Cannabis-Induced Catatonia in a 15-Year-Old Male: A Case Report

Introduction: Catatonia is a syndrome of primarily psychomotor disturbances most common in psychiatric mood disorders but that also rarely has been described in association with cannabis use. Case Presentation: A 15-year-old White male presented with left leg weakness, altered mental status, and chest pain, which then progressed to global weakness, minimal speech, and a fixed gaze. After ruling out organic causes of his symptoms, cannabis-induced catatonia was suspected, and the patient responded immediately and completely to lorazepam administration. Discussion(s): Cannabis-induced catatonia has been described in several case reports worldwide, with a wide range and duration of symptoms reported. There is little known about the risk factors, treatment, and prognosis of cannabis-induced catatonia. Conclusion(s): This report emphasizes the importance of clinicians maintaining a high index of suspicion to accurately diagnose and treat cannabis-induced neuropsychiatric conditions, which is especially important as the use of high-potency cannabis products in young people increases.Copyright © 2023, State Medical Society of Wisconsin. All rights reserved.

Ganoderma Lucidum- A Potential Medicinal Mushroom Against MDR Isolates from The Secondary Infections of Covid-19

The severe acute respiratory syndrome produced by COVID-19 is a highly infectious and pathogenic viral infection. Many COVID-19 patients have secondary bacterial infections, which enhance disease and increase death, particularly when requiring invasive mechanical ventilation. One of the most important medicinal mushrooms, Ganoderma lucidum, has been used for food, feed, and medication since the dawn of humanity. The present investigation aims to discover the potential of the medicinal mushroom Ganoderma lucidum inhibited multidrug-resistant isolates from secondary infection of Covid-19 patients. Isolation and identification of urine samples from secondary infection of post-Covid-19 patients and evaluate the antibiotic sensitivity assay, as identification of bioactive compounds, anti-inflammatory and antioxidant activity from Ganoderma lucidum. Totally 6 clinical urine samples were collected from the age group 45 to 60;3 were male, and 3 were female. In total, nine bacteria and 10 fungi were isolated and identified. As antibiotic sensitivity assays of ceftriaxone, fluoroquinolones, azithromycin and amphotericin, nystatin and fluconazole were performed by the disc diffusion method against bacteria and fungi, the zone of inhibition was maximal in Klebsiella pneumoniae and Fusarium oxysporum. The aqueous and ethanolic extracts of Ganoderma lucidum were analyzed for the bioactive compounds, viz., steroids, flavonoids, alkaloids and phenolic compounds. The effect of the anti-inflammatory activity of the aqueous extract was excellent. The activity of the DPPH assay was maximum in aqueous and ethanolic extracts of all concentrations (100 to 500 ml). Antibiotic resistance could probably rise due to the frequent prescription of broad-spectrum empiric antimicrobials to COVID-19 patients. Hence, Ganoderma lucidum can be exploited to prevent secondary infection in COVID-19 patients.

SARS-CoV-2 breakthrough infections during the second wave of COVID-19 at Pune, India.

Breakthrough infections following SARS-CoV-2 vaccination remain the global concern. The current study was conducted during the second wave of COVID-19 (1st March-7th July 2021) in Pune, India, at two tertiary care hospitals. Of the 6,159 patients diagnosed as COVID-19, 372/2,210 (16.8%) were breakthrough infections. Of these, 81.1 and 18.8% received one or two doses of Covishield or Covaxin, respectively. Of note, 30.7% patients were with comorbidities, hypertension being the commonest (12.44%). The majority of infections were mild (81.2%). Forty-three patients with breakthrough infections were hospitalized with severe (n = 27, 62.8%) or moderate (n = 16, 37.2%) disease. The receptor binding domain (RBD) sequences from vaccinated (n = 126) and non-vaccinated (n = 168) samples were used for variant analysis. The delta variant was predominant followed by kappa in both vaccinated and non-vaccinated groups. Viral load (qRT-PCR) was not different among these categories. Full-genome comparisons of sequences in relation to vaccination status did not identify any mutation characteristic of the vaccinated group. Irrespective of the number of doses, neutralizing antibody titers (PRNT50) during the first week of clinical disease were higher in the vaccinated patients than the unvaccinated category. In conclusion, though not completely, SARS-CoV-2 vaccines used for country-wide immunization did reduce disease severity among the individuals without any comorbidity by inducing rapid immune response against distinctly different delta and kappa variants. The utility against emerging variants with further mutations need to be carefully examined.

