Development of real-time RT-PCR systems for detection and quantitation of bovine enteric viral pathogens

The enteric viruses in animals are responsible for severe and devastating losses to the livestock owners with a profound negative impact on animal, health, welfare, and productivity. These viruses are usually transmitted via the feco-oral route and primarily infect the digestive tract of the humans, bovines and different mammals as well as birds. Some of the important enteric viruses in ruminants are: Rotavirus A (RVA), Peste des petits virus (PPRV), Norovirus (NV), Bovine corona virus (BoCV) and Bluetongue virus (BTV). In the present study, sensitive, specific and reliable TaqMan probe-based RT-qPCRs were developed and standardized for the rapid detection and quantification of enteric viruses from fecal samples. The assays result in efficient amplification of the RVA, BTV and BoCV RNA with a limit of detection (LoD) of 5, 5 and 4 copies, respectively, which is 1000 times more sensitive than the traditional gel-based RT-PCR. The reproducibility of each assay was satisfactory, thus allowing for a sensitive and accurate measurement of the viral RNA load in clinical samples. In conclusion, real time PCR developed for these viruses are highly specific and sensitive technique for the detection of diarrheic viral pathogens of cattle and buffalo. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Subperiosteal inferior maxillectomy in mucormycosis patients: case series.

OBJECTIVE: Mucormycosis is a rapidly progressive and fulminant fungal infection mainly affecting the nose and paranasal sinuses and often requiring aggressive surgical debridement, which commonly includes inferior maxillectomy. Conventional inferior maxillectomy involves removal of the bony hard palate and its mucoperiosteum. This can lead to formation of an oroantral fistula and thereby increase the morbidity in these patients leading to prolonged rehabilitation. Subperiosteal inferior maxillectomy involves sparing of the uninvolved mucoperiosteum of the hard palate. This flap is used for closure of the oroantral fistula, which preserves the functional capabilities of the patient, such as speech, mastication and deglutination. METHOD: This case series describes the experience of using the technique of mucosa-preserving subperiosteal inferior maxillectomy in five patients with mucormycosis. RESULTS: With the technique used in this study, complete oronasal separation was achieved in all six patients. The overall surgery time was also decreased when compared with free tissue transfer. Patients also did not have to bear the weight of prosthesis. CONCLUSION: Mucoperiosteal palatal flap-preserving subperiosteal inferior maxillectomy is an excellent approach for all patients with mucormycosis and healthy palatal mucosa.

Willingness To Take The COVID-19 Vaccine: Motivator And Barrier Factors Associated With Vaccine Acceptance Decision Among Healthcare Students Of India

Background: Healthcare students are among the group of frontline healthcare providers being exposed to COVID-19. As future healthcare providers, they will be responsible for recommending vaccination to their future patients and entrusted with counseling to their future vaccine-hesitant patients. Thus, it is very important to achieve high COVID-19 vaccination acceptance rates in these groups. This study aims to explore the level of the acceptability of a COVID-19 vaccine among healthcare students in India and determine the motivators and barriers factors that may affect vaccine acceptance decision-making. Method(s): After the second wave of the pandemic in 2021, an online cross-sectional questionnaire survey study was carried out among the intended population in many states of India. Bivariate analysis and multivariable logistic regression models were utilized to describe and formulate the frequency of all the variables, including the sociodemographic characteristics, and the factors associated with vaccine acceptance and hesitancy. Result(s): Among 596 respondents, 89.3% would willing to get accept a COVID-19 vaccine. Urban students were 2.5 times more willing to take vaccines compared to rural students. Motivator factors behind the willingness to get vaccinated were to know someone who had COVID-19 and wanted to protect own selves from COVID-19 (87.1%). Concerns regarding the COVID-19 vaccine's side effects (50%), poor vaccine efficacy (48.4%), unduly rapid vaccine development (39.1%), belief regarding the non-existence of COVID-19 (32%), and insufficient information regarding the COVID-19 vaccine's benefits (28.1%) as some of the possible barrier factors associated with hesitancy. Conclusion(s):The results highlight the need for an evidence-based educational interventional curriculum to provide adequate information regarding the Vaccine's safety/efficacy, promote uptake of the COVID-19 vaccine, and alleviate any fear/disbelief associated with the COVID-19 vaccine. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

