Anti-aspergillosis and anti-mucormycosis potential of essential oils from two Cymbopogon spp. targeting riboflavin synthesis pathway

Background: Cymbopogon martinii (palmrose essential oil, PEO) and Cymbopogon citratus (lemon grass essential oil, (LEO) are used as complementary and traditional medicine worldwide. PEO and LEO from Cymbopogon genus, contains a diversity of pharmacologically active compounds. Due to the complex nature of essential oils, their antifungal mechanism of action against aspergillosis and mucormycosis is still not completely understood. Purpose: Hence, the present study aimed at determining the chemical profile of each PEO and LEO and performing a molecular docking of two of their components geraniol and geranial against fungal enzymes involved in riboflavin synthesis pathway viz: riboflavin synthase (RS), riboflavin biosynthesis protein RibD domain-containing protein (RibD), and 3,4-dihydroxy-2-butanone 4-phosphate synthase (DBPS) as opposite sites for drug designing against aspergillosis and mucormycosis and in vitro confirmation. Study design and method: Chemical profile of PEO and LEO was performed by GC-FID analysis. For molecular docking, patch-dock tool was conducted. Ligand-enzyme 3-D interactions were also calculated. ADMET properties (absorption, distribution, metabolism, excretion and toxicity) were also calculated. Antifungal activity was evaluated agaist three test pathogens Aspergillus niger, Aspergillus oryzae and Mucor indicus using poisoned food technique. Results: GC-FID showed geraniol/geranial as the major components in PEO/LEO, thus, they were selected for docking analysis. Docking analysis specified active binding of geraniol and geranial to riboflavin synthase (RS), riboflavin biosynthesis protein RibD domain-containing protein (RibD), and 3,4-dihydroxy-2-butanone 4-phosphate synthase (DBPS) fungal enzymes. Wet-lab authentication was achieved by three fungal strains A. niger, A. oryzae and M. indicus. Docking studies revealed that the ligands geraniol/geranial exhibited interactions with RS, RibD, and DBPS fungal enzymes by H- bond and hydrophobic interactions. Geraniol and geranial obeyed LIPINSKY rule, and exhibited adequate bioactivity. Wet lab results indicated that PEO/LEO was able to inhibit fungal growth against test pathogens. Conclusions: These findings confirm the fungicidal properties PEO/LEO essential oils as possible alternatives to synthetic fungicides. © 2023 The Author(s)

Automated Stacking Ensemble Model for Forecasting COVID-19 Cases

COVID-19 is an infectious disease caused by the SARS-Cov2 virus. Multiple variants of COVID-19 such as beta and omicron have spread all over the world that has caused more than six million fatalities till now and it is still not halted. Multiple vaccinations have been already created but are not full-proof solutions for all the existing mutations and also its protection against any upcoming mutations is not known. Therefore, forecasting of COVID-19 cases becomes the most important weapon to avoid the spread of COVID-19 due to any forthcoming mutation. This research presents an automated stacking ensemble method to forecast COVID-19 cases. The proposed method employs multilayer perceptron, long short-term memory, and linear regression together with a genetic algorithm. The purpose of this research is create an automated model to foresee COVID-19 cases so that any impending COVID-19 wave can be discovered at an early stage to prevent it from spreading. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Hybrid CNN-SVM Model for Face Mask Detector to Protect from COVID-19

The 2019 coronavirus outbreak (COVID-19) has had a huge impact on humanity. By May 2021, nearly, 172 million people worldwide were affected by the infectious spread of COVID-19. While the distribution of vaccines has already begun, mass distribution around the world has yet to take place. According to the World Health Organization (WHO), wearing a face mask can significantly reduce the spread of the COVID-19 virus. However, even improper wearing of face mask can prevent the purposes and lead to the spread of the virus. Under the influence of public health and the global economy, an effective Covid-19 pandemic strategy requires a lot of attention of humanity. To prevent the spread of such deadly virus, intelligent techniques are required. In the proposed work, an intelligent face mask detector framework is proposed based on deep learning concept which can classify the person who wear mask from those who are not wearing mask. In the proposed work, a hybrid model of convolution neural network with support vector machine is used for designing the mask detector. The performance of the proposed method is evaluated on real-world masked face recognition dataset (RMFD) and medical mask dataset (MDD). When implemented, it has been found that the proposed method can achieve high accuracy (99.11%). The excellent performance of the proposed model is very suitable for video surveillance equipment also. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Automated Stacking Ensemble Model for Forecasting COVID-19 Cases

