientific exclusive gestures have been designed under the direction of following the doctor's advice. The experiment is conducted jointly with the chief physicians of the geriatrics department in the authoritative class-A hospitals of Class III. Our experiment, which lasted for two months, showed that the virtual training system with social factors added had the best rehabilitation effect and enhanced the initiative of patients. The system has value for popularization during the COVID-19 epidemic.

Viral Vector Vaccine Development and Application during the COVID-19 Pandemic.

With the accumulation of mutations in SARS-CoV-2 and the continuous emergence of new variants, the importance of developing safer and effective vaccines has become more prominent in combating the COVID-19 pandemic. Both traditional and genetically engineered vaccines have contributed to the prevention and control of the pandemic. However, in recent years, the trend of vaccination research has gradually transitioned from traditional to genetically engineered vaccines, with the development of viral vector vaccines attracting increasing attention. Viral vector vaccines have several unique advantages compared to other vaccine platforms. The spread of Omicron has also made the development of intranasal viral vector vaccines more urgent, as the infection site of Omicron is more prominent in the upper respiratory tract. Therefore, the present review focuses on the development of viral vector vaccines and their application during the COVID-19 pandemic.

Sinicized Exploration of Sustainable Digital Fashion: Chinese Game Players' Intention to Purchase Traditional Costume Skins

Digitalization is not only blurring boundaries between the real world and virtual space, but, since COVID-19, it has also made the traditional fashion industry less reliant on physical materials. In this context, digital fashion and virtual design have emerged. Although China has started to digitally distribute cultural products based on the digitization of museums, there is still a gap in the field of digital fashion. In order to achieve the sustainable development of Chinese traditional costume culture and explore the Sinicization of digital fashion, this article proposes to transfer Chinese traditional costumes into a series of digitalized commodities, serving as computer game skins for online sales. This research involved the construction of a hypothetical model based on the technology acceptance model (TAM), including perceived usefulness, purchase price perceptions, perceived playfulness, cultural elements authenticity, satisfaction, and purchase intention through the related literature. In total, the survey data of 219 Chinese game players were collected, and a structural equation model (SEM) was constructed to verify these research hypotheses. The results showed that perceived playfulness and cultural elements authenticity had a positive effect on the players' satisfaction and purchase intentions, whereas perceived usefulness had a negative influence on the players' satisfaction and purchase intentions. In addition, purchase price perceptions had no significant negative effect on the players' satisfaction or their purchase intentions. Overall, this study contributes to the co-development of digital fashion and traditional costume culture in China, as well as the improvement of product design and marketing management for game companies.

A risk perception scale for travel to a crisis epicentre: visiting Wuhan after COVID-19. (Special Issue: COVID-19 and tourism.)

Although the significance of tourist risk perceptions is well documented, perspectives on risk associated with major pandemics such as COVID-19 remain poorly understood, especially from the viewpoint of destination crisis management. This research measured risk perceptions among Chinese residents related to travelling to Wuhan after the outbreak of COVID-19. Based on the concept and dimensions of tourist risk perceptions, a risk perception scale with 13 items on four dimensions (health, financial, social. performance) was developed and validated using exploratory and confirmatory factor analysis. Risk perception differences among visitor groups were identified based on 1818 survey responses collected during the COVID-19 outbreak in China. The results show that occupations and place of residence had significant effects on all 13 items, while gender, age, educational attainment, and income independently affected some items. Similarly, respondent involvement in disease prevention and control, losses suffered during the pandemic, and previous experiences of visiting Wuhan were found to produce significant differences.

Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies.

The SARS-CoV-2 B.1.1.529 (Omicron) variant contains 15 mutations of the receptor-binding domain (RBD). How Omicron evades RBD-targeted neutralizing antibodies requires immediate investigation. Here we use high-throughput yeast display screening1,2 to determine the profiles of RBD escaping mutations for 247 human anti-RBD neutralizing antibodies and show that the neutralizing antibodies can be classified by unsupervised clustering into six epitope groups (A-F)-a grouping that is highly concordant with knowledge-based structural classifications3-5. Various single mutations of Omicron can impair neutralizing antibodies of different epitope groups. Specifically, neutralizing antibodies in groups A-D, the epitopes of which overlap with the ACE2-binding motif, are largely escaped by K417N, G446S, E484A and Q493R. Antibodies in group E (for example, S309)6 and group F (for example, CR3022)7, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but a subset of neutralizing antibodies are still escaped by G339D, N440K and S371L. Furthermore, Omicron pseudovirus neutralization showed that neutralizing antibodies that sustained single mutations could also be escaped, owing to multiple synergetic mutations on their epitopes. In total, over 85% of the tested neutralizing antibodies were escaped by Omicron. With regard to neutralizing-antibody-based drugs, the neutralization potency of LY-CoV016, LY-CoV555, REGN10933, REGN10987, AZD1061, AZD8895 and BRII-196 was greatly undermined by Omicron, whereas VIR-7831 and DXP-604 still functioned at a reduced efficacy. Together, our data suggest that infection with Omicron would result in considerable humoral immune evasion, and that neutralizing antibodies targeting the sarbecovirus conserved region will remain most effective. Our results inform the development of antibody-based drugs and vaccines against Omicron and future variants.

