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This study compares the serological antibody level post-COVID-19 vaccine among healthy subjects and psychiatric patients on antidepressant therapy. It also examines the difference in antidepressants' side effects experienced by psychiatric patients following the completion of two vaccine doses. A comparative posttest quasi-experimental study was conducted among healthy subjects and psychiatric patients on antidepressant medication in a teaching hospital in Malaysia. Elecsys Anti-SARS-CoV-2 assay was used to detect the antibody titre between weeks 4 and 12 post vaccination. The antidepressant side-effect checklist (ASEC) was used to monitor the occurrence of antidepressant-related side effects pre-and post-vaccination. 24 psychiatric patients and 26 healthy subjects were included. There was no significant difference in the antibody level between the patients (median = 1509 u/ml) and the healthy subjects (median = 995 u/ml). There was no significant worsening in the antidepressant-related side effects. The antibody level post-COVID-19 vaccine did not differ significantly between patients on antidepressant therapy and healthy subjects. Additionally, there was no change in the antidepressant side effects experienced by the patients following the completion of the vaccine.Copyright © 2022, Research Trends (P) LTD.. All rights reserved.
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The adoption of the Internet of Things (IoT) has revolutionized the way the health care industry works. IoT en-abled smart and connected solutions like smart sensors, wearable devices, and smart health monitoring systems are used to unleash the potential growth of the health care industry. IoT based health care solutions are on greater priority among IoT service providers since the disruptions caused by the COVID-19. According to experts, there still exist white spots in research studies on the Internet of Things (IoT) and health care Systems. The study conducted in this paper aims to explore emerging global research trends and topical focus in the field of IoT in health care System. Bibliometric analysis is used to analyze the research articles on 'Internet of Things' and 'Health care Systems' extracted from SCOPUS and WoS database using VoS Viewer tool;the analysis used to assess the growth and research trends of different research fields over a period of time. The parameters considered during analysis include year-wise citations, year-wise publications, keyword clustering analysis, author-wise analysis, country-wise research trends and publication trend over the years. The results showcased that there has been significant change in utilization of IoT in healthcare systems continuously during the period under study conducted. © 2022 IEEE.
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More people have died as a result of disease transmission than have died in genuine wars. Despite being a naturally occurring disease, the great influenza epidemic of 1918 killed 20 million people globally during World War I. However, genetic engineering is employed to develop bioweapon agents. Bioweapons are weapons that involve the deliberate use of chemicals and microorganisms to cause sickness and death in people. Because biological agents are readily available and are easy to carry from one location to another, they are less likely to be detected during routine security checks and they are inexpensive to produce. This weapon is both deadly and appealing to use. This paper discusses various bioweapon systems as well as computer-based techniques used in the medical and agricultural fields to detect and counter any disease spread by bioweapons. A mathematical model (SEIR) for the prediction of infectious diseases has been described and modelled, and it can be used to predict cases in certain areas. © 2023 selection and editorial matter, Preeti Nagrath, Jafar A. Alzubi, Bhawna Singla, Joel J. P. C. Rodrigues and A. K. Verma;individual chapters, the contributors.
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Novel Coronavirus (COVID-19) globally affects the people's health and social life, and it became a challenging task for pharma and research communities. Several medical research or scientific institutions are trying to develop potent antiviral vaccine/drugs against the coronavirus. There are urgent needs to explore all the possibilities against the pandemic disease, and, among that, it is well cited in many literature that Ayurveda has an important role since ancient time against many viral diseases. The Ayurvedic medicinal system is mainly based on herbal formulations, which boost the immune system or work synergistically to protect our body against invading harmfull micro-organisms. The herbal medicinal system has identified several herbs used in various home remedies. It is thought to effectively fight corona and improve health immunity;the current chapter describes the therapeutics of plants Phyllanthus emblica, Azadirachta indica, and Swertia chirata in the current scenario against COVID-19. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.
