Molecular Crowding Modulates SARS-CoV-2 Aptamer Affinity

SARS-CoV-2 aptamer is a favorable candidate for the recognition and detection of SARS-CoV-2, owing to its small size and easy synthesis. However, the issue of compromised binding affinities in real samples and targeting mutant SARS-CoV-2 hinder wide applications of the aptamer. In this study, it is discovered that molecular crowding could increase binding affinity of CoV2-6C3 aptamer against RBD (Receptor Binding Domain) of SARS-CoV-2 via increasing the absolute value of the enthalpy change. The values of the equilibrium dissociation constant in molecular crowding decrease by 70% and 150%, respectively, against wild-type and mutant RBD compared with those in buffer without crowding. Moreover, the detection limit of SARS-CoV-2 pseudovirus is up to 5 times lower under molecular crowding compared to dilute conditions. The discovery deepens the understanding of aptamer-target interaction mechanisms in crowding conditions and provides an effective way to apply SARS-CoV-2 aptamer for virus recognition and detection.

Resilience during the lockdown: insignificance of perceived social support

Pre-pandemic studies had established that human resilience is mainly based on the social feedback that enables the formation of one’s perceived social support (PSS). In the Malaysian context, the enforcement of the movement control order (MCO) amidst the pandemic altered the social interaction pattern. The shift had involved more dependence on online communication (i.e., social media). Therefore, the way PSS plays its role in predicting resilience could have been affected. Due to the reason mentioned above and the reports that Malaysians tend to increase their levels of spirituality during the MCO, we hypothesized that the sense of being empowered fully mediates the contribution of PSS on resilience while moderated by the levels of spirituality. Four hundred and five adults who reside in Malaysia during the MCO 2 were recruited to respond to scales of PSS, spirituality, empowerment, and resilience through the online survey. Our results suggested that the sense of empowerment significantly and fully mediated the relationship between PSS and resilience among individuals with low and moderate levels of spirituality. Scope, limitations, implications, and suggestions were also discussed at the end of this paper. © 2022, Intelektual Pustaka Media Utama. All rights reserved.

COMPARISON BETWEEN CAMRY AND JAMAR DYNAMOMETERS IN MEASURING HAND GRIP STRENGTH AMONG OLDER POST-ACUTE COVID-19 OUTPATIENTS

Introduction Hand grip strength is a useful measure of muscle function. Many hand dynamometers that are less costly than the gold standard Jamar dynamometer are available but their use in clinical outpatient setting has yet to be validated. This study aimed to determine the inter-instrument reliability between Camry electronic and Jamar hydraulic dynamometers. Method A cross-sectional study was conducted on patients aged ≥65 years during their post COVID-19 follow up clinic visit. Hand grip strength was assessed using both Jamar and Camry dynamometers following standard protocol while information on participants’ demographics, health and COVID-19 hospitalizations were collected from hospital electronic medical records. Reliability between both devices was determined using intraclass correlation coefficient (ICC) and devices were compared based on subcategories of participants’ demographics and clinical characteristics. Results Ninety-three participants (mean age: 73 ± 6 years, 52.7% males) were recruited in this study. Average grip strength recorded with Jamar dynamometer (18.1 ± 7.4 kg) was higher than Camry dynamometer (19.5 ± 6.6 kg). Sub categorical comparison depicted no significant discrepancy between the devices discovered among male participants (p = 0.262), Malay participants (p = 0.243) and participants aged >70 years (p = 0.090). According to the diagnostic cut-off recommended by Asian Working Group for Sarcopenia (AWGS) 2019, similar number of participants had low grip strength using Jamar (n = 69, 74.2%) and Camry (n = 68, 73.2%) dynamometers. The odds of Camry detecting low grip strength was 0.946 times (95% CI: 0.493–1.817) as compared to Jamar dynamometer. Readings measured using both dynamometers were highly correlated to each other (r = 0.88) with ICC of 0.92, indicating an excellent inter-instrument reliability. Conclusion Comparable measures between Jamar and Camry hand dynamometers support the interchangeable use of the devices among older population. Hence, the alternative use of Camry dynamometer is appropriate for the outpatient setting.

