Summary
The major sources of dietary lipids are edible oils, which include both vegetable and fish oils. Crude oil extracted from vegetable and fish sources contain mono‐, di‐, triacylglycerols along ...with impurities, which necessitates refining. The main objective of refining is to remove the contaminants that adversely affect the quality of oil, thereby reducing the shelf life and consumer acceptance. However, this refining process needs to be tailored as the composition of crude oil is highly variable, depending upon the plant/fish species, geographical location of the source and method of oil extraction. Recently, extensive efforts have been made to develop refining technology, using either conventional physical/chemical processes or several unconventional processes including biological and membrane processes. The first section of this review gives a brief description of general composition of some commonly used vegetable and fish oils, followed by the review of various refining methods and their effects on the oil constituents. Finally, an effort is made to understand the technological gaps in the existing methods and possible directions of research to overcome the said gaps.
Edible oil is refined in industry typically through four steps viz., degumming, deacidification, bleaching and deoderization, and each step in turn may employ one or more technologies to accomplish the desired task. This figure summarizes all the existing and potential technologies available for refining the edible oil.
More information about a person's genetic makeup, drug response, multi-omics response, and genomic response is now available leading to a gradual shift towards personalized treatment. Additionally, ...the promotion of non-animal testing has fueled the computational toxicogenomics as a pivotal part of the next-gen risk assessment paradigm. Artificial Intelligence (AI) has the potential to provid new ways analyzing the patient data and making predictions about treatment outcomes or toxicity. As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. AI can process and integrate a multitude of data including genome data, patient records, clinical data and identify patterns to derive predictive models anticipating clinical outcomes and assessing the risk of any personalized medicine approaches. In this article, we have studied the current trends and future perspectives in personalized medicine & toxicology, the role of toxicogenomics in connecting the two fields, and the impact of AI on personalized medicine & toxicology. In this work, we also study the key challenges and limitations in personalized medicine, toxicogenomics, and AI in order to fully realize their potential.
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•Established the relationship between personalized medicine and toxicology.•Outlined the importance of artificial intelligence in the current clinical decision-making process.•Overview of the various bottlenecks in artificial intelligence applications.•Provided a roadmap to future researchers on integrating precision medicine, toxicology and artificial intelligence.
Computational drug repurposing is an efficient method to utilize existing knowledge for understanding and predicting their effect on neurological diseases. The ability of a molecule to cross the ...blood-brain barrier is a primary criteria for effective therapy. Thus, accurate predictions by employing Machine learning models can effectively identify the drug candidates that could be repurposed for neurological conditions. This study comprehensively analyzes the performance of the well-known machine learning models on two different datasets to overcome dataset-related biases. We found that random forest and extratrees (i.e., tree-based ensembled models) have the highest accuracy with mol2vec fingerprint for BBB permeability prediction, attaining AUC_ROC of 0.9453 and 0.9601 on BBB and B3DB dataset, respectively. Additionally, we have analyzed the impact of the data balancing technique (i.e., SMOTE) to improve the specificity of the models. Finally, we have explored the impact of different fingerprint combinations on accuracy. By employing SMOTE and fingerprint combination, SVC attains the highest AUC_ROC of 0.9511 on BBB dataset. Finally, we used the best-performing models of the B3DB dataset to evaluate the BBB permeability for drugs intended to be used for repurposing. Model validation for repurposing predicted the non-passage for most antihypertensive drugs and passage for CYP17A1 cancer drugs.
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.
Increasing data on the infection indicate that maternal infections are severe. Under the realms of vaccine development, virus‐like particles (VLP)/nanoparticles (NPs) hold the promise of targeted ...control of therapeutics transfer across the placental barrier with the potential to trigger innate immune responses. Though the placenta is known to act as a barrier against exogenous materials, viruses exploit the transport systems and overcome the barrier properties. VLPs can be strategically designed to obtain the necessary mechanisms for navigation across the placenta and immune response. However, several knowledge gaps on the chemical, viral transmission strategies and the host defense response exist owing to the highly dynamic etiology of the placental barrier. This further complicates the toxicological analysis of the developed therapeutics. Herein, placental physiology and functions are discussed in significance with chemical toxicology, viral infections, and the host defense. Further, the promising applications of VLPs and perspective on their design to overcome the placental gatekeeper to gain the necessary immune response or therapy are provided. Finally, a holistic approach to various bioengineering models for studying chemical toxicants, viral infections, and effects of VLPs is provided to facilitate better translation of these VLPs to clinical applications.
Herein, placental physiology and functions are discussed in significance with chemical toxicology, viral infections, and the host defense. Further, the promising applications of virus‐like particles and perspective on their design to overcome the placental gatekeeper to gain the necessary immune response or therapy are provided.
