SAA-UNet: Spatial Attention and Attention Gate UNet for COVID-19 Pneumonia Segmentation from Computed Tomography.

The disaster of the COVID-19 pandemic has claimed numerous lives and wreaked havoc on the entire world due to its transmissible nature. One of the complications of COVID-19 is pneumonia. Different radiography methods, particularly computed tomography (CT), have shown outstanding performance in effectively diagnosing pneumonia. In this paper, we propose a spatial attention and attention gate UNet model (SAA-UNet) inspired by spatial attention UNet (SA-UNet) and attention UNet (Att-UNet) to deal with the problem of infection segmentation in the lungs. The proposed method was applied to the MedSeg, Radiopaedia 9P, combination of MedSeg and Radiopaedia 9P, and Zenodo 20P datasets. The proposed method showed good infection segmentation results (two classes: infection and background) with an average Dice similarity coefficient of 0.85, 0.94, 0.91, and 0.93 and a mean intersection over union (IOU) of 0.78, 0.90, 0.86, and 0.87, respectively, on the four datasets mentioned above. Moreover, it also performed well in multi-class segmentation with average Dice similarity coefficients of 0.693, 0.89, 0.87, and 0.93 and IOU scores of 0.68, 0.87, 0.78, and 0.89 on the four datasets, respectively. Classification accuracies of more than 97% were achieved for all four datasets. The F1-scores for the MedSeg, Radiopaedia P9, combination of MedSeg and Radiopaedia P9, and Zenodo 20P datasets were 0.865, 0.943, 0.917, and 0.926, respectively, for the binary classification. For multi-class classification, accuracies of more than 96% were achieved on all four datasets. The experimental results showed that the framework proposed can effectively and efficiently segment COVID-19 infection on CT images with different contrast and utilize this to aid in diagnosing and treating pneumonia caused by COVID-19.

SCN-SAM: A Modified Self-Cure Network for Facial Expression Recognition under Face Masks

Due to COVID-19, wearing masks has become more common. However, it is challenging to recognize expressions in the images of people wearing masks. In general facial recognition problems, blurred images and incorrect annotations of images in large-scale image datasets can make the model's training difficult, which can lead to degraded recognition performance. To address this problem, the Self-Cure Network (SCN) effectively suppresses the over-fitting of the network to images with uncertain labeling in large-scale facial expression datasets. However, it is not clear how well the SCN suppresses the uncertainty of facial expression images with masks. This paper verifies the recognition ability of SCN on images of people wearing masks and proposes a self-adjustment module to further improve SCN (called SCN-SAM). First, we experimentally demonstrate the effectiveness of SCN on the masked facial expression dataset. We then add a self-adjustment module without extensive modifications to SCN and demonstrate that SCN-SAM outperforms state-of-the-art methods in synthetic noise-added FER datasets. © 2023 Global IT Research Institute (GiRI).

Electrochemical Biosensor for the Determination of Specific Antibodies against SARS-CoV-2 Spike Protein.

In this article, we report the development of an electrochemical biosensor for the determination of the SARS-CoV-2 spike protein (rS). A gold disc electrode was electrochemically modified to form the nanocrystalline gold structure on the surface. Then, it was further altered by a self-assembling monolayer based on a mixture of two alkane thiols: 11-mercaptoundecanoic acid (11-MUA) and 6-mercapto-1-hexanol (6-MCOH) (SAMmix). After activating carboxyl groups using a N-(3-dimethylaminopropyl)-N'-ethyl-carbodiimide hydrochloride and N-hydroxysuccinimide mixture, the rS protein was covalently immobilized on the top of the SAMmix. This electrode was used to design an electrochemical sensor suitable for determining antibodies against the SARS-CoV-2 rS protein (anti-rS). We assessed the association between the immobilized rS protein and the anti-rS antibody present in the blood serum of a SARS-CoV-2 infected person using three electrochemical methods: cyclic voltammetry, differential pulse voltammetry, and potential pulsed amperometry. The results demonstrated that differential pulse voltammetry and potential pulsed amperometry measurements displayed similar sensitivity. In contrast, the measurements performed by cyclic voltammetry suggest that this method is the most sensitive out of the three methods applied in this research.

