Mucocutaneous manifestations of COVID-19-associated mucormycosis: A retrospective cross-sectional study.

Background Cutaneous mucormycosis has shown a significant upsurge during the COVID-19 pandemic. Due to the rapid progression and high mortality of cutaneous mucormycosis in this context, it is important to identify it early. However, very few studies report detailed clinical descriptions of cutaneous mucormycosis in COVID-19 patients. Objectives To describe mucocutaneous lesions of COVID-19-associated mucormycosis based on clinical morphology and attempt to correlate them with radiological changes. Methods A retrospective cross-sectional study was conducted at a tertiary care centre from 1st April to 31st July 2021. Eligibility criteria included hospitalised adult patients of COVID-19-associated mucormycosis with mucocutaneous lesions. Results All subjects were recently recovering COVID-19 patients diagnosed with cutaneous mucormycosis. One of fifty-three (2%) patients had primary cutaneous mucormycosis, and all of the rest had secondary cutaneous mucormycosis. Secondary cutaneous mucormycosis lesions presented as cutaneous-abscess in 25/52 (48%), nodulo-pustular lesions in 1/52 (2%), necrotic eschar in 1/52 (2%) and ulcero-necrotic in 1/52 (2%). Mucosal lesions were of three broad sub-types: ulcero-necrotic in 1/52 (2%), pustular in 2/52 (4%) and plaques in 1/52 (2%). Twenty out of fifty-two patients (38%) presented with simultaneous mucosal and cutaneous lesions belonging to the above categories. Magnetic resonance imaging of the face showed variable features of cutaneous and subcutaneous tissue involvement, viz. peripherally enhancing collection in the abscess group, "dot in circle sign" and heterogeneous contrast enhancement in the nodulo-pustular group; and fat stranding with infiltration of subcutaneous tissue in cases with necrotic eschar and ulcero-necrotic lesions. Limitations The morphological variety of cutaneous mucormycosis patients in a single-centre study like ours might not be very precise. Thus, there is a need to conduct multi-centric prospective studies with larger sample sizes in the future to substantiate our morphological and radiological findings. Conclusions COVID-19-associated mucormycosis patients in our study presented with a few specific types of mucocutaneous manifestations, with distinct magnetic resonance imaging findings. If corroborated by larger studies, these observations would be helpful in the early diagnosis of this serious illness.

Healthcare professionals are "corona saviors" not "warriors".

During the coronavirus disease 2019 (COVID-19) pandemic, the role of doctors and healthcare professionals came into highlight as they are at the forefront since the onset of the pandemic, keeping themselves and their families at risk just to treat this disease and save lives. However, healthcare workers are not warriors. Let our healthcare professionals be called as "Corona Saviors" instead of "Corona Warriors" without any prejudice; they are the "Angels of Saviors of Health."

SARS-CoV-2 infection of human-induced pluripotent stem cells-derived lung lineage cells evokes inflammatory and chemosensory responses by targeting mitochondrial pathways.

The COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primarily affects the lung, particularly the proximal airway and distal alveolar cells. NKX2.1+ primordial lung progenitors of the foregut (anterior) endoderm are the developmental precursors to all adult lung epithelial lineages and are postulated to play an important role in viral tropism. Here, we show that SARS-CoV-2 readily infected and replicated in human-induced pluripotent stem cell-derived proximal airway cells, distal alveolar cells, and lung progenitors. In addition to the upregulation of antiviral defense and immune responses, transcriptomics data uncovered a robust epithelial cell-specific response, including perturbation of metabolic processes and disruption in the alveolar maturation program. We also identified spatiotemporal dysregulation of mitochondrial heme oxygenase 1 (HMOX1), which is associated with defense against antioxidant-induced lung injury. Cytokines, such as TNF-α, INF-γ, IL-6, and IL-13, were upregulated in infected cells sparking mitochondrial ROS production and change in electron transport chain complexes. Increased mitochondrial ROS then activated additional proinflammatory cytokines leading to an aberrant cell cycle resulting in apoptosis. Notably, we are the first to report a chemosensory response resulting from SARS-CoV-2 infection similar to that seen in COVID-19 patients. Some of our key findings were validated using COVID-19-affected postmortem lung tissue sections. These results suggest that our in vitro system could serve as a suitable model to investigate the pathogenetic mechanisms of SARS-CoV-2 infection and to discover and test therapeutic drugs against COVID-19 or its consequences.