A Retrospective Observational Study of Neurological Manifestations in COVID-19 (SON-CoV)

Objectives: Coronavirus disease 2019 (COVID-19) has neurologic manifestations associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to retrospectively analyze SARS COVID-19 patients with neurological manifestations and identify patterns of presentation including the site of neuroaxis involvement, neuroimaging, and associated systemic involvement. Methods and subjects: This retrospective observational study was conducted at two tertiary care hospitals in western Rajasthan. Data on age, sex, presenting symptoms, and comorbidities (hypertension, diabetes, cardiac, cerebrovascular disease, and cancer) were collected from 28th February 2020 to 31st December 2020 through medical records, discharge summaries, and radiological studies. Verbal/written patient consent was obtained due to the prevailing COVID-19 norms at the time of the first wave. Major inclusion criteria were as follows: age >18 years, consent from patient/surrogate, positive RT-PCR report in case of active COVID cases, or positive COVID antibody test in case of post-COVID neurological sequelae. All neurological manifestations were reviewed by at least two neurologists and were divided into central nervous system (CNS) and peripheral nervous system (PNS) manifestations. Systemic features and their temporal relationship with neurological features were recorded. Various other specialized assessments and therapeutic interventions were conducted. Statistical analysis was performed using the SPSS software. A Chi-square test was performed to determine the association between variables. Student's t-test and one-way analysis of variance were used to determine differences in mean values. Statistical significance was set at p < 0.05. Results: The mean age was 57.32 years for the CNS group and 40 years for the PNS group (p = 0.025). Age was significantly lower in the PNS group than in the CNS group (p = 0.025). Anemia, leucocytosis, and elevated serum creatinine were more commonly seen in the CNS group, although the difference was not statistically significant. The most common CNS manifestations were stroke (41.8%), of which ischemic stroke constituted 83% of cases, followed by seizure (22%), encephalopathy (20.9%), headache (15.1%), and vertigo (3.8%). The most common PNS manifestation was neuropathy (57%), which included Guillain-Barré syndrome (GBS), critical illness neuropathy, and autonomic neuropathy. Conclusion: CNS symptoms of COVID-19 are more common than PNS symptoms. Stroke is the most frequent (46%) COVID-CNS symptom, which occurs in people of age above 35 years and is associated with high mortality. © The Author(s). 2022Open Access This article is distributedunder the terms ofthe Creative Commons Attribution 4.0InternationalLicense (https://creativecommons.org/licenses/by-nc/4.0/)

Double Domination and Regular Domination in Intuitionistic Fuzzy Hypergraph

This study investigates the domination, double domination, and regular domination in intuitionistic fuzzy hypergraph (IFHG), which has enormous application in computer science, networking, chemical, and biological engineering. Few properties of double domination and regular domination of IFHG are established. Furthermore, the definitions of complement and independent set of IFHG are given. The relation between the domination of an IFHG and the independent set of its complement was discussed. Moreover, the application of the double domination in the IFHG was illustrated by determining the containment zones for epidemic situations like COVID-19.

Progressive Multifocal Leukoencephalopathy in immunocompetent a case report and review of literature

Objective: NA Background: Progressive multifocal leukoencephalopathy, (PML) a demyelinating disease of the brain, caused by the John Cunningham (JC Virus) is usually seen in patients who are immunocompromised. Here, we describe a case of an immunocompetent patient diagnosed with PML and a comprehensive literature review. Case Description: A 64-year-old Caucasian male presented with acute worsening of progressive neurological decline with difficulty in vision and reading. The patient was diagnosed with Coronavirus disease 2019 (COVID-19). Following COVID-19 infection he started to have difficulty in maintaining balance, poor attention span and expressive aphasia. Based on history, examination, CSF markers, histopathology, and T2/FLAIR MRI Brain at the time of presentation the patient was diagnosed with PML in a setting of no immunosuppression disorder. Results: In our literature review, it was seen that the average age of symptom presentation was 57.5 with predominance in males. Most of the patients presented with progressive neurological deficits with symptomology ranging from mild confusion, aphasia, anxiety to sensory disturbances with numbness, hemiparesis and hemianopsia. Out of the 21 cases, patients responded to mirtazapine and intravenous pulse methylprednisolone (IVMP). The mortality rate was close to 50% with 11 fatal cases and 10 non-fatal cases. None of the cases had any immunosuppressive conditions or underlying HIV, malignancy, solids organ or stem cell transplants and were not on immunosuppressive medications. Conclusions: Our case and literature review demonstrate the possibility that PML may very rarely occur in patients that are immunocompetent. Furthermore, our review showed that patients responded well to mirtazapine and IVMP. In our case, the patient was treated with Pelfilgrastim with encouraging results and could be explored as a possible treatment option. We also want to highlight that mortality rate was lower in this review and was only compared to mortality in PML associated with immunocompromised status.