Batteryless wireless magnetostrictive Fe30Co70/Ni clad plate for human coronavirus 229E detection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been garnered increasing for its rapid worldwide spread. Each country had implemented city-wide lockdowns and immigration regulations to prevent the spread of the infection, resulting in severe economic consequences. Materials and technologies that monitor environmental conditions and wirelessly communicate such information to people are thus gaining considerable attention as a countermeasure. This study investigated the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). Light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, direct current (DC) voltage storage capacitor, and wireless information transmission circuits were developed for this purpose. The power consumption was reduced by improving the energy storage circuit, and the magnetostrictive clad plate under bending vibration stored a DC voltage of 1.9 V and wirelessly transmitted a signal to a personal computer once every 5 min and 10 s under bias magnetic fields of 0 and 10 mT, respectively. Then, on the clad plate surface, a novel CD13 biorecognition layer was immobilized using a self-assembled monolayer of -COOH groups, thus forming an amide bond with -NH2 groups for the detection of HCoV-229E. A bending vibration test demonstrated the resonance frequency changes because of HCoV-229E binding. The fluorescence signal demonstrated that HCoV-229E could be successfully detected. Thus, because HCoV-229E changed the dynamic characteristics of this plate, the CD13-modified magnetostrictive clad plate could detect HCoV-229E from the interval of wireless communication time. Therefore, a monitoring system that transmits/detects the presence of human coronavirus without batteries will be realized soon.

Dynamic asymmetric connectedness in technological sectors

This paper investigates the asymmetric, time, and frequency-based volatility spillovers in global IT industries. To this end, we introduce a new Wavelet-Time Varying Parameter-VAR (W-TVP-VAR) approach to compute connectedness combined with the asymmetrical connectedness of (Barndorff-Nielsen et al., 2010) and (Baruník et al., 2016, 2017) at different frequencies. Daily stock prices of the IT sector in thirteen countries representing the top technologically advanced countries ranging from January 15, 2016, until June 24, 2022, are used. The empirical results show that the aggregate volatility is slowly transmitted across markets with an effect lasting more than twenty days. The result also supports the presence of asymmetrical transmission as downside spillovers dominate upside spillovers, regardless of the frequency. Furthermore, the time-varying spillover shows the dominance of downside spillovers in various crisis periods, especially during the pandemic. The time and frequency-based spillover indicate that the overall spillover increased during the recent COVID-19 pandemic crisis period, which is mostly driven by the short-term, suggesting that panic decisions and herd behavior result in extreme connectedness. These findings are helpful to participants and policymakers.

Addressing the COVID-19 Shock: The Potential Job Creation in China by the RCEP.

In 2020, coronavirus disease (COVID-19) left around 81% of the global workforce, nearly 2.7 billion workers, affected. Employment in China was the first to be hit by COVID-19. The Regional Comprehensive Economic Partnership (RCEP) is expected to bring dynamism to China's employment market in an era of long COVID-19. This study aims to examine the number of sectoral jobs that the RCEP will create in China, with the number of skilled or unskilled labour employed in each sector. The exogenous shocks to the RCEP can be reflected in the number of jobs created through multipliers based on a social accounting matrix compiled from China's input-output tables in 2017, combined with the employment satellite accounts compiled. The results show that the RCEP is expected to create over 17 million potential jobs in China, with unskilled labour accounting for 10.44 million and skilled labour for 6.77 million. It is even expected that there will be job losses in the metalworking machinery sector. The contribution of this paper can serve as a reference for policies to protect vulnerable sectors, further open up trade markets and strengthen cooperation among RCEP members as important measures to address the employment impact of long COVID-19.

Prime Minister's Overarching Scheme for Holistic Nutrition (POSHAN) on Wheels as a Drive Towards Combating Malnutrition Among Children in Coastal Gujarat.

