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Objective: Immunohistochemistry of post-mortem lung tissue from Covid-19 patients with diffuse alveolar damage demonstrated marked increases in chondroitin sulfate and CHST15 and decline in N-acetylgalactosamine-4-sulfatase. Studies were undertaken to identify the mechanisms involved in these effects. Method(s): Human primary small airway epithelial cells (PCS 301-010;ATCC) were cultured and exposed to the SARSCoV- 2 spike protein receptor binding domain (SPRBD;AA: Lys310-Leu560;Amsbio). Expression of the spike protein receptor, angiotensin converting enzyme 2 (ACE2), was enhanced by treatment with Interferon-beta. Promoter activation, DNA-binding, RNA silencing, QPCR, Western blots, ELISAs, and specific enzyme inhibitors were used to elucidate the underlying molecular mechanisms. Result(s): Treatment of the cultured cells by the SPRBD led to increased CHST15 and CHST11 expression and decline in ARSB expression. Sulfotransferase activity, total chondroitin sulfate, and sulfated glycosaminoglycan (GAG) content were increased. Phospho-T180/T182-p38-MAPK and phospho- S423/S425-Smad3 were required for the activation of the CHST15 and CHST11 promoters. Inhibition by SB203580, a phospho-p38 MAPK inhibitor, and by SIS3, a Smad3 inhibitor, blocked the CHST15 and CHST11 promoter activation. SB203580 reversed the SPRBD-induced decline in ARSB expression, but SIS3 had no effect on ARSB expression or promoter activation. Phospho-p38 MAPK was shown to reduce retinoblastoma protein (RB) S807/S811 phosphorylation and increase RB S249/T252 phosphorylation. E2F-DNA binding declined following exposure to SPRBD, and SB203580 reversed this effect. This indicates a mechanism by which SPRBD, phospho-p38 MAPK, E2F, and RB can regulate ARSB expression and thereby impact on chondroitin 4-sulfate and dermatan sulfate and molecules that bind to these sulfated GAGs, including Interleukin-8, bone morphogenetic protein-4, galectin-3 and SHP-2 (Src homology region 2-containing protein tyrosine phosphatase 2). Conclusion(s): The enzyme ARSB is required for the degradation of chondroitin 4-sulfate and dermatan sulfate, and accumulation of these sulfated GAGs can contribute to lung pathophysiology, as evident in Covid-19. Some effects of the SPRBD may be attributable to unopposed Angiotensin II, when Ang1-7 counter effects are diminished due to binding of ACE2 with the SARS-CoV-2 spike protein and reduced production of Ang1-7. Aberrant cell signaling and activation of the phospho-p38 MAPK and Smad3 pathways increase CHST15 and CHST11 production, which can contribute to increased chondroitin sulfate in infected cells. Decline in ARSB may occur as a consequence of effects of phospho-p38 MAPK on RB phosphorylation and E2F1 availability. Decline in ARSB and the resulting impaired degradation of sulfated GAGs have profound consequences on cellular metabolic, signaling, and transcriptional events. Funding is VA Merit Award.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.
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The past decade has witnessed a tremendous boom in the field of nanotechnology. Owing to several desirable properties of nanomaterials, nanotechnology have revolutionised the current therapeutic paradigm, by carving a niche in the domains of healthcare. Products made by applying the principles of nanotechnology are not only cost-effective from the economic point of view, but also have tremendous advantages like increased specificity, tuneable physico-chemical properties, high surface to volume ratio when compared to their conventional counterparts. In this chapter, a comprehensive portrait of the use of nanotechnology in various aspects of healthcare engineering - ranging from basic research to the fabrication of translational marketed products have been provided. A host of innovative products for application in healthcare including healing body pads, self-heating quilt, smart nano biosensors for health care monitoring, and for diagnosis of several medical conditions have been discussed. This chapter also enlists an array of the recent patents filed for the products made using nano-based approaches in the field of healthcare engineering. The concerns regarding the safe use of nanotechnology-based products for healthcare are also discussed. © 2023 Elsevier Inc. All rights reserved.