COVID-19-related vasculopathy of the brain.

The COVID-19 pandemic is revealing growing reports of atypical presentation of the disease beyond the respiratory system. SARS-CoV-2 infection has been linked to multisystem vasculopathy including cardiopulmonary, cerebral and renal vasculature, potentially brought on by a dysregulated host immune response in a probable setting of a cytokine storm. Here, we describe a case of a previously healthy and active 74-year-old man presenting with acute cognitive decline with preceding non-specific influenza-like symptoms. He was then diagnosed with cerebral amyloid angiopathy (CAA)-associated intracerebral haemorrhage and was found to be COVID-19 positive. COVID-19-induced immune response may have further compromised the cerebral vessels already weakened by CAA, triggering multiple microhaemorrhages leading to clinical presentation. The limited evidence about the heterogeneity of COVID-19 manifestations suggests that clinicians should be aware and screen for concurrent COVID-19 in patients presenting with neurological features during the peak of this pandemic, as this offers the best chance for better clinical outcome.

Risk factors for severe and critically ill COVID-19 patients: A review.

The pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused an unprecedented global social and economic impact, and high numbers of deaths. Many risk factors have been identified in the progression of COVID-19 into a severe and critical stage, including old age, male gender, underlying comorbidities such as hypertension, diabetes, obesity, chronic lung diseases, heart, liver and kidney diseases, tumors, clinically apparent immunodeficiencies, local immunodeficiencies, such as early type I interferon secretion capacity, and pregnancy. Possible complications include acute kidney injury, coagulation disorders, thoromboembolism. The development of lymphopenia and eosinopenia are laboratory indicators of COVID-19. Laboratory parameters to monitor disease progression include lactate dehydrogenase, procalcitonin, high-sensitivity C-reactive protein, proinflammatory cytokines such as interleukin (IL)-6, IL-1ß, Krebs von den Lungen-6 (KL-6), and ferritin. The development of a cytokine storm and extensive chest computed tomography imaging patterns are indicators of a severe disease. In addition, socioeconomic status, diet, lifestyle, geographical differences, ethnicity, exposed viral load, day of initiation of treatment, and quality of health care have been reported to influence individual outcomes. In this review, we highlight the scientific evidence on the risk factors of severity of COVID-19.

Transfer learning for establishment of recognition of COVID-19 on CT imaging using small-sized training datasets.

The coronavirus disease, called COVID-19, which is spreading fast worldwide since the end of 2019, and has become a global challenging pandemic. Until 27th May 2020, it caused more than 5.6 million individuals infected throughout the world and resulted in greater than 348,145 deaths. CT images-based classification technique has been tried to use the identification of COVID-19 with CT imaging by hospitals, which aims to minimize the possibility of virus transmission and alleviate the burden of clinicians and radiologists. Early diagnosis of COVID-19, which not only prevents the disease from spreading further but allows more reasonable allocation of limited medical resources. Therefore, CT images play an essential role in identifying cases of COVID-19 that are in great need of intensive clinical care. Unfortunately, the current public health emergency, which has caused great difficulties in collecting a large set of precise data for training neural networks. To tackle this challenge, our first thought is transfer learning, which is a technique that aims to transfer the knowledge from one or more source tasks to a target task when the latter has fewer training data. Since the training data is relatively limited, so a transfer learning-based DensNet-121 approach for the identification of COVID-19 is established. The proposed method is inspired by the precious work of predecessors such as CheXNet for identifying common Pneumonia, which was trained using the large Chest X-ray14 dataset, and the dataset contains 112,120 frontal chest X-rays of 14 different chest diseases (including Pneumonia) that are individually labeled and achieved good performance. Therefore, CheXNet as the pre-trained network was used for the target task (COVID-19 classification) by fine-tuning the network weights on the small-sized dataset in the target task. Finally, we evaluated our proposed method on the COVID-19-CT dataset. Experimentally, our method achieves state-of-the-art performance for the accuracy (ACC) and F1-score. The quantitative indicators show that the proposed method only uses a GPU can reach the best performance, up to 0.87 and 0.86, respectively, compared with some widely used and recent deep learning methods, which are helpful for COVID-19 diagnosis and patient triage. The codes used in this manuscript are publicly available on GitHub at (https://github.com/lichun0503/CT-Classification).

Growth years and post-harvest processing methods have critical roles on the contents of medicinal active ingredients of Scutellaria baicalensis.