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In this study, four water quality parameters were reviewed at 14 stations of river Ganga in pre-, during and post-lockdown and these parameters were modeled by using different machine learning algorithms. Various mathematical models were used for the computation of water quality parameters in pre-, during and post- lockdown period by using Central Pollution Control Board real-time data. Lockdown resulted in the reduction of Biochemical Oxygen Demand ranging from 55 to 92% with increased concentration of dissolved oxygen at few stations. pH was in range of 6.5-8.5 of during lockdown. Total coliform count declined during lockdown period at some stations. The modeling of oxygen saturation deficit showed supremacy of Thomas Mueller model (R 2 = 0.75) during lockdown over Streeter Phelps (R 2 = 0.57). Polynomial regression and Newton's Divided Difference model predicted possible values of water quality parameters till 30th June, 2020 and 07th August, 2020, respectively. It was found that predicted and real values were close to each other. Genetic algorithm was used to optimize hyperparameters of algorithms like Support Vector Regression and Radical Basis Function Neural Network, which were then employed for prediction of all examined water quality metrics. Computed values from ANN model were found close to the experimental ones (R 2 = 1). Support Vector Regression-Genetic Algorithm Hybrid proved to be very effective for accurate prediction of pH, Biochemical Oxygen Demand, Dissolved Oxygen and Total coliform count during lockdown. Supplementary Information: The online version contains supplementary material available at 10.1007/s13762-022-04423-1.
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Data visualization is a very important step in data analysis as it provides insight into the data in a more effective manner that is interesting, simple, and understandable to every-one without any language barrier. It can also represent a huge amount of data in a small space very easily. In the previous two years, the whole world has suffered from a very terrifying nightmare known as COVID-19. Known to be starting from the country of China, the pandemic affected not only the health and well-being of mankind, but also had serious impacts on the economies of various countries. Hence, a visualization of the data set of the pandemic might provide beneficial insights for finding a possible solution and can help in overcoming the impacts of the pandemic. Microsoft Power BI is a very famous tool for analyzing data. Power BI provides a different way to visualize the data. This paper has been analyzed the covid-19 data by using Power BI to understand the trends and patterns of the Pandemic. With the help of visualizing the data, it can be represented in stacked column charts, tables, and maps. These three ways are easy and simple to understand the patterns of the pandemic. It also helps to understand how covid impact the world. This research with power BI dashboard by using a dashboard feature that connects different pieces of visual graphs. © 2023 IEEE.
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With India's rapid educational growth towards virtual education, the education system has intensified. India has gone through critical condition like COVID-19. There is huge increment in the implementation of online learning management system. This helped the educational institutions to manage their education system without being physically present in the institution. This paper is presenting the challenges required by institutions to transform their manual education system into virtual/online education system. The online learning management system has enhanced the way of teaching and learning process of students. This study will tell us about how online LMS has speeding up the quality of education for the On-Campus enrolled students as well as distance learning students also. In general, LMS are built to provide the course material in a static way only. The modern LMS has the ability for the group discussion which is helping the student to achieve the qualities of team-working. © 2022 IEEE.
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Cytokines are immunomodulating agents that act through cell surface receptors. They can be either glycoproteins or peptides. A number of properties have been attributed to cytokines like pleiotropy, redundancy, synergy, antagonism and cascade induction. Cell differentiation, proliferation or activation are the effects of cytokines. They may stimulate the action in their own cell, in a nearby cell or in a distant cell depending on the stimulus. Cytokines are classified based on their structure and function into different types and have a crucial role in defeating diseases. Recombinant cytokines are being produced and are used in the pharmaceutical industry as a drug. Cytokine therapy is a new research approach to treat patients suffering from cancer, covid or other malignancies. © 2023 selection and editorial matter, Indrakant Singh and Poonam Sharma;individual chapters, the contributors.
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Introduction and Objective: Telemedicine is an established modality to deliver health care to patients remotely. Its role in pediatric urology followup among middle-class semi-urban families is unknown. We conducted a prospective observational questionnaire-based study to assess the patient and provider(urologist) satisfaction and feasibility of teleconsultation across different socioeconomic strata in follow-up of paediatric urology patients during the COVID 19 pandemic. Method(s): The guardians of children treated earlier and due for follow-up were explained and the appointment for teleconsultation was fixed using a video conferencing app. After consultation, consenting caregivers were explained about study and the provider survey was filled by consulting urologist, while the patient questionnaire was filled by principal investigator telephonically. Result(s): A total of 77 virtual visits were completed over 10 months. Median age was 8 years(IQR= 4 to 12) and 82% were boys. The clinical conditions were posterior urethral valves(22%), hypospadias(18%), PUJ obstruction(18%), vesicoureteric reflux(12%) and others(30%). Clinicians found that virtual visits were effective(78%) in deliverance of the care equivalent to the inpatient visit. Patients were equally satisfied(75%). Technical difficulties due to internet connectivity were faced in 24 visits(31%). Video clarity and inability to examine were additional limitations faced(23%). Majority(90%) belonged to the middle socioeconomic strata as per modified Kuppuswamy scale. Families were estimated to have saved a mean of 26,934 rupees(SD +- 7998.06) and a median of 7 days(Range 1-15) of travel time. Conclusion(s): Telemedicine has potential for successful follow-up with cost and time savings. With improving internet connectivity, its potential is likely to increase in future.
