Nanotheranostics to target antibiotic-resistant bacteria: Strategies and applications

Various health agencies, such as the European Medical Agency (EMA), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO), timely cited the upsurge of antibiotic resistance as a severe threat to the public health and global economy. Importantly, there is a rise in nosocomial infections among covid-19 patients and in-hospitalized patients with the delineating disorder. Most of nosocomial infections are related to the bacteria residing in biofilm, which are commonly formed on material surfaces. In biofilms, microcolonies of various bacteria live in syntropy;therefore, their infections require a higher antibiotic dosage or cocktail of broad-spectrum antibiotics, aggravating the severity of antibiotic resistance. Notably, the lack of intrinsic antibacterial properties in commercial-grade materials desires to develop newer functionalized materials to prevent biofilm formation on their surfaces. To devise newer strategies, materials prepared at the nanoscale demonstrated reasonable antibacterial properties or enhanced the activity of antimicrobial agents (that are encapsulated/chemically functionalized onto the material surface). In this manuscript, we compiled such nanosized materials, specifying their role in targeting specific strains of bacteria. We also enlisted the examples of nanomaterials, nanodevice, nanomachines, nano-camouflaging, and nano-antibiotics for bactericidal activity and their possible clinical implications.Copyright © 2023 The Author(s)

Total Stromal Fraction (TSF)-Fortified Adipose Tissue-Derived Stem Cells Source: An Emerging Regenerative Realm Against COVID-19 In-duced Pulmonary Compromise

The inception of the COVID-19 pandemic has jeopardized humanity with markedly dam-pening of worldwide resources. The viral infection may present with varying signs and symptoms, imitating pneumonia and seasonal flu. With a gradual course, this may progress and result in the deadliest state of acute respiratory distress syndrome (ARDS) and acute lung injury (ALI). More-over, following recovery from the severe brunt of COVID-19 infection, interstitial portions of alve-oli have been found to undergo residual scarring and further to have compromised air exchange. Such alterations in the lung microenvironment and associated systemic manifestations have been recognized to occur due to the extensive release of cytokines. The mortality rate increases with advancing age and in individuals with underlying co-morbidity. Presently, there is no availability of specific antiviral therapy or any other definitive modality to counter this progressive worsening. However, we believe principles and advancing cell-based therapy may prove fruitful in subjugating such reported worsening in these patients. This article reviews eminent knowledge and relevant ad-vancements about the amelioration of lung damage due to COVID-19 infection using adipose tis-sue-derived-total stromal fraction (TSF).Copyright © 2022 Bentham Science Publishers.

Validation of an Information Diffusion based Health Social Media on Yoga and Ayurveda

The deadly COVID-19 coupled with other diseases has proven to be the biggest challenge humans have seen in ages. Healthcare systems, even in the most developed countries, have completely shattered during the peak of waves. Thus, leaving millions rendered helpless and alone around the globe. This proves the importance of self-care and immunity to being the best possible way for being healthy. Solutions specific to strengthening immunity are available in the Indian sciences of Yoga and Ayurveda and has been scientifically proven. These have been around in India for ages but there is an immense lack of awareness in India and around the globe regarding that. This review paper aims at filling the lack of awareness by proposing a model and validating it further by collecting and comparing the pre and post-implementation data. © 2022 IEEE.

Identification of Pneumonia in Corona Virus Patient

A novel corona virus is dangerous and life threatening as patient's lungs are affected very severely by pneumonia. When found in x-ray the chest was fully dense and made lungs rubber type. This pneumonia was quite different from normal pneumonia. In Corona virus 19 people's lungs were so much affected that they were unable to breathe and their oxygen level declined very rapidly and the nebulizer didn't work for them as it is more effective in normal pneumonia patients. In this paper we have taken 2000 dataset to study the difference between person suffering from lung disease chest x-ray/ corona virus patient chest x-ray and pneumonia patient chest x-ray by using deep learning. With the help of chest X-ray (CXR) pictures, system categorizes corona virus into pneumonia, non- pneumonia, and healthy images. 1468 CXR pictures were acquired from publicly available datasets, consisting of 222, 683, and 700 CXR images of corona virus pneumonia, non-pneumonia, and healthy samples, respectively. The system used VGG16 model and a mixture of traditional and approaches for data augmentation. The VGG16-based model was compared to other types of models. The Corona Automatic diagnosis x-ray images (CADx) system was built and evaluated. A test set of 192 CXR pictures was used to assess three-category accuracy. This system obtained 83.6 percent of accuracy over chest x-rays to classify corona virus pneumonia, non-pneumonia and healthy patient. The sensitivity was above 95%. © 2022 IEEE.

