A Universal Hydrogel Microneedle for on-Site Detection of Small Molecules, Proteins, and Ribonucleic Acids
Notice bibliographique
Résumé
Point-of-care testing (POCT) of clinical biomarkers is critical to health monitoring and timely treatment, yet biosensing assays capable of detecting biomarkers without the need for costly external equipment and reagents are limited. Blood-based assays are, specifically, challenging as blood collection is invasive, and several processing steps are required. A promising alternative to blood is interstitial fluid (ISF), which originates from blood and fills the extracellular space; thus, it has common biomarkers with plasma/serum while also containing biomarkers unique to the local cells. A wide range of metabolites, including amino acids, lipids, nucleotides, and protein biomarkers, can be detected in ISF, emphasizing the potential of ISF for health monitoring. Microneedle (MN)-based biosensors have recently emerged as a promising approach for investigating the ISF. They enable minimally invasive penetration through the skin for ISF access. Specifically, Hydrogel-based MNs have two main advantages; i) their fabrication is cost-effective and simple, ii) they are highly biocompatible. Therefore, they overcome the challenges with conventional solid MNs. However, Hydrogel Microneedles (HMN) capable of both extracting ISF and sensing an analyte on-microneedle (without any need for post-sampling processing) have been limited. Here, we report a versatile assay that employs HMNs to both extract (ISF) and perform on-MN sensing of a specific analyte/biomarker in a minimally invasive manner. Our assay incorporates graphene oxide-nucleic acid (GO.NA) optical sensors for sensing. The GO.NA optical sensor consists of GO nanosheets conjugated to fluorophore-modified nucleic acid (NA), in which GO acts as a quencher. Single-stranded NAs have high affinity for binding to GO, therefore, in the absence of the biomarker of interest the NAs are tightly bound to GO; in turn, their fluorophore tag is quenched. However, in the presence of a specific biomarker, the NAs bind to their target, inducing a conformational change that distances the fluorophore tag from GO, leading to fluorescence recovery and generation of an optical signal. GO also acts as a substrate for NA immobilization; therefore, it protects the NA from degradation and prevents any potential NA release from HMN-GO.NA. To enable microscope-free patch visualization and optical measurements for POCT, we developed a miniaturized smartphone-based system that captures fluorescence images of the HMN-GO.NA patches (Scheme 1A and 1B), which are then analyzed using freely available software (ImageJ). Our system could successfully measure six clinically important biomarkers (glucose, uric acid, insulin, and serotonin as well as microribonucleic acid 210 and 21) in-vitro (using phantom gel) and ex-vivo (using porcine skin). Further, we have been able to accurately detect glucose and uric acid in live diabetic animal models, proving the efficacy of our system. Figure 1
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 | 0,000 |
| 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 ».