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In a closed-loop supply chain (CLSC), acquiring end-of-life vehicles (ELVs) and their components from both primary and secondary markets has posed a huge uncertainty and risk. Moreover, the constant supply of ELV components with minimization of cost and exploitation of natural resources is another pressing challenge. To address the issues, the present study has developed a risk simulation framework to study market uncertainty/risk in a CLSC. In the first phase of the framework, a total of 12 important variables are identified from the existing studies. The total interpretive structural model (TISM) is used to develop a causal relationship network among the variables. Then, Matriced Impacts Cruoses Multiplication Applique a un Classement is used for determining the nature of relationships (i.e., driving or dependence power). In the second phase, the relationship of TISM is used to derive a Bayesian belief network model for determining the level of risks (i.e., high, medium, and low) associated with the CLSC through the generation of conditional probabilities across 1) multi-, 2) single-, and 3) without-parent nodes. The study findings will help decision-makers in adopting strategic and operational interventions to increase the effectiveness and resiliency of the network. Furthermore, it will help practitioners to make decisions on change management implementation for stakeholders'performance audits on the attributes of the ELV recovery program and developing resilience in the CLSC network. Overall, the present study holistically contributes to a broader investigation of the implications of strategic decisions in automobile manufacturers and resellers. IEEE
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Many changes in our digital corpus have been brought about by the interplay between rapid advances in digital communication and the current environment characterized by pandemics, political polarization, and social unrest. One such change is the pace with which new words enter the mass vocabulary and the frequency at which meanings, perceptions, and interpretations of existing expressions change. The current state-of-the-art algorithms do not allow for an intuitive and rigorous detection of these changes in word meanings over time. We propose a dynamic graph-theoretic approach to inferring the semantics of words and phrases ("terms”) and detecting temporal shifts. Our approach represents each term as a stochastic time-evolving set of contextual words and is a count-based distributional semantic model in nature. We use local clustering techniques to assess the structural changes in a given word's contextual words. We demonstrate the efficacy of our method by investigating the changes in the semantics of the phrase "Chinavirus”. We conclude that the term took on a much more pejorative meaning when the White House used the term in the second half of March 2020, although the effect appears to have been temporary. We make both the dataset and the code used to generate this paper's results available. © 2023 by the authors.
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Social Media is used by many as a source of information for current world events, followed by publicly sharing their sentiment about these events. However, when the shared information is not trustworthy and receives a large number of interactions, it alters the public's perception of authentic and false information, particularly when the origin of these stories comes from malicious sources. Over the past decade, there has been an influx of users on the Twitter social network, many of them automated bot accounts with the objective of participating in misinformation campaigns that heavily influence user susceptibility to fake information. This can affect public opinion on real-life matters, as previously seen in the 2020 presidential elections and the current COVID-19 epidemic, both plagued with misinformation. In this paper, we propose an agent-based social simulation environment that utilizes the social network Twitter, with the objective of evaluating how the beliefs of agents representing regular Twitter users can be influenced by malicious users scattered throughout Twitter with the sole purpose of spreading misinformation. We applied two scenarios to compare how these regular agents behave in the Twitter network, with and without malicious agents, to study how much influence malicious agents have on the general susceptibility of the regular users. To achieve this, we implemented a belief value system to measure how impressionable an agent is when encountering misinformation and how its behavior gets affected. The results indicated similar outcomes in the two scenarios as the affected belief value changed for these regular agents, exhibiting belief in the misinformation. Although the change in belief value occurred slowly, it had a profound effect when the malicious agents were present, as many more regular agents started believing in misinformation.
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I argue in this essay that in some circumstances lyric poems written from the colony or the postcolony move in the direction of expressive totality by engaging with multiple worlds of reference at once. György Lukács suggested that the totality that we find in epic poetry and, to a lesser extent, in the novel, is absent from lyric poetry. In a re-reading, inflected by the Covid-19 pandemic, of two mid-twentieth-century Bengali poems written by Bishnu Dey (1909–1982), of which I provide the English translations, I illustrate how lyric poems about disaster, enacting a disorientation of the senses and a dissolution of the fixity of reference, creates transpositions across multiple worlds. In the case of these particular poems, the worlds are those of Greek myth and Indian myth, parallels among which weave intertextually together in an expressive totality. It follows that, alongside other genres, poetry too continues to be a resource with which to think our contemporary moment. © 2023 South Asian Literary Association.