A systemic review of neurological manifestations of COVID-19 infection

Objective: The purpose of the study is to systematically review literature on the neurological manifestations of COVID-19. Our review aims to inform the physicians treating COVID-19 of the neurological manifestations experienced within these patients. Background: While COVID-19 typically presents as a respiratory disease, the neurological manifestations are not uncommon. Neurological reports of COVID-19 patients described headache, dizziness, hypogeusia, hyposmia, acute cerebrovascular disease, myopathy, neuromuscular disorders, encephalitis, ataxia, delirium, and others. There are also reports of Guillaine Barrè syndrome associated with COVID-19. More data is needed to establish the incidence, outcomes and causal mechanisms between COVID-19 and its neurological sequel. Risk factors that may predispose a person with COVID-19 to neurological manifestations also need to be identified. Design/Methods: A PubMed and Scopus search has been conducted identify published papers for systematic review. Case reports, case series, editorials, reviews, case-control and cohort studies were evaluated, and relevant information was ed. Results: We identified 27 article meeting our criteria in the final analysis which included experimental studies, case reports, series of cases, cohort studies, and systematic reviews. Common reported symptoms included hyposmia, headaches, weakness, altered consciousness. Encephalitis, demyelination, neuropathy, and stroke have been associated with COVID-19. The most frequently reported neurological complication was acute ischemic cerebrovascular accident, followed by Guillain-Barré syndrome, with least common being meningitis and/or encephalitis. Presence of preexisting neurological disorders was associated with increased risk of developing neurological signs and/or syndromes with COVID-19. Conclusions: Considering the possibility of neurological involvement in patients with SARSCoV-2 infection can result in earlier diagnosis and treatment. Neurologic manifestations in COVID-19 should alert physicians and medical practitioners to rule in high-risk patients. Using a global network with standardized protocols and common data elements is critical to facilitate further studies to understand COVID-19 neurological manifestations.

Rapid Forecasting of Pandemic Outbreak Using Machine Learning: The Case of COVID-19

Some huge scope outside impact pandemics has risen in the course of the most recent two decades, including human, natural life, and plant plagues. Authorities face strategy issues that are reliant on deficient information and require sickness gauges. In this manner, there is an earnest need to create models that empower us to outline all accessible information to estimate and screen an advancing pandemic in an ideal way. This chapter targets assessing different models and proposing an early-cautioning AI approach that can conjecture potential flare-ups of ailments. For gauge COVID-19 episodes, the SEIR model, molecule channel calculation and an assortment of pandemic-related datasets are utilized to investigate different models and strategies. In this chapter, various intermediaries have been clarified for the pandemic season prompting comparative conduct of the powerful multiplication number. We found that a solid relationship exists among conferences and analyzed datasets, particularly when considering time based models. Singular parameters gave like distinctive episode seasons esteems, in this way offering an open door for future flare-ups to utilize such data. © 2021 Scrivener Publishing LLC.

