Flavonoids as Potential Therapeutics Against Neurodegenerative Disorders: Unlocking the Prospects.

Neurodegeneration, the decline of nerve cells in the brain, is a common feature of neurodegenerative disorders (NDDs). Oxidative stress, a key factor in NDDs such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease can lead to neuronal cell death, mitochondria impairment, excitotoxicity, and Ca2+ stress. Environmental factors compromising stress response lead to cell damage, necessitating novel therapeutics for preventing or treating brain disorders in older individuals and an aging population. Synthetic medications offer symptomatic benefits but can have adverse effects. This research explores the potential of flavonoids derived from plants in treating NDDs. Flavonoids compounds, have been studied for their potential to enter the brain and treat NDDs. These compounds have diverse biological effects and are currently being explored for their potential in the treatment of central nervous system disorders. Flavonoids have various beneficial effects, including antiviral, anti-allergic, antiplatelet, anti-inflammatory, anti-tumor, anti-apoptotic, and antioxidant properties. Their potential to alleviate symptoms of NDDs is significant.

Neuropharmacological potential of honokiol and its derivatives from Chinese herb Magnolia species: understandings from therapeutic viewpoint.

Honokiol is a neolignan biphenol found in aerial parts of the Magnolia plant species. The Magnolia plant species traditionally belong to China and have been used for centuries to treat many pathological conditions. Honokiol mitigates the severity of several pathological conditions and has the potential to work as an anti-inflammatory, anti-angiogenic, anticancer, antioxidant, and neurotherapeutic agent. It has a long history of being employed in the healthcare practices of Southeast Asia, but in recent years, a greater scope of research has been conducted on it. Plenty of experimental evidence suggests it could be beneficial as a neuroprotective bioactive molecule. Honokiol has several pharmacological effects, leading to its exploration as a potential therapy for neurological diseases (NDs), including Alzheimer's disease (AD), Parkinson's disease (PD), cerebral ischemia, anxiety, depression, spinal cord injury, and so on. So, based on the previous experimentation reports, our goal is to discuss the neuroprotective properties of honokiol. Besides, honokiol derivatives have been highlighted recently as possible therapeutic options for NDs. So, this review focuses on honokiol's neurotherapeutic actions and toxicological profile to determine their safety and potential use in neurotherapeutics.

Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach.

Narcissism is a multifaceted construct often linked to pathological conditions whose neural correlates are still poorly understood. Previous studies have reported inconsistent findings related to the neural underpinnings of narcissism, probably due to methodological limitations such as the low number of participants or the use of mass univariate methods. The present study aimed to overcome the previous methodological limitations and to build a predictive model of narcissistic traits based on neural and psychological features. In this respect, two machine learning-based methods (Kernel Ridge Regression and Support Vector Regression) were used to predict narcissistic traits from brain structural organization and from other relevant normal and abnormal personality features. Results showed that a circuit including the lateral and middle frontal gyri, the angular gyrus, Rolandic operculum, and Heschl's gyrus successfully predicted narcissistic personality traits (p < 0.003). Moreover, narcissistic traits were predicted by normal (openness, agreeableness, conscientiousness) and abnormal (borderline, antisocial, insecure, addicted, negativistic, machiavellianism) personality traits. This study is the first to predict narcissistic personality traits via a supervised machine learning approach. As such, these results may expand the possibility of deriving personality traits from neural and psychological features.

A candidate multi-epitope vaccine against Lumpy skin disease.

Lumpy skin disease (LSD) is a fulminant infectious disease that mostly affects cattle and causes considerable economic loss throughout the globe. This study was conducted to develop a new multi-epitope-based vaccine against LSD that can elicit immunological responses using an in silico reverse vaccinology approach. Initially, three antigenic proteins, protein E5, E3 ubiquitin-protein ligase LAP and 62 kDa protein, were manipulated to recognize potential T-cell and B-cell epitopes. To identify superior epitopes, a variety of bioinformatic techniques including antigenicity testing, transmembrane topology screening, allergenicity assessment, conservancy analysis, and toxicity evaluation were used. Finally, three new subunit vaccines (construct V1, V2 and V3) were developed employing the most effective epitopes, suitable adjuvants, pan HLA DR-binding epitope (PADRE) and linkers. Then, based on the antigenicity, solubility, and validation score of the 3D structures, construct V2 was chosen as one of the best candidate vaccines. The results of the molecular dynamic simulation and disulphide engineering indicated that the vaccine (construct V2) was stable. Additionally, the immunological simulation findings supported the vaccine candidate's ability to trigger humoral and cellular immune responses. Further validation of the proposed vaccine candidate may necessitate additional in vitro and in vivo investigations.