COVID-19 is an infectious disease caused by the SARS-Cov2 virus. Multiple variants of COVID-19 such as beta and omicron have spread all over the world that has caused more than six million fatalities till now and it is still not halted. Multiple vaccinations have been already created but are not full-proof solutions for all the existing mutations and also its protection against any upcoming mutations is not known. Therefore, forecasting of COVID-19 cases becomes the most important weapon to avoid the spread of COVID-19 due to any forthcoming mutation. This research presents an automated stacking ensemble method to forecast COVID-19 cases. The proposed method employs multilayer perceptron, long short-term memory, and linear regression together with a genetic algorithm. The purpose of this research is create an automated model to foresee COVID-19 cases so that any impending COVID-19 wave can be discovered at an early stage to prevent it from spreading. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Forecasting of COVID-19 Cases in India Using Machine Learning: A Critical Analysis

COVID-19 is an infectious disease that has spread over the world since the first case was discovered in China in December 2019. Multiple variants of COVID-19 have been discovered in the last two years, indicating that it is highly mutable. The most recent variant is omicron, which has similar transmissibility to the delta variant and so has a significant risk of producing a third wave in India. This study analyzes five distinct time series forecasting models: autoregression (AR), exponential smoothing (ES), multilayer perceptron (MLP), long-short term memory (LSTM), autoregressive integrated moving average (ARIMA), and their hybrid models. The purpose of this research is to find the best machine learning model for forecasting COVID-19 cases, as the number of novel variant omicron cases in India is on the rise. As a result, it is necessary to forecast COVID-19 cases to make appropriate precautionary actions in order to avert the third wave of COVID-19 in India. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

RESPIRATORY RATE – OXYGENATION (ROX) INDEX CORRELATION WITH HIGH-FLOW NASAL CANNULA OUTCOME IN COVID-19 RESPIRATORY FAILURE: A SINGLE CENTER EXPERIENCE

SESSION TITLE: Outcomes Across COVID-19 SESSION TYPE: Rapid Fire Original Inv PRESENTED ON: 10/19/2022 11:15 am - 12:15 pm PURPOSE: The ROX index (Respiratory rate - OXygenation), obtained by the calculation of SpO2/FiO2/respiratory rate (RR), is a tool previously found to predict intubation in patients with acute hypoxic respiratory failure (AHRF). There is variation in the time intervals described from HFNC to ROX index assessment as well as the cutoff value. This study investigates the role of the ROX index from 12 to 72 hours after HFNC initiation to predict intubation or death while on HFNC in patients with COVID-19 AHRF. METHODS: Adult patients (18 years or older) with confirmed nasopharyngeal PCR SARS-CoV-2 infection who received HFNC therapy between March 1 and July 15, 2020, at Monmouth Medical Center were included. 52 patients were available for analysis. Patients were divided into two groups: those able to be weaned to traditional nasal cannula (group one) and those who were intubated or died while on HFNC (group two). RESULTS: Of the 52 patients evaluated, 28 (54%) required intubation or died while on HFNC (Group two). Group two mortality was 53.85% and overall mortality was 42.31%. A Kaplan-Meier analysis comparing patients whose ROX remained above 4.67 (Group A) with those with ROX <= 4.67 (Group B) within the first 12 hours showed that patients in Group B had a significantly shorter time to the event than those in Group A. CONCLUSIONS: Generally, higher ROX index values are associated with a lower risk of intubation on HFNC in AHRF. In this patient sample, any ROX index less than 4.67 at 12 hours or less than 4.04 at 24 hours was associated with an increased risk of eventual intubation or death while on HFNC. Thus, a low or decreasing ROX index may prompt more frequent reassessment and, if accompanied by other evidence of deterioration, may trigger an escalation of care. CLINICAL IMPLICATIONS: This study shows that the ROX index can stratify patients into low or higher risk for deterioration on HFNC among patients with COVID-19 AHRF. This could help optimize the use of critical care services, minimize PPE use, and promote safety for patients and healthcare workers. Future studies may include prospective analysis of the ROX index and exploration of modalities for monitoring patients receiving non-invasive ventilation. DISCLOSURES: No relevant relationships by Reem alhashemi no disclosure on file for Alvin Buemio;No relevant relationships by Kenneth Granet No relevant relationships by Ikwinder Preet Kaur No relevant relationships by Violet Kramer No relevant relationships by Mohsin Mughal No relevant relationships by Chandler Patton