Évaluation des performances diagnostiques d'infection à SARS-CoV-2 d'un algorithme utilisant l'analyse de signaux physiologiques à partir d'une montre connectée

Introduction Le diagnostic de l'infection SARS-CoV-2 est basé sur la détection du virus par rt-PCR. Une application à été élaborée qui permet d'aider au diagnostic de la COVID-19 sans prélèvement biologique en utilisant des signaux physiologiques recueillis par une montre connectée et un bref questionnaire sur smartphone. L'intelligence artificielle par deep learning/réseaux de neurones a été utilisée pour produire un algorithme de classification diagnostique de COVID-19. Cette étude a pour but d'évaluer les performance diagnostiques de l'application dans des conditions du diagnostic clinique chez des malades et des soignants français. Matériels et méthodes Etude observationnelle multicentrique portant sur des patients hospitalisés et des soignants chez lesquels un test PCR à la recherche de SARS-CoV-2 doit être réalisé (cas suspect ou contact). L'enregistrement se faisait via une montre jumelée à un smartphone dans un délai de 3 jours du test PCR. Recueil d'information clinique et enregistrement par montre connectée de la fréquence cardiaque, de l'intervalle RR, la conductance galvanique de la peau. Les flux de données étaient synchronisés et fenêtrés. L'analyse des résultats porte sur les sensibilité, spécificité, taux de faux positifs et de faux négatifs de l'application par rapport à la PCR. Un questionnaire téléphonique à 7 et 15 jours a été réalisé pour connaitre l'évolution clinique et les résultats d'éventuelles PCR de contrôle. Résultats D'aout 2020 à Mars 2021, 363 participants (239 patients et 94 soignants) ont été inclus et 305 enregistrements étaient analysables. Le jour de l'enregistrement 167 participants étaient asymptomatiques (46 %). Le suivi complet des participants à J7 et J14 a été réalisé pour 248 participants,162 (65.3 %) avait une PCR- et absence de symptôme (P-S-), neuf (3.6 %) des symptomes et PCR neg (P-S+), 62 (25,4 %) un COVID symptomatique PCR+ (P+S+), et 14 (5.6 %) une PCR+ asymptomatique (P+S-). Les données acquises ont été répartie dans différents set d'analyse. Un Training set (52), un Validation set (17) et un Test set (18). Trois modèles de réseaux de neurones ont été entrainé sur les données acquises. Les capacités diagnostiques de l'application ont été évaluées à partir de deux combinaisons de paramètres acquis par la montre. La classification était correcte avec une efficacité (eff) de 99.1 %,un taux de faux positif (FP) de 3 % et pas de faux négatif (FN) pour la première combinaison et eff=97 %, .FP=0, FN=5 % pour la deuxième. Conclusion Les performance diagnostiques de l'application s'appuyant sur des réseaux de neurones entrainés en condition diagnostique chez des malades et des soignants français imitent très bien les performances des tests PCR. L'utilisation d'outils connectés capturant des signaux physiologiques associés à des analyse d'intelligence artificielle et de réseaux de neurones pourrait permettre de réduire le recours aux tests biologiques en ciblant les patients les plus suscpet d'infdection virale active. Liens d'intérêts déclarés Neu Tiger en tant qu'investigateur

Inclusive Analysis of Covid-19 disease and Vaccination in India

The covid-19 outbreak has appeared to be a threat to mankind for all the countries, especially India. The first wave of this virus arrived in the country in 2020, and due to various control measures taken by the government, the situation was somewhat controllable. Unfortunately, the second wave has brought enormous trouble to the citizens, and even the measures couldn't possibly stop the mess. This study presents a comprehensive analysis of the second wave of corona virus spread in India, along with visualized information about vaccination undertaken by the citizens. The datasets over which the study has been performed are taken from 16 January 2021 to 2nd May 2021. © 2021 IEEE.

