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Background: Because of its diverse range of use in several ethics of diagnosis and care of multiple diseases, nanotechnology has seen remarkable growth and has become a key component of medical sciences. In recent years, there has been rapid advancement in medicine and biomaterials. Nanomedicine aids in illness prevention, diagnosis, monitoring, and treatment., Aim: The purpose of this work is to evaluate the antibacterial, anti-inflammatory, and cytotoxic capabilities of green produced silver nanoparticle with the addition of curcumin-assisted chitosan nanocomposite (SCCN) against wound pathogenic as reducing agents., Materials and Methods: The plant extract of Pongamia pinnata , silver nanoparticles, and its based curcumin nanoformulations was studied in this study utilizing UV visible spectrophotometer, selected area electron diffraction (SAED), and TEM. Anti-inflammatory, antimicrobial, and cytotoxic tests were performed on silver nanoparticles with the addition of curcumin-assisted chitosan nanocomposite (SCCN). Furthermore, these produced nanocomposites were coated on clinical silk and tested for antibacterial activity., Results: The produced silver nanoparticle with the addition of curcumin-assisted chitosan nanocomposite (SCCN) has significant antibacterial activities against Pseudomonas aeruginosa and staphylococcus aureus . They are as well as possess anti-inflammatory activity and furthermore prove to be biocompatible., Conclusion: This advancement in the field of biomaterials, which means nanocomposite, not only helps to reduce the harmful effects of pathogenic organisms while representing an environmentally benign material but it also shows to be a material with zero danger to humans and the environment., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Rajeshkumar Shanmugam et al.)

Coronavirus disease (COVID-19), a life-threatening disease, is caused by SARS-CoV-2. The targeted therapeutics of small molecules helps the scientific community to fight against SARS-CoV-2. In this article, some oxazine substituted 9-anilinoacridines ( A1-A48 ) was designed by docking, MM-GBSA and molecular dynamics (MD) simulation studies for their COVID-19 inhibitory activity. The docking of ligands A1-A48 against SARS-CoV-2 (PDB ID: 5R82) are performed by using Glide module, in silico ADMET screening by QikProp module, binding energy using Prime MM-GB/SA module, MD simulation by Desmond module and atomic charges were derived by Jaguar module of Schrodinger suit 2019-4. Compound A38 has the highest G-score (-7.83) when compared to all the standard compounds which are proposed for COVID-19 treatment such as ritonavir (-7.48), lopinavir (-6.94), nelfinavir (-5.93), hydroxychloroquine (-5.47) and mataquine (-5.37). Compounds A13 , A23 , A18 , A7 , A48 , A46 , A32 , A20 , A1 and A47 are significantly active against SARS-CoV-2 main protease when compared with hydroxychloroquine and mataquine. The residues GLN19, THR24, THR25, THR26, LEU27, HIE41, SER46, MET49, ASN119, ASN142, HIE164, MET165, ASP187, ARG188 and GLN189 of SARS-CoV-2 main protease play a crucial role in binding with ligands. The in silico ADMET properties of the molecules are within the recommended values. The binding free energy was calculated using PRIME MM-GB/SA studies. From the ligands A38 , A13 , A23 , A18 , A7 , A48 and A46 with significant Glide scores may produce significant COVID-19 activity for further development. Compound A38 was subjected to MD simulation at 100 ns to study the dynamic behaviour of protein-ligand complex.Communicated by Ramaswamy H. Sarma.

Enantiomeric resolution of the drug and complete separation from its degradation products was successfully achieved on a PAK IG-3 (150 × 4.6 mm i.d., 3 µm particle size) column, using UV detector at a wavelength of 290 nm, with mobile phase consisting of acetonitrile, 20 mM ammonium bicarbonate at the ratio of 95:05 (v/v), and a flow rate of 0.7 mL/min. In order to subjected to stress conditions, the drug has been exposed to alkaline, acidic, neutral, oxidative, and photolytic conditions. The products of degradation were well resolved from the main peak and proved the method's stability-indicating method. The method linear ranged between 10-110 μg/mL and 5-100 μg/mL for (+) and (-) midodrine enantiomers and regression analysis showed a correlation coefficient value ( r 2 ) of 0.999. The recovery of the method was found to be in the range of 99.1-101.2%. The detection limit for the (+) and (-) enantiomers was found to be 4 μg/mL and 1 μg/mL, respectively. The HPLC method was validated as per ICH guidelines with respect to specificity, precision, linearity, and robustness.

