An innovative cellular medicine approach via the utilization of novel nanotechnology-based biomechatronic platforms as a label-free biomarker for early melanoma diagnosis
Notice bibliographique
Résumé
Innovative cellular medicine (ICM) is an exponentially emerging field with a promising approach to combating complex and ubiquitous life-threatening diseases such as multiple sclerosis (MS), arthritis, Parkinson's disease, Alzheimer's, heart disease, and cancer. Together with the advancement of nanotechnology and bio-mechatronics, ICM revolutionizes cellular therapy in understanding the essence and nature of the disease initiated at a single-cell level. This paper focuses on the intricate nature of cancer that requires multi-disciplinary efforts to characterize it well in order to achieve the objectives of modern world contemporary medicine in the early detection of the disease at a cellular level and potentially arrest its proliferation mechanism. This justifies the multidisciplinary research backgrounds of the authors of this paper in advancing cellular medicine by bridging the gap between experimental biology and the engineering field. Thus, in pursuing this approach, two novel miniaturized and highly versatile biomechatronic platforms with dedicated operating software and microelectronics are designed, modeled, nanofabricated, and tested in numerous in vitro experiments to investigate a hypothesis and arrive at a proven theorem in carcinogenesis by interrelating cellular contractile force, membrane potential, and cellular morphology for early detection and characterization of melanoma cancer cells. The novelties that flourished within this work are manifested in sixfold: (1) developing a mathematical model that utilizes a Heaviside step function, as well as a pin-force model to compute the contractile force of a living cell, (2) deriving an expression of cell-membrane potential based on Laplace and Fourier Transform and their Inverse Transform functions by encountering Warburg diffusion impedance factor, (3) nano-fabricating novel biomechatronic platforms with associated microelectronics and customized software that extract cellular physics and mechanics, (4) developing a label-free biomarker, (5) arrive at a proved theorem in developing a mathematical expression in relating cancer cell mechanobiology to its biophysics in connection to the stage of the disease, and (6) to the first time in literature, and to the best of the authors' knowledge, discriminating different stages and morphology of cancer cell melanoma based on their cell-membrane potentials, and associated contractile forces that could introduce a new venue of cellular therapeutic modalities, preclinical early cancer diagnosis, and a novel approach in immunotherapy drug development. The proposed innovative technology-based versatile bio-mechatronic platforms shall be extended for future studies, investigating the role of electrochemical signaling of the nervous system in cancer formation that will significantly impact modern oncology by pursuing a targeted immunotherapy approach. This work also provides a robust platform for immunotherapy practitioners in extending the study of cellular biophysics in stalling neural-cancer interactions, of which the FDA-approved chimeric antigen receptor (CAR)-T cell therapies can be enhanced (genetically engineered) in a lab by improving its receptors to capture cancer antigens. This work amplifies the importance of studying neurotransmitters and electrochemical signaling molecules in shaping the immune T-cell function and its effectiveness in arresting cancer proliferation rate (mechanobiology mechanism).
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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 | 0,000 |
| 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 | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| 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 ».