Early Diagnosis of Small Fiber Neuropathies By Electrochemical Means: Optimization of Sensing Materials
Notice bibliographique
Résumé
Small fiber neuropathy is a dysfunction caused by diseases such as type II diabetes and cystic fibrosis. Nowadays, it is possible to analyze neuropathy with Sudoscan TM technology (Impeto Medical Inc.) which provides a rapid and non-invasive early diagnosis. This technology is based on measurements of the electrochemical conductance of the skin via the imposition of low amplitude voltages between electrodes applied to the skin and measuring the low current generated. The output measurement is related to the sweat composition associated to glands innervations and their permeability to chloride and proton ions [1]. The results obtained with this in vivo technology show a typical anode current response (curve J-E) with a significant offset and a linear part. The characteristic shape of the J-E graph easily indicates the type of disease and its progress [2]. To have a deeper understanding of the mechanisms occurring at electrodes and optimize the sensitivity of the instrument, in vitro experiments were performed in mimetic electrolytic solutions of sweat. Preliminary in vitro experiments led to same shapes than in vivo but with larger current densities (≈ 50 times greater than those obtained in vivo ) . This phenomenon is probably due to the high resistivity of a human body and the difference of the electrodes system between in vitro and in vivo measurements. For these reasons, it was necessary to modify in vitro conditions to get similar current densities and mimic realistically in vivo conditions. To this end, major modifications in the in vitro system were realized: (i) Concerning the in vitro configuration: the electrodes arrangement was changed and 3 identical electrodes were used leading to a decrease in the current densities by a factor of 10 (ii) To simulate the body resistance and, consequently, to decrease the current densities in vitro , the electrolyte composition was optimized by increasing its viscosity to reduce the flux of chloride ions to the electrode surface. The new composition allowed to reach current densities close to those obtained in vivo [3] . The aim of this work was to find the optimized electrolyte, mimicking sweat in terms of composition and the resistance of the human body under in vitro conditions. Then, the goal was to go deeper in the knowledge on the mechanism governing the electrode response to sweat. For this, linear voltammetry and electrochemical impedance spectroscopy were implemented to study the influence of sweat components such as pH, chloride concentration, buffer and carbonate concentration on a nickel model electrode [4]. Finally, different stainless steel electrodes were tested. Such electrodes are required because they are not allergenic and less expensive than nickel, but they need to be sensible to ions detection in sweat, with reproducible results allowing the early detection of diseases. References: [1] A. Calmet, H. Ayoub, V. Lair, and S. Griveau, Actual. Chim. , vol. 390, pp. 48–49, 2014. [2] P. Brunswick and N. Bocquet, “Système d’analyse électrophysiologique,” 0753461. [3] A. Calmet, K. Khalfallah, H. Ayoub, V. Lair, S. Griveau, P. Brunswick, F. Bedioui, and M. Cassir, Electrochim. Acta , vol. 140, pp. 37–41, Sep. 2014. [4] H. Ayoub , S. Griveau, V. Lair, P. Brunswick, M. Cassir, and F. Bedioui, Electroanalysis , vol. 22, no. 21, pp. 2483–2490, Nov. 2010.
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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 | 0,000 | 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 | 0,000 | 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 ».