Knowledge, Attitudes and Perceptions towards COVID-19 Vaccinations: A Cross-Sectional Survey in Pakistan.

Background and Objectives: Several vaccines have been approved for the prevention of the coronavirus disease, discovered on 31 December in Wuhan, China. Pakistan procured vaccines from various countries. However, the lack of knowledge and reluctance of the general population to embrace the use of the vaccines are considered to be the major determinant of the slow vaccination rate. Hence, it is necessary to evaluate the willingness of the general population about their perception of the COVID-19 vaccination. Materials and Methods: A cross sectional survey based on a self-structured questionnaire comprising 18 questions was conducted (from 21 April-21 June) on 400 Pakistani participants to evaluate their knowledge, attitude, and perception towards the COVID-19 vaccination. Chi-square independent t-test and one-way Anova including a multiple step wise linear regression were used to draw conclusions about the results. p < 0.05 was considered significant. Results: A total of 400 participants responded in the knowledge, attitude, and perception (KAP) survey of which 46.5% were female and 53.5% were male. The mean age of participants was 36.08 years. This survey showed a poor knowledge (50.5%), a fair attitude (75.1%) and a poor perception (58.1%) towards the COVID-19 vaccination. Higher mean knowledge and attitude scores were reported in the age group 21-40, females, and unmarried urban citizens. Regression analysis showed that age, education, residence, and employment status influenced the knowledge and perception score to a considerable extent. Conclusions: The findings reflect an inadequate knowledge and perception on the one hand, but a better attitude towards the COVID-19 vaccination. This knowledge attitude and perception (KAP) survey will help in better understanding the opinion of the general population towards vaccination, and will be useful for policy makers and health care authorities aiming to increase the vaccination rate.

Knowledge, Attitudes and Perceptions towards COVID-19 Vaccinations: A Cross-sectional Survey in Pakistan (preprint)

Background Several vaccines have been approved for prevention of the coronavirus disease discovered on 31st December in Wuhan, China. Pakistan procured vaccines from various countries. However, the lack of knowledge and reluctance of the general population to embrace the use of the vaccines are considered to be the major determinants of the slow vaccination rate. Hence, it is necessary to evaluate the willingness of the general population about their perception of the COVID-19 vaccination. Methods A cross sectional survey based on a self-structured questionnaire comprising 18 questions was conducted (from April 21-June 21) on 400 Pakistani participants to evaluate their knowledge, attitude and perception towards the COVID-19 vaccination. Chi-square independent t-test and one-way Anova including a multiple step wise linear regression were used to draw conclusions about the results. P< 0.05 was considered significant. Results A total of 400 participants responded in the KAP survey of which 46.5% were female and 53.5% were male. The mean age of participants was 36.08 years. This survey showed a poor knowledge (50.5%), a fair attitude (75.1%) and a poor perception (58.1%) towards the COVID-19 vaccination. Higher mean knowledge and attitude scores was reported in the age group 21-40, females and unmarried urban citizens. Regression analysis showed that age, education, residence and employment status influenced the knowledge and perception score to a considerable extent. Conclusions The findings reflect an inadequate knowledge and perception on the one hand but a better attitude towards the COVID-19 vaccination. This KAP survey will help in better understanding the opinion of the general population towards vaccination and will be useful for policy makers and health care authorities aiming to increase the vaccination rate.

DEEMD: Drug Efficacy Estimation Against SARS-CoV-2 Based on Cell Morphology With Deep Multiple Instance Learning.

Drug repurposing can accelerate the identification of effective compounds for clinical use against SARS-CoV-2, with the advantage of pre-existing clinical safety data and an established supply chain. RNA viruses such as SARS-CoV-2 manipulate cellular pathways and induce reorganization of subcellular structures to support their life cycle. These morphological changes can be quantified using bioimaging techniques. In this work, we developed DEEMD: a computational pipeline using deep neural network models within a multiple instance learning framework, to identify putative treatments effective against SARS-CoV-2 based on morphological analysis of the publicly available RxRx19a dataset. This dataset consists of fluorescence microscopy images of SARS-CoV-2 non-infected cells and infected cells, with and without drug treatment. DEEMD first extracts discriminative morphological features to generate cell morphological profiles from the non-infected and infected cells. These morphological profiles are then used in a statistical model to estimate the applied treatment efficacy on infected cells based on similarities to non-infected cells. DEEMD is capable of localizing infected cells via weak supervision without any expensive pixel-level annotations. DEEMD identifies known SARS-CoV-2 inhibitors, such as Remdesivir and Aloxistatin, supporting the validity of our approach. DEEMD can be explored for use on other emerging viruses and datasets to rapidly identify candidate antiviral treatments in the future. Our implementation is available online at https://www.github.com/Sadegh-Saberian/DEEMD.