Background: The COVID 19 pandemic created a global public health crisis. Physical distancing, masks, personal protective equipment worn by the doctors created difficulties in effective doctor-patient communication., Objectives: This study was conducted to assess the difficulties faced by patients in communicating with their doctors due to the COVID 19 preventive measures, and its impact on the trust on their doctors., Methods: A cross sectional study of 359 persons attending a tertiary care center in Chennai, sampled in a non-probabilistic manner selected from the outpatient department, wards, and isolation facilities, was conducted using a questionnaire containing items covering three dimensions namely difficulties faced in accessing the health facility, difficulties in doctor-patient communication and trust in the doctors. The data were collected using Google Forms and analyzed using GNU PSPP open-source statistical software version 1.4.0., Results: More than 60% of the participants complained of difficulty in accessing the health facility. More than 60% had difficulties in communicating with the doctors. There was a high level of trust in doctors among more than 80% of the participants. Comparison of the mean scores revealed that accessibility was a problem across ages, sexes, education and occupation groups. Communication barriers decreased with age and increased with education, but trust increased with age, but reduced with increasing education. Multivariable linear regression analysis revealed that difficulties in communication had a negative impact on trust (β = -0.63, p<0.001) and increasing education had a negative impact on trust (β = -0.42, p = 0.034)., Conclusions: The COVID 19 pandemic and the preventive strategies such as lock-down, physical distancing, face mask and personal protective equipment created barriers to effective doctor patient communication and led to some compromise in trust in doctors during this time., Competing Interests: The authors declare that no competing interests exist.

An enantiomeric separation of meclizine enantiomers by liquid chromatography with tandem mass spectrometry LC-MS method was developed and validated for the analysis of Meclizine enantiomers. Enantiomeric resolution of the drug products were successfully achieved on a Phenomenex® lux cellulose 1 C18 (250 mm × 4.6 mm i.d, 5 µm particle size) column with mobile phase consisting of acetonitrile: 5 mM ammonium format pH (5.5) adjusted with formic acid (90:10) (v/v), and a flow rate of 0.4 mL/min. The developed method provided linear responses within the concentration range 1-5 ng/mL, and regression analysis showed a correlation coefficient value (r 2 ) of 0.999. The optimized mobile phase separated (+) Meclizine at 1.58 min and (-) Meclizine at 2.20 min, respectively. The LC/MS method was validated as per ICH guidelines with respect to specificity, precision, linearity and robustness. Limit of detection (LOD) and limit of quantification (LOQ) were found to be 1.0 ng/mL and 5.0 ng/mL respectively. The proposed method is suitable for analysis of meclizine enantiomers in pharmaceutical formulations and quality control analysis.