HAND GRIP STRENGTH AMONG POST-ACUTE COVID-19 OLDER ADULTS

Introduction Muscle strength is one crucial determinant of functional activity among older adults. While COVID-19 infection is often described as an acute respiratory disease with potential multiorgan involvement, its severe inflammatory nature may lead to changes to structure and function of skeletal muscles. This present study aimed to evaluate grip strength among post COVID-19 elderly with exploration of factors influencing the change in grip strength. Method Patients with history of COVID-19 infection aged ≥65 years were recruited in the COVID-19 follow up clinic. Grip strength was assessed using Jamar dynamometer following standard protocol while baseline clinical information was collected from hospital electronic medical record. Data collected were analysed to evaluate grip strength in relation to participants’ demographics, comorbidity, length of hospital stay and steroids medication use. Total steroids equivalent doses were calculated and dichotomy of 400 mg was selected based on its median. Results Ninety-three participants (mean [SD] age: 73 [6], 52.7% males) were recruited at an average (SD) of 55 (37) days after hospital discharge, with 79.6% participants hospitalized with COVID-19 of clinical category 4. Majority (74.2%) of the participants recorded measurements lower than diagnostic cut-off for low grip strength recommended by Asian Working Group for Sarcopenia (AWGS) 2019. Results showed that increasing age was associated with a decrease in grip strength (r = −0.30, p = 0.003). Besides, increase in hospital stay (r = −0.22, p = 0.035) and Charlson Comorbidity Index (CCI) score (r = −0.42, p = 0.000) were associated with decreasing grip strength measurements. No significant discrepancy in grip strength was observed between subgroups of patients receiving total steroids equivalent doses of <400 mg and ≥ 400 mg (p = 0.881). Conclusion Low grip strength readings were recorded among post COVID-19 elderly particularly patients of older age, with longer hospital stay and higher CCI. This suggests the need for close monitoring and provision of rehabilitation intervention to older adults affected by COVID-19 infection.

Guest Editorial Emerging IoT-Driven Smart Health: From Cloud to Edge

The papers in this special section focus on emerging Internet of Medical Things. Recent advances in advances in healthcare can be experienced with the development of smart sensorial things, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), edge computing, Edge AI, 6G, cloud computing, and connected healthcare have attracted a great deal of attention and a wide range of views. However, the need to deliver real-time and accurate healthcare services to patients, while reducing costs is a challenging issue [1]. Especially, COVID-19 has recently demonstrated the importance of fast, comprehensive, and accurate intelligent healthcare involving different types of medical, physiological, and epidemiological investigation data to diagnose the virus. Smart health is a real-time, intelligent, ubiquitous healthcare service based on Internet of bioMedical Things (IoMT). With the rapid development of related technologies such as deep learning, edge computing and IoT, smart health is playing vital role in healthcare industry to increase the accuracy, reliability, and productivity of mobile sensory devices.

A Personalized Comprehensive Cloud-Based Method for Heterogeneous MAGDM and Application in COVID-19

This paper proposes a personalized comprehensive cloud-based method for heterogeneous multi-attribute group decision-making (MAGDM), in which the evaluations of alternatives on attributes are represented by LTs (linguistic terms), PLTSs (probabilistic linguistic term sets) and LHFSs (linguistic hesitant fuzzy sets). As an effective tool to describe LTs, cloud model is used to quantify the qualitative evaluations. Firstly, the regulation parameters of entropy and hyper entropy are defined, and they are further incorporated into the transformation process from LTs to clouds for reflecting the different personalities of decision-makers (DMs). To tackle the evaluation information in the form of PLTSs and LHFSs, PLTS and LHFS are transformed into comprehensive cloud of PLTS (C-PLTS) and comprehensive cloud of LHFS (C-LHFS), respectively. Moreover, DMs' weights are calculated based on the regulation parameters of entropy and hyper entropy. Next, we put forward cloud almost stochastic dominance (CASD) relationship and CASD degree to compare clouds. In addition, by considering three perspectives, a comprehensive tri-objective programing model is constructed to determine the attribute weights. Thereby, a personalized comprehensive cloud-based method is put forward for heterogeneous MAGDM. The validity of the proposed method is demonstrated with a site selection example of emergency medical waste disposal in COVID-19. Finally, sensitivity and comparison analyses are provided to show the effectiveness, stability, flexibility and superiorities of the proposed method.