SARS-CoV-2 breakthrough infections during the second wave of COVID-19 at Pune, India

Breakthrough infections following SARS-CoV-2 vaccination remain the global concern. The current study was conducted during the second wave of COVID-19 (1st March−7th July 2021) in Pune, India, at two tertiary care hospitals. Of the 6,159 patients diagnosed as COVID-19, 372/2,210 (16.8%) were breakthrough infections. Of these, 81.1 and 18.8% received one or two doses of Covishield or Covaxin, respectively. Of note, 30.7% patients were with comorbidities, hypertension being the commonest (12.44%). The majority of infections were mild (81.2%). Forty-three patients with breakthrough infections were hospitalized with severe (n = 27, 62.8%) or moderate (n = 16, 37.2%) disease. The receptor binding domain (RBD) sequences from vaccinated (n = 126) and non-vaccinated (n = 168) samples were used for variant analysis. The delta variant was predominant followed by kappa in both vaccinated and non-vaccinated groups. Viral load (qRT-PCR) was not different among these categories. Full-genome comparisons of sequences in relation to vaccination status did not identify any mutation characteristic of the vaccinated group. Irrespective of the number of doses, neutralizing antibody titers (PRNT50) during the first week of clinical disease were higher in the vaccinated patients than the unvaccinated category. In conclusion, though not completely, SARS-CoV-2 vaccines used for country-wide immunization did reduce disease severity among the individuals without any comorbidity by inducing rapid immune response against distinctly different delta and kappa variants. The utility against emerging variants with further mutations need to be carefully examined.

Mucormycosis diagnosis revisited: Current and emerging diagnostic methodologies for the invasive fungal infection (Review).

Mucormycosis, which is a life threatening condition, is one of the side effects experienced by post-COVID-19 patients. Early identification and timely treatment are essential to stop the dissemination of the disease, since invasive mucormycosis has a very high fatality rate and significant disease dispersion. Conventional diagnostic techniques, including clinical diagnosis, serology, histopathology and radiology, have limitations in diagnosing the disease at an early stage. This warrants the need for advanced diagnostic tools such as nucleic acid diagnostics, advanced serological tests (ELISpot), PCR (pan-Mucorale test) and multiplex PCR. These techniques have been introduced to identify this invasive fungal infection at an incipient stage, thereby helping clinicians to prevent adverse outcomes. The use of biosensors and micro-needle based diagnostic methodologies will pave the way for devising more point-of-care tests that can be employed for the detection of mucormycosis at an incipient stage. The present review discusses the current techniques available and their drawbacks, and the usefulness of advanced diagnostic tools. Furthermore, the possibility of using future diagnostic methods for the diagnosis of mucormycosis is highlighted.

Development of bioreactors: current scenario and future challenges

Bioreactors since their invention have eased the feasibility of lab-scale processes to the industrial-scale level. They have been an integral part of the downstream processes. Apart from the product development, they have also been part of sustainable environmental practices such as reduction of wastage, treatment of waste products, wastewater, detoxification. The chapter focuses on the recent scenario of reactor development in terms of waste management. As the onset of the SARS-CoV2 pandemic has changed the course of action the bioreactors do have a major role to play in the handling of COVID waste as well. © 2022 Elsevier Inc. All rights reserved.

Rationale for anxiety associated with dental visits during the COVID-19 pandemic among the general public - an observational study.

BACKGROUND: The effect of COVID-19 on various facets such as physical, psychological, financial, social, and so on has been investigated extensively. However, the wariness influencing the decision to visit the dentist during this pandemic has received relatively little attention in Indian scenario. The study sought to investigate the general public's anxiety regarding visiting a dentist during the COVID-19 pandemic, including the factors that possibly contribute towards this apprehension among Indian nationals. METHODS: Structured questionnaire based cross sectional observational study. Completed responses were received from 259 individuals. Information was collected on demographic details, medical history, history of COVID-19 infection, history of dental problems, anxiety associated with dental visit and reason for dental visit during the pandemic, whether vaccinated and expecting the dentist to be vaccinated. Apprehension or concerns regarding dental visits were acquired via nine closed-ended questions with dichotomous responses. RESULTS: During the pandemic, 25.9% had dental problems, 24.7% visited the dentist and 81% were anxious about dental visits. 72.6% were concerned about contracting infection from the clinic, 81.5% were concerned about contracting infection in the waiting area, and 87.3% were concerned about whether the clinicians/assistants would meticulously follow standard operating protocols, 88% were concerned about disinfection between patients and 75.7% expressed concern on higher treatment charges due to the pandemic. CONCLUSIONS: The general public is concerned about disease transmission in the dentist's office and increased treatment costs, both of which could have a negative impact on the use of dental services during this COVID-19 pandemic.