Background: 1,3,4-thiadiazolo pyrimidine is a lead molecule that is versatile for a wide variety of biological activities and in continuation of our interest in establishing some novel heterocyclic compounds for antitumor activity., Objective: The objective of the study was to synthesize a series of 5-amino-7-(substituted aldehyde)-2[(naphthalene- 2-yloxy)methyl] -[1,3,4]thiadiazolo-[3,2-α]-pyrimidine-6- carbonitrile derivatives and evaluate their possible in vitro and in vivo anticancer activity., Methods: Herein, we report the synthetic scheme, which was followed for the preparation of a series of title compounds B1- B9 outlined in scheme 1. The intermediate 5-[(naphthalen-2- yloxy)methyl]-1,3,4-thiadiazolo- 2-amine was prepared by heating 2-naphthoxyacetic acid and thiosemicarbazide in the presence of phosphoryl chloride at a temperature of 65-75°C. The obtained compound reacted with malononitrile and an appropriate amount of aromatic and heteroaromatic aldehydes in refluxing ethanol yielded 5-amino-7-(substituted aldehyde)-2[(naphthalene-2-yloxy)methyl] -[1,3,4]thiadiazolo-[3,2-α]-pyrimidine-6- carbonitrile derivatives (B1 - B9). The purity of the synthesized compounds was ensured by various spectral analyses., Results: In in silico molecular docking studies, compounds B3 and B9 show binding affinity like known PARP1 inhibitor olaparib. The cellular evaluation indicates that the anticancer profile of compounds B1, B3, and B9 is significant when compared to the standard drug (olaparib) against MDA-MB-232 cell line and compounds B3, B6, and B7 are the most active against MCF-7 cell lines. The most active compound B3 was subjected to acute oral toxicity studies by OECD 423 guidelines and in vivo anti-cancer studies were carried out using DMBA induced model., Conclusion: The in silico docking study of the newly synthesized compounds was performed; the results showed good binding mode in the active site of PARP1 enzyme. In silico ADME properties of synthesized compounds were also studied and showed good drug-like properties., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: In early 2020, many scientists are rushing to discover novel drugs and vaccines against the coronavirus, and treatments for COVID-19, because coronavirus disease 2019 (COVID-19), a life-threatening viral disease, affected first in China and quickly spread throughout the world. In this article, in silico studies have been performed to explore the binding modes of chemical constituents for natural remedies like Curcuma longa (turmeric) and Andrographis paniculata against COVID-19 (PDB ID 5R82) targeting coronavirus using Schrodinger suit 2019-4. The molecular docking studies are performed by the Glide module, in silico ADMET screening was performed by the QikProp module, and binding energy of ligands was calculated using the Prime MM-GB/SA module., Results: The chemical constituents from turmeric like cyclocurcumin and curcumin and from Andrographis paniculata like andrographolide and dihydroxy dimethoxy flavone are significantly binding with the active site of SARS CoV-2 main protease with Glide score more than - 6 when compared to the currently used drugs hydroxychloroquine (- 5.47) and nelfinavir (- 5.93). When compared to remdesivir (- 6.38), cyclocurcumin from turmeric is significantly more active. The docking results of the compounds exhibited similar mode of interactions with SARS CoV-2. Main protease and the residues THR24, THR25, THR26, LEU27, SER46, MET49, HIE41, GLN189, ARG188, ASP187, MET165, HIE164, PHE181, and THR54 play a crucial role in binding with ligands., Conclusion: Based on in silico investigations, the chemical constituents from turmeric like cyclocurcumin and curcumin and from Andrographis paniculata like andrographolide and dihydroxy dimethoxy flavone, significantly binding with the active site of SARS CoV-2 main protease, may produce significant activity and be useful for further development., Competing Interests: Competing interestsThe authors have no competing interests to declare., (© The Author(s) 2020.)

Context: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data which are becoming difficult to manage. Identifying the desired featured chemical with the desired biological activity from millions of chemicals is a challenging task., Aims: In this study, we investigate and explore big data technologies and machine learning approaches to do an efficient chemical data mining for endocrine receptor disruption prediction and virtual compound screening. The power of artificial neural network (ANN) in predicting chemicals' activity toward androgen receptor (AR) and estrogen receptor (ER) and thereby classifying into human endocrine disruptor or nondisruptor is investigated., Subjects and Methods: Molecules are collected along with their Inhibitory Concentration (IC 50 ) values toward AR and ER. Training and test datasets are created with active and inactive classes of molecules. Molecular fingerprints of Electro Topological State (E-State) are generated for describing every compound. ANN machine learning model is created using Apache Spark and implemented in Hadoop big data environment. Test chemical's structural similarity toward active class of training compounds is estimated and combined with ANN model for improving prediction accuracy., Results: AR and ER predictive models applied on corresponding test datasets gave 86.31% and 89.57% accuracies, respectively, in correctly classifying molecules as disruptor or nondisruptor. Molecular fragments and functional groups are ranked based on their importance in forming ANN model and influence toward the AR and ER disruption behavior. Training molecules that are specific to the test molecules' endocrine disruption prediction are retrieved based on the structural similarity values., Conclusions: The current study demonstrates a new approach of chemical endocrine receptor disruption prediction combining ANN machine learning method and molecular similarity in a big data environment. This method of predictive modeling can be further tested with more receptors and hormones and predictive power can be examined., Competing Interests: There are no conflicts of interest.

The development of hybrid scaffolds mimicking the extracellular matrix with bioactive factors has great potential to regenerate tissues in tissue engineering and wound-healing applications. Herein, poly(dialdehyde) gum acacia was synthesized by the selective oxidation of gum acacia and was blended with collagen and melatonin to fabricate biomimetic hybrid scaffolds. The inclusion of poly(dialdehyde) gum acacia improved the stability of collagen and immobilized the melatonin in the hybrid scaffolds. The prepared hybrid scaffolds showed significant biocompatibility when cultured with the Swiss 3T6 mouse fibroblast cell lines in vitro. When subjected to open excisional skin wounds in Wistar albino rats in vivo, the collagen-poly(dialdehyde) gum acacia-melatonin hybrid scaffolds accelerated re-epithelialization and collagen deposition. The results indicate that the melatonin-immobilized hybrid scaffold promotes rapid tissue regeneration and wound repair owing to its antioxidant and anti-inflammatory properties, thereby demonstrating its potential for application in burns and chronic wounds.

