Summary
Poor oxidative stability exhibited by n‐3 polyunsaturated fatty acid rich sardine oil is a major challenge for its utilisation in industry. Considering the fact that water is always present ...in bulk oil in trace amounts during storage, an effort was made to understand and compare the effectiveness of rutin and its corresponding lipophilic ester in enhancing oxidative stability of refined sardine oil containing trace water (0.16% w/w). Peroxide value, conjugated diene value, p‐anisidine value and thiobarbituric acid reactive substances (TBARS) value were determined during 20 days storage. Rutin fatty ester showed 50% reduction in primary oxidation and 42.46% reduction in secondary oxidation, whereas rutin showed 20.6% and 20.43% reduction in primary and secondary oxidation, respectively, by the end of 20 days storage. Thus, it is clearly established that rutin fatty ester is more effective than hydrophilic rutin in sardine oil containing trace water, which contradicts the polar paradox theory.
Effectiveness of rutin and rutin fatty ester in reducing peroxide value and TBARS value in sardine oil..
The blood–brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The ...structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots’ development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.
Multicomponent antioxidant mixture is proved to be highly effective in imparting oxidative stability to the edible oil. It is believed that the high efficacy of those mixtures is due to the ...synergistic effect exhibited by two or more components. The current study aims to analyse the synergistic effect of a flavonoid and its corresponding ester in improving the oxidative stability of
n
-3 PUFA rich sardine oil. The oxidative stability of rutin, esterified rutin and their combinations at three different concentrations was studied in sardine oil stored at 37 ºC for 12 days in contact with air under darkness. The combination of rutin and rutin ester showed maximum reduction of 54.2% in oxidation at 100 mg/kg and 150 mg/kg. Perhaps this is the first report on the synergistic effect of a flavonoid and its lipophilized ester for improving the oxidative stability of
n
-3 PUFA rich oil.
Given the diverse routes of oxidation and a variety of oxidation products, the right combination of antioxidants is expected to exhibit synergistic effects in retarding refined sardine oil oxidation. ...In this study, a full factorial design (24) was utilized to choose a combination of natural antioxidants which exhibit interactive effect and response surface modelling (RSM) was used to identify the optimal concentration of the selected antioxidant mixture which exhibit synergistic effect. Catechin and resveratrol showed a strong interactive effect among the four natural antioxidants (sinapic acid, vanillic acid, catechin, and resveratrol) studied in sardine oil stored for 50 days at 25ºC under darkness. Two optimal concentrations of interactive antioxidants were found through RSM. Catechin and resveratrol at 0.5 mM and 0.625 mM respectively, exhibited a strong synergistic effect whereas, at 0.5 mM and 3.7 mM respectively, showed prooxidant effect. This is the first of its kind report on the formulation of a synergistic antioxidant mixture for retarding oxidation using statistical approaches.
The potential of computational models to identify new therapeutics and repurpose existing drugs has gained significance in recent times. The current ‘COVID-19’ pandemic caused by the new SARS CoV2 ...virus has affected over 200 million people and caused over 4 million deaths. The enormity and the consequences of this viral infection have fueled the research community to identify drugs or vaccines through a relatively expeditious process. The availability of high-throughput datasets has cultivated new strategies for drug development and can provide the foundation towards effective therapy options. Molecular modeling methods using structure-based or computer-aided virtual screening can potentially be employed as research guides to identify novel antiviral agents. This review focuses on in-silico modeling of the potential therapeutic candidates against SARS CoVs, in addition to strategies for vaccine design. Here, we particularly focus on the recently published SARS CoV main protease (Mpro) active site, the RNA-dependent RNA polymerase (RdRp) of SARS CoV2, and the spike S-protein as potential targets for vaccine development. This review can offer future perspectives for further research and the development of COVID-19 therapies via the design of new drug candidates and multi-epitopic vaccines and through the repurposing of either approved drugs or drugs under clinical trial.
The antioxidant capacities of three derivatives of hydroxybenzoic acids (Gentisic acid, protochatechuic acid and vanillic acid) in sardine oil werecompared. Peroxide value, conjugated diene value, ...p-anisidine value and thiobarbituric acid reactive substances (TBARS) value were assessed todetermine the oxidative stability provided by these substances to the sardine oil. Results showed that gentisic acid (2,5 dihydroxy benzoic acid)was the most effective of the chosen hydroxybenzoic acids in imparting oxidative stability to the sardine oil. Protochatechuic acid (3,4 dihydroxybenzoic acid) provided relatively less oxidative stability, while vanillic acid had no effect. Results from this work showed that the position ofhydroxylation and methyl substitution influences the antioxidant capacity of the molecules in sardine oil. Furthermore, it was found that the extentof oxidative stability conferred by the antioxidants in lipid systems is influenced by several other physical and chemical factors as well.
The diversification in fish oil use and the need for softer processing demand new oil refining processes. In considering the advantages ofmembrane technology, three different membranes (polyamide ...(PA), polytetrafluoroethylene (PTFE) and polyethersulfone (PES)) were used in thisparticular study. Preliminary results in the separation of free fatty acids (FFA) from glycerides of sardine oil/ethanol mixtures using a single deadend microfiltration mode have been reported here. The influence of experimental factors like pressure and oil/ethanol ratios (w/v) on the permeateflux and the reduction of FFA (%) in the permeate was studied. PTFE membrane showed promising results in terms of residual FFA in permeate(%), % oil loss (15.12%, 5.45%) as compared to PA (20.50%, 6.66%) and PES membranes (20.60%, 8.92%). PA membrane showed a higher fluxof 4.4 L/m2/h, followed by PTFE 3.34 L/m2/h and PES, 1.19 L/m2/h at 3.5 bar trans-membrane pressure. These results showed that using PTFEmembrane could be an ideal strategy for the membrane assisted deacidification of sardine oil using solvents.
The diversification in fish oil use and the need for softer processing demand new oil refining processes. In considering the advantages of membrane technology, three different membranes (polyamide ...(PA), polytetrafluoroethylene (PTFE) and polyethersulfone (PES)) were used in this particular study. Preliminary results in the separation of free fatty acids (FFA) from glycerides of sardine oil/ethanol mixtures using a single dead end microfiltration mode have been reported here. The influence of experimental factors like pressure and oil/ethanol ratios (w/v) on the permeate flux and the reduction of FFA (%) in the permeate was studied. PTFE membrane showed promising results in terms of residual FFA in permeate (%), % oil loss (15.12%, 5.45%) as compared to PA (20.50%, 6.66%) and PES membranes (20.60%, 8.92%). PA membrane showed a higher flux of 4.4 L/m2/h, followed by PTFE 3.34 L/m2/h and PES, 1.19 L/m2/h at 3.5 bar trans-membrane pressure. These results showed that using PTFE membrane could be an ideal strategy for the membrane assisted deacidification of sardine oil using solvents.
Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an ...alternative to animal testing. The ability of a molecule to effectively cross the placental barrier and reach the fetus determines the drug's toxicological effects on the fetus. In this regard, our study aims to predict the permeability of molecules across the placental barrier. Based on publicly available datasets, several machine learning models are comprehensively analysed across different fingerprints and toolkits to find the best suitable models. Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. K-nearest neighbour (KNN), standard vector classifier (SVC) and Multi-layer perceptron (MLP) are found to be the best-performing models with a prediction percentage of 82%, 86.4% and 90.8%, respectively. Different models are compared to predict the chosen set of drugs, drugs like Aliskiren, some insulin secretagogues and glucocorticoids are found to be negative while predicting the permeability.
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