A hybrid blood–brain barrier (BBB)-on-chip cell culture device is proposed in this study by integrating microcontact printing and perfusion co-culture to facilitate the study of BBB function under ...high biological fidelity. This is achieved by crosslinking brain extracellular matrix (ECM) proteins to the transwell membrane at the luminal surface and adapting inlet–outlet perfusion on the porous transwell wall. While investigating the anatomical hallmarks of the BBB, tight junction proteins revealed tortuous zonula occludens (ZO-1), and claudin expressions with increased interdigitation in the presence of astrocytes were recorded. Enhanced adherent junctions were also observed. This junctional phenotype reflects in-vivo-like features related to the jamming of cell borders to prevent paracellular transport. Biochemical regulation of BBB function by astrocytes was noted by the transient intracellular calcium effluxes induced into endothelial cells. Geometry-force control of astrocyte–endothelial cell interactions was studied utilizing traction force microscopy (TFM) with fluorescent beads incorporated into a micropatterned polyacrylamide gel (PAG). We observed the directionality and enhanced magnitude in the traction forces in the presence of astrocytes. In the future, we envisage studying transendothelial electrical resistance (TEER) and the effect of chemomechanical stimulations on drug/ligand permeability and transport. The BBB-on-chip model presented in this proposal should serve as an in vitro surrogate to recapitulate the complexities of the native BBB cellular milieus.
The antioxidant capacities of three derivatives of hydroxybenzoic acids (Gentisic acid, protochatechuic acid and vanillic acid) in sardine oil were compared. Peroxide value, conjugated diene value, ...p-anisidine value and thiobarbituric acid reactive substances (TBARS) value were assessed to determine 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 dihydroxy benzoic acid) provided relatively less oxidative stability, while vanillic acid had no effect. Results from this work showed that the position of hydroxylation and methyl substitution influences the antioxidant capacity of the molecules in sardine oil. Furthermore, it was found that the extent of oxidative stability conferred by the antioxidants in lipid systems is influenced by several other physical and chemical factors as well.
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•Three esters of 3,4-dihydroxyphenylacetic acid (DHPA) were synthesized.•Binary solvent system with Amberlyst-15 was used to synthesize esters.•Esters were subjected to In vitro ...antioxidant assays and oil storage study.•Methyl ester showed higher efficacy relative to butyl and hexyl esters in bulk oil.•Esters performance in bulk oil system was compliant with polar paradox theory.
Lipophilization of natural antioxidants is a proven strategy to enhance the solubility in bulk oil systems, thereby increasing their efficacy against oxidative degradation. This study aims to synthesize esters of 3,4-dihydroxyphenylacetic acid (3,4-DHPA) using Amberlyst-15 and to study the application of these esters in refined fish oil. Lipophilic esters were synthesized by esterification and transesterification of 3,4-DHPA in various solvent systems. Esters of methanol, butanol and hexanol were obtained with percent conversion of 81.1, 69.3 and 78.8 respectively, and were subjected to molecular characterization and in vitro oxidant assays. The 3,4-DHPA and its methyl ester showed 36% reduction in the TOTOX value over 30 days of storage. The length of the acyl chain in the ester was found to exert a high influence on its efficacy and lipophilicity. This is the first report of 3,4-DHPA and its lipophilic esters studied for enhancing the oxidative stability of fish oil.
The inhalation toxicology of multifaceted particulate matter from the environment, cigarette smoke, and e-cigarette liquid vapes is a major research topic concerning the adverse effect of these items ...on lung tissue. In vitro air–liquid interface (ALI) culture models hold more potential in an inhalation toxicity assessment. Apropos to e-cigarette toxicity, the multiflavor components of the vapes pose a complex experimental bottleneck. While an appropriate ALI setup has been one part of the focus to overcome this, parallel attention towards the development of an ideal exposure system has pushed the field forward. With the advent of microfluidic devices, lung-on-chip (LOC) technologies show enormous opportunities in in vitro smoke-related inhalation toxicity. In this review, we provide a framework, establish a paradigm about smoke-related inhalation toxicity testing in vitro, and give a brief overview of breathing LOC experimental design concepts. The capabilities with optimized bioengineering approaches and microfluidics and their fundamental pros and cons are presented with specific case studies. The LOC model can imitate the structural, functional, and mechanical properties of human alveolar-capillary interface and are more reliable than conventional in vitro models. Finally, we outline current perspective challenges as well as opportunities of future development to smoking lungs-on-chip technologies based on advances in soft robotics, machine learning, and bioengineering.
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..
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