Development of a Tablet-Based Sensor for Point-of-Care Analyses Utilizing Pullulan-Stabilized Gold Nanoparticles
Notice bibliographique
Résumé
The quickly expanding fields of nanotechnology and engineered nanomaterials helped solve serious issues that environments and human health suffer from for a long period of time. By accelerating the diagnoses and providing portable sensors that enable the demarcation of processes in biological systems to a previously unattainable degree, this nanotechnology will have an impact on clinical research and the detection of many analytes. Tablet-based sensors have emerged as a powerful tool for point-of-care analyses, revolutionizing the way healthcare professionals diagnose and monitor patients. These sensors, when integrated with tablets, offer numerous advantages and play a crucial role in enhancing healthcare delivery. This advancement in tablet-based sensors for point-of-care analyses should include features such as; enabling healthcare professionals to conduct rapid and accurate diagnostics of various biomarkers, pathogens, and diseases by providing instant results. This real-time information allows for timely interventions and treatment decisions, reducing the need for sending samples to a laboratory and waiting for results, which can lead to delays in treatment. Importantly, the portability and compactness of tablets are highly required especially in remote or resource-limited settings. Furthermore, tablet-based sensors offer a cost-effective alternative to traditional laboratory-based diagnostics where the need for expensive laboratory equipment is eliminated, reducing the overall cost of diagnostics. Additionally, portable tablet sensors do not require training, enabling healthcare professionals to perform tests without extensive specialized expertise. Notably, patients can interact with the sensors and see the results in real-time, empowering them to actively participate in their healthcare. This engagement fosters better patient-provider communication, improves treatment adherence, and increases patient satisfaction. Finally, tablet-based sensors not only aid in diagnostics but also facilitate continuous monitoring of patients by tracking vital signs, glucose levels, and drug concentrations. This routine monitoring helps healthcare professionals make informed decisions, promptly adjust treatments, prevent health complications, and save the lives of millions of people. Following nanotechnology and based on encapsulation of materials, in this work the fabrication of pullulan stabilized gold nanoparticles tablet (AuNPs-pTab) was used as a point-of-care (POC) analytical device utilizing pullulan-AuNPs solution (AuNPs-pSol) without the need for any extra ingredients, which were subsequently used as colorimetric sensors for glucose and cysteamine detection in human saliva and serum samples, respectively. This newly offered AuNPs-pTab sensor has demonstrated excellent peroxidase-like activity and gives an easy substitute for AuNPs solution with enhanced catalytic efficiency. Additionally, the AuNPs-pTab sensor is a promising platform for point-of-care devices due to its fulfillment of RE-ASSURED criteria (Real-time, Ease of specimen collection, Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment-free, and Deliverable to end users) which is considered of great importance in the field of diagnosis and detection. AuNPs-pTab sensor is an attractive tool that has the potential to open a new horizon in disease diagnosis due to its functionality in H2O2 detection which is a possible biomarker for many diseases. Even though a range of nanozymes has been reported to date for their enzyme-mimicking catalytic activity as a solution-based sensor. However, in remote areas, the need for portable, cost-effective, and one-pot preparation is extremely demanding. Therefore, this work is appealing to researchers working in nanotechnology, and the advancement of innovative portable bioassays as well as point-of-care devices.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».