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1.
International Journal of System Assurance Engineering and Management ; 13:828-841, 2022.
Article in English | ProQuest Central | ID: covidwho-2048611

ABSTRACT

Traditional statistical as well as artificial intelligence techniques are widely used for stock market forecasting. Due to the nonlinearity in stock data, a model developed using the traditional or a single intelligent technique may not accurately forecast results. Therefore, there is a need to develop a hybridization of intelligent techniques for an effective predictive model. In this study, we propose an intelligent forecasting method based on a hybrid of an Artificial Neural Network (ANN) and a Genetic Algorithm (GA) and uses two US stock market indices, DOW30 and NASDAQ100, for forecasting. The data were partitioned into training, testing, and validation datasets. The model validation was done on the stock data of the COVID-19 period. The experimental findings obtained using the DOW30 and NASDAQ100 reveal that the accuracy of the GA and ANN hybrid model for the DOW30 and NASDAQ100 is greater than that of the single ANN (BPANN) technique, both in the short and long term.

2.
Life (Basel) ; 12(7)2022 Jul 19.
Article in English | MEDLINE | ID: covidwho-1938890

ABSTRACT

The COVID-19 era has prompted several researchers to search for a linkage between COVID-19 and its associated neurological manifestation. Toll-like receptor 4 (TLR-4) acts as one such connecting link. spike protein of SARS-CoV-2 can bind either to ACE-2 receptors or to TLR-4 receptors, leading to aggregation of α-synuclein and neurodegeneration via the activation of various cascades in neurons. Recently, dithymoquinone has been reported as a potent multi-targeting candidate against SARS-CoV-2. Thus, in the present study, dithymoquinone and its six analogues were explored to target 3CLpro (main protease of SARS-CoV-2), TLR4 and PREP (Prolyl Oligopeptidases) by using the molecular docking and dynamics approach. Dithymoquinone (DTQ) analogues were designed in order to investigate the effect of different chemical groups on its bioactivity. It is noteworthy to mention that attention was given to the feasibility of synthesizing these analogues by a simple photo-dimerisation reaction. The DTQ analogue containing the 4-fluoroaniline moiety [Compound (4)] was selected for further analysis by molecular dynamics after screening via docking-interaction analyses. A YASARA structure tool built on the AMBER14 force field was used to analyze the 100 ns trajectory by taking 400 snapshots after every 250 ps. Moreover, RMSD, RoG, potential energy plots were successfully obtained for each interaction. Molecular docking results indicated strong interaction of compound (4) with 3CLpro, TLR4 and PREP with a binding energy of -8.5 kcal/mol, -10.8 kcal/mol and -9.5 kcal/mol, respectively, which is better than other DTQ-analogues and control compounds. In addition, compound (4) did not violate Lipinski's rule and showed no toxicity. Moreover, molecular dynamic analyses revealed that the complex of compound (4) with target proteins was stable during the 100 ns trajectory. Overall, the results predicted that compound (4) could be developed into a potent anti-COVID agent with the ability to mitigate neurological manifestations associated with COVID-19.

3.
Entropy (Basel) ; 24(7)2022 Jun 26.
Article in English | MEDLINE | ID: covidwho-1911248

ABSTRACT

The association of COVID-19 with neurological complications is a well-known fact, and researchers are endeavoring to investigate the mechanistic perspectives behind it. SARS-CoV-2 can bind to Toll-like receptor 4 (TLR-4) that would eventually lead to α-synuclein aggregation in neurons and stimulation of neurodegeneration pathways. Olive leaves have been reported as a promising phytotherapy or co-therapy against COVID-19, and oleuropein is one of the major active components of olive leaves. In the current study, oleuropein was investigated against SARS-CoV-2 target (main protease 3CLpro), TLR-4 and Prolyl Oligopeptidases (POP), to explore oleuropein potency against the neurological complications associated with COVID-19. Docking experiments, docking validation, interaction analysis, and molecular dynamic simulation analysis were performed to provide insight into the binding pattern of oleuropein with the three target proteins. Interaction analysis revealed strong bonding between oleuropein and the active site amino acid residues of the target proteins. Results were further compared with positive control lopinavir (3CLpro), resatorvid (TLR-4), and berberine (POP). Moreover, molecular dynamic simulation was performed using YASARA structure tool, and AMBER14 force field was applied to examine an 100 ns trajectory run. For each target protein-oleuropein complex, RMSD, RoG, and total potential energy were estimated, and 400 snapshots were obtained after each 250 ps. Docking analyses showed binding energy as -7.8, -8.3, and -8.5 kcal/mol for oleuropein-3CLpro, oleuropein-TLR4, and oleuropein-POP interactions, respectively. Importantly, target protein-oleuropein complexes were stable during the 100 ns simulation run. However, an experimental in vitro study of the binding of oleuropein to the purified targets would be necessary to confirm the present study outcomes.