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Alzheimer’s dementia is the commonest form of dementia, affecting about 60-70% of diagnosed cases;however, there are several types of dementias such as vascular dementias, Lewy body dementias, dementia associated with Parkinson’s disease, fronto temporal dementias and other secondary dementias of varied aetiology. Neuropsychiatric symptoms in dementias include agitation, depression, delusions and hallucinations and are often the major cause of distress to person with dementia and their carer. Delirium has been found to be an independent risk factor for dementia, and dementia has been associated with an increased risk of developing delirium. Several studies have shown that COVID-19 quarantine is linked with an increase in behavioural and psychological symptoms of dementia (BPSD). The COVID-19 pandemic has had a significant negative impact on the availability of social support services for PWD and their carers, with closure of day centres and suspension of support groups. © 2023 Taylor and Francis.
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The occurrence of SARS-CoV-2 in 2019 is the second coronavirus spread-out after the SARS-CoV, which has pandemic potential. Search for its remedies is dependent on integrative knowledge of cell signaling pathways, which is under clinical scrutiny. The major cascades triggered by coronavirus entry include Renin-Angiotensin System, MAPK, NF-κB, JAK/STAT which are involved with innate immunity. Some other modes are, unfolded protein response signaling and inflammasome mediated apoptosis activation. Virulence factors of the SARS-CoVs like spike, envelope, nonstructural proteins etc., interfere with some of these viral defense pathways. Therapeutically, the viral intrusion, multiplication, as well as tissue-injurious cytokine overreactions are targeted by pathway-specific drugs. Viral entry blockers, p38 MAPK inhibitors, cytokine regulators, JAK inhibitors, and anti-inflammatory drugs are either being repurposed or innovated with scopes for futuristic modeling. This chapter is aimed to elucidate the pathological signaling network behind Severe Acute Respiratory Syndrome, for evaluation of existing and postulated drug targets. © 2022 Elsevier Inc. All rights reserved.
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Introduction: Structured diabetes education (DE) is vital to manage pediatric diabetes (PD) but educators are scarce in developing countries. Due to familiarity with virtual teaching in the COVID pandemic, a virtual PDE course was planned for India. Objective(s): Evaluate outcomes of a virtual PDE course in a limitedresource (LR) setting. Method(s): A 9-member ISPAE (Indian Society for Pediatric & Adolescent Endocrinology) committee, with 47 experienced volunteer faculty planned a 12-week comprehensive curriculum (delivered in English, fee INR 5000 = US$65) basic & advanced skills: diagnosis, pathophysiology, insulin, SMBG, CGMS, CSII, MNT, exercise, psychology, toddlers, adolescents, type 1&2, other special situations: 17 teaching +5 feedback sessions, exit exam;practical assignments for each session. Result(s): Trainees working with T1D selected from across India: semiurban were preferred. Lengthy course with 90%-95% attendance (highly motivated) possible as no leave, travel, or stay costs needed. Easier for women to join. Significant rise in post-test scores that is, knowledge improved. Certification was based on stringent criteria. Other advantages: intense interaction, personal commitment, continued networking, and awareness of resources. Challenges: widely varied resource, language, and social settings: language barriers, limited resources, variable baseline knowledge. Conclusion(s): The IDEAL PDE training model being virtual & intensive is an affordable & accessible alternative to a physical program in LR settings. We hope to make it high quality, sustainable, and replicable.
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SARS-CoV-2 has very recently posed a potential threat to humanity due to its very rapid rate of mutations and repairing mechanism. The spread of this virus is considered to have occurred in Wuhan, China in December 2019. Characterized by high rates of transmission, the virus is constantly evolving towards attaining higher rates of stability and transmissibility through acquiring mutations in its genome. Therefore, this study aims to analyse the mutational profiles of SARS-CoV-2 isolates. Analysis of the mutational profiles in individual SARS-CoV-2 proteins will allow us to look into the rates of mutations associated with each protein. Frequently mutated residues have been identified in this research by aligning 688 SARS-CoV-2 nucleotide sequences, which were downloaded from NCBI (National Center For Biotechnology Information) repository. Further, mutational frequencies of these mutated residues have been studied, which is instrumental in identifying the proteins that are resistant to changes, as well as the ones that have a greater proclivity towards incorporating mutations. © 2022, Walailak University. All rights reserved.
