Evaluation of Gold Nanoparticle-Doxorubicin Conjugates for their Use in Drug Delivery
Notice bibliographique
Résumé
Since the seminal work on spherical nucleic acids (SNAs) by Mirkin and co-workers in 1996, substantial research investment has been devoted to gold nanoparticle (AuNP)-based biotechnology advancement. AuNPs have several unique attributes, making them ideal for a wide variety of applications ranging from medicinal diagnostics and cancer therapy to environmental and chemical sensing. First, AuNPs are known to exhibit high surface area-to- volume ratios leading to rapid reaction kinetics and enhanced drug and polymer loading capabilities. Additionally, gold nanoparticles offer a high degree of biocompatibility, controllable synthesis, and near covalent-strength interactions with thiolated molecules. Moreover, gold nanomaterials embody fascinating and unique optical properties derived from the interaction between surface electrons and electromagnetic radiation. By tuning the nanoparticle shape, size and ligand density, these optical properties can be altered, leading to an impressive diversity of technological and medicinal applications. \n \nDoxorubicin is an effective chemotherapeutic used to treat a variety of cancers including solid masses and leukemia. Clinically, its mechanism of action involves the intercalation of double-stranded DNA and the inhibition of important cellular replication enzymes. Typically, doxorubicin is administered in liposomal forms in order to mitigate the harsh cardiotoxicity associated with its use. Despite advances in this field, many side effects still exist and innovative delivery mechanisms remain highly desirable. Drug delivery studies employing doxorubicin often rely on the molecule’s fluorescent region for effective quantification, despite previously-reported issues related to non-specific adsorption of the drug molecule to container surfaces. \n \nHere, several research questions related to AuNPs and doxorubicin are addressed. First, the extent to which doxorubicin non-specifically adsorbs to plastic vessels in drug delivery studies is examined and a simple blocking technique using trace amounts of polyethylene glycol is reported and systematically characterized. Through the inclusion of trace amounts of polyethylene glycol in fluorescence measurement buffer, quantitative errors can be inhibited, ensuring accurate drug loading for downstream experimental application. Second, the chemical adsorption mechanism between doxorubicin and AuNPs is systematically studied. Traditionally, the interaction was believed to be dominated by an electrostatic attraction between the protonated moiety of the drug and the negatively-charged citrate-capping agent coating the nanoparticle surface. Here, that theory is challenged upon the proposal of a multifaceted adsorption process, whereby coordination and cation-π-based interactions between the drug and nanoparticle are dominant. \n \nThe investigations described above help to advance the fields of nanotechnology and drug delivery by first providing a robust doxorubicin quantification method and second by providing insights into the chemical nature of doxorubicin-gold conjugates. Together, these discoveries may influence future drug delivery research studies that utilize both doxorubicin and gold nanomaterials.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 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 | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».