GC-FID based aromatic profiling and molecular docking studies of lemon grass (Cymbopogon citratus L.) essential oil as novel therapeutic for SARS-Cov2 spike protein

SARS-CoV-2 (COVID-19) caused more than 15 % mortality worldwide. Spike (S) protein has recently been regarded as a suitable target for drug design. The present in silico docking study was designed to evaluate the effect of potent bioactive molecule citral present in essential oils of lemon grass plant leaves against Spike (S) protein from SARS-CoV-2. Till date there is no work is undertaken on in-silico analysis of these compounds against Spike (S) protein of SARS-CoV-2. In the present study, GC-FID (gas chromatography with flame-ionization detection) based aroma profile, molecular docking studies were conducted by using Patchdock analysis. Protein Interactions Calculator was used for protein interactions. In-silico absorption, distribution, metabolism, excretion and toxicity (ADMET) profile was also studied. GC-FID revealed citral as major compound in lemon grass oil. The calculated parameters such as docking score indicated effective binding of citral to COVID-19 S-protein. Interactions results indicated that, Spike (S) protein/citral complexes forms hydrophobic interactions. In-silico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies provided guidelines and mechanistic scope for identification of potent anti-COVID 19 drug. Therefore, essential oil from lemon grass may represent potential herbal treatment to act as COVID-19 Spike (S) protein inhibitor. © 2022, Moroccan Institute of Scientific and Technical Information. All rights reserved.

Hybrid CNN-SVM Model for Face Mask Detector to Protect from COVID-19

The 2019 coronavirus outbreak (COVID-19) has had a huge impact on humanity. By May 2021, nearly, 172 million people worldwide were affected by the infectious spread of COVID-19. While the distribution of vaccines has already begun, mass distribution around the world has yet to take place. According to the World Health Organization (WHO), wearing a face mask can significantly reduce the spread of the COVID-19 virus. However, even improper wearing of face mask can prevent the purposes and lead to the spread of the virus. Under the influence of public health and the global economy, an effective Covid-19 pandemic strategy requires a lot of attention of humanity. To prevent the spread of such deadly virus, intelligent techniques are required. In the proposed work, an intelligent face mask detector framework is proposed based on deep learning concept which can classify the person who wear mask from those who are not wearing mask. In the proposed work, a hybrid model of convolution neural network with support vector machine is used for designing the mask detector. The performance of the proposed method is evaluated on real-world masked face recognition dataset (RMFD) and medical mask dataset (MDD). When implemented, it has been found that the proposed method can achieve high accuracy (99.11%). The excellent performance of the proposed model is very suitable for video surveillance equipment also. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Tachyarrhythmias in covid-19 patients admitted to the intensive care unit