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In the current situation, modern technologies are one of the pillars not only in education but in the whole education process also. Tendencies to include modern technologies in education have significantly supported the pandemic COVID-19 and the transfer of education to the virtual environment. The pedagogues at all levels of education provide students with material for home studying, hand out homework and share links for more supportive materials. Thanks to possibilities of internet and software are possible to teach online, organize classes, have consultation, parents meeting etc. This article aims to investigate in perspectives of primary schools' teachers and their approach to modern technologies as educating tools. What are their experiences and what technologies (software and hardware) they have to work with? © 2023 American Institute of Physics Inc.. All rights reserved.
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In the era of COVID-19, most of the business declined and a huge loss of jobs due to no demand and automobile sector is not the exception. Nearly 7.5% of India's GDP comes from the car industry, and supply chain is one of the key factors in a firm's overall value creation. The efficient and effective supply chain is dependent on information and communication technologies (ICTs) at present, and hence, it implies that ICT is spine of SCM. The major objective of the study was to draw conclusions on how information and communications technology practices affect supply chain management performance in the Indian auto-sector. The outcomes state that ICT practices have high correlation and direct impact on SCM performance, however, it does not have much impact on operational performance. The research also suggested that better and more effective ICT practices result better supply chain performance. The limitation of the research was the respondents' voluntary cooperation, and the ICT practices are limited to supply chain operational performance in various departments and functions only and not the applications in any vehicles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Background We present a unique case of a female who developed a large pericardial effusion (PEff) from a rare cause. Case A 36-year-old female with recent COVID-19 infection presented with acute dyspnea. She had undergone liposuction, rectus plication and breast augmentation two months ago. Heart rate was 90/min and blood pressure 86/57mmHg. CT angiogram of the chest revealed a massive PEff with tamponade. She had large right-sided pleural effusion also. She underwent ultrasound-guided pericardiocentesis with the removal of 950 milliliters of serosanguineous fluid. Follow-up echocardiogram showed re-accumulation of fluid. Due to the rapid onset of PEff, she underwent a pericardial window and bilateral chest tube placement. Decision-making Pleural and pericardial fluid analysis showed silicone-gel particles (Figure. 1). Pericardial biopsy showed nonspecific chronic inflammation. Autoimmune workup was unremarkable. Elevated ESR and CRP in the presence of embolized gel particles indicated foreign body reaction from silicone embolism. Plastic surgery advised implant removal. Silicone embolism is known to cause silicone thorax, pleural effusions, and anaplastic large cell lymphoma. To our knowledge, this is the first reported case of PEff due to silicone embolism from breast implants. Conclusion Cardiologists should be aware of this rare but serious complication. Silicone embolism should be considered in the differential of PEff in patients with breast implants. [Formula presented]Copyright © 2023 American College of Cardiology Foundation
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Background Anomalous origin of the left coronary artery from the pulmonary artery (ALCAPA) is an extremely rare disorder. Case A 20-year-old, 36-week pregnant female (G1P0) presented with acute shortness of breath, sharp chest pain and fever. She was COVID-19 positive and required BiPAP. Echocardiogram showed 40% EF, dilated LV with global hypokinesis and moderate mitral regurgitation (MR). She was hypotensive and on oxygen despite diuresis, emergent cesarean and COVID-19 treatment. Left heart catheterization showed anomalous takeoff of the left main coronary artery (LCA) from the dilated pulmonary artery (PA) with coronary steal (Figure 1). She had ALCAPA repair with LIMA to LAD bypass grafting. Decision-making Differential diagnoses included peripartum cardiomyopathy, Covid-myocarditis, pulmonary embolism, and spontaneous coronary artery dissection. LHC was performed only when symptoms failed to improve and troponin kept rising. ALCAPA has two major clinical subtypes - Infantile type and adult type. Adult type presents as dyspnea, chest pain, reduced exercise ability, and sudden cardiac death. Despite having good RCA to LCA collaterals, adult patients can still have ongoing ischemia of the LV myocardium, causing ischemic MR, malignant ventricular dysrhythmias. Diagnosis was delayed due to pregnancy and COVID-19 infection. Conclusion ALCAPA is a lethal coronary disorder. Elevated troponin and dilated cardiomyopathy with acute MR should raise suspicion of ALCAPA in young adults. [Formula presented]Copyright © 2023 American College of Cardiology Foundation