Performance evaluation of micro lens arrays: Improvement of light intensity and efficiency of white organic light emitting diodes.

This paper proposes a unique method to improve light intensity and efficiency of white organic light emitting diodes (OLEDs) by engraving micro lens arrays (MLAs) on the outer face of the substrate layer. The addition of MLAs on the substrate layer improves the light intensity and external quantum efficiency (EQE) of the OLEDs. The basic OLED model achieved an EQE of 14.45% for the effective refractive index (ERI) of 1.86. The spherical and elliptical (planoconvex and planoconcave) MLAs were incorporated on the outer face of the substrate layer to increase the EQE of the OLEDs. The maximum EQE of 17.30% was obtained for Convex-1 (elliptical planoconvex) MLA engraved OLED where the ERI was 1.70. In addition, Convex-1 MLA engraved OLED showed an improvement of 3.8 times on the peak electroluminescence (EL) light intensity compared to basic OLED. Therefore, Convex-1 MLA incorporated OLED can be considered as a potential white OLED because of its excellent light distribution and intensity profile.

COVID-19 vaccine hesitancy among the adult population in Bangladesh: A nationwide cross-sectional survey.

INTRODUCTION: Studies related to the COVID-19 vaccine hesitancy are scanty in Bangladesh, despite the growing necessity of understanding the population behavior related to vaccination. Thus, the present study was conducted to assess the prevalence of the COVID-19 vaccine hesitancy and its associated factors in Bangladesh to fill the knowledge gap. METHODS AND MATERIALS: This study adopted a cross-sectional design to collect data from 1497 respondents using online (Google forms) and face-to-face interviews from eight administrative divisions of Bangladesh between 1-7 February 2021. We employed descriptive statistics and multiple logistic regression analysis. RESULTS: The prevalence of vaccine hesitancy was 46.2%. The Muslims (aOR = 1.80, p ≤ 0.01) and the respondents living in the city corporation areas (aOR = 2.14, p ≤0.001) had more hesitancy. There was significant variation in vaccine hesitancy by administrative divisions (geographic regions). Compared to the Sylhet division, the participants from Khulna (aOR = 1.31, p ≤0.001) had higher hesitancy. The vaccine hesitancy tended to decrease with increasing knowledge about the vaccine (aOR = 0.88, p≤0.001) and the vaccination process (aOR = 0.91, p ≤ 0.01). On the other hand, hesitancy increased with the increased negative attitudes towards the vaccine (aOR = 1.17, p≤0.001) and conspiracy beliefs towards the COVID-19 vaccine (aOR = 1.04, p≤0.01). The perceived benefits of COVID-19 vaccination (aOR = 0.85, p≤0.001) were negatively associated with hesitancy, while perceived barriers (aOR = 1.16, p ≤0.001) were positively associated. The participants were more hesitant to accept the vaccine from a specific country of origin (India, USA, Europe). CONCLUSIONS: Our findings warrant that a vigorous behavior change communication campaign should be designed and implemented to demystify negative public attitudes and conspiracy beliefs regarding the COVID-19 Vaccine in Bangladesh. The policymakers should also think about revisiting the policy of the online registration process to receive the COVID-19 vaccine, as online registration is a key structural barrier for many due to the persistent digital divide in the country. Finally, the government should consider the population's preference regarding vaccines' country of manufacture to reduce the COVID-19 vaccine hesitancy.

Health Belief Model, Theory of Planned Behavior, or Psychological Antecedents: What Predicts COVID-19 Vaccine Hesitancy Better Among the Bangladeshi Adults?

