Label-Free Antibody Detection Using a Screen-Printed Organic Electrochemical Transistor (OECT) Platform
Notice bibliographique
Résumé
Cancer is one of the leading causes of mortality worldwide, and early detection is critical to improving patient survival rates [1].Despite progress in diagnostic technologies, identifying cancer at its earliest stages remains a major challenge.Conventional methods such as imaging and biopsies often detect cancer only after it has progressed, limiting treatment options and reducing survival prospects [2].These techniques are also invasive, time-consuming, and dependent on specialized infrastructure, making them less accessible particularly in lowresource environment.This emphasizes the urgent need for innovative, sensitive, and cost-effective diagnostic tools that can be deployed at the point of care.In recent years, antibodies have emerged as valuable biomarkers for early diagnosis of cancer, autoimmune disorders, and infectious diseases.Their presence in bodily fluids reflects specific immune responses, often preceding the onset of clinical symptoms [3,4].However, commonly used antibody detection techniques such as flow cytometry, Enzyme-linked Immunosorbent assay (ELISA), and Western blotting are typically labelled, laborintensive, and reliant on centralized laboratory infrastructure [5].These factors limit their applicability in rapid and decentralized diagnostic settings.To address these limitations, we have developed a biosensing platform based on Organic Electrochemical Transistors (OECTs) for the selective and label-free detection of antibodies.OECTs offer several advantages for biosensing applications, including high transconductance, low-voltage operation, simple fabrication, and inherent signal amplification [6].In this study, we demonstrate an OECT-based biosensor designed for the detection of immunoglobulin G (IgG) and immunoglobulin M (IgM) antibodies in phosphate-buffered saline (PBS) solution.The sensor was fabricated by functionalizing the gate electrode with anti-IgG and anti-IgM antibodies to enable selective binding.Upon exposure to target antibodies, specific binding events at the gate interface caused measurable changes in the drain current, which were recorded through amperometric titration.We performed a series of experiments to evaluate the sensor's performance, including the detection of individual antibodies and the assessment of cross-reactivity using mixed samples (IgG + IgM).The biosensor exhibited high sensitivity, excellent selectivity, and effectively distinguishing between antibody isotypes even in the presence of mixed analytes.This proof-of-concept study highlights the potential of OECTs for real-time, label-free immunoassays.The platform is low-cost, scalable, and adaptable, making it a strong candidate for point-of-care diagnostics and early disease screening.While this work focuses on antibody detection, the sensing approach provides a solid foundation for future development aimed at the selective capture of cancer-associated extracellular vesicles (EVs) through antibody-based recognition.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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.
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