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Researches and Applications of Artificial Intelligence to Mitigate Pandemics: History, Diagnostic Tools, Epidemiology, Healthcare, and Technology offers readers an interdisciplinary view of state-of-art research related to the COVID-19 outbreak, with a focus on tactics employed to model the number of cases of COVID-19 (time series modeling), models employed to diagnostics COVID-19 based on images, and the panoramic of COVID-19 since its discovery and up to this book's publication. This book showcases the algorithms and models available to manage pandemic data, the role of AI, IoT and Mathematical Modeling, how to prevent and fight COVID-19, and the existing medical, social and pharmaceutical support. Chapters cover methods and protocols, the basics and history of diseases, the fast diagnosis of disease with different automated algorithms and artificial intelligence tools and techniques, the methods of handling epidemiology for mitigating the spread of disease, artificial intelligence and mathematical modeling techniques, and how mental and physical health is affected with social media usage. © 2021 Elsevier Inc. All rights reserved.
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With the widespread use of social media platforms within our modern society, these platforms have become a popular medium for disseminating news across the globe. While some of these platforms are considered reliable sources for sharing news, others publicize the information without much validation. The transmission of fake news on social media impacts people's behavior and negatively influences people's decisions. During the COVID-19 outbreak, it was more evident than ever. This has led to a demand for conducting research studies to explore sophisticated approaches to assess the integrity of news worldwide. The main objective of this research paper was to outline our proposed experimental methodology to detect and access fake news using Data Mining and Natural Language Processing. The presented research effort provides a method to verify the authenticity of the news disseminated in social networks by dividing the process into four significant stages: news aggregation, publication collection, data analysis, and matching results. © 2022 ACM.
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Objective: Assess the SARS-CoV2 Spike antibody response in multiple sclerosis (MS) patients on high efficacy immunotherapies. Background: There is limited knowledge about SARS-CoV2 mRNA vaccine response in MS patients on immunotherapy. Design/Methods: Patients with MS, aged 18-65, on fingolimod, siponimod, ofatumumab, or ocrelizumab for at least 3 months prior to first mRNA SARS-CoV2 vaccine (Pfizer or Moderna) were offered enrollment. A cohort of healthy controls who received the mRNA vaccines were also enrolled. Blood samples for the SARS-CoV2 Spike antibody (Anti-SARS-CoV2 S, RocheElecsys) were collected 2-3 months after the second mRNA vaccine. The proportion who seroconverted (antibody>0.4 U/ml), and SARS-CoV2 Spike antibody levels were assessed. Results: A total of 39 MS patients (6 fingolimod, 33 ocrelizumab) and 31 controls were included in this interim analysis. 33%(13/39) of MS patients seroconverted, compared to 100%(31/31) in the control group, with an estimated risk difference of -0.67,(95% confidence interval: -0.81, -0.52;Fisher's exact test, p=9.0∗10-10 ). There was no difference in seroconversion rates between MS patients who received the Pfizer (34%, 10/29) versus the Moderna vaccine (30%, 3/10) (95% confidence interval -0.38, 0.29;Fisher's exact test=1). Seroconversion was found in 100% (31/31) of controls, 66.7% (4/6) of fingolimod-treated patients, and 27.3% (9/33) of ocrelizumab-treated patients (three group comparison, Fisher's exact test p-value =2.7∗10 -10). The median Spike antibody level was <0.4 U/ml in MS patients, and 1,663 U/ml in controls (Wilcoxon rank sum test, p-value= 1.0∗10-12 ). The median Spike antibody level in the ocrelizumab group was <0.4 U/ml, 3.45 U/ml in the fingolimod group, and 1,663 U/ml in the control group (Kruskal Wallis test, p-value=5.9∗10-12 ). Total IgG correlated with Spike antibody levels in the ocrelizumab-treated group only (Spearman correlation, p=0.025). Conclusions: MS patients on ocrelizumab and fingolimod have significantly lower rates of seroconversion, and lower median Spike antibody levels in response to the mRNA SARS-CoV2 vaccines compared to controls.