Sensitivity Enhancement of Dual Gate FET Based Biosensor Using Modulated Dielectric for Covid Detection

This paper presents a dual gate dielectric modulated FET (DGDMFET) biosensor with enhanced sensitivity for covid detection. In earlier literature, the biosensors are operated using the surface interaction with the virus biomolecules that are reflected through a channel or gate. The downside of these types of sensors has limited sensitivity. In this paper, we have considered that the change in the dielectric constant due to virus proteins results in a significant shift in the threshold voltage of FET. Enhancement of sensitivity is done by using the novel dual metal gate arrangement with different work functions (higher at the source end and lower at the drain end) and the chromic oxide (Cr2O3) layer, which is carved out vertically to form nanogap. At the same time, interface charge density is maintained nearly equal to 1.0 × 1011 cm−2 at the Si-SiO2 layer. To demonstrate the proposed biosensor, electrical parameters (electron concentration, surface potential, energy band distribution, and electric field) and the absolute percentage sensitivity of threshold voltage, subthreshold slope, ON current, and transconductance are evaluated and compared with related literature. The ATLAS device simulator is used for the simulation of the proposed device.

Chapter 6 - Modeling of COVID-19 Outbreak in Reference to Physical Parameters

The spread of coronavirus disease 2019 (COVID-19) in various countries varies in different manners, depending on the demographic and climatic conditions. This needs expediting better strategies to combat the novel coronavirus and also the emergence of new viral strains in the future. Our in-depth analysis suggests the spread of COVID-19 cases worldwide, the timeline of spread among most affected countries as of September 3, 2020. Evaluation of the climatic conditions in 2-week interval is carried out. The study recorded most of the countries getting affected by COVID-19 belong to the range of 25–35°C maximum temperature, 20–30°C minimum temperature, and 60%–80% relative humidity. To get a more generalized view on the spread, the study explored the temperature distribution of affected countries and chronicled in both minimum and maximum temperatures so that the number of COVID-19 cases mostly follows a lognormal distribution. In different ranges of relative humidity, not a single distribution is obtained to explain the spread of COVID-19 cases worldwide. A comparison between theoretic and descriptive parameters is also done to support the spread of COVID-19.

Case study of SARS-CoV-2 transmission risk assessment in indoor environments using cloud computing resources (preprint)

Complex flow simulations are conventionally performed on HPC clusters. However, the limited availability of HPC resources and steep learning curve of executing on traditional supercomputer infrastructure has drawn attention towards deploying flow simulation software on the cloud. We showcase how a complex computational framework -- that can evaluate COVID-19 transmission risk in various indoor classroom scenarios -- can be abstracted and deployed on cloud services. The availability of such cloud-based personalized planning tools can enable educational institutions, medical institutions, public sector workers (courthouses, police stations, airports, etc.), and other entities to comprehensively evaluate various in-person interaction scenarios for transmission risk. We deploy the simulation framework on the Azure cloud framework, utilizing the Dendro-kT mesh generation tool and PETSc solvers. The cloud abstraction is provided by RocketML cloud infrastructure. We compare the performance of the cloud machines with state-of-the-art HPC machine TACC Frontera. Our results suggest that cloud-based HPC resources are a viable strategy for a diverse array of end-users to rapidly and efficiently deploy simulation software.

Dynamic data-driven algorithm to predict cumulative COVID-19 infected cases using susceptible-infected-susceptible model

In recent times, researchers have used Susceptible-Infected-Susceptible (SIS) model to understand the spread of the COVID-19 pandemic. The SIS model has two compartments, susceptible and infected. In this model, the interest is to determine the number of infected cases at a given time point. However, it is also essential to know the cumulative number of infected cases at a given time point, which is not directly available from the SIS model's present structure. The objective is to provide a modified SIS model to address that gap.In this work, we propose a modified structure of the SIS model to determine the cumulative number of infected cases at a given time point. We develop a dynamic data-driven algorithm to estimate the model parameters based on an optimally chosen training phase to predict the number of cumulative infected cases.We demonstrate the proposed algorithm's prediction performance using COVID-19 data from Delhi, India's capital city. Considering different time periods, we observed the proposed algorithm’s performance using the modified SIS model is well to predict the cumulative infected cases with two different prediction periods 30 and 40. Our study supports the idea of estimating the modified SIS model's parameters based on the optimal training phase instead of the entire history as the training phase.Here, we have provided a modified SIS model that accounts for deaths due to disease and predicts cumulative infected cases based on an optimally chosen training phase. The proposed estimation process is beneficial when the disease under study changes its spreading pattern over time. We have developed the modified SIS model considering COVID-19 as the disease under focus. However, the model and algorithms can be applied to predict the cumulative cases of other infectious diseases.