Background Gujarat, India, is home to severe acute malnutrition. Wasting in children is associated with a higher risk of death if not treated properly. The present study identified children under five years of age with severe acute malnutrition (SAM). It provided energy-dense nutrition supplement (EDNS) during the rising cases of COVID-19 to treat them as per the guidelines of the government of Gujarat in Devbhumi Dwarka District of Gujarat State, India.  Methods A descriptive research design was used in the study. Children were screened by a Nutrition Assistant in the presence of an Anganwadi Worker (AWW), Auxiliary Nurse Midwife (ANM)/Community Health Officer (CHO) at Anganwadi Centre or the Child's home using weight/length Z score <-3 standard deviations (SDs) or mid-upper arm circumference (MUAC) <11.5 and identified severe acute malnourished children were provided EDNS (WHO composition) for a period of seven days initially for a starting period as per the child's body weight then followed up to eight weeks. Data was entered on the spot in a Google sheet, which nutrition assistants maintained. Data were analyzed using IBM SPSS Statistics for Windows, Version 26.0 (Released 2019; IBM Corp., Armonk, New York, United States) and Microsoft Excel 2019. Results The study revealed that 23% of children were considered in the SAM category, followed by 21% in the Bhanvad block and 24% in the Dwarka block. For the Bhanvad block, 40% of the children were treated normally with a maximum weight gain of 1 to 2 kgs (63%). Similarly, for the Dwarka block, 29% of children were treated normally with a weight gain of 1 to 2 kgs (64%). Conclusions The study identified children with SAM and provided EDNS for eight weeks. To strengthen the program, the engagement of frontline functionaries of government should be increased, which plays an active role in the community and can be a bridge to the community. As in the community-based management of acute malnutrition (CMAM) program, Accredited Social Health Activists (ASHAs) are responsible for reaching out the ready-to-use therapeutic food (RUTF) to the mothers, weighing of children is done jointly by AWWs and ASHAs on a weekly basis, as well as counselling of the mothers on care and feeding practices and hygiene, and therefore every ASHA receives an incentive of Rs. 25 per child per week to monitor the progress of the child, reach out the therapeutic food, and counsel the mother. This system should be linked with Prime Minister's Overarching Scheme for Holistic Nutrition (POSHAN) on wheels program.

Computational Analysis of SAM Analogs as Methyltransferase Inhibitors of nsp16/nsp10 Complex from SARS-CoV-2.

Methyltransferases (MTases) enzymes, responsible for RNA capping into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are emerging important targets for the design of new anti-SARS-CoV-2 agents. Here, analogs of S-adenosylmethionine (SAM), obtained from the bioisosteric substitution of the sulfonium and amino acid groups, were evaluated by rigorous computational modeling techniques such as molecular dynamics (MD) simulations followed by relative binding free analysis against nsp16/nsp10 complex from SARS-CoV-2. The most potent inhibitor (2a) shows the lowest binding free energy (-58.75 Kcal/mol) and more potency than Sinefungin (SFG) (-39.8 Kcal/mol), a pan-MTase inhibitor, which agrees with experimental observations. Besides, our results suggest that the total binding free energy of each evaluated SAM analog is driven by van der Waals interactions which can explain their poor cell permeability, as observed in experimental essays. Overall, we provide a structural and energetic analysis for the inhibition of the nsp16/nsp10 complex involving the evaluated SAM analogs as potential inhibitors.

Effect of visual imagery in COVID-19 social media posts on users' perception.