This study aimed to determine the prevalence and investigate the constellations of psychological determinants of the COVID-19 vaccine hesitancy among the Bangladeshi adult population utilizing the health belief model-HBM (perceived susceptibility to and severity of COVID-19, perceived benefits of and barriers to COVID-19 vaccination, and cues to action), the theory of planned behavior-TPB (attitude toward COVID-19 vaccine, subjective norm, perceived behavioral control, and anticipated regret), and the 5C psychological antecedents (confidence, constraints, complacency, calculation, and collective responsibility). We compared the predictability of these theoretical frameworks to see which framework explains the highest variance in COVID-19 vaccine hesitancy. This study adopted a cross-sectional research design. We collected data from a nationally representative sample of 1,497 respondents through both online and face-to-face interviews. We employed multiple linear regression analysis to assess the predictability of each model of COVID-19 vaccine hesitancy. We found a 41.1% prevalence of COVID-19 vaccine hesitancy among our study respondents. After controlling the effects of socio-economic, demographic, and other COVID-19 related covariates, we found that the TPB has the highest predictive power (adjusted R 2 = 0.43), followed by the 5C psychological antecedents of vaccination (adjusted R 2 = 0.32) and the HBM (adjusted R 2 = 0.31) in terms of explaining total variance in the COVID-19 vaccine hesitancy among the adults of Bangladesh. This study provides evidence that theoretical frameworks like the HBM, the TPB, and the 5C psychological antecedents can be used to explore the psychological determinants of vaccine hesitancy, where the TPB has the highest predictability. Our findings can be used to design targeted interventions to reduce vaccine hesitancy and increase vaccine uptake to prevent COVID-19.

Do knowledge and attitudes matter for preventive behavioral practices toward the COVID-19? A cross-sectional online survey among the adult population in Bangladesh.

The Government of Bangladesh has adopted several non-therapeutic measures to tackle the pandemic of SARS-CoV-2. However, the curve of COVID-19 positive cases has not significantly flattened yet, as the adoption of preventive measures by the general population is predominantly a behavioral phenomenon that is often influenced by people's knowledge and attitudes. This study aimed to assess the levels of knowledge, attitudes, and preventive behavioral practices toward COVID-19 and their interrelationships among the population of Bangladesh aged 18 years and above. This study adopted a web-based cross-sectional survey design and collected data from 1056 respondents using the online platform Google Form. We employed the independent sample t-test, one-way ANOVA, Pearson's product-moment correlation, and Spearman rank-order correlation to produce the bivariate level statistics. We also run multiple linear and logistic regression models to identify the factors affecting knowledge, attitudes, and preventive behavioral practices toward COVID-19. The respondents had an average knowledge score of 17.29 (Standard Deviation (SD) = 3.30). The average score for attitude scale toward COVID-19 was 13.6 (SD = 3.7). The respondents had excellent preventive behavioral practices toward COVID-19 (mean 7.7, SD = 0.72). However, this study found that knowledge and attitudes did not matter for preventive behavioral practices toward COVID-19. Instead, education appeared as a sole predictor for preventive behavioral practices toward COVID-19; that means preventive behavioral practices toward COVID-19 was lower among the less educated respondents. This study suggests increasing education as a long-term strategy and taking immediate action to increase knowledge and decrease negative attitudes toward COVID-19 through targeted health education initiatives as a short-term strategy.

Population-Level Preparedness About Preventive Practices Against Coronavirus Disease 2019: A Cross-Sectional Study Among Adults in Bangladesh.

This study assessed the preparedness regarding the preventive practices toward the coronavirus disease 2019 (COVID-19) among the adult population in Bangladesh. Data were collected through an online survey with a sample size of 1,056. We constructed four variables (individual, household, economic, and community and social distancing) related to preparedness based on the principal component analysis of eight items. We employed descriptive statistics and multiple linear regression analysis. The results showed that the accuracy rate of the overall preparedness scale was 68.9%. The preparedness level related to economic, individual, household, and community and social distancing was 64.9, 77.1, 50.4, and 83.2%, respectively. However, the economic preparedness significantly varied by sex, education, occupation, attitude, and worries related to COVID-19. Individual preparedness was significantly associated with education, residence, and attitudes. The household preparedness significantly varied by education, residence, and worries, while the respondent's community and social distancing-related preparedness significantly varied by sex, region, residence, and attitude. This study implies the necessity of the coverage of financial schemes for the vulnerable group. Increased coverage of health education regarding personal hygiene targeting the less educated and rural population should be ensured.