Deep Transfer Learning-Based COVID-19 Prediction Using Chest X-Rays

The novel coronavirus disease (COVID-19) is spreading very rapidly across the globe because of its highly contagious nature and is declared as a pandemic by the World Health Organization (WHO). Scientists are endeavouring to ascertain the drugs for its efficacious treatment. Because, until now, no full-proof drug is available to cure this deadly disease. Therefore, identifying COVID-19 positive people and quarantining them can be an effective solution to control its spread. Many machine learning and deep learning techniques are being used quite effectively to classify positive and negative cases. In this work, a deep transfer learning-based model is proposed to classify the COVID-19 cases using chest X-rays or CT scan images of infected persons. The proposed model is based on the ensembling of DenseNet121 and SqueezeNet1.0, which is named as DeQueezeNet. The model can extract the importance of various influential features from the X-ray images, which are effectively used to classify the COVID-19 cases. The performance study of the proposed model depicts its effectiveness in terms of accuracy and precision. A comparative study has also been done with the recently published works, and it is observed that the performance of the proposed model is significantly better.

Flexible strain sensor with high sensitivity, fast response, and good sensing range for wearable applications.

Flexible strain sensors are emerging rapidly and overcoming the drawbacks of traditional strain sensors. However, many flexible sensors failed to balance the sensitivity, response time, and the desired sensing range. This work proposes a novel and cost-effective strain sensor which simultaneously achieved high sensitivity, fast response, and a good sensing range. It illustrates a prototype strain sensor realized with a nanocomposite constituting reduced graphene oxide and palladium as the primary sensing elements. These sensors were fabricated with manual screen-printing technology. The sensor exhibited an outstanding performance for the different strains ranging from 0.1% to 45%. As a result, a substantially high gauge factor around 1523 at a strain of as high as 45% and a rapid response time of 47 ms was obtained. This work demonstrated potential applications like real-time monitoring of pulse and respiration, and other physical movement detection, which become crucial parameters to be measured continuously during the COVID-19 pandemic.

User Perceptions and Experiences of a Handheld 12-Lead Electrocardiographic Device in a Clinical Setting: Usability Evaluation.

BACKGROUND: Cardiac arrhythmias are a leading cause of death. The mainstay method for diagnosing arrhythmias (eg, atrial fibrillation) and cardiac conduction disorders (eg, prolonged corrected QT interval [QTc]) is by using 12-lead electrocardiography (ECG). Handheld 12-lead ECG devices are emerging in the market. In tandem with emerging technology options, evaluations of device usability should go beyond validation of the device in a controlled laboratory setting and assess user perceptions and experiences, which are crucial for successful implementation in clinical practice. OBJECTIVE: This study aimed to evaluate clinician and patient perceptions and experiences, regarding the usability of a handheld 12-lead ECG device compared to a conventional 12-lead ECG machine, and generalizability of this user-centered approach. METHODS: International Organization for Standardization Guidelines on Usability and the Technology Acceptance Model were integrated to form the framework for this study, which was conducted in outpatient clinics and cardiology wards at Westmead Hospital, New South Wales, Australia. Each patient underwent 2 ECGs (1 by each device) in 2 postures (supine and standing) acquired in random sequence. The times taken by clinicians to acquire the first ECG (efficiency) using the devices were analyzed using linear regression. Electrocardiographic parameters (QT interval, QTc interval, heart rate, PR interval, QRS interval) and participant satisfaction surveys were collected. Device reliability was assessed by evaluating the mean difference of QTc measurements within ±15 ms, intraclass correlation coefficient, and level of agreement of the devices in detecting atrial fibrillation and prolonged QTc. Clinicians' perceptions and feedback were assessed with semistructured interviews based on the Technology Acceptance Model. RESULTS: A total of 100 patients (age: mean 57.9 years, SD 15.2; sex: male: n=64, female n=36) and 11 clinicians (experience acquiring ECGs daily or weekly 10/11, 91%) participated, and 783 ECGs were acquired. Mean differences in QTc measurements of both handheld and conventional devices were within ±15 ms with high intraclass correlation coefficients (range 0.90-0.96), and the devices had a good level of agreement in diagnosing atrial fibrillation and prolonged QTc (κ=0.68-0.93). Regardless of device, QTc measurements when patients were standing were longer duration than QTc measurements when patients were supine. Clinicians' ECG acquisition times improved with usage (P<.001). Clinicians reported that device characteristics (small size, light weight, portability, and wireless ECG transmission) were highly desired features. Most clinicians agreed that the handheld device could be used for clinician-led mass screening with enhancement in efficiency by increasing user training. Regardless of device, patients reported that they felt comfortable when they were connected to the ECG devices. CONCLUSIONS: Reliability and usability of the handheld 12-lead ECG device were comparable to those of a conventional ECG machine. The user-centered evaluation approach helped us identify remediable action to improve the efficiency in using the device and identified highly desirable device features that could potentially help mass screening and remote assessment of patients. The approach could be applied to evaluate and better understand the acceptability and usability of new medical devices.