People receive a wide variety of news from social media. They especially look for information on social media in times of crisis with the desire to assess the risk they face. This risk assessment, and other aspects of user reactions, may be affected by characteristics of the social media post relaying certain information. Thus, it is critical to understand these characteristics to deliver information with the reactions in mind. This study investigated various types of imagery used as thumbnails in social media posts regarding news about the COVID-19 pandemic. In an experimental design, 300 participants viewed social media posts containing each of the three types of imagery: data visualization (directly about risk information), advisory (not containing direct risk information, but instead help on how to lower risk), or clickbait (containing no risk-related information, just generic visuals). After observing the social media posts, they answered questionnaires measuring their emotions (valence, arousal, and dominance), risk perception, perceived credibility of the post, and engagement. The participants also indicated their emotions towards and interest in COVID-19 news coverage, age, gender, and how often and actively they use social media. These variables acted as controls. The data were analysed using mixed linear models. Results indicated that advisory imagery positively influenced valence, arousal, dominance, credibility, and (lower) risk perception. Alternatively, imagery showing data visualizations yielded low valence, arousal, dominance, credibility, and high risk perception. Clickbait-styled thumbnails which carry no information are usually measured between the other two types. The type of imagery did not affect the motivation to engage with a post. Aside from visual imagery, most variables were affected by COVID sentiment and the usual activity on social media. These study results indicate that one should use advisory imagery for more comfortable news delivery and data visualization when the poster wishes to warn users of existing risks.

Determination of rSpike Protein by Specific Antibodies with Screen-Printed Carbon Electrode Modified by Electrodeposited Gold Nanostructures.

In this research, we assessed the applicability of electrochemical sensing techniques for detecting specific antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins in the blood serum of patient samples following coronavirus disease 2019 (COVID-19). Herein, screen-printed carbon electrodes (SPCE) with electrodeposited gold nanostructures (AuNS) were modified with L-Cysteine for further covalent immobilization of recombinant SARS-CoV-2 spike proteins (rSpike). The affinity interactions of the rSpike protein with specific antibodies against this protein (anti-rSpike) were assessed using cyclic voltammetry (CV) and differential pulse voltammetry (DPV) methods. It was revealed that the SPCE electroactive surface area increased from 1.49 ± 0.02 cm2 to 1.82 ± 0.01 cm2 when AuNS were electrodeposited, and the value of the heterogeneous electron transfer rate constant (k0) changed from 6.30 × 10-5 to 14.56 × 10-5. The performance of the developed electrochemical immunosensor was evaluated by calculating the limit of detection and limit of quantification, giving values of 0.27 nM and 0.81 nM for CV and 0.14 nM and 0.42 nM for DPV. Furthermore, a specificity test was performed with a solution of antibodies against bovine serum albumin as the control aliquot, which was used to assess nonspecific binding, and this evaluation revealed that the developed rSpike-based sensor exhibits low nonspecific binding towards anti-rSpike antibodies.

Electrochemical Determination of Interaction between SARS-CoV-2 Spike Protein and Specific Antibodies.

The serologic diagnosis of coronavirus disease 2019 (COVID-19) and the evaluation of vaccination effectiveness are identified by the presence of antibodies specific to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, we present the electrochemical-based biosensing technique for the detection of antibodies specific to the SARS-CoV-2 proteins. Recombinant SARS-CoV-2 spike proteins (rSpike) were immobilised on the surface of a gold electrode modified by a self-assembled monolayer (SAM). This modified electrode was used as a sensitive element for the detection of polyclonal mouse antibodies against the rSpike (anti-rSpike). Electrochemical impedance spectroscopy (EIS) was used to observe the formation of immunocomplexes while cyclic voltammetry (CV) was used for additional analysis of the surface modifications. It was revealed that the impedimetric method and the elaborate experimental conditions are appropriate for the further development of electrochemical biosensors for the serological diagnosis of COVID-19 and/or the confirmation of successful vaccination against SARS-CoV-2.

