Blood Flow Mediated Hybrid Nanoparticles in Human Arterial System: Recent Research, Development and Applications
Notice bibliographique
Résumé
Blood flow dynamics contributes an elemental part in the formation and expansion of cardiovascular diseases in human body. Computational simulation of blood flow in the human arterial system has been widely used in recent decades for better understanding the symptomatic spectrum of various diseases, in order to improve already existing or develop new therapeutic techniques. The characteristics of the blood flow in an artery can be changed significantly by arterial diseases, such as aneurysms and stenoses. The progress of atherosclerosis or stenosis in a blood vessel is quite common which may be caused due to the addition of lipids in the arterial wall. Nanofluid is a colloidal mixture of nanometer sized (which ranges from 10–100 m) metallic and non-metallic particles in conventional fluid (such as water, oil). The delivery of nanoparticles is an interesting and growing field in the development of diagnostics and remedies for blood flow complications. An enhancement of nano-drug delivery performance in biological systems, nanoparticles properties such as size, shape and surface characteristics can be regulated. Nanoparticle offers remarkably advantages over the traditional drug delivery in terms of high specificity, high stability, high drug carrying capacity, ability for controlled release. Highly dependency has been found for their behavior under blood flow while checking for their ability to target and penetrate tissues from the blood. In the field of nano-medicine, organic (including polymeric micelles and vesicles, liposomes) and inorganic (gold and mesoporous silica, copper) nanoparticles have been broadly studied as particular carriers because as drug delivery systems they delivered a surprising achievement as a result of their biocompatibility with tissue and cells, their subcellular size, decreased toxicity and sustained release properties. For the extension of nanofluids research, the researchers have also tried to use hybrid nanofluid recently, which is synthesized by suspending dissimilar nanoparticles either in mixture or composite form. The main idea behind using the hybrid nanofluid is to further improve the heat transfer and pressure drop characteristics. Nanoparticles are helpful as drug carriers to minimize the effects of resistance impedance to blood flow or coagulation factors due to stenosis. Discussed various robust approaches have been employed for the nanoparticle transport through blood in arterial system. The main objective of the paper is to provide a comprehensive review of computational simulations of blood flow containing hybrid-nanoparticles as drug carriers in the arterial system of the human body. The recent developments and analysis of convective flow of particle-fluid suspension models for the axi-symmetric arterial bodies in hemodynamics are summarized. Detailed existing mathematical models for simulating blood flow with nanoparticles in stenotic regions are reviewed. The review focuses on selected numerical simulations of physiological convective flows under various stenosis approximations and computation of the temperature, velocity, resistance impedance to flow, wall shear stress and the pressure gradient with the corresponding boundary conditions. The current review also highlights that the drug carrier nanoparticles are efficient mechanisms for reducing hemodynamics of stenosis and could be helpful for other biomedical applications. The review considers flows through various stenoses and the significances of numerical fluid mechanics in clinical medicine. The review examines nano-drug delivery systems, nanoparticles and describes recent computational simulations of nano-pharmacodynamics.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».