A Comparative Study of Students Online Learning During Pandemic Using Machine Learning Model

As we know that COVID-19 Pandemic persists and it is resilient for students to attend classroom due to health concerns. Almost every academic institution has shifted towards an online education system. It is mandatory to encounter problems which are usually faced by students during online education. A survey was conducted to spot whether a student is contented with this new era of online education or not, by foreseeing the complications and outcomes of online education. A questionnaire with variegated sections was shared among students to cover supplementary issues faced by them and a response about the same was received from 263 students in total. Proposed model of classification will acquire data for training from the survey. It will predict the sentiment of students towards online education. Along with the model, the survey data is useful to discover additional problems faced by students and also do the needful in favor of students. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Mental Health Status among the Quarantined Population during COVID-19 Pandemic: A Cross-sectional Study from Western Rajasthan

Introduction: Although isolation and quarantine are important measures to curb the exponential growth of the prevailing Coronavirus disease 2019 (COVID-19) pandemic, but at same time this can impose psychological issues among the affected population and also to their family members. Aims: To evaluate the mental health problems, their severity and associated factors in quarantined population during the COVID-19 pandemic. Materials and Methods: This cross-sectional study was conducted among 207 quarantined subjects at different quarantine centres of Ajmer, associated with JLN Medical College, Ajmer, from August 2020 to October 2020,after getting approval from ethics committee of the centre. All the consenting quarantined subjects who were of age 18 years and above, irrespective of their gender were enrolled in the study. For the assessment of psychiatric morbidity, participants were screened using Mini-International Neuropsychiatric Interview (MINI) 6.0.0. Finally, the relevant psychiatric assessment tools like Hamilton Rating Scale for Depression (HAM-D),Hamilton Anxiety Rating Scale (HAM-A) and Yale-Brown Obsessive Compulsive Scale were applied to assess the severity of the disorders. Pearson correlation analysis was used to evaluate the relationship among various clinical variables.The level of significance was considered at p-value lt;0.05. Results: Majority 85 (41%) subjects belonged to the age group 31-40 years of age. Around 116 (77.3%) participants were male. Around 51 (24.6%) presented moderate depression and 25 (12%) presented with severe depression. Also 182 (87.9%) presented with moderate anxiety. The study showed a statistically significant association between depression/anxiety and substance abuse, insomnia, co-morbidities, suicidal ideation/attempts. Conclusion: The findings of the present study concluded that a significant proportion of the quarantined population suffered from psychological issues. So, the psychological impact of a mandatory quarantine should be weighed more thoughtful and in an evidence based manner.

Digital communication platforms in cardiothoracic surgery during COVID-19 pandemic: keeping us connected or isolated?

During the COVID-19 pandemic, performing a surgeon's duties has become challenging while adhering to social distancing mandates. To aid in the continuity of healthcare services, rapid implementation of digital communication tools became a necessity. This is an account of experiences using digital communication platforms, namely Microsoft Teams and Zoom, for clinical and educative purposes in the field of Cardiothoracic Surgery in the UK. While enabling ongoing virtual clinical meetings, conferences and learning opportunities for residents with little face-to-face contact, are these digital communication platforms keeping us connected or isolated?

Prediction of Data Breaches using Classification Algorithms

Security across network has become a major concern during this Covid-19 scenario. Security threats happens due to variety of reasons like theft of analytical property, software attacks, identity theft, stealing of equipment or information, sabotage, and information extraction. The wrong use of protocols over network also causes security threat. Introduction of data mining techniques in network security field plays a major role with data extraction, data transformation and analysation of the huge amount of data. The various data mining algorithms provides an insight to analyse and predict the data and the threats over the computer networks. This paper focusses on the approaches to predict security threats over networks using various classification algorithms. The four-classification algorithm majorly focussed here is Naive Bayes Classifier, Decision Tree Classifier, K Nearest Neighbours and Logistic Regression. It compares the performance of the above-mentioned classification algorithms to detect the threats.

