Role of adjunctive vitamin C supplement therapy in combating COVID-19

Since the COVID-19 pandemic began in December 2019, the disease has continued to spread, highlighting the urgent need for immunization and a cure. People are seeking ways in which to potentially protect themselves from the virus or to alleviate its effects once caught.  This article reviews what vitamin C is, how it affects immunity, how it’s being tried for COVID-19 patients in a hospital setting. Vitamin C affects immune health in several ways through its antioxidant ability, collagen synthesis or directly strengthening cells in the fight against infection

Molecular docking of potential Indian medicinal plant compounds against dengue viral proteins

Dengue fever is one of the major health issue caused by Dengue virus. The present work focuses on virtual screening of compounds from the selected medicinal plants, Azadirachta indica, Andrographis paniculata, Tinospora cordifolia and Carica papaya for their anti-viral activity against dengue virus. The envelop protein and methyl transferase enzyme of dengue virus has been selected for the study. Computer aided docking of plant compounds with selected viral proteins known for its pathogenicity in humans were performed using AutoDock software after checking their drug likeness property based on Lipinski’s rule of five. Most of the selected compounds docked well with the viral protein in terms of their binding energy and ligand efficiency with effective drug likeness property as compared to the reference synthetic drug.  Nimbocinol and Meliacinanhydride of Azadirachta indica were found to be the top most compounds against selected dengue viral protein displaying highest binding affinity. Andrographolide of A. paniculata and Tinosporide and Berberine of T. cordifolia also showed promising results against viral proteins. Since these naturally derived compounds have several advantages over synthetic drugs, these compounds can be used as an anti-viral drug for the treatment of dengue fever after checking their efficacy and safety by in-vitro and in-vivo experiments

Recent Trends in Application of Neural Networks to Speech Recognition

: In this paper, we review the research work that deal with neural network based speech recognition and the various approaches they take to bring in accuracy. Three approaches of speech recognition using neural network learning models are discussed: (1) Deep Neural Network(DNN) - Hidden Markov Model(HMM), (2) Recurrent Neural Networks(RNN) and (3) Long Short Term Memory(LSTM). It also discusses how for a given application one model is better suited than the other and when should one prefer one model over another.A pre-trained Deep Neural Network - Hidden Markov Model hybrid architecture trains the DNN to produce a distribution over tied triphone states as its output. The DNN pre-training algorithm is a robust and often a helpful way to initialize deep neural networks generatively that can aid in optimization and reduce generalization error. Combining recurrent neural nets and HMM results in a highly discriminative system with warping capabilities. To evaluate the impact of recurrent connections we compare the train and test characteristic error rates of DNN, Recurrent Dynamic Neural Networks (RDNN), and Bi-Directional Deep Neural Network (BRDNN) models while roughly controlling for the total number of free parameters in the model. Both variants of recurrent models show substantial test set characteristic error rate improvements over the non-recurrent DNN model. Inspired from the discussion about how to construct deep RNNs, several alternative architectures were constructed for deep LSTM networks from three points: (1) input-to-hidden function, (2) hidden-to-hidden transition and (3) hidden-to-output function. Furthermore, some deeper variants of LSTMs were also designed by combining different points

Assessment of genetic variability and diversity analysis in medium duration rice accessions

A total of 64 medium duration rice accessions were evaluated for their genetic variability and genetic divergence during Rabi season 2020 at Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal. Analysis of variance revealed significant differences for all the traits considered for the study. The traits spikelets per panicle and filled grains per panicle recorded high GCV as well as PCV thereby indicating that these traits would be improved effectively through selection. Other yield component traits viz., plant height, productive tillers per plant, spikelets per panicle, filled grains per panicle, fertility per cent, grain weight and single plant yield revealed high heritability coupled with high genetic advance, indicating that simple selection could be effective for improving these characters. The D2 values and hierarchical clustering analysis grouped the 64 germplasm into seven clusters. In both the clustering methods, the genotype Gold 44 was grouped under separate clusters indicating that, this is a diverse genotype among all the genotypes taken for study. Further, genotype AD 16124 was grouped under the same cluster in both the clustering methods with the highest cluster mean for grain yield per plant. Hence, this genotype could be efficiently utilized for the yield improvement programme in rice

Molecular docking of potential Indian medicinal plant compounds against dengue viral proteins

537-544Dengue fever is one of the major health issue caused by Dengue virus. The present work focuses on virtual screening of compounds from the selected medicinal plants, Azadirachta indica, Andrographis paniculata, Tinospora cordifolia and Carica papaya for their anti-viral activity against dengue virus. The envelop protein and methyl transferase enzyme of dengue virus has been selected for the study. Computer aided docking of plant compounds with selected viral proteins known for its pathogenicity in humans were performed using Auto Dock software after checking their drug likeness property assessed on the basis of Lipinski’s rule of five. Most of the selected compounds docked well with the viral protein in terms of their binding energy and ligand efficiency with effective drug likeness property as compared to the reference synthetic drug. Nimbocinol and Meliacinanhydride of Azadirachta indica were found to be the top most compounds against selected dengue viral protein displaying highest binding affinity. Andrographolide of A. paniculata and Tinosporide and Berberine of T. cordifolia also showed promising results against viral proteins. Since these naturally derived compounds have several advantages over synthetic drugs, these compounds can be used as an anti-viral drug for the treatment of dengue fever after checking their efficacy and safety by in-vitro and in-vivo experiments

Molecular docking of triterpenoids from Neem with the ecdysone receptor of lepidopteran pests

237-248An in silico docking study was performed to evaluate the interaction of various triterpenoids present in neem with the ecdysone receptor of two economically important lepidopteran pests viz., Helicoverpa armigera (HaEcR) and Plutella xylostella (PxEcR). Twenty triterpenoids were selected for the study, and their docking scores with HaEcR and PxEcR were calculated using the program AutoDock Vina. A commercially available DAH insecticide, tebufenozide, was used as a reference ligand. Out of the twenty triterpenoids used for the study, six and nine triterpenoids recorded binding energy lower than the reference ligand, tebufenozide, when docked with HaEcR and PxEcR, respectively. Four triterpenoids, viz., isomeldenin, azdiradione, 6-deacetylnimbinene, and nimocinol, docked effectively with the ecdysone receptor of both insect pests. In addition, nimbinene and 6-deacetylnimbin also docked effectively with HaEcR and epoxyazadiradione and nimbocinol with PxEcR. Most of the lead compounds were able to form hydrogen bonds with the ecdysone receptor molecule. We found two key amino acid residues, Asn of HaEcR and Ser of PxEcR, at the 504th position, based on their ability to form hydrogen bonds with many lead triterpenoids tested. Other residues, such as Trp 526 in HaEcR and Lys 372 and Phe 520 in PxEcR, were involved in hydrophobic and π-π stacking interactions with many lead triterpenoids, suggesting these residues as an important point of interaction between receptor and ligand molecules. Triterpenoids such as tirucallol, 3-tigloylazadirachtol, and azadirone, although recorded binding energy lower than tebufenozide when docked with PxEcR, failed the prerequisite conditions laid down by Tice rule for a successful pesticide. The lower binding energy of the lead compounds suggests their stable interaction with the receptor molecule and their possible use as an ecdysone agonist or antagonist for effective insect control

PERFORMANCE OF ITERATED EKF TECHNIQUE TO ESTIMATE TIME VARYING CHANNEL USING PILOT ASSISTED METHOD IN MIMO-OFDM SYSTEM

ABSTRACT In this paper Iterative Extended Kalman Filter (IEKF) technique has been proposed to estimate the time varying channel for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing systems (OFD