The Rapid Assessment of Aggregated Wastewater Samples for Genomic Surveillance of SARS-CoV-2 on a City-Wide Scale (preprint)

Throughout the course of the ongoing SARS-CoV-2 pandemic there has been a need for approaches that enable rapid monitoring of public health using an unbiased and minimally invasive means. A major way this has been accomplished is through the regular assessment of wastewater samples by qRT-PCR to detect the prevalence of viral nucleic acid with respect to time and location. Further expansion of SARS-CoV-2 wastewater monitoring efforts to include the detection of variants of interest / concern through next-generation sequencing have enhanced the understanding of the SARS-CoV-2 outbreak. In this report we detail the results of a collaborative effort between public health and metropolitan wastewater management authorities and the University of Louisville to monitor the SARS-CoV-2 pandemic through the monitoring of aggregate wastewater samples over a period of 28 weeks. Our data indicates that wastewater monitoring of water quality treatment centers and smaller neighborhood-scale catchment areas is a viable means by which the prevalence and genetic variation of SARS-CoV-2 within a metropolitan community of approximately one million individuals may be monitored. Importantly, these efforts confirm that regional emergence and spread of variants of interest / concern may be detected as readily in aggregate wastewater samples as compared to the individual wastewater sheds.

Scalable adaptive PDE solvers in arbitrary domains (preprint)

Efficiently and accurately simulating partial differential equations (PDEs) in and around arbitrarily defined geometries, especially with high levels of adaptivity, has significant implications for different application domains. A key bottleneck in the above process is the fast construction of a `good' adaptively-refined mesh. In this work, we present an efficient novel octree-based adaptive discretization approach capable of carving out arbitrarily shaped void regions from the parent domain: an essential requirement for fluid simulations around complex objects. Carving out objects produces an $\textit{incomplete}$ octree. We develop efficient top-down and bottom-up traversal methods to perform finite element computations on $\textit{incomplete}$ octrees. We validate the framework by (a) showing appropriate convergence analysis and (b) computing the drag coefficient for flow past a sphere for a wide range of Reynolds numbers ($\mathcal{O}(1-10^6)$) encompassing the drag crisis regime. Finally, we deploy the framework on a realistic geometry on a current project to evaluate COVID-19 transmission risk in classrooms.

TB care for women and Covid-A double health crisis in the offing?

The COVID-19 pandemic and its health, economic and social aftermath has currently overshadowed every other health concern throughout the world. There are numerous ways in which this will impact existing public health issues. In this article we aim to examine and reflect on the interactions between COVID-19 and tuberculosis (TB) another scourge which has long been the world's leading infectious killer. There are potentially grave consequences for existing and undiagnosed TB patients globally, particularly in low and middle income countries like India where TB is endemic and health services poorly equipped. TB control programmes are likely to be strained due to diversion of resources, and an inevitable loss of health system focus. This is likely to lead to a reduction in quality of TB care and worse outcomes. The symptoms of TB and COVID-19 can be similar, for instance symptoms like cough and fever. Not only can this create diagnostic confusion, but it could worsen the stigmatization of TB patients especially in LMICs, given the fear of COVID-19. Women with TB in India are a vulnerable group as gender disparities play a significant role in how men and women access healthcare in the public and private sectors. They are especially likely to suffer as part of the "collateral damage" and also experience the impact of the double stigma disproportionately. In this paper the researchers examine the impact of Covid 19 on women seeking TB care in India.

Covid-19 Pandemic: Resumption of Orthopedic Care and Medical Education.