MLTF: Model less time-series forecasting

Multi-step ahead long term forecasting remains a pertinent challenge in time series literature due to non-stationary behaviour of real-world data. Predominantly most traditional time series models are parametric in nature and they use the predicted values to generate forecast for future time steps. This leads to error accumulation in each step of the forecasting horizon which causes increasingly poorer forecast in long-term. Other than the problem of error accumulation, most parametric algorithms also require significant pre-processing, hyper-parameter tuning, training and post-processing which can often put high computational burden on the system. Therefore, this paper proposes, Model Less Time-series Forecasting (MLTF), a non-parametric approach for forecasting which does not require any pre-processing or traditional training (i.e. Backpropagation). MLTF is a non-parametric method which uses statistical representations such as trend, linearity, entropy etc. to cluster series from a pre-defined repository and the series from same cluster are tagged as similar series. The trajectory of the target series is extracted from these similar series after applying an adaptive re-sampling technique. There is minimal training involved in MLTF, therefore this framework is computationally very efficient. The model-less nature also enables it to not suffer from error accumulation in long-horizon forecast. MLTF is validated empirically with a rich set of experiments involving M1, M3 competition dataset, Electricity, Volatility and COVID-19 data (over 4500 independent uni-variate series of different frequencies i.e. Hourly, Daily, Monthly, Quarterly and Yearly). The experiments demonstrate that, MLTF is significantly faster while being similar (or better) in terms of forecasting accuracy than the state-of-the-art DL methods and other non-parametric time series model. © 2022 Elsevier Inc.

Gastrointestinal Manifestations Of Covid-19 In Icu And Non-Icu Patients: A Multi-Center Cohort Study

Background: Coronavirus disease 2019 (COVID-19) has infected over 62 million people worldwide as of November 28, 2020. Emerging studies have revealed a high prevalence of gastrointestinal (GI) symptoms among patients with COVID-19, and coronavirus particles have been found in their stool. However, there are minimal data regarding the impact of COVID-19 severity on the GI system. In this study, we evaluated GI and hepatobiliary manifestations in a large number of hospitalized patients across the United States (US) with COVID-19 based on admission to the intensive care unit (ICU), a surrogate for COVID-19 severity. Methods: Seven US academic centers ed data from patients who had a positive COVID-19 test and were hospitalized. Demographics, presenting symptoms, clinical, and laboratory data were ed, as were hospitalization outcomes. Patients were stratified According to admission to the ICU (yes/no) during their hospital course. GI and hepatobiliary manifestations and outcomes were compared using the Chi-square test, and parametric laboratory values were compared using Student’s t test. Results: Of a total of 1,896 COVID-19 positive patients, 730 patients (38.5%) were admitted to the ICU (Table 1). ICU admissions were more likely to be male (64.2% vs. 52.1%;p<0.01). The most common presenting symptom was dyspnea in ICU patients (57.8%) versus cough in non-ICU patients (47.9%).The prevalence of patients reporting GI symptoms was similar between ICU and non-ICU patients (20.4% vs 21.1%;p=0.14). Compared with non-ICU patients, ICU patients had a higher prevalence of abnormal serum aspartate aminotransferase (AST) values (16.0% vs. 6.7%;p<0.01) and total bilirubin > 3 mg/dL (3.1% vs. 0.8%;p<0.01) (Table 2). There was not a significant difference in prevalence of abnormal alanine aminotransferase (ALT) values between the two groups (9.6% vs. 7.1%;p=0.13). The peak values of AST, ALT, and total bilirubin among all patients in the cohort were 3384 U/L, 1274 U/L, and 54 mg/dL, respectively. Conclusions: In a large US-based cohort of hospitalized patients with COVID-19, GI symptoms did not differ between ICU and non-ICU patients despite their high prevalence. ICU patients were more likely to have serum liver test abnormalities. In this context, further investigation is needed to clarify whether hepatobiliary dysfunction stems from direct injury from COVID-19 or an indirect effect of ICU-related multi-organ dysfunc-tion. Such insight would help guide future management to reduce the risk of and mitigate hepatic injury in these patients (Table Presented) (Table Presented)