4.
Data Science for COVID-19 ; : 275-295, 2021.
Article in English | EuropePMC | ID: covidwho-1781978

ABSTRACT

COVID-19 is a kind of virus of the Corona family originated from Wuhan, China, and spread over more than 215 countries in the world, more than 2.3 lakhs people died, and more than 32 lakhs are affected globally till date and numbers are continuously increasing. Because of this global pandemic, citizens of the country are in a panic situation. Sentiment Analysis (SA) is a prominent field to analyze data available on social media. This research work explores SA using the Lexicon-based approach to analyze the sentiment of six different countries: India, the USA, Spain, Italy, France, and the UK. Data from March 15 to April 15, 2020 extracted from Twitter and used to identify sentiment as Negative, Neutral, or Positive using Lexicon-based and Valence Aware Dictionary for Sentiment Reasoning (VADER)-based approaches. Empirical results show that negativity exists in almost all the countries because of COVID-19. Out of six countries considered for the SA, the UK has the highest negativity of 23.03%, followed by France with 22.71%, the USA with 22.01%, and India is having negativity of 18.39% using Simple Lexicon-based approach. At the same time, it is 35.92% in France, 35.68% in the UK, and 35.38% in the USA, while India has the least negativity of 31.03% based on the VADER-based approach. Both approaches are almost producing negativity in the same order with slight variations. Furthermore, a comparative detail analysis of India has also been done based on Twitter data. The data collected before and after lockdown using a simple Lexicon-based approach, and it has been observed that negativity is increasing after lockdown and slightly decreased during lockdown 2.0. Overall implication of this research work is that however negativity exists but people are more positive toward panic situation because of COVID-19 and also fighting against COVID-19 with restrictions like lockdown, home isolation, quarantine, limited access of resources, etc.

5.
Med Mycol Case Rep ; 35: 9-14, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1693101

ABSTRACT

We report the first case of Coronavirus Disease 2019 (COVID-19)-associated brain abscess caused by a rare Trichosporon species, T. dohaense. The patient was a known diabetic and had received systemic corticosteroids for the treatment of COVID-19. He underwent craniotomy and evacuation of abscess. The pus aspirate grew a basidiomycetous yeast, morphologically resembling Trichosporon species. The isolate was initially misidentified by VITEK® MS due to lack of mass spectral database of T. dohaense. Accurate identification was achieved by internal transcribed spacer-directed panfungal polymerase chain reaction. The patient had a favorable outcome following surgical intervention and antifungal therapy.

6.
Processes ; 9(10):1814, 2021.
Article in English | MDPI | ID: covidwho-1470946

ABSTRACT

Background: The outbreak of the coronavirus (SARS-CoV-2) has drastically affected the human population and caused enormous economic deprivation. It belongs to the β-coronavirus family and causes various problems such as acute respiratory distress syndrome and has resulted in a global pandemic. Though various medications have been under trial for combating COVID-19, specific medicine for treating COVID-19 is unavailable. Thus, the current situation urgently requires effective treatment modalities. Nigella sativa, a natural herb with reported antiviral activity and various pharmacological properties, has been selected in the present study to identify a therapeutic possibility for treating COVID-19. Methods: The present work aimed to virtually screen the bioactive compounds of N. sativa based on the physicochemical properties and docking approach against two SARS-CoV-2 enzymes responsible for crucial functions: 3CLpro (Main protease) and NSP15 (Nonstructural protein 15 or exonuclease). However, simulation trajectory analyses for 100ns were accomplished by using the YASARA STRUCTURE tool based on the AMBER14 force field with 400 snapshots every 250ps. RMSD and RMSF plots were successfully obtained for each target. Results: The results of molecular docking have shown higher binding energy of dithymoquinone (DTQ), a compound of N. sativa against 3CLpro and Nsp15, i.e., −8.56 kcal/mol and −8.31 kcal/mol, respectively. Further, the dynamic simulation has shown good stability of DTQ against both the targeted enzymes. In addition, physicochemical evaluation and toxicity assessment also revealed that DTQ obeyed the Lipinski rule and did not have any toxic side effects. Importantly, DTQ was much better in every aspect among the 13 N. sativa compounds and 2 control compounds tested. Conclusions: The results predicted that DTQ is a potent therapeutic molecule that could dual-target both 3CLpro and NSP15 for anti-COVID therapy.