Covid-19 is a respiratory disease caused by coronavirus 2 (SARS-CoV-2) first identified in Wuhan, China (December 2019). The disease rapidly crossed the barrier of countries, continents and spread globally. Non-pharmaceutical measures such as social distancing, face mask, frequent hand washing and use of sanitizer remained the best available option to prevent the spread of disease. OPD, IPD admissions, elective O. Ts were curtailed. Orthopedic care was only limited to emergency and semi-urgent procedures like necrotizing fasciitis, open fracture, and compartment syndrome. These measures were taken to preserve infrastructure and manpower to manage covid-19 pandemic. The children were thought to have a low susceptibility to covid-19 as compared to an adult. Deferring the patient during pandemic has led to high orthopedic disease burden, morbidity and disease-related sequelae, hence elective care must be resumed with modified hospital infrastructure. Resumption of elective/emergent orthopedic care should be slow, phasic and strategic, much similar to unlocking. Cases must be stratified depending on covid status and severity. Dedicated O.Ts with neutral/negative pressure and HEPA filter for covid positive and suspected patients are to be used. All symptomatic and suspected patients should be investigated for covid-19 by RT-PCR, blood counts and CT scan. Regional anaesthesia should be preferred to General anaesthesia. Power drill/saw/burr/pulse lavage should be minimized to avoid aerosol generation. Postoperatively continuous surveillance and monitoring to be done for covid related symptoms. Medical institutes rapidly shifted to the online mode of education. Blended learning (virtual & physical) and imparting skills have to be continued in post covid phase with equitable distribution of teaching hours to students of different years.

Multidimensional impact of COVID-19 pandemic in India-Challenges and future direction.

Direct impact of COVID-19 pandemic on lives is almost well known to the world with gradual reporting of its various systemic effects from almost every country. But this disease doesn't have direct impacts only, it causes collateral damage along with some hidden effects which may or may not be reported now and many will be come in future. India, a developing country, also got affected during this pandemic and now ranks under five in relation to the number of cases being reported till now. Here in this manuscript, various hidden aspects of COVID-19 has been discussed like issues related to healthcare infrastructure, food insecurities, domestic issues, mental and physical health, effect on education, screen time, and its challenges because of new trend of distant education, human resources, effects on labor class, material management, monetary issues, economic and industrial downfall, etc., along with challenges on both side for the Government as well as general public faced during this pandemic. Manuscript has been structured on the basis of concept and design of authors and various information put here on the basis of practical scenario being seen in the community and from various data published on Government sites, published articles from journal as well as media report.

COVID-19 Outbreak: Neurological Manifestations Beyond Cough and Fever.

COVID-19 is one of the most disastrous respiratory diseases (after the 1918 influenza outbreak) spreading in the community. So far, it has killed 7,37,417 individuals. High variability in the viral genome and its greater ability to spread in the human community are badly affecting the comorbid individuals. Although infected individuals mainly possess respiratory issues, neurological manifestations in these individuals cannot be overlooked. The literature search is based on the recent development in the concerned field. We searched databases like PubMed, Google Scholar, and ScienceDirect using the keywords "COVID-19", "neurological manifestations", "CNS", and "PNS". The major neurological complications observed in these patients are encephalitis, necrotising haemorrhagic encephalopathy, Guillain-Barré Syndrome, smell/taste impairment, epileptic seizures, and abnormal states of consciousness. COVID-19 infection is just more than a cough, fever, and respiratory illness; it can cause indirect neurological complications in infected patients. It is therefore advised to treat and have a careful observation of the COVID-19 patients for neurological manifestations.

Wastewater sample site selection to estimate geographically-resolved community prevalence of COVID-19: A research protocol (preprint)

Background: Wastewater monitoring for virus infections within communities can complement conventional clinical surveillance. Currently, most SARS-CoV-2 testing is performed during clinical encounters with symptomatic individuals, and therefore likely underrepresents actual population prevalence. Randomized testing on a regular basis to estimate population-level infection rates is prohibitively costly and is hampered by a range of barriers associated with participation in clinical research. In comparison, community-level fecal monitoring can be performed through wastewater surveillance and can effectively surveil communities with less temporal lag than other surveillance methods. However, epidemiologically-defined protocols for wastewater sample site selection are lacking. Methods: Herein we describe methods for developing a geographically-resolved population-level wastewater sampling approach in Jefferson County, Kentucky which may have general applicability for cities throughout the United States. This approach was developed by the selection of sampling locations along sewer lines transporting raw wastewater from geographically and demographically distinct areas that correspond with locations where random testing of residents occurs. Conclusions: Development of this protocol for population-level sampling for SARS-CoV-2 prevalence in wastewater can be utilized to inform consistent wastewater monitoring among cities for up-to-date and geographically-resolved information on COVID-19 prevalence within communities. This information could substantially supplement public health surveillance of COVID-19 and thus serve to better guide targeted mitigation strategies throughout the United States.