GASTROINTESTINAL MANIFESTATIONS OF COVID-19 ACROSS THE UNITED STATES: A MULTI-CENTER COHORT STUDY

Background: Coronavirus disease 2019 (COVID-19) has infected over 14 million people in the United States (US) as of December 1, 2020. Recent data have shown that COVID-19 strains appear to demonstrate geographic variation, such as Asian strains predominating in the Western US and European strains predominating in the Eastern US. However, the clinical significance of this variation remains unclear. In this large, multi-center cohort study, we evaluated gastrointestinal (GI) manifestations of COVID-19 regionally and throughout the US. Methods: Patients hospitalized with a positive COVID-19 test were identified at seven US academic centers. As a surrogate for differing COVID-19 strains, patients were stratified into regions (West, Midwest, or Northeast) depending on hospital location. Demographics, presenting symptoms, laboratory data, and hospitalization outcomes were ed. Statistical comparisons were performed with Chi-square and ANOVA tests, as appropriate. Results: A total of 1896 patients were identified (Table 1). Most patients were male (56.8%), and the most prevalent race was Caucasian (40.5%). The mean age was 58.1 years (±19.1), and the mean body mass index (BMI) was 29.9 (±8.4). A third (29.2%) of patients had a known COVID-19 exposure. The mean presenting temperature was 37.3 °C, and dyspnea was the most common presenting symptom (48.2%). GI symptoms were present in 20.3% of the overall cohort (Table 2);diarrhea was most common (12.4%), followed by nausea and/or vomiting (10.3%) and abdominal pain (6.0%). Geographically, GI symptoms were significantly less common in the Western cohort (17.8%) than the Northeastern (25.6%) and Midwestern (26.7%) cohorts. GI complications (GI hemorrhage and pancreatitis) were also significantly less common in the Western cohort (1.5%, 0.2%) than the Northeastern (6.9%, 1.5%) and Midwestern (3.3%, 1.7%) cohorts. The Midwestern cohort had a higher prevalence of moderately elevated serum aspartate aminotransferase (AST;23.5% vs 8.5% in Western and 10.5% in Northeastern cohorts;p<0.01). Compared to the Northeastern and Midwestern cohorts, the Western cohort had a higher prevalence of mildly elevated serum alanine aminotransferase (ALT;20.9% and 20.9% vs 28.5%;p=0.01) and total bilirubin (6.7% and 7.0% vs 11.4%;p=0.03). The presence of GI symptoms was not associated with increased mortality (p=0.15). Conclusions: Although GI manifestations were common among patients hospitalized with COVID-19, there is significant variability in prevalence across the US. GI symptoms and complications were less common in the West than the Northeast or Midwest. Our study highlights notable geographic variations in GI manifestations of COVID-19, prompting the need for further investigation into the mechanisms of these differences. Such insight could identify strategies that mitigate GI complications of COVID-19 infection.(Table presented) Demographic and Clinical Data of Patients with COVID-19 by Geographic Region. (Table presented) Gastrointestinal Manifestations of COVID-19 in Patients by Geographic Region.

Unsupervised and Supervised Learning based Classification Models for Air Pollution Data

As far as, air quality index (AQI) is concerned, the long duration lockdown that was applied in India in year 2020 due to Covid-19 pandemic was very fruitful. The reason being, due to complete ban on the movement of people and automobiles, the air became so pure and clean, and AQI value went much down. The secondary air pollution data of the lockdown duration, for Uttarakhand, is the base of this research work. This work attempts to design unsupervised and supervised classification models to classify the provided data into two classes i.e class 1 ('clean') and class 2 ('hazardous') using MATLAB. The techniques used are FCM clustering and Probabilistic neural network (PNN). Eventually, a comparative study of the performance of both models is performed. © 2021 IEEE.

Study of COVID-19 Infection, its Severity and Outcome in COVID-19 Vaccinated People at Tertiary Health Care Center, North West Rajasthan

OBJECTIVE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of corona virus-induced disease 19 (COVID-19) that was declared as a global pandemic in March 2020 by the world health organization (WHO). Two vaccines were granted for emergency use by the Central Drugs Standard Control Organization (CDSCO) in India, Covishield® (AstraZeneca's vaccine manufactured by Serum Institute of India) and Covaxin® (manufactured by Bharat Biotech Limited). Sputnik - V has been granted EUA in the month of April 2021. The purpose of this study is to determine the association of COVID-19 infection, its severity and outcome in COVID-19 vaccinated people. METHODS: This was a hospital based prospective cohort study done between March to June 2021 at PBM Associated Group of Hospitals (AGH), Bikaner, Raj. Total 1028 COVID suspected cases consulted in COVID OPD or hospitalized under department of medicine, out of which 146 satisfied the inclusion and exclusion criteria, out of these 146, first 100 cases who gave consent for part of study were selected. RESULTS: Among 100 COVID-19 infected cases, 49 received first dose while rest got both doses. After first dose of vaccination 42.86% had mild and 32.65% had severe clinical infection while after both doses 80.39% had mild and 11.76% had severe clinical infection. On evaluation of HRCT Chest, after first dose 8.16% had normal 40.82% were in severe category while those who got both doses it was 52.82% 3.92% respectively. Among 49 who got first dose, 10.20% recovered on just home based treatment without any need of hospitalization, while 89.8% got admitted in dedicated COVID hospital out of which 73.47% got recovered and 16.33% died. Among 51 who got both the doses, 66.67% recovered on just home based treatment, while 33.33% required hospitalization out of which 25.49% got recovered and 7.84% died. CONCLUSION: After 2nd dose of vaccine there is a significant risk reduction in need of hospitalization and getting severe infection and mortality when compared with first dose only. © Journal of the Association of Physicians of India 2011.