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In the midst of a COVID-19 pandemic-struck India, this paper was born as an autoethnographic and analytical inquiry;it presents qualitative and multimodal research into a martial arts dance tradition, Lathi Khela, conducted from 2017 to 2018. This practice developed as a martial art, with little or no patronage, during the colonial days of the still undivided Bengal. Indeed, it still lives on as a popular martial arts dance tradition in many districts and rural communities of Bengaluru, Bangladesh. Compared to other districts, the Lathi Khela group from the Narail district has continued this practice through innovative methods. The distinctive character of the district is governed by the multi-generational practitioners of Lathi Khela and their creative choreographies, as well as the knowledge it articulates and embodies. Moreover, in Narail, this previously male-dominated profession has also included women since 2008. The focus of this work was the role of gender in the continuity of the Lathi Khela tradition in this district. This was achieved through five semi-structured, demonstrative interviews intuitively applied in the field. The research also drew on an ongoing conversation on Facebook with Rahat, a veteran Lathi Khela practitioner, who took stock of the current cultural landscape in the context of COVID-19. On the one hand, the women of this district occupy a contested space when representing this male-dominated tradition, and on the other, they physically embody lives within the patrilineal boundaries of kinship and marriage. The performativity of gender is thus directly connected to the symbolic meaning of maan, that is, the prestige attributed to the female body within the sociocultural contexts of the Lathi Khela.
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The COVID-19 pandemic attributed to the SARs-Cov-2 virus has disrupted the lives of individuals in every corner of the world, causing millions of infections and numerous deaths worldwide. Identifying and isolating infected people is very crucial to slow down the spread of the disease. In this paper, we report a design of highly sensitive, graphene-metasurface based biosensor for detecting the S1 spike protein expressed on the surface of the SARSCoV-2 virus in the terahertz band. Our structure consists of a silicon dioxide substrate sandwiched between a complete gold layer at the bottom, and a graphene monolayer on top etched with a phi-shaped slot tilted at 45 degree, which performs a wideband reflective-type cross-polarization conversion of the incident electromagnetic (EM) wave. The optimized polarization conversion ratio (PCR) has been achieved at 0.75eV chemical potential value of the graphene layer. When samples of Sars-CoV-2 virus contained in a phosphate buffer saline (PBS) solvent is put on top of proposed design of the sensing surface, the spike proteins of the virus interact with the spike antibody grown on the sensing surface;and it changes the refractive index of the overall system (Biosensor + Analyte), which in turn changes the PCR and the corresponding frequency of the reflected wave. The biosensor response has been computed using the Finite Integration Technique (FIT) in the terahertz region. The sensitivity of the biosensor is found to be 354 GHz/RIU at the PCR of 0.9. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.
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We present the design and analysis of a graphene metasurface-based cross polarization converter operating within the terahertz gap for detecting biomolecules over a broad spectral range, taking the SARS-CoV-2 virus as a specific example. To the best of our knowledge, our design reports the widest band of operation in the THz region of a graphene-based metasensor. Each meta-atom comprises a graphene pattern on silicon dioxide atop a continuous gold layer and exhibits near-unity cross polarization conversion ratio (PCR) and a 90% PCR bandwidth of 0.926 THz within the desired band (1.88 THz-2.81 THz). The proposed device demonstrates additional benefits which include a thin configuration (λ/7.84) and compact lattice size (λ/10.66), which are significantly better than other recently reported graphene metasurface biosensors. The device provides a sensitivity up to 490 GHz/RIU and a figure of merit (FoM) of 0.377 over a wide span of 0.926 THz within the terahertz gap. The electromagnetic response of this device has been validated via rigorous numerical analyses of simulated outputs as well as by developing a detailed circuit model representation of the same. The device demonstrates angular stability of nearly 40°under oblique incidence of the incident wave. IEEE