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads

The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can deliver this combination of higher quality and speed. Here, we describe an Integrated Modeling PipEline for COVID Cure by Assessing Better LEads (IMPECCABLE) that employs multiple methodological innovations to overcome this fundamental limitation. We also describe the computational framework that we have developed to support these innovations at scale, and characterize the performance of this framework in terms of throughput, peak performance, and scientific results. We show that individual workflow components deliver 100 × to 1000 × improvement over traditional methods, and that the integration of methods, supported by scalable infrastructure, speeds up drug discovery by orders of magnitudes. IMPECCABLE has screened ∼1011 ligands and has been used to discover a promising drug candidate. These capabilities have been used by the US DOE National Virtual Biotechnology Laboratory and the EU Centre of Excellence in Computational Biomedicine. © 2021 ACM.

Scalable HPC & AI infrastructure for COVID-19 therapeutics

COVID-19 has claimed more than 2.7 × 106 lives and resulted in over 124 × 106 infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. We discuss innovations in computational infrastructure and methods that are accelerating and advancing drug design. Specifically, we describe several methods that integrate artificial intelligence and simulation-based approaches, and the design of computational infrastructure to support these methods at scale. We discuss their implementation, characterize their performance, and highlight science advances that these capabilities have enabled. © 2021 ACM.

Do public awareness and behaviors in rural domestic waste classification help reduce covid-19? A case study in China

Rural domestic waste classification (RDWC) is one of the main strategies for waste management, which plays a significant role in the circular economy and sustainable management. As one of the first pilot cities of waste classification in China, Hangzhou took the lead in promoting the classification and recycling of rural domestic waste. Based on the probability sampling procedure, this study focuses on the influencing factors of residents’ awareness and behaviors toward RDWC in Hangzhou rural areas. The results of the questionnaire survey show that the perception of the importance of RDWC is weak in rural areas of China. Moreover, regression analyses show that the public’s RDWC awareness is positively influenced by the cleanliness of waste rooms, age, and educational level. And their RDWC behaviors are negatively influenced by human supervision but positively influenced by the attitude to waste classification, satisfaction with the situation of RDWC and environment. Besides, exploring the relationship between the number of COVID-19 cases and the waste classification performance shows cities with better waste classification performance have fewer confirmed cases. These results imply that the proper waste classification methods and supporting infrastructure facilities could be fitted to other rural areas. © 2021, HARD Publishing Company. All rights reserved.

Progress on the incubation period of COVID-19

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease caused by SARS-CoV-2. Effective treatments are still lacking. The incubation period of COVID-19 is the period between the infection of an individual by a pathogen (SARS-CoV-2) and the manifestation of the illness or disease. The incubation period is one of the important epidemiological parameters of infectious diseases. The study of the incubation period of COVID-19 is of great significance for better understanding the natural history of the disease, tracing the source of infection, determining the detention, quarantine and isolation of contacts, determining the time of immunization, and making prevention and control measures. This study mainly reviews the progress of the incubation period of COVID-19. In previous studies, a direct calculation or parameter estimation method is usually used to estimate the incubation period, and the commonly used distributions are lognormal distribution, Weibull distribution, Gamma distribution, etc. Due to the differences in the study population, data sources and estimation methods, there are differences in the estimation results of the incubation period of COVID-19 in various studies. The estimated median incubation period for COVID-19 was about 5.9 d (95%CI: 2.98-10.51) and the average incubation period was about 5.7 d (95%CI: 4.3-8.9). The median incubation period for COVID-19 was estimated to be about 5.2 d (95%CI: 3.0-11.9) in studies using the direct calculation method, and about 5.25 d (95%CI: 3.57-8.19) in studies using the parameter estimation method. To calculate the incubation period of COVID-19, it is important to accurately collect the date of exposure and the date of symptoms onset. Due to the diversity of COVID-19 transmission routes and the possibility of multiple exposures to the same source of infection or to different sources of infection, it is often difficult to determine the exact exposure time for some patients, which brings the difficulty to the accurate estimation of the incubation period. The choice of methods depends on the epidemiological data of the study population and application scenarios. For example, in the early stage of an outbreak, when the incubation period data of small samples of infected persons are quickly obtained through field epidemiological investigation, it is advisable to adopt the direct calculation method for rapid estimation and timely guidance for prevention and control measures. As the epidemic progresses, when more epidemiological survey data are available, the parameter estimation method is a better choice. The optimal method can be selected for estimation. Either direct calculation or parameter estimation method, the accuracy of the data is crucial. Therefore, the recall bias should be minimized to obtain relatively accurate data at each key time point. At the same time, a more accurate estimate of the incubation period can be obtained by taking the infector-infected pairs with a clear transmission chain as the study population. © 2021, Science Press. All right reserved.