Nanopore ReCappable sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs.

The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested subgenomic RNAsused to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.

RNA binding to human METTL3-METTL14 restricts N6-deoxyadenosine methylation of DNA in vitro.

Methyltransferase like-3 (METTL3) and METTL14 complex transfers a methyl group from S-adenosyl-L-methionine to N6 amino group of adenosine bases in RNA (m6A) and DNA (m6dA). Emerging evidence highlights a role of METTL3-METTL14 in the chromatin context, especially in processes where DNA and RNA are held in close proximity. However, a mechanistic framework about specificity for substrate RNA/DNA and their interrelationship remain unclear. By systematically studying methylation activity and binding affinity to a number of DNA and RNA oligos with different propensities to form inter- or intra-molecular duplexes or single-stranded molecules in vitro, we uncover an inverse relationship for substrate binding and methylation and show that METTL3-METTL14 preferentially catalyzes the formation of m6dA in single-stranded DNA (ssDNA), despite weaker binding affinity to DNA. In contrast, it binds structured RNAs with high affinity, but methylates the target adenosine in RNA (m6A) much less efficiently than it does in ssDNA. We also show that METTL3-METTL14-mediated methylation of DNA is largely restricted by structured RNA elements prevalent in long noncoding and other cellular RNAs.

Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review.

BACKGROUND: Mental disorders are normally diagnosed exclusively on the basis of symptoms, which are identified from patients' interviews and self-reported experiences. To make mental health diagnoses and monitoring more objective, different solutions have been proposed such as digital phenotyping of mental health (DPMH), which can expand the ability to identify and monitor health conditions based on the interactions of people with digital technologies. OBJECTIVE: This article aims to identify and characterize the sensing applications and public data sets for DPMH from a technical perspective. METHODS: We performed a systematic review of scientific literature and data sets. We searched 8 digital libraries and 20 data set repositories to find results that met the selection criteria. We conducted a data extraction process from the selected articles and data sets. For this purpose, a form was designed to extract relevant information, thus enabling us to answer the research questions and identify open issues and research trends. RESULTS: A total of 31 sensing apps and 8 data sets were identified and reviewed. Sensing apps explore different context data sources (eg, positioning, inertial, ambient) to support DPMH studies. These apps are designed to analyze and process collected data to classify (n=11) and predict (n=6) mental states/disorders, and also to investigate existing correlations between context data and mental states/disorders (n=6). Moreover, general-purpose sensing apps are developed to focus only on contextual data collection (n=9). The reviewed data sets contain context data that model different aspects of human behavior, such as sociability, mood, physical activity, sleep, with some also being multimodal. CONCLUSIONS: This systematic review provides in-depth analysis regarding solutions for DPMH. Results show growth in proposals for DPMH sensing apps in recent years, as opposed to a scarcity of public data sets. The review shows that there are features that can be measured on smart devices that can act as proxies for mental status and well-being; however, it should be noted that the combined evidence for high-quality features for mental states remains limited. DPMH presents a great perspective for future research, mainly to reach the needed maturity for applications in clinical settings.

Structural basis for continued antibody evasion by the SARS-CoV-2 receptor binding domain.

Many studies have examined the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on neutralizing antibody activity after they have become dominant strains. Here, we evaluate the consequences of further viral evolution. We demonstrate mechanisms through which the SARS-CoV-2 receptor binding domain (RBD) can tolerate large numbers of simultaneous antibody escape mutations and show that pseudotypes containing up to seven mutations, as opposed to the one to three found in previously studied variants of concern, are more resistant to neutralization by therapeutic antibodies and serum from vaccine recipients. We identify an antibody that binds the RBD core to neutralize pseudotypes for all tested variants but show that the RBD can acquire an N-linked glycan to escape neutralization. Our findings portend continued emergence of escape variants as SARS-CoV-2 adapts to humans.

