Notice bibliographique
Résumé
ConspectusUpconversion nanoparticles (UCNPs) have become one of the most frequently used nanomaterials for optical biosensing and imaging. UCNPs unique properties include high photostability, low toxicity, large anti-Stokes shifts, and negligible sample background fluorescence under near-infrared (NIR) excitation. Combining these advantages with Förster resonance energy transfer (FRET) for the investigation of biomolecular interactions seems to be an obvious choice. However, UCNPs are rather large and have low absorption cross sections, which makes the development of UCNP-based FRET systems challenging. Nevertheless, various UCNP-FRET approaches have been developed over the last 20 years, and, in particular, the development of smaller UCNPs and new UCNP architectures has significantly advanced UCNP-FRET.Donor-acceptor distance is extremely important in FRET because its efficiency decreases with the sixth power of that distance. In UCNPs, the donors are the emitting lanthanide ions (activators), which can be placed all over the UCNP volume, resulting in some being close to and others far from the UCNP surface. The "far ones" may be bright because they are well protected from the environment, but they can only provide very low FRET efficiencies to an outside acceptor. The "close ones" can generate high FRET efficiencies but are also exposed to efficient quenching from the surrounding environment on the UCNP surface. This twisted tongue requires an ideal compromise between bright donor ions and a close surface distance for high FRET efficiency.The combination of different core-shell UCNP architectures with the ability to dope cores and shells with different amounts of sensitizers and activators, smaller UCNP sizes, reduced water absorption by changing the excitation wavelength from 980 to 808 nm, functional surface coatings and bioconjugation, as well as optimized FRET acceptor concepts are important parameters to overcome the limits of UCNP-FRET. Careful photophysical characterization, with spatial resolution throughout the entire UCNP volume and on its surface, and advanced modeling to better interpret the experimental results and understand the underlying mechanisms are key to translating UCNP-FRET into the application space.This Account discusses the recent advances of UCNP-FRET, including advanced UCNP core-shell architectures, UCNP surface chemistry and bioconjugation, versatility in acceptor selection, a better understanding of the UCNP-FRET mechanisms, UCNP-FRET modeling approaches, and applications in biosensing, bioimaging, and theranostics. We highlight the challenges of combining UCNPs and FRET and share our vision concerning future developments toward a complete understanding of UCNP-FRET, optimization of nanobiohybrid materials, multiplexed biosensing, and translation of UCNP-FRET technology into broadly usable applications in bioanalysis and biomedicine.
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 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 | 0,001 |
| 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 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 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 ».