Introduction: The SARS-CoV-2 infection has been associated with new-onset arrhythmias. Newonset tachyarrhythmias including atrial fibrillation, atrial flutter, and ventricular tachycardias (VT) have been reported from different retrospective studies. It is proposed that new-onset arrhythmias are likely associated with systemic illness, and not only triggered by SARS-CoV-2 infection. Hypothesis: We hypothesized that patients who were admitted to the ICU/CCU level of care were more likely to have new-onset tachyarrhythmias vs hospitalized patients who were not admitted to the ICU/CCU. Methods: This is a multi-center retrospective study. The RT-PCR confirmed adult COVID-19 patients consecutively admitted from March 1st to April 30, 2020, were included. Demographic characteristics, comorbidities, and the onset of new arrhythmias were manually extracted from EMR. Categorical variables are shown in percentages;continuous variables are shown in mean (SD). Data were extracted manually using the hospital's electronic medical record. Categorical variables were compared using the chi-square test;continuous variables were compared using the t-test (with equal variance assumption). P-value <0.05 was considered significant. Results: A total of 720 patients were admitted to the hospital. Of these, 11% had new-onset tachyarrhythmias. The onset of new tachyarrhythmias was significantly high in patients who were admitted to ICU/CCU vs non-ICU setting (p-value, <0.001). 13% of patients admitted to ICU/CCU developed new-onset atrial fibrillation vs 7% in the non-ICU setting. 1.5% developed new-onset atrial flutter in ICU/CCU setting vs 1% in the non-ICU setting. Incidence of VT and VF were also higher in ICU/CCU settings. Table1 Conclusions: Patients who were hospitalized with COVID-19 and received ICU/CCU level care were more likely to develop new-onset tachyarrhythmias.

Targeting UDP-Glycosyltransferase, Glucosamine-6-Phosphate Synthase and Chitin Synthase by Using Bioactive 1,8 Cineole for "Aspergillosis" Fungal Disease Mutilating COVID-19 Patients: Insights from Molecular Docking, Pharmacokinetics and In-vitro Studies

SARS-CoV-2 (COVID-19)-associated co-infections like "Aspergillosis", has recently baffled the world. Due to its key role in cell wall synthesis, in the present study UDP-glycosyltransferase, glucosamine-6-phosphate synthase and chitin synthase have been chosen as appropriate targets for molecular docking. The objective of the present study was molecular docking of eucalyptus essential oil component 1,8 cineole against cell wall enzymes followed by in vitro validation. For molecular docking, patch-dock web based online tool was used. Ligand-Protein 2D and 3D Interactions were also studied. Drug likeliness, toxicity profile and cancer cell line toxicity were also studied. Molecular docking results indicated that 1,8 cineole form hydrogen bonding and hydrophobic interactions with UDP-glycosyltransferase, glucosamine-6-phosphate synthase and chitin synthase enzymes. 1,8 cineole also depicted drug likeliness by showing compliance with the LIPINSKY rule, sufficient level of bioactivity and cancer cell line toxicity thus signifying its role as a potent anti-fungal drug.

WARD-BASED MEDICAL TEAMS: IMPACT ON THE CARE OF THE OLDER PERSON WARD

Background The COVID-19 pandemic forced healthcare management to make structural adaptations in the interest of infection control. One such adaptation is the introduction of ward-based medical teams. The multidisciplinary team (MDT) is one of the cornerstones of geriatric medicine. Therefore, we aimed to explore the perception of the care of the older person MDT on the introduction of ward-based medical teams. Methods Qualitative data was collected on a geriatric ward in October 2020 via written questionnaire. The questionnaire analysed how the transition to ward based medical teams was perceived in terms of inter-professional collaboration and clinical service delivered to patients. Results There were 14 respondents, 10 of whom were nursing staff (71%). 86% strongly agreed that the medical team was more accessible, with most interactions occurring face-to-face. Patient care and safety was thought to have improved, 79% and 71% of respondents respectively. 93% felt they had a better rapport with the medical team. 71% felt the MDT meeting is more effective, 57% believed the meeting had greater impact on patient care. However, 93% felt there was less workspace. 21% believed there were more daily admissions and 57% felt the majority of patient transfers from other wards were inappropriate. Overall 86% favoured ward-based medical teams, with 57% of staff reporting that the change led to increased personal job satisfaction. Conclusion By increasing the geographic proximity of doctors to other professionals, doctors were more accessible, issues were tackled quicker, and there was less time wasted bleeping medical teams. Overall staff favoured a ward-based system. However, there are challenges implementing this system. Particular attention should be paid to the availability of adequate workspace, including telephones and computers. Ward transfers should be minimized as continuity of care can be compromised. Strategies should be implemented so medical charts are available to the MDT during consultant-led ward rounds.