Guest Editorial: Digital Divide: Closing the Gap

The promise of ubiquitous connectivity has been a Utopian goal for several decades. And yet, to this day, the digital divide not only persists, but in many cases continues to widen. According to the United Nation's report [1], less than half of the population in underdeveloped areas has access to fourth generation mobile networks. Furthermore, the inequality between urban and rural areas exists even in developed countries [2], [3]. As a result, bridging the digital divide has been identified as a goal for sustainable development by the United Nations [4]. The problem of digital information and communication technologies (ICT) access divide has especially been amplified in the last two years, when COVID-19 forced the majority of the world's workforce to work from home.

Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs (preprint)

The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.

Docking Simulations Exhibit Bortezomib and other Boron-containing Peptidomimetics as Potential Inhibitors of SARS-CoV-2 Main Protease

Background: Treatment of the COVID19 pandemic requires drug development. Boron- containing compounds are attractive chemical agents, some of them act as proteases inhibitors. Objective: The present study explores the role of boronic moieties in molecules interacting on the binding site of the SARS-CoV-2 main protease. Methods: Conventional docking procedure was applied by assaying boron-free and boron-containing compounds on the recently reported crystal structure of SARS-CoV-2 main protease (PDB code: 6LU7). The set of 150 ligands includes bortezomib and inhibitors of coronavirus proteases. Results: Most of the tested compounds share contact with key residues and pose on the cleavage pocket. The compounds with a boron atom in their structure are often estimated to have higher affinity than boron-free analogues. Conclusion: Interactions and the affinity of boron-containing peptidomimetics strongly suggest that boron-moieties increase affinity on the main protease, which is tested by in vitro assays. A Bis-boron-containing compound previously tested active on SARS-virus protease and bortezomib were identified as potent ligands. These advances may be relevant to drug designing, in addition to testing available boron-containing drugs in patients with COVID19 infection.

Learning through Discovery in the Online Environment. Examples, Principles, Advantages, and Difficulties. A Case Study on Renewable Energy

The aim of this research is to investigate how learning through discovery can be achieved by Z generationpupils using the textbook and the online available sources. We have analyzed a lesson from the textbook Mathematics and Environment Exploration and an animated film from the point of view of learning through discovery, an activity performed into the virtual classroom based on these materials.Weidentified the difficulties and the problems both pupils and teachers cope with, and wehighlighted certain principles and advantages of learning through discovery performed by accessing web sources. We concluded that the film proposed by the teacher for viewing on YouTube represented a valuable information source that corresponded to the pupils' level of knowledge and, more than that, satisfied their curiosity. However, the success of the educational activities depended much on parents' supervision and support.

The mystery of the COVID toes - turning evidence-based medicine on its head.

The recent and rapid emergence of COVID-19 infection has led to a flood of publications describing all aspects of the disease and its presentation. The appearance of chilblain-like lesions, in children and young adults has particularly caught the attention of healthcare professionals with an interest in the foot. With such a novel infection, demand for information is high at a time when evidence is scarce. Consequently, there has been a renaissance in the publication of case studies. This type of research, previously relegated from many mainstream journals, as a low level source of evidence, has permitted the rapid reporting, publication and dissemination of much needed clinical data which can be used as a foundation to inform further research and investigations about a new global infection.

ILROG emergency guidelines for radiation therapy of hematological malignancies during the COVID-19 pandemic.

The International Lymphoma Radiation Oncology Group (ILROG) guidelines for using radiation therapy (RT) in hematological malignancies are widely used in many countries. The emergency situation created by the COVID-19 pandemic may result in limitations of treatment resources. Furthermore, in recognition of the need to also reduce the exposure of patients and staff to potential infection with COVID-19, the ILROG task force has made recommendations for alternative radiation treatment schemes. The emphasis is on maintaining clinical efficacy and safety by increasing the dose per fraction while reducing the number of daily treatments. The guidance is informed by adhering to acceptable radiobiological parameters and clinical tolerability. The options for delaying or omitting RT in some hematological categories are also discussed.