Demystifying corona virus disease (COVID-19) using graph data science

Data science is emerging as a novel domain in the area of not only computers but also medical, agriculture, machine learning, social networking, and health care. As the data increases every second, the success of any real-world data analytical application majorly depends on the type and efficiency of its storage and management system. In these applications where there is difficulty in organizing the data in structured form materializes the role of Graph databases. Graph databases are well-organized to manage and store the data in the real world. Often, the graph databases have the capability of representing trillions of relationships which exist in any of the web or social networking dataset. The world is suffering from COVID-19 pandemic. Many researchers are working on post lockdown strategies that will control the spread of the coronavirus as well as unlock some of our freedoms. This situation is quite tricky, but data science as technology can probably provide a solution. One of the major objectives of this paper is that how graph database like Neo4j can help us information of policies which leads to achieve social isolation and to provide a solution for contact tracing problems which is a hurdle to social isolation [18]. © 2022 Author(s).

Dilated CNN for Crowd Count

In the current scenario of the COVID-19 pandemic estimating the count of number of people present in public places at a particular time has become a significant task. Crowd count is attracting a lot of researchers from the computer vision and deep learning field. It has been found that to achieve this objective computer vision techniques such as deep learning, machine learning, etc. outperform traditional ways of estimating crowd count that uses handcrafted features such as Histogram of gradients, Haar, Scale Invariant Feature Transform and gives better results with higher accuracy. The paper studies the effect of dilation on convolution layers in estimating the crowd count. We have also done a comparative analysis of the developed model with different dilation rates on the ShanghaiTech dataset (part A and part B). The model is trained with images containing occluded and restricted visibility of heads. The model outputs the result with substantial accuracy in estimating the headcount in images of the dense crowd in a sensibly less amount of time. © 2021 IEEE.

Predicting ischemic stroke in emergency departments: Development and validation of machine learning models

Background: Stroke misdiagnosis is estimated to occur in 9% of all stroke patients and is associated with poor outcomes. We hypothesized that machine learning (ML) could be used to detect ischemic stroke at the point of care in emergency departments (ED). Methods: Clinical data from 13 hospitals of a large health system in Pennsylvania, United States, from September 2003 to May 2019 were used for model development. Data from June 2019 to December 2020 were prospectively collected and divided into pre- and post-COVID cohorts for validation. We simulated three clinical settings by enrollment with different inclusion/exclusion criteria and created two ML pipelines: ML applied to pre-event clinical data, and natural language processing (NLP) with ML applied to clinical notes during triaging. Misdiagnosed stroke in ED was a case study to show the discriminative power. Results: We included a total of 49,155 patient encounters (8,900 consecutive ischemic stroke patients and 40,255 controls). The best model, based on the patient's pre-event information, was XGBoost (AUROC=0.91). Using NLP+ML pipeline, we collected 2,070 notes during the triage process and 9,607 notes (non-stroke) for modeling. For independent validation, we identified 2,989 notes for stroke and 4,303 notes for non-stroke. We identified nine models that reached a balanced performance in terms of AUROC, sensitivity, and specificity. Model performance, in terms of AUROC, ranged from 0.876 to 0.985. Model sensitivity and specificity reached 0.993 and 0.975, respectively. There was no performance difference between models tested on pre- and post-COVID. Three out of four models correctly identified a separate case series of five misdiagnosed strokes. Conclusion: Available clinical information can be used to reduce stroke misdiagnosis in real-time. In addition, this study serves as a foundation for prospective trials to establish how pre-event clinical data and triage information can be used to improve care.