Facial Mask-related Acne and Acneiform Eruption During the Coronavirus Disease 2019 Pandemic: A Case Series

Use of a facial mask is a necessity during the current pandemic. The associated occlusion with extended daily use can lead to physiological changes in the skin with resultant irritation, itching, and infections. This can lead to exacerbation of pre-existing dermatoses or induction of irritant dermatitis or bacterial folliculitis. We observed several patients with previously controlled acne vulgaris who developed a flare. Also, in those without a history of pre-existing acne, an acneiform eruption was noted. The majority of patients were women who had pre-existing acne and needed to wear a N95 respirator or a surgical mask for several hours a day, every day. A few suggested simple preventative measures provided herein might help this vulnerable population.

IS TRANSAMINITIS AN INDEPENDENT RISK FACTOR FOR ALL-CAUSE MORTALITY IN COVID-19?

Background Elevated transaminases (AST, ALT) have been seen with COVID-19, especially in severely sick patients. It is unclear whether SARS-CoV-2 directly causes hepatic injury. Other reasons can be hepatotoxic drugs (tocilizumab, remdesivir), sepsis, cytokine induced damage and hypoxic liver injury. Liver histopathology reports have shown macrovesicular steatosis, mild acute hepatitis, mild portal inflammation and sinusoidal microthrombi. Viral RNA using PCR of liver tissue was identified in 55% of patients in a study. Association of transaminitis with all-cause mortality in COVID-19 needs further research. Methods In this single center study, adult patients with confirmed SARS-CoV-2 infection by nasopharyngeal RT-PCR who were hospitalized from March 1st to August 20, 2020, were included. Data were manually extracted using the hospital electronic medical record retrospectively after IRB approval. Patients were divided into two cohorts: survivors (n=182) and non survivors (n=41). Categorical variables were compared by conducting a chi-square test or Fisher's exact test while continuous ones were compared by conducting a median two-sample test. Multivariate logistic regression analysis was done including age, gender, baseline and peak transaminases (AST, ALT). Statistical analysis was done with SAS software. Missing values were adjusted using f variance. Results A total of 223 patients were included in the study. Of 233 patients, 182 were discharged alive from the hospital and 41 were non survivors. Median liver function tests (AST, ALT, ALP, Albumin, INR) and inflammatory markers (LDH, CRP, Ferritin, D-dimer) on admission and peak values during hospitalization are presented in table-1. It showed that LDH value varied significantly between two cohorts similar to ferritin and D-dimer. Treatment options like remdisivir and tocilizumab were used more commonly in cohort 2 which could have led to higher peak ALT and AST during hospitalization, however, there was no statistical significance. Further, multivariate analysis (adjusted for age and sex) showed that higher ALT and AST on admission was not associated with higher odds of all cause mortality in hospitalized COVID-19 patients. Conclusion Our data revealed that transaminitis (elevation in ALT and AST) on admission is not an independent risk factor for all cause mortality in COVID-19. (Table presented.)