Towards an Electrochemical Immunosensor for the Detection of Antibodies against SARS-CoV-2 Spike Protein

Herein we report the electrochemical system for the detection of specific antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins in blood serum patient samples after coronavirus disease 2019 (COVID-19). For this purpose, the recombinant SARS-CoV-2 spike protein (SCoV2-rS) was covalently immobilised on the surface of the gold electrode pre-modified with mixed self-assembled monolayer (SAMmix) consisting of 11-mercaptoundecanoic acid and 6-mercapto-1-hexanol. The affinity interaction of SCoV2-rS with specific antibodies against this protein (anti-rS) was detected using two electrochemical methods: cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The anti-rS was detected with a detection limit of 2.53 nM and 1.99 nM using CV and EIS methods, respectively. The developed electrochemical immunosensor is suitable for the confirmation of COVID-19 infection or immune response in humans after vaccination.

Prospects of NIR fluorescent nanosensors for green detection of SARS-CoV-2.

The pandemic of the novel coronavirus disease 2019 (COVID-19) is continuously causing hazards for the world. Effective detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can relieve the impact, but various toxic chemicals are also released into the environment. Fluorescence sensors offer a facile analytical strategy. During fluorescence sensing, biological samples such as tissues and body fluids have autofluorescence, giving false-positive/negative results because of the interferences. Fluorescence near-infrared (NIR) nanosensors can be designed from low-toxic materials with insignificant background signals. Although this research is still in its infancy, further developments in this field have the potential for sustainable detection of SARS-CoV-2. Herein, we summarize the reported NIR fluorescent nanosensors with the potential to detect SARS-CoV-2. The green synthesis of NIR fluorescent nanomaterials, environmentally compatible sensing strategies, and possible methods to reduce the testing frequencies are discussed. Further optimization strategies for developing NIR fluorescent nanosensors to facilitate greener diagnostics of SARS-CoV-2 for pandemic control are proposed.

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.

Benchmarking strategic alignment of business and IT strategies: opportunities, risks, challenges and solutions.

Business and IT strategy alignment is a complex dynamic process in which organizations are in a position to enable extensive IT capabilities to achieve their business objectives. This interdependence is amplified by the COVID-19 crisis, which makes the integration of IT and business strategies more important than ever. This paper mainly aims to contribute to the understanding of strategic alignment from a practical perspective, as well as to demonstrate the applicability and robustness of the Strategic Alignment Model (SAM). Moreover, potential opportunities and risks associated with the strategic alignment of business and IT strategies are analysed. Findings are discussed after a qualitative analysis of 31 participants (semi-structured survey and interviews). Results indicated several difficulties affecting the strategic alignment implementation transcend the business and IT strategies like communication, corporate culture, governance, resource prioritization, and effective leadership. The study contends that there is a need to align and harmonize different agendas and interests within an organization and improve the understanding of the value of Strategic Alignment.

Bioengineering of Novel Non-Replicating mRNA (NRM) and Self-Amplifying mRNA (SAM) Vaccine Candidates Against SARS-CoV-2 Using Immunoinformatics Approach.

Presently, the world needs safe and effective vaccines to overcome the COVID-19 pandemic. Our work has focused on formulating two types of mRNA vaccines that differ in capacity to copy themselves inside the cell. These are non-amplifying mRNA (NRM) and self-amplifying mRNA (SAM) vaccines. Both the vaccine candidates encode an engineered viral replicon which can provoke an immune response. Hence we predicted and screened twelve epitopes from the spike glycoprotein of SARS-CoV-2. We used five CTL, four HTL, and three B-cell-activating epitopes to formulate each mRNA vaccine. Molecular docking revealed that these epitopes could combine with HLA molecules that are important for boosting immunogenicity. The B-cell epitopes were adjoined with GPGPG linkers, while CTL and HTL epitopes were linked with KK linkers. The entire protein chain was reverse translated to develop a specific NRM-based vaccine. We incorporate gene encoding replicase in the upstream region of CDS encoding antigen to design the SAM vaccine. Subsequently, signal sequences were added to human mRNA to formulate vaccines. Both vaccine formulations translated to produce the epitopes in host cells, initiate a protective immune cascade, and generate immunogenic memory, which can counter future SARS-CoV-2 viral exposures before the onset of infection.

Effectiveness and Coverage of Treatment for Severe Acute Malnutrition Delivered by Community Health Workers in the Guidimakha Region, Mauritania.