Synergism of CD28 Immune Molecule in Late Immunosuppressive Phase of COVID-19: Effectiveness in Vaccinated Individuals

CONTEXT: Lymphopenia has been frequently documented and linked to coronavirus disease 2019 (COVID-19) in a severe acute respiratory syndrome (SARS)-coronavirus 2 (CoV-2) attack. A decrease in the T-lymphocyte count has shown promise as a clinical indicator and predictor of COVID-19 severity. OBJECTIVE: The review intended to examine the relationship of COVID-19 infections in individuals to lost expression of CD28 on naive CD4+/CD8+-mediated, vaccine-specific, neutralizing antibody responses. DESIGN: The research team performed a narrative review by searching eight databases: Medline, Elsevier, Cochrane, PubMed, Google Scholar, Mendeley, and Springer Nature. The search used the following key terms: SARS CoV-2, clinical aspects and pathology of SARS CoV-2, involvement of viral spike (S) protein in SARS CoV-2, immunological changes in COVID-19 infection, basic overview of CD28 immuno-molecule ligand, reduction of vaccine therapeutic efficacy in COVID-19 infection, and immunomodulatory response of lost CD28 ligand. SETTING: This study was done in a Maharishi Arvind College of Pharmacy, Jaipur, India. RESULTS: In COVID-19 patients, particularly those with severe disease, had increased levels of IL-2 or IL-2R. Given IL-2's supportive role in the expansion and differentiation of T cells, the authors exhibiting that lymphopenia, particularly in severe COVID-19, could be attributed to nonfunctional and dysfunctional differentiation of CD4+ and CD8+ T cells as a result of low CD28 immuno-molecule expression on naive T cells. CONCLUSIONS: The literature review found that independent, early immunological prognostic markers for a poor prognosis, in addition to higher levels of IL-6, include a substantial proportion of large inflammatory monocytes and a small proportion of chronic CD28+ CD4+T cells. The current findings suggest that a combination of COVID-19 vaccination with SARS CoV-2-reactive naive T cells with the CD28 immune-molecule may be a viable method for establishing T-cell-based, adaptive cellular immunotherapy against COVID-19 infection. Further research is needed, especially larger studies to confirm the current findings, to improve early clinical treatment.

Pharmacovigilance of COVID-19 vaccines in the context of Nepal: an assessment based on early adverse drug reaction reports

Objective The objective of this study was to assess the ongoing pharmacovigilance of coronavirus disease-19 (COVID-19) vaccines in the Nepalese context based on the available preliminary adverse drug reaction (ADR) reports and suggest approaches for strengthening pharmacovigilance mechanisms. Methods Currently, many COVID-19 vaccines are under advanced development and some have begun to be administered. In Nepal, the vaccination programme was initiated with Oxford/AstraZeneca COVID-19 AZD1222 (Covishield) vaccine on January 27th targeting frontline healthcare professionals, sanitary staff and security workers. Newspaper reports and ADR reports received at a regional pharmacovigilance centre in Nepal were analysed. Nepal initiated a national pharmacovigilance programme 15 years back and has 14 functioning regional pharmacovigilance centres. The authors examine the strengths and challenges facing the current pharmacovigilance system in ensuring the safety of COVID-19 vaccines. Key findings The news coverage has not mentioned any deaths till date with COVID-19 vaccination. Some patients reported vomiting, urticaria and sudden increase in blood pressure. Few people suffered from headache, fever and myalgia after being vaccinated. A vaccine, approved in an accelerated manner may have safety concerns. The vaccine may cause several types of reactions, but serious reactions have not been reported. Occurrence of adverse effects due to the vaccine is being studied. Conclusions Involving key stake holders, training health professionals and strengthening existing reporting procedures are important. Developing a system of reporting and analysing ADRs daily can help generate actionable intelligence to improve the safety of the vaccination programme. Establishing functioning communication channels between regulatory authorities and other stakeholders is crucial.

Predict COVID-19 with Chest X-ray

Covid-19 is an increasingly growing infective virus which really infects humans that interacted with it. Whilst these clinicians have mostly been infected with such a respiratory tract disease whenever they come in contact with both the disease, it was revealed in a clinical trial of COVID-19 treated persons that they had been mostly diagnosed with a respiratory tract infection when they made contact with the disease. A chest x-ray (also recognised as radiography) is a somewhat complicated imaging technique for detecting concerns in the respiratory system. Artificial intelligence is the most widely used accomplished machine learning algorithm for examining a substantial array of chest x-ray images, but it has the capacity to have a significant impact on Covid-19 testing. In this study, we have used PA interpret of x-rays tests both for covid-19 patients and safe individuals. We tested CNN templates and deep learning strategies. To review ResNeXt models and examine their performance in order to ascertain the presentation, 6432 chest x-ray scan specimens were taken from of the Kaggle database. To make no health claims, these researches primarily focus on potential alternative treatments for cluster covid-19 infected patients. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