Unilateral axillary adenopathy following COVID-19 vaccination: a multimodality pictorial illustration and review of current guidelines.

We present a multimodality pictorial review of axillary lymphadenopathy in patients recently vaccinated against COVID-19. As the mass vaccination programme continues to be rolled out worldwide in an effort to combat the pandemic, it is important that radiologists consider recent COVID-19 vaccination in the differential diagnosis of unilateral axillary lymphadenopathy and are aware of typical appearances across all imaging methods. We review current guidelines on the management of unilateral axillary lymphadenopathy in the context of recent COVID-19 vaccination.

Viewing the Development Process of Coronavirus from the Diagnosis and Treatment of New Coronavirus

As of May 23, 2020, there were above 5.38 million cases of new coronavirus (SARS-CoV-2) infection and around 350,000 death toll. The World Health Organization (WHO) publicized on March 12, 2020 that the COVID-19 caused by the SARS-CoV-2 virus has characteristics of a global pandemic. Currently, there are no vaccines or particular drugs to combat the virus. Although scientists around the world are working hard to develop a vaccine, due to the double-blind experiments that vaccines and specific drugs must go through, it is impossible to produce a vaccine in less than half a year after the outbreak. So, the most effective measure for SARS-CoV-2 is immediate detection, isolation of new sources of infection, and diagnosis and treatment of confirmed patients. But, in order to cope with the outbreak, it is significant to understand the nature and clinical characteristics of the virus in detail. The research progress on the structure and genome of new coronaviruses, epidemiology, disease diagnosis, treatment, and future scenarios were carried out. © 2020 ACM.

"Five-early" model: The magic weapon against covid-19

Background: COVID-19(2019 novel coronavirus disease)has brought tremendous pressure to the prevention and control of the national epidemic due to its concealed onset, strong infectivity and fast transmission speed. Methods: In this retrospective study, 226 patients diagnosed with 2019 novel coronavirus pneumonia (NCP) in the Chongqing University Three Gorges Hospital were included. The patients' clinical data, including general information, initial symptoms at the onset, time of disease diagnosis, time to treatment in hospital, time of nucleic acid conversion to negative, disease classification, total time of hospitalization were collected. The clinical data of the mild and severe patients were compared. Results: Fever, cough, sore throat, poor appetite andfatigue were the main symptoms of the diagnosed patients. The time of diagnosis was significantly shorter in the mild patients (4.96 ± 4.10 days) than severe patients (7.63 ± 9.17 days) (P=0.004). Mild patients had shorter time to treatment in hospital (6.09 ± 4.47 vs. 8.71 ± 9.04 days) and less time of nucleic acid conversion to negative (7.58 ± 2.51 vs. 11.6 ± 4.67 days) compared to the severe patients. Conclusion: The above results can be used as a quantitative basis for the “five-early"(early detection, early screening, early diagnosis, early isolation treatment, and early recovery) model. The government, the masses, and the hospitals' joint prevention and optimization of the "five-early" model will provide important scientific reference for further prevention and control of the epidemics. © 2020, Iranian Journal of Public Health. All rights reserved.

Impact of the COVID-19 event on air quality in central China

In early 2020, the COVID-19 epidemic spread globally. This study investigated the air quality of three cities in Hubei Province, Wuhan, Jingmen, and Enshi, central China, from January to March 2017–2020 to analyze the impact of the epidemic prevention and control actions on air quality. The results indicated that in the three cities, during February 2020, when the epidemic prevention and control actions were taken, the average concentrations of atmospheric PM2.5, PM10, SO2, CO, and NO2 in the three cities were 46.1 µg m-3, 50.8 µg m-3, 2.56 ppb, 0.60 ppm, and 6.70 ppb, and were 30.1%, 40.5%, 33.4%, 27.9%, and 61.4% lower than the levels in February 2017–2019, respectively. However, the average O3 concentration (23.1, 32.4, and 40.2 ppb) in 2020 did not show a significant decrease, and even increased by 12.7%, 14.3%, and 11.6% in January, February, and March, respectively. This is because a lower concentration of NO2 resulted in constraints on the NO + O3 reaction, and the O3 could not be effectively further depleted. In addition, the average air quality index (AQI) for the three cities in January, February, and March 2020 were 32.2%, 27.7%, and 14.9% lower than the levels in 2017–2019, respectively. Based on the AQIs for the three cities, the combined proportions of Class I and Class Ⅱ in January, February, and March 2020 increased by 27.9%, 24.8%, and 4.3%, respectively, while the combined proportion of AQI Classes III, IV, V, and VI was reduced from 34.8% to 15.8%. In addition, in the first three months of 2020, the indicatory air pollutants in the three cities for the AQIs were predominant in the following order: PM2.5 (72.0%), O3 (16.4%), PM10 (8.3%), NO2 (2.9%), and CO (0.4%). This study provides useful information for establishing a scientific air pollution control strategy and is a valuable reference for future research on improving urban air quality. © Taiwan Association for Aerosol Research.