Geographical and economic access barriers to health facilities (HF) have been identified as some of the most important causes of the low coverage of severe acute malnutrition (SAM) treatment. The objective of this study is to assess the effectiveness and coverage of SAM treatment delivered by community health workers (CHWs) in the Guidimakha region in Mauritania, compared to the HF based approach. This study was a nonrandomized controlled trial, including two rural areas. The control group received outpatient treatment for uncomplicated SAM from HF, whilst the intervention group received outpatient treatment for uncomplicated SAM from HF or CHWs. A total of 869 children aged 6-59 months with SAM without medical complications were included in the study. The proportion of cured children was 82.3% in the control group, and 76.4% in the intervention group, we found no significant difference between the groups. Coverage in the intervention zone increased from 53.6% to 71.7%. In contrast, coverage remained at approximately 44% in the control zone from baseline to end-line. This study is the first to demonstrate in Mauritania that the decentralization model of CHWs treating SAM improves acute malnutrition treatment coverage and complies with the international quality standards for community treatment of acute malnutrition. The non-randomized study design may limit the quality of the evidence, but these results could be used by political decision-makers as a first step in revising the protocol for acute malnutrition management.

Label-Free, Rapid and Facile Gold-Nanoparticles-Based Assay as a Potential Spectroscopic Tool for Trastuzumab Quantification.

Monoclonal antibody-based immunotherapy is one of the pillars of cancer treatment. However, for an efficient and personalized approach to the therapy, a quantitative evaluation of the right dose for each patient is required. In this study, we developed a simple, label-free, and rapid approach to quantify Trastuzumab, a humanized IgG1 monoclonal antibody used against human epidermal growth factor receptor 2 (HER2), overexpressed in breast cancer patients, based on localized surface plasmon resonance (LSPR). The central idea of this work was to use gold nanoparticles (AuNPs) as plasmonic scaffolds, decorated with HER2 binders mixed with oligo-ethylene glycol (OEG) molecules, to tune the surface density of the attached macromolecules and to minimize nonspecific binding events. Specifically, we characterized and optimized a self-assembled monolayer of mixed alkylthiols terminated with nitrilotriacetic acid (NTA), and OEG3 as a spacing ligand to achieve both excellent dispersibility and high reliability in protein immobilization. The successful immobilization of histidine-tagged HER2 (His-tagged HER2) on NTA via cobalt (II) chelates was demonstrated, confirming the fully functional attachment of the proteins to the AuNP surface. The proposed design demonstrates the capability of producing a clear readout that enables the transduction of a Trastuzumab/HER2 binding event into optical signals based on the wavelength shifts in LSPR, which allowed for detecting clinically relevant concentrations of Trastuzumab down to 300 ng/mL in the buffer and 2 µg/mL in the diluted serum. This strategy was found to be fast and highly specific to Trastuzumab. These findings make the present platform an auspicious tool for developing affordable bio-nanosensors.

Co-crystallization and structure determination: An effective direction for anti-SARS-CoV-2 drug discovery.

Safer and more-effective drugs are urgently needed to counter infections with the highly pathogenic SARS-CoV-2, cause of the COVID-19 pandemic. Identification of efficient inhibitors to treat and prevent SARS-CoV-2 infection is a predominant focus. Encouragingly, using X-ray crystal structures of therapeutically relevant drug targets (PLpro, Mpro, RdRp, and S glycoprotein) offers a valuable direction for anti-SARS-CoV-2 drug discovery and lead optimization through direct visualization of interactions. Computational analyses based primarily on MMPBSA calculations have also been proposed for assessing the binding stability of biomolecular structures involving the ligand and receptor. In this study, we focused on state-of-the-art X-ray co-crystal structures of the abovementioned targets complexed with newly identified small-molecule inhibitors (natural products, FDA-approved drugs, candidate drugs, and their analogues) with the assistance of computational analyses to support the precision design and screening of anti-SARS-CoV-2 drugs.