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The imposition of nation-wide lockdowns and sporadic transition to remote work produced unforeseen psychological challenges likely to impact the medium of care and workload of mental health professionals. The present study explored the lived occupational experiences of clinical psychologists, counsellors, and psychotherapists working in the National Health Service (NHS) and private practice in the UK during COVID-19 pandemic. Nineteen professionals (11 employed in the NHS and 8 working in independent settings) were interviewed about their professional experiences during first and second waves of the pandemic. Data were analysed using interpretative phenomenological analysis. Three main themes emerged from the analysis: (i) transition from face to face to online therapy;(ii) novel changes and wellbeing;and (iii) uncertain professional support in uncertain times. The findings suggest that lack of experience in providing online or telephonic psychotherapeutic services from home negatively impacted professionals' physical and psychological health and wellbeing. Thus, to cope with it, they availed psychological and structural support from colleagues, co-workers, clinical supervisors, managers, organisations, and professional bodies. This study adds to the existing body of research on the impact of the pandemic on UK-based mental health professionals and from an applied perspective, it highlights the need for skill-upgradation of professionals. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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The purpose of this paper is to enhance the performance of the virtual assistant. So, what exactly is a virtual assistant. Application software, often called virtual assistants, also known as AI assistants or digital assistants, is software that understands natural language voice commands and can perform tasks on your behalf. What does a virtual assistant do. Virtual assistants can complete practically any specific smartphone or PC activity that you can complete on your own, and the list is continually expanding. Virtual assistants typically do an impressive variety of tasks, including scheduling meetings, delivering messages, and monitoring the weather. Previous virtual assistants, like Google Assistant and Cortana, had limits in that they could only perform searches and were not entirely automated. For instance, these engines do not have the ability to forward and rewind the song in order to maintain the control function of the song;they can only have the module to search for songs and play them. Currently, we are working on a project where we are automating Google, YouTube, and many other new things to improve the functionality of this project. Now, in order to simplify the process, we've added a virtual mouse that can only be used for cursor control and clicking. It receives input from the camera, and our index finger acts as the mouse tip, our middle finger as the right click, and so forth.Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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Background: Chest X-rays are important for tracking the progression of lung abnormalities, particularly in critically ill COVID-19 patients in the intensive care units (ICU). We aimed to assess correlation of chest X-ray findings with the COVID-19 disease severity and outcome. Methods: This prospective observational study was conducted at B & C Teaching Hospital, Birtamode from 15 March to 15 July 2021. All diagnosed COVID-19 patients admitted in the ICU for respiratory distress with oxygen saturation < 90% and evaluated by portable X-rays were enrolled. The radiographic findings were evaluated for the distribution and patterns of affection, and the total severity score was calculated using RALE scales of 0 - 8 and Brixia scales of 0 - 18. The scores were then compared between the expired and improved patients. Results: The age of patients (mean +or- SD) was 48.2 +or- 13.84 years. During the first four days of hospitalization, there was no significant difference in Brixia score (p = 0.793) or RALE score (p = 0.842) between expired and improved patients. The differences in both (Brixia and RALE) scores grew with each passing day (p < 0.05). The Brixia and RALE severity scores had a strong positive correlation at various stages of disease in both expired and improved patients. (r > 0.75, p < 0.001). Conclusion: In resource limited setting, the severity scores (RALE or Brixia) can be used as a quantitative method of the extent of COVID-19 pneumonia, correlating with an increased risk of ICU admission.