Renal mucormycosis following COVID-19 treatment with immune modulators: A case report

Mucormycosis is an opportunistic fungal infection that occurs primarily in immunocompromised individuals, usually affecting the rhino-orbital areas followed by the lungs. This case report presents renal mucormycosis in a young man after COVID-19 pneumonia that escalates the need for regular follow-up of COVID-19 patients. Post-COVID-19 fungal infections are on a steep rise, and the increased use of steroids and immune modulators for COVID-19-associated immune dysregulation and cytokine syndrome increases the risk among patients treated for COVID-19. © 2022 Tehran University of Medical Sciences.

Guillain-Barre Syndrome Secondary to SARS-CoV-2

Guillain-Barre Syndrome (GBS) is an acute autoimmune disorder that is provoked by a preceding infection. It is characterized by progressive, ascending, symmetrical muscle weakness accompanied by hyporeflexia or areflexia. We describe two cases of GBS associated with COVID-19. 36-year-old Hispanic female presented ten days after diagnosis of COVID-19 with symptoms of headache, bilateral leg and facial weakness, and facial paresthesias for five days. Within 24 hours of admission, she developed areflexia and progressive bulbar and appendicular weakness. Nerve conduction study and electromyography were consistent with demyelinating form of GBS. Due to difficulty with clearing oral secretions, patient was intubated two times during the hospitalization. 79-year-old Caucasian female presented with progressive weakness, weight loss and fevers. She was diagnosed with COVID-19 on the day of admission. She had paralysis of all four extremities with dysphagia and required intubation. She was extubated and re-intubated two more times due to worsening hypoxia and stridor which led to placement of a tracheostomy tube. Both our patients developed features of dysautonomia, including hypotension and tachycardia. Severe respiratory muscle weakness and dysphagia led to recurrent intubations. Their CT head and MRI brains were negative for facial nerve enhancement. Lumbar punctures in both revealed albuminocytologic dissociation. Plasma exchange was initiated in both females immediately after first intubation for total duration of five days. Upon outpatient follow up, they had significant improvement in motor function. Common precipitants of GBS are Campylobacter jejuni, EBV, CMV, HIV and Zika virus. Clearly, GBS is an infrequent complication of COVID-19. It is possible that SARS-CoV-2 evokes an immune response against peripheral nerve components leading to acute polyneuropathy of heterogenous presentation. Typically, demyelinating and axonal forms of GBS have been described. However, in our cases, both had demyelinating features including symmetric weakness with predominant bulbar symptoms of dysphagia and dysphonia. These cases highlight that GBS is a potential neurological complication of COVID-19 that physicians must be aware of. Thorough daily neurological exam is critical, and early recognition of GBS symptoms may prompt regular evaluation of negative inspiratory force and vital capacity. This may lead to early initiation of intravenous immunoglobulin (IVIG) or plasma exchange leading to improvement in motor symptoms thus avoiding ventilatory support. Plasma exchange should be considered as a first line treatment in COVID-19 patients since high concentrations of IVIG can lead to increased blood viscosity in these patients who are already at increased risk for thrombotic complications.

Post-COVID-19 respiratory management: expert panel report

This report is the first expert panel report on the management of post-COVID-19 patients from India. The report contains high risk groups, post-COVID-19 patient management at primary care level, general principles of medical management of post-COVID-19 in primary care settings, management of post-COVID-19 symptoms in primary care settings, recommendations for inclusion and exclusion into the Pulmonary Rehabilitation Programme, post-COVID-19 patient management at tertiary care level, post-COVID-19 complete assessment and management, and respiratory disease-specific conditions requiring expert opinion and further research.