CovidDeep: SARS-CoV-2/COVID-19 Test Based on Wearable Medical Sensors and Efficient Neural Networks

The novel coronavirus (SARS-CoV-2) has led to a pandemic. The current testing regime based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been unable to keep up with testing demands, and also suffers from a relatively low positive detection rate in the early stages of the resultant COVID-19 disease. Hence, there is a need for an alternative approach for repeated large-scale testing of SARS-CoV-2/COVID-19. The emergence of wearable medical sensors (WMSs) and deep neural networks (DNNs) points to a promising approach to address this challenge. WMSs enable continuous and user-transparent monitoring of physiological signals. However, disease detection based on WMSs/DNNs and their deployment on resource-constrained edge devices remain challenging problems. To address these problems, we propose a framework called CovidDeep that combines efficient DNNs with commercially available WMSs for pervasive testing of the virus and the resultant disease. CovidDeep does not depend on manual feature extraction. It directly operates on WMS data and some easy-to-answer questions in a questionnaire whose answers can be obtained through a smartphone application. We collected data from 87 individuals, spanning three cohorts including healthy, asymptomatic (to detect the virus), and symptomatic (to detect the disease) patients. We trained DNNs on various subsets of the features automatically extracted from six WMS and questionnaire categories to perform ablation studies to determine which subsets are most efficacious in terms of test accuracy for a three-way classification. The highest test accuracy obtained was 98.1%. The models were also shown to perform well on other performance measures, such as false positive rate, false negative rate, and F1 score. We augmented the real training dataset with a synthetic training dataset drawn from the same probability distribution to impose a prior on DNN weights and leveraged a grow-and-prune synthesis paradigm to learn both DNN architecture and weights. This boosted the accuracy of the various DNNs further and simultaneously reduced their size and floating-point operations. This makes the CovidDeep DNNs both accurate and efficient, in terms of memory requirements and computations. The resultant DNNs are embedded in a smartphone application, which has the added benefit of preserving patient privacy. Author

The effectiveness of bains circuit in improving oxygenation and reducing the total oxygen consumption in patients with severe COVID 19 disease

Background: In the wake of the rapid rise in COVID patients in the country, world is experiencing an acute shortage of mechanical ventilators and medical oxygen to an extent that many hypoxic patients are not able to get oxygen support. (1) The need of the hour is a more efficient Oxygen Delivery device which can be easily accessible to most of remote health setups that are devoid of ICU beds or Ventilators. Moreover with the growing Oxygen Crisis, we also need devices that can help in Oxygen conservation. Aim: to study the effectiveness of Bains Circuit in Improving Oxygenation and reducing the total consumption of Oxygen in patients with Severe COVID 19 disease Objective: To compare the spO2, arterial Oxygen and Carbondioxide levels in COVID 19 patients receiving Oxygen via NRBM to those receiving Oxygen via Bains Circuit. To compare the total Oxygen Requirement in patients receiving Oxygen via Non Rebreathing Masks compared with Bains Circuit. Methodology: RCT conducted on patients presenting with severe COVID 19 Disease. The study subjects will be randomly assigned to both control and experimental group. Baseline data (spO2 levels, pAO2 levels) will be collected, the experimental group will be Oxygenated using Bains Circuit and control group w started on NRBM. spO2 and pAO2 levels will be compared between both groups. Also, the total Oxygen consumption by each patient of both groups will be compared.ausing acute shortage of Oxygen, ventilator beds and ICU beds in most parts of India, the use of Bains Circuit, if proven efficient over NRBM can be a major help to most of the rural and low resource setups. It can be a useful device for transportation of severely hypoxic patients to higher DCHCs.