Optimizing the processing technology is an effective way to improve the yield of active ingredients for the industrial production of medicinal crops. Baikal Skullcap (Scutellaria baicalensis Georgi) is a perennial herb in the Lamiaceae family and its dried root is used as a famous traditional Chinese medicine (TCM). Modern pharmacological studies have shown that the active ingredients of S. baicalensis have important pharmacological effects including anti-oxidation, anti-bacterial, anti-viral, anti-tumor, and anti-inflammation. Specifically, it is recently found that S. baicalensis has significant curative effects on the treatment of corona virus disease 2019 (COVID-19). In recent years, the market demand for the medicinal products of S. baicalensis is increasing because of its great medicinal values. However, the annual yield of active ingredients originated from the root of S. baicalensis is limited due to that little progress has been made on the traditional processing technology used in the extraction process. A pressing issue faced by both herbalists and scientists is how to improve the processing efficiency, thereby obtaining the maximum yield of products for S. baicalensis. In this study, a systematic analysis on the effects of growth years and post-harvest processing on the contents of medicinal active ingredients of S. baicalensis was conducted. The contents of eight active ingredients (baicalin, wogonoside, baicalein, wogonin, scutellarin, scutellarein, apigenin, and chrysin) in roots of S. baicalensis of different growth years (ranging from 1 year to 15 years) were estimated using high performance liquid chromatography (HPLC) and further analyzed to determine the optimal harvest period. In particular, the contents of six active ingredients in different parts (cortex and stele) of the root of S. baicalensis were estimated and compared. Meanwhile, the dynamic changes of the contents of active ingredients in fresh-crush and fresh-cut roots of S. baicalensis at room temperature were compared and analyzed to reveal the influence of post-harvest treatment on the contents of active ingredients. In addition, the effects of six different post-harvest treatments on the contents of active ingredients were systematically designed and compared to determine the best primary processing technology. The results showed that the best harvesting period for S. baicalensis should be determined as 2-3 years based on comprehensive evaluation of active ingredient content, annual yield increment, and land use efficiency. The contents of active ingredients including baicalin, wogonoside, baicalein, and wogonin in cortex were significantly higher than those in stele (P ≤  0.05). The contents of baicalin, wogonoside, and scutellarin in fresh roots of S. baicalensis significantly reduced as the storage time increased, but the reduction of fresh-cutting was significantly lower than that of fresh-crushing. For the effects of different processing treatments, the contents of four main active ingredients (baicalin, wogonoside, baicalein, and wogonin) under drying (D) and cutting-drying (C-D) treatments were significantly higher than those of the other four treatments (P ≤  0.05). Collectively, the above results will not only provide novel processing methods that will improve the yield of active ingredients for S. baicalensis, but also shed light on the optimization of processing technology for the industrial production of medicinal crops.

Clinical course and risk factors for recurrence of positive SARS-CoV-2 RNA: a retrospective cohort study from Wuhan, China.

The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of this study was to determine the clinical course and risk factors for patients showing recurrent SARS-CoV-2 RNA positivity. A total of 1087 COVID-19 patients confirmed by RT-PCR from February 24, 2020 to March 31, 2020 were retrospectively enrolled. Advanced age was significantly associated with mortality. In addition, 81 (7.6%) of the discharged patients tested positive for SARS-CoV-2 RNA during the isolation period. For patients with recurrent RT-PCR positivity, the median duration from illness onset to recurrence was 50 days. Multivariate regression analysis identified elevated serum IL-6, increased lymphocyte counts and CT imaging features of lung consolidation during hospitalization as the independent risk factors of recurrence. We hypothesized that the balance between immune response and virus toxicity may be the underlying mechanism of this phenomenon. For patients with a high risk of recurrence, a prolonged observation and additional preventative measures should be implemented for at least 50 days after illness onset to prevent future outbreaks.

Early Research on COVID-19: A Bibliometric Analysis.

In December 2019, an outbreak of pneumonia, which was named COVID-2019, emerged as a global health crisis. Scientists worldwide are engaged in attempts to elucidate the transmission and pathogenic mechanisms of the causative coronavirus. COVID-19 was declared a pandemic by the World Health Organization in March 2020, making it critical to track and review the state of research on COVID-19 to provide guidance for further investigations. Here, bibliometric and knowledge mapping analyses of studies on COVID-19 were performed, including more than 1,500 papers on COVID-19 available in the PubMed and China National Knowledge Infrastructure databases from January 1, 2020 to March 8, 2020. In this review, we found that because of the rapid response of researchers worldwide, the number of COVID-19-related publications showed a high growth trend in the first 10 days of February; among these, the largest number of studies originated in China, the country most affected by pandemic in its early stages. Our findings revealed that the epidemic situation and data accessibility of different research teams have caused obvious difference in emphases of the publications. Besides, there was an unprecedented level of close cooperation and information sharing within the global scientific community relative to previous coronavirus research. We combed and drew the knowledge map of the SARS-CoV-2 literature, explored early status of research on etiology, pathology, epidemiology, treatment, prevention, and control, and discussed knowledge gaps that remain to be urgently addressed. Future perspectives on treatment, prevention, and control are also presented to provide fundamental references for current and future coronavirus research.