A Mathematical Model of Plasma Membrane Electrophysiology of a Brain Capillary Pericyte: Investigating Pericyte Contribution to the Electrical Properties of the Capillary Network
Notice bibliographique
Résumé
Introduction Pericyte cells (PCs) are specialized cells found primarily on the abluminal surface of capillary blood vessels alongside endothelial cells (ECs). They play a role in angiogenesis, formation of the blood‐brain barrier, as well as in the regulation of blood flow. Due to their contractile nature, PCs can modulate capillary diameter and perfusion, however, little is known regarding their contribution to the electrical properties of the capillary network. Furthermore, recent studies show that capillaries can sense neural activity in the brain and transmit electrical signals to upstream feeding arterioles and arteries to match blood supply to local demand. Although passive electrotonic spread underlies signal propagation along the endothelium in larger vessels, evidence for amplification of transmitted signals and preferential upstream propagation have been presented in vessels as branching order increases. We use mathematical modeling to test under what conditions a PC can affect the electrical properties of the capillary network and whether it can act as a sink or an amplifier of conducted hyperpolarization. Methods A PC and an EC model incorporate the dynamic behavior of known plasma membrane currents, release and uptake of Ca 2+ by intracellular stores and dynamic tracking of ionic (Ca 2+ , K + , Na + , and Cl − ) concentrations in the cytosol (Fig. 1). The PC is electrically coupled to capillary ECs through gap junctions and a multicellular model of a capillary network is created. Electrical signal attenuation is examined following hyperpolarizing stimuli at capillary ends in the presence as well as absence of PCs at network bifurcations. Results Cell models predict physiological resting membrane potential and ionic concentrations. Model predictions were compared against experimental responses to agonist stimulation and K + challenge for validation. Simulations show that a sufficient inwardly rectifying K + , Kir, channel current density may allow PCs to amplify conducted hyperpolarization. Increased coupling between a PC with the parent relative to the daughter capillaries at a bifurcation may allow preferential conduction of an electrical signal upstream the vascular network. Conclusion A detailed model of a brain capillary pericyte was developed and validated against experimental data. Model simulations suggest that with sufficient Kir density, pericytes can amplify conducted hyperpolarization and regulate the distance and direction of propagating vasodilation and thus blood flow distribution in the vascular network. Support or Funding Information This work was supported by the Ronald E. McNair Post‐Baccalaureate Achievement Program. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0,001 | 0,001 |
| 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 | 0,001 |
| 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 ».