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Background: The scientific community has supported the medicinal flora of ancient as well as modern times in extracting chemicals, which holds therapeutic potential. In many previous studies, Amentoflavone discovered as an anti-viral agent, and it is present as a bioactive constituent in many plants of different families like Selaginellaceae, Euphorbiaceae, and Calophyllaceae. Withania somnifera (Ashwagandha) is already considered a significant anti-viral agent in traditional medicine, and it is the main source of Somniferine-A and Withanolide-B. Objective(s): In this study, phytochemicals such as withanolide-b, somniferine-a, stigmasterol, amentoflavone, and chavicine were analyzed to screen protein inhibitors, out of them;such proteins are involved in the internalization and interaction of SARS-CoV-2 with human cytological domains. This will help in developing a checkpoint for SARS-CoV-2 internalization. Method(s): Chemi-informatic tools like basic local alignment search tool (BLAST), AutoDock-vina, SwissADME, MDWeb, Molsoft, ProTox-II, and LigPlot were used to examine the action of pharmacoactive agents against SARS-CoV-2. The tools used in the study were based on the finest algorithms like artificial neural networking, machine learning, and artificial intelligence. Result(s): On the basis of binding energies less than equal to-8.5 kcal/mol, amentoflavone, stigmasterol, and somniferine-A were found to be the most effective against COVID-19 disease as these chemical agents exhibit hydrogen bond interactions and competitively inhibit major proteins (SARS-CoV-2 Spike, Human ACE-2 receptor, Human Furin protease, SARS-CoV-2 RNA binding protein) that are involved in its infection and pathogenesis. Simulation analysis provides more validity to the selection of the drug candidate Amentoflavone. ADMET properties were found to be in the feasible range for putative drug candidates. Conclusion(s): Computational analysis was successfully used for searching pharmacoactive phytochemicals like Amentoflavone, Somniferine-A, and Stigmasterol that can bring control over COVID-19 expansion. This new methodology was found to be efficient, as it reduces monetary expenditures and time consumption. Molecular wet-lab validations will provide approval for finalizing our selected drug model for controlling the COVID-19 pandemic.Copyright © 2022 Bentham Science Publishers.
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The density functional theory calculation has been carried out for the analysis of 5-chlorouracil using DFT/Gaussian 09 with GAR2PED. Recorded experimental spectra for Raman and IR of 5-chlorouracil have been analyzed all fundamental vibrational modes using the outcome results of DFT at 6-311++G** of Gaussian 09 calculations and the GaussView 5.09. To help the analysis of vibrational modes, GAR2PED program has been used in the calculation of PEDs. The charge transfer properties of 5-chlorouracil have been analyzed using HOMO and LUMO level energy analysis. HOMO and LUMO energy gap study supports the charge transfer possibility in molecule. These have been made to study for reactivity and stability of heterocyclic molecules for the analysis of antiviral drugs against the new corona virus: COVID-19. Here, the smaller energy gap of 5-chlorouracil is more responsible for charge transfer interaction in the heterocyclic drug molecules and a reason of more bioactivity. The electron density mapping within molecular electrostatic potential plot and electrostatic potential plotting within iso-surface plot have been evaluated the charge distribution concept in the molecule as the nucleophilic reactions and electrophilic sites. These computations have been used to produce the molecular charges, structure and thermodynamic functions of biomolecule. This study has been made to all internal modes of chloro group substituent at pyrimidine ring of C5 atom. The splitting of frequencies has arisen in the two species for the normal distribution modes.
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Background: At the onset of a pandemic, such as COVID-19, data with proper labeling/attributes corresponding to the new disease might be unavailable or sparse. Machine Learning (ML) models trained with the available data, which is limited in quantity and poor in diversity, will often be biased and inaccurate. At the same time, ML algorithms designed to fight pandemics must have good performance and be developed in a time-sensitive manner. To tackle the challenges of limited data, and label scarcity in the available data, we propose generating conditional synthetic data, to be used alongside real data for developing robust ML models. Methods: We present a hybrid model consisting of a conditional generative flow and a classifier for conditional synthetic data generation. The classifier decouples the feature representation for the condition, which is fed to the flow to extract the local noise. We generate synthetic data by manipulating the local noise with fixed conditional feature representation. We also propose a semi-supervised approach to generate synthetic samples in the absence of labels for a majority of the available data. Results: We performed conditional synthetic generation for chest computed tomography (CT) scans corresponding to normal, COVID-19, and pneumonia afflicted patients. We show that our method significantly outperforms existing models both on qualitative and quantitative performance, and our semi-supervised approach can efficiently synthesize conditional samples under label scarcity. As an example of downstream use of synthetic data, we show improvement in COVID-19 detection from CT scans with conditional synthetic data augmentation.