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The in silico method has provided a versatile process of developing lead compounds from a large database in a short duration. Therefore, it is imperative to look for vaccinations and medications that can stop the havoc caused by SARS-CoV-2. The spike protein of SARS-CoV-2 is required for the viral entry into the host cells, hence inhibiting the virus from fusing and infecting the host. This study determined the binding interactions of 36 flavonoids along with two FDA-approved drugs against the spike protein receptor-binding domain of SARS-CoV-2 through molecular docking and molecular dynamics (MD) simulations. In addition, the molecular mechanics generalized Born surface area (MM/GBSA) approach was used to calculate the binding-free energy (BFE). Flavonoids were selected based on their in vitro assays on SARS-CoV and SARS-CoV-2. Our pharmacokinetics study revealed that cyanidin showed good drug-likeness, fulfilled Lipinski’s rule of five, and conferred favorable toxicity parameters. Furthermore, MD simulations showed that cyanidin interacts with spike protein and alters the conformation and binding-free energy suited. Finally, an in vitro assay indicated that about 50% reduction in the binding of hACE2 with S1-RBD in the presence of cyanidin-containing red grapes crude extract was achieved at approximately 1.25 mg/mL. Hence, cyanidin may be a promising adjuvant medication for the SARS-CoV-2 spike protein based on in silico and in vitro research.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, has been a global concern. While there have been some vaccines and drugs, the rapid emergence of variants due to mutations has threatened public health. As the de novo drug development process is expensive and time-consuming, repurposing existing antiviral drugs against SARS-CoV-2 is an alternative and promising approach to mitigate the current situation. Several studies have indicated that some natural products exhibit inhibitory activities against SARS-CoV-2. This study is aimed at analyzing the potential of natural alkaloids, using various computational tools, as drug candidates against SARS-CoV-2. The molecular docking analysis predicted that naturally occurring alkaloids can bind with RNA-dependent RNA-polymerase (RdRP). The QSAR analysis was conducted by using the way2drug/PASS online web resource, and the pharmacokinetics and toxicity properties of these alkaloids were predicted using pkCSM, SwissADME, and ProTox-II webserver. Among the different alkaloids studied, neferine and berbamine were repurposed as potential drug candidates based on their binding affinity and interactions with RdRP. Further, molecular dynamics simulation of 90 ns revealed the conformational stability of the neferine-RdRP complex.

Traditional herbal medicines have been consumed in Nepal and other parts of the eastern hemisphere since ancient times. Many of these plants reportedly have been effective against ailments as well. This study aims to analyze the phytochemical constituents from the extracts of ten such plants and evaluate their antimicrobial, cytotoxicity, and antioxidant properties. In addition, the study aims to study the correlation of cytotoxicity and antioxidant activities with the total phenolic, flavonoid, and tannin contents. The plants investigated were Oroxylum indicum, Kalanchoe pinnata, Phragmites vallatoria, Ehretia acuminata, Cirsium wallichii, Ampelocissus tomentosa, Dichrocephala integrifolia, Boenninghausenia albiflora, Cynoglossum zeylanicum, and Clerodendrum serratum. Phytochemical analyses were performed to evaluate secondary metabolites, such as glycosides, flavonoids, terpenoids, saponins, alkaloids, and fats. The total phenolic contents of the extracts ranged from 14.94 to 229.89 mg GAE/g, the total flavonoid contents varied from 66.67 to 900 mg QE/g, and the total tannin contents were 42 to 168 mg GAE/g. The results of the antioxidant studies showed that the highest antioxidant activity was exhibited by the extract of A. tomentosa (IC50 = 7.89 µg/mL) followed by E. acuminata (IC50 = 24.82 µg/mL) and C. serratum (IC50 = 32.91 µg/mL). The extracts from P. vallatoria and A. tomentosa exhibited substantial antimicrobial activity. The extracts of A. tomentosa and B. albiflora showed lethality against brine shrimp with LC50 values of 33.11 µg/mL.

In recent decades, educational policy researchers have considered critical policy sociology, mostly known as 'policy sociology', as a useful research methodology for analysing educational policies. However, despite its increasing popularity, policy sociology has been a confusing concept hence it is often used interchangeably with other terms such as policy analysis. In the main, there is a dearth of literature outlining its key underlying assumptions and how this methodology helps policy researchers to analyse social, political and economic issues related to educational policy. By reviewing current body of literature in the field, this paper identifies policy sociology as one of the four major traditions in the policy analysis field. The paper presents six key underlying assumptions of policy sociology -- value based study, political study, historical study, multidisciplinary study, assemblage study, and discourse study -- and discusses how researchers have used policy sociology as a research methodology for analysing educational policies.

Atmospheric effects, such as turbulence and background thermal noise, inhibit the propagation of light used in ON–OFF keying (OOK) free-space optical (FSO) communication. Here we present and experimentally validate a convolutional neural network (CNN) to reduce the bit error rate of FSO communication in post-processing that is significantly simpler and cheaper than existing solutions based on advanced optics. Our approach consists of two neural networks, the first determining the presence of bit sequences in thermal noise and turbulence and the second demodulating the bit sequences. All data used for training and testing our network is obtained experimentally by generating OOK bit streams, combining these with thermal light, and passing the resultant light through a turbulent water tank which we have verified mimics turbulence in the air to a high degree of accuracy. Our CNN improves detection accuracy over threshold classification schemes and has the capability to be integrated with current demodulation and error correction schemes.

Cooperatives are associations of people who voluntarily cooperate for mutual socio-economic and cultural benefits. It is important to understand the performance of cooperatives as perceived by their members, which would be crucial to sustaining a cooperative in the future. However, there is limited research that unpacks members' perceived performance of the cooperatives in the Nepalese context. This study (a) assesses the perceived performance of the board members and general members of the Devisthan Agriculture Cooperative Limited (DACL), and (b) examines if the perceived performance varies by members' characteristics. We used a self-administered questionnaire to collect data from 138 randomly sampled respondents who were members of the DACL. The survey included five indicators to measure performance: relevancy, efficiency, effectiveness, impact, and sustainability. Both descriptive and inferential statistical tools were used for analysis. Findings showed that the perceived performance of the members on various indicators of performance significantly varied. The characteristics -respondents' category, sex group, caste/ethnicity, involvement in business, formal education, and participation in capacity and skill development training -- were among the significant predictors influencing performance. Implications for enhancing the performance of agriculture cooperatives have been discussed. [ABSTRACT FROM AUTHOR]

Background: Abortion was legalized in Nepal in 2002, following advocacy efforts highlighting high maternal mortality from unsafe abortion. We sought to assess whether legalization led to reductions in the most serious maternal health consequences of unsafe