The artificial materials for bone implant applications are gaining more importance in the recent years. The series titania-chitosan-chondroitin 4-sulphate nanocomposites of three different concentrations (2:1:x, where x- 0.125, 0.25, 0.5) have been synthesised by in situ sol-gel method and characterised by various techniques. The particle size of the nanocomposites ranges from 30-50 nm. The bioactivity, swelling nature, and the antimicrobial nature of the nanocomposites were investigated. The swelling ability and bioactivity of the composites is significantly greater and they possess high zone of inhibition against the microorganisms such as Staphylococcus aureus and Escherichia coli. The cell viability of the nanocomposites were evaluated by using MG-63 and observed the composites possess high cell viability at low concentration. The excellent bioactivity and biocompatibility makes these nanocomposites a promising biomaterial for bone implant applications.

Biomaterials based entirely on biological resources are ideal for tissue engineering applications. Here we report the preparation of hybrid collagen scaffolds comprising gulmohar seed polysaccharide (GSP) and cinnamon bark extract as cross-linking agent. (1)H NMR spectrum of GSP confirms the presence of galactose and mannose in the ratio of 1:1.54, which was further corroborated using FT-IR. The hybrid scaffolds show better enzyme and thermal stability in contrast to pure collagen scaffold probably due to weak interactions from GSP and covalent interaction through cinnamaldehyde. Gas permeability and scanning electron microscopic analysis show that the porosity of the hybrid scaffolds is slightly reduced with the increase in the concentration of GSP. The infrared and circular dichroic spectral studies show that the secondary structure of the collagen did not change after the interaction with GSP and cinnamaldehyde. The hybrid scaffolds stabilized with cinnamaldehyde show good antimicrobial activity against the common multi-drug resistant wound pathogens. These results suggest that the prepared hybrid scaffolds have great potential for antimicrobial wound dressing applications., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Development of hybrid scaffolds with synergistic combination of growth factor is a promising approach to promote early in vivo wound repair and tissue regeneration. Here, we show the rapid wound healing in Wistar albino rats using biomimetic collagen-poly(dialdehyde) guar gum based hybrid porous scaffolds covalently immobilized with platelet derived growth factor-BB. The immobilized platelet derived growth factor in the hybrid scaffolds not only enhance the total protein, collagen, hexosamine, and uronic acid contents in the granulation tissue but also provide stronger tissues. The wound closure analysis reveal that the complete epithelialization period is 15.4 ± 0.9 days for collagen-poly(dialdehyde) guar gum-platelet derived growth factor hybrid scaffolds, whereas it is significantly higher for control, collagen, collagen- poly(dialdehyde) guar gum and povidine-iodine treated groups. Further, the histological evaluation shows that the immobilized platelet derived growth factor in the hybrid scaffolds induced a more robust cellular and vascular response in the implanted site. Hence, we demonstrate that the collagen-poly(dialdehyde) guar gum hybrid scaffolds loaded with platelet derived growth factor stimulates chemotactic effects in the implanted site to promote rapid tissue regeneration and wound repair without the assistance of antibacterial agents., (© 2015 Wiley Periodicals, Inc.)

The emergence of video surveillance is the most promising solution for people living independently in their home. Recently several contributions for video surveillance have been proposed. However, a robust video surveillance algorithm is still a challenging task because of illumination changes, rapid variations in target appearance, similar nontarget objects in background, and occlusions. In this paper, a novel approach of object detection for video surveillance is presented. The proposed algorithm consists of various steps including video compression, object detection, and object localization. In video compression, the input video frames are compressed with the help of two-dimensional discrete cosine transform (2D DCT) to achieve less storage requirements. In object detection, key feature points are detected by computing the statistical correlation and the matching feature points are classified into foreground and background based on the Bayesian rule. Finally, the foreground feature points are localized in successive video frames by embedding the maximum likelihood feature points over the input video frames. Various frame based surveillance metrics are employed to evaluate the proposed approach. Experimental results and comparative study clearly depict the effectiveness of the proposed approach.