Impact of the COVID-19 pandemic: The perceptions of educators about change in medical education

Objectives: COVID-19 pandemic has created havoc in every sphere of life and medical education is no exception. To overcome crisis of this pandemic, currently, there is an entire shift in teaching in medical colleges from face-to-face classes to online classes. Virtual teaching requires both technical and pedagogical support and the present study was carried out to assess the perception of medical teachers about this change in medical education. Methods: This analytical, observational, online, and cross-sectional study used newly developed questionnaire that was given to teachers of medical colleges of North India during lockdown period. Answers for the items were read on a five-point Likert-type scale and data was analysed using Descriptive statistics and t-test. Results: A total of 131 participants filled the questionnaire. Out of these 70 (53.4%) were females and 61 (46.6%) were males. Many teachers (33.6%) found online tools to be easier to use and (35.1%) participants were of opinion of possessing sufficient knowledge and skills for conducting online classes but 44.3% of participants want to undergo training for this purpose. Majority of educators (67.2%) did not want to take online classes along with face-to-face classes after COVID pandemic time. Conclusion: Online teaching in medical education is still relatively new but this crisis should be taken as opportunity to explore the potential of online platforms and should enhance technological knowledge for the benefit of future budding doctors.

Homology modeling and molecular docking of natural metabolites from eucalyptus essential oil against sars-cov-2 spike protein

SARS-CoV-2 spreading its tentacles across the world as a major world pandemic. There is a race to develop suitable drug drugs and vaccines for this disease. Due to lack ofdrug drugs s at present, various anti-HIV drug drugs s have been repurposed. Due to its vital role in virus replication, Spike (S) protein has recently been regarded as a suitable target for drug drugs design. With an urgent and key need for safe and effective drugs to combat this disease, we have explored 12 bioactive compounds from eucalyptus oil against Spike (S) protein from SARS-CoV-2. SWISS-MODEL was used for homology modeling. Molecular docking studies were conducted by using Patch dock analysis. Protein Interactions Calculator was used for protein interactions. Pharmacokinetics and Insilico ADMET profile (absorption, distribution, metabolism, excretion and toxicity) was also studied. Docking score showed effective binding of all bioactive molecules especially Toruatone to COVID-19 S-protein. Interactions results indicated that Spike (S) protein / Toruatone complexes forms hydrogen and hydrophobic interactions. Insilico absorption, distribution, metabolism, excretion and toxicity (ADMET) studies provided guidelines and mechanistic scope for identification of potent anti-COVID 19 drugs. This study highlights the potential of existing bioactive components from essential oil from eucalyptus to act as anti-COVID-19drug drugs. © 2021, Moroccan Institute of Scientific and Technical Information. All rights reserved.

Molecular docking and pharmacokinetic screening of eucalyptol (1,8 cineole) from eucalyptus essential oil against SARS-CoV-2

SARS-CoV-2 (COVID-19), member of corona virus family, is a positive single stranded RNA virus. Due to lack of drugs it is spreading its tentacles across the world. Being associated with cough, fever, and respiratory distress, this disease caused more than 15% mortality worldwide. Mpro/3CLpro has recently been regarded as a suitable target for drug design due to its vital role in virus replication. The current study focused on the inhibitory activity of eucalyptol (1,8 cineole), an essential oil component from eucalyptus oil, against Mpro/3CLprofrom SARS-CoV-2. Till date there is no work is undertaken on in-silico analysis of this compound against Mpro/3CLproof SARS-CoV-2. Molecular docking studies were conducted by using 1-click dock tool and Patchdock analysis. In-silico absorption, distribution, metabolism, excretion and toxicity (ADMET) profile were also studied. The calculated parameters such as docking score indicated effective binding of eucalyptol to COVID-19 Mpro protein. Active site prediction revealed the involvement of active site residues in ligand binding. Interactions results indicated that, Mpro/3CLpro/eucalyptol complexes forms hydrophobic interactions. ADMET studies provided guidelines and mechanistic scope for identification of potent anti-COVID 19 drug. Therefore, eucalyptol may represent potential herbal treatment to act as COVID-19 Mpro/3CLproinhibitor, a finding which must be validated in vivo. © 2020 Articles by the authors;SHST, Cluj-Napoca, Romania. All Rights Reserved.