Risk of stroke in hospitalized sars-cov-2 infected patients a multinational population-based study

The goal of this study was to better depict the short-term risk of stroke and its associated factors among SARS-CoV-2 hospitalized patients. Data Source: This multicenter, multinational observational study includes hospitalized SARS-CoV-2 patients from North and South America (United States, Canada, and Brazil), Europe (Greece, Italy, Finland, and Turkey), Asia (Lebanon, Iran, and India), and Oceania (New Zealand). Main Outcomes and Measures: The outcome was the risk of subsequent stroke (ischemic stroke, intracranial hemorrhage, cerebral venous/sinus thrombosis). The counts and clinical characteristics including laboratory findings and imaging of the patients with and without a subsequent stroke were recorded according to a predefined study protocol. Data Extraction and Synthesis: Quality, risk of bias, and heterogeneity assessments were conducted according to ROBINS-E and Cochrane Q-test. The risk of subsequent stroke was estimated through meta-analyses with random effect models. Binary logistic regression was used to determine the associated factors with the outcome measure. The study was reported according to the STROBE, MOOSE, and EQUATOR guidelines. Results: We received data from 18,311 hospitalized SARS-CoV-2 patients from 77 tertiary centers in 46 regions of 11 countries until May 1 , 2020. A total of 17,799 patients were included in metaanalyses. Among them, 156(0.9%) patients had a stroke-123(79%) ischemic stroke, 27(17%) intracerebral/subarachnoid hemorrhage, and 6(4%) cerebral sinus thrombosis. Subsequent stroke risks calculated with meta-analyses, under low to moderate heterogeneity, were 0.5% among all centers in all countries, and 0.7% among countries with higher health expenditures. The need formechanical ventilation (OR: 1.9, 95% CI:1.1-3.5, p = 0.03) and the presence of ischemic heartdisease (OR: 2.5, 95% CI:1.4-4.7, p =0-006) were predictive of stroke. Conclusion and Relevance: The results of this multi-national study on hospitalized patients withSARS-CoV-2 infection indicated an overall stroke risk of 0.5% (pooled risk: 0.9%). The need formechanical ventilation and the history of ischemic heart disease are the independent predictors ofstroke among SARS-CoV-2 patients.

Sars-cov-2 and stroke characteristics a report from the multinational COVID-19 stroke study group

Objective and Design: We conducted a multinational observational study on features of consecutive acute ischemic stroke (AIS), intracranial hemorrhage (ICH), and cerebral venous or sinus thrombosis (CVST) among SARS-CoV-2 infected patients. Main Outcome Measures: We investigated the association of demographics, clinical data, geographical regions, and countries' health expenditure among AIS patients with the risk of large vessel occlusion (LVO), stroke severity as measured by National Institute of Health stroke scale (NIHSS), and stroke subtype as measured by the TOAST criteria. Additionally, we applied unsupervised machine learning algorithms to uncover possible similarities among stroke patients. Results: Among the 136 tertiary centers of 32 countries who participated in this study, 71 centers from 17 countries had at least one eligible stroke patient. Out of 432 patients included, 323(74.8%) had AIS, 91(21.1%) ICH, and 18(4.2%) CVST. Among 23 patients with subarachnoid hemorrhage, 16(69.5%) had no evidence of aneurysm. A total of 183(42.4%) patients were women, 104(24.1%) patients were younger than 55 years, and 105(24.4%) patients had no identifiable vascular risk factors. Among 380 patients who had known interval onset of the SARS-CoV-2 and stroke, 144(37.8%) presented to the hospital with chief complaints of stroke-related symptoms, with asymptomatic or undiagnosed SARS-CoV-2 infection. Among AIS patients 44.5% had LVO;10% had small artery occlusion according to the TOAST criteria. We observed a lower median NIHSS (8[3-17], versus 11[5-17];p=0.02) and higher rate of mechanical thrombectomy (12.4% versus 2%;p<0.001) in countries with middle to high-health expenditure when compared to countries with lower health expenditure. The unsupervised machine learning identified 4 subgroups, with a relativelylarge group with no or limited comorbidities. Conclusions and Relevance: We observed a relatively high number of young, and asymptomaticSARS-CoV-2 infections among stroke patients. Traditional vascular risk factors were absent amonga relatively large cohort of patients. The stroke severity was lower and rate of mechanicalthrombectomy was higher among countries with middle to high-health expenditure.