7.
Int J Environ Health Res ; 32(8): 1815-1826, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1196926

ABSTRACT

At the end of 2019 and 2020s, a wave of coronavirus disease 19 (COVID-19) epidemics worldwide has catalyzed a new era of 'communicable infectious diseases'. However, the world is not currently prepared to deal with the growing burden of COVID-19, with the unexpected arrival of Hantavirus infection heading to the next several healthcare emergencies in public. Hantavirus is a significant class of zoonotic pathogens of negative-sense single-stranded ribonucleic acid (RNA). Hemorrhagic renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) are the two major clinical manifestations. Till date, there is no effective treatments or vaccines available, public awareness and precautionary measures can help to reduce the spread of hantavirus disease. In this study, we outline the epidemiology, virology, clinical aspects, and existing HFRS and HCPS management approaches. This review will give an understanding of virus-host interactions and will help for the early preparation and effective handling of further outbreaks in an ever-changing environment.


Subject(s)
COVID-19 , Hantavirus Infections , Hantavirus , Hemorrhagic Fever with Renal Syndrome , COVID-19/epidemiology , Disease Outbreaks , Hantavirus/genetics , Hantavirus Infections/epidemiology , Hemorrhagic Fever with Renal Syndrome/epidemiology , Humans
8.
Int J Clin Pract ; 75(6): e14134, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1121139

ABSTRACT

BACKGROUND: The global cases of COVID-19 increasing day by day. On 25 November 2020, a total of 59 850 910 cases reported globally with a 1 411 216 global death. In India, total cases in the country now stand at 91 77 841 including 86 04 955 recoveries and 4 38 667 active cases as on 24 November 2020, as per the data issued by ICMR. A new generation of voice/audio analysis application can tell whether the person is suffering from COVID-19 or not. AIMS: To describe how to established a new generation of voice/audio analysis application to identify the suspected COVID-19 hidden cases in hotspot areas with the help of an audio sample of the general public. MATERIALS & METHODS: The different patents and data available as literature on the internet are evaluated to make a new generation of voice/audio analysis application with the help of an audio sample of the general public. RESULTS: The collection of the audio sample will be done from the already suffered COVID-19 patients in (.Wave files) personally or through phone calls. The audio samples such as the sound of the cough, the pattern of breathing, respiration rate and way of speech will be recorded. The parameters will be evaluated for loudness, articulation, tempo, rhythm, melody and timbre. The analysis and interpretation of the parameters can be made through machine learning and artificial intelligence to detect corona cases with an audio sample. DISCUSSION: The voice/audio application current project can be merged with a mobile App called 'AarogyaSetu' by the Government of India. The project can be implemented in the high-risk area of COVID-19 in the country. CONCLUSION: This new method of detecting cases will decrease the workload in the COVID-19 laboratory.


Subject(s)
COVID-19 Testing , COVID-19 , SARS-CoV-2 , Artificial Intelligence , COVID-19/diagnosis , Humans , India , Respiration , Sound , Speech , Voice
9.
Indian J Otolaryngol Head Neck Surg ; : 1-8, 2021 Jan 03.
Article in English | MEDLINE | ID: covidwho-1012250

ABSTRACT

COVID-19 epidemic has varied spectrum of symptoms. With this study we aim to evaluate prevalence of Olfactory and Gustatory dysfunction in COVID-19 patients. To assess Olfactory and Gustatory dysfunction in COVID-19 Patients in Indian Population. Settings and Design: Prospective observational study. RT-PCR proven COVID-19 patients were enrolled in the study. Detailed history and olfactory function and Taste function were evaluated. Patient with symptoms of olfactory dysfunction were subjected to fill (sQOD-NS questionnaire). Re-evaluation was done weekly till the time of discharge. Analysis was done with Wilcoxon test with help of SPSS software. A total of 152 patients (Male-78, Female-74) completed the study after weekly evaluation. Olfactory and Gustatory dysfunction was seen in 28 (18.41%) and 20 (13.15%). Mean duration of symptoms was 2.4444 ± 0.352 days. Olfactory dysfunction was the first presenting symptom in 11 out of 152 patients (7.23%). Mean QD-NOS score in patients with Anosmia and Hyposmia (28 patients) was 11.4 ± 2.01 and 13.61 ± 2.82 at 1st evaluation, 20.3 ± 1.49 and 20.33 ± 1.57 at 7th day and 21 in both subgroups at 14th day follow up. Dysgeusia was noticed in 20/152 patients (13.15%). Recovery in olfactory dysfunction and Dysgeusia was complete in all patients. Olfactory and gustatory dysfunctions are significant part of clinical spectrum of COVID-19 disease In Indian Population.

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