Cancer patients' perspectives on the real-world impact of COVID-19 pandemic: A multidisciplinary survey

Background: The outbreak of the COVID-19 pandemic has led to unprecedented disruptions to global cancer care delivery. We conducted this multidisciplinary survey to gain insights into the real-life impact of the pandemic as perceived by cancer patients. Methods: Cancer patients at various stages of their cancer journeys were surveyed with a questionnaire constructed by a multidisciplinary panel of oncologists, clinical psychologists, occupational therapists, physiotherapists and dieticians. The 64-question survey covered patient's concerns on cancer care resources, treatment provision and quality, changes in health-seeking behaviour;the impact of social isolation on physical wellbeing and psychological repercussions. Results: 600 cancer patients in Hong Kong were surveyed in May 2020. Preliminary results showed that 70% of respondents related a COVID-19 diagnosis to compromised cancer treatment and outcome. Although only 45% considered hospital attendance as safe, 80% indicated their willingness to attend oncology appointments remained unaffected. 91% of patients stated their decision to receive chemotherapy was not changed;however, 40% would be willing to trade off the efficacy/side-effect profile for an outpatient regimen. Patients also reported compromised physical wellbeing due to social isolation, in particular, deterioration in exercise tolerance & limb power (44%), reduced appetite (29%), worse sleep quality (35%). Interestingly, 59% of pts reported better care support as a result of family spending more time together. Anxiety and depression were reported in 70% and 54% of patients, respectively. In addition, 20 oncologists provided their predictions on changes in pt's health-seeking behaviours under the pandemic. Results showed that they significantly underestimated patients' willingness and preference to keep their scheduled oncology appointments and treatments despite the risk involved. Conclusions: This original survey revealed the breadth and profoundness of the impact of the COVID-19 pandemic as perceived by cancer patients, headlining patients’ care priorities and showing their unmet needs. It should be taken into consideration as we modify the way cancer care is provided during this unsettling period and beyond. Legal entity responsible for the study: The authors. Funding: The Kowloon Central Cluster Research Committee KCC Research Grant 2020/21, Hong Kong (KCC/RC/G/2021-B01). Disclosure: All authors have declared no conflicts of interest.

Effects of Lianhua Qingwen Granules Plus Arbidol on Treatment of Mild Corona Virus Disease-19

OBJECTIVE: To discuss the effects of Lianhua Qingwen granules plus arbidol on treatment of mild corona virus disease-19 (COVID-19). METHODS: A total of 295 COVID-19 patients (2020.2.17-2020.3.6) in Wuhan Third Hospital were chosen and randomly assigned to control group (n=148) and observation group (n=147). The control group orally took arbidol and the observation group took Lianhua Qingwen granules and arbidol. TCM symptom scores, white blood count (WBC), lymphocyte count (LYM), C-reactive protein (CRP), procalcitonin (PCT) and chest CT review conditions were compared. RESULTS: Total effective rate in the observation group was significantly higher than control group ((80.95% vs. 64.86%);severe transfer rate in the observation group was lower than control group (14.29% vs. 23.65%) (P＜0.05);after 7 d of treatment, TCM syndromes like fever, weakness, cough, throat dryness and sore and chest discomfort, CRP and PCT levels in the observation group were significantly lower than control group (P＜0.05);WBC and LYM levels in the observation group were significantly higher than control group (P＜0.05);based on CT review, effective cure rate in the observation group (69.39%) and control group (62.84%) was not significantly different (P＞0.05). Both of groups had no serious adverse reactions. CONCLUSION: Lianhua Qingwen granules combined with arbidol can relieve the clinical symptoms, adjust the inflammatory factors, increase the curative effects and reduce the severe transfer rate.