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Record W4392291464 · doi:10.1101/2024.02.27.582351

L-Type Ca <sup>2+</sup> channels and TRPC3 channels shape brain pericyte Ca <sup>2+</sup> signaling and hemodynamics throughout the arteriole to capillary network <i>in vivo</i>

2024· preprint· en· W4392291464 on OpenAlexafffund
Jessica Meza-Resillas, Finnegan O’Hara, Syed Kaushik, Michael Stobart, Noushin Ahmadpour, Meher Kantroo, Shahin Shabanipour, John Smith Del Rosario, Megan Rodriguez, Dmytro Koval, Chaim Glück, Bruno Weber, Jillian L. Stobart

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsUniversity of Manitoba
FundersResearch ManitobaAzrieli FoundationHealth CanadaUniversity of ManitobaGovernment of CanadaNatural Sciences and Engineering Research Council of CanadaFondation Brain Canada
KeywordsArterioleIn vivoPericyteTRPC3ChemistryBiophysicsPhysicsBiologyIn vitroTRPCInternal medicineMicrocirculationBiochemistryMedicineGenetics

Abstract

fetched live from OpenAlex

Abstract Pericytes play a crucial role in regulating cerebral blood flow (CBF) through processes like vasomotion and neurovascular coupling (NVC). Recent work has identified different pericyte types at distinct points in the cerebrovascular network, such as the arteriole-capillary transition zone (ACT) and distal capillaries, sparking debate about their functional roles in blood flow control. Part of this discussion has comprised the possible mechanisms that may regulate pericyte Ca 2+ signaling. Using in vivo two-photon Ca 2+ imaging and a pharmacological approach with Ca 2+ channel blockers (nimodipine and Pyr3), we assessed the contribution of L-type voltage-gated Ca 2+ channels (VGCC) and transient receptor potential canonical 3 (TRPC3) channels to Ca 2+ signaling in different pericyte types, ensheathing and capillary pericytes. We also measured local hemodynamics such as vessel diameter, blood cell velocity and flux during vasomotion, and following somatosensory stimulation to evoke NVC. We report that VGCC and TRPC3 channels underlie spontaneous fluctuations in ensheathing pericyte Ca 2+ that trigger vasomotor contractions, but the contribution of each of these mechanisms to vascular tone depends on the specific branch of the ACT. Distal capillary pericytes also express L-type VGCCs and TRPC3 channels and they mediate spontaneous Ca 2+ signaling in these cells. However, only TRPC3 channels maintain resting capillary tone, possibly by a receptor-operated Ca 2+ entry mechanism. By applying the Ca 2+ channel blockers during NVC, we found a significant involvement of L-type VGCCs in both pericyte types, influencing their ability to dilate during functional hyperemia. These findings provide new evidence of VGCC and TRPC3 activity in pericytes in vivo and establish a clear distinction between brain pericyte types and their functional roles, opening avenues for innovative strategies to selectively target their Ca 2+ dynamics for CBF control. Significance Statement Although brain pericytes contribute to the regulation of CBF, there is uncertainty about how different types of pericytes are involved in this process. Ca 2+ signaling is believed to be important for the contractility and tone of pericytes, but there is a limited understanding of the Ca 2+ pathways in specific pericyte types. Here, we demonstrate that both VGCC and TRPC3 channels are active in distinct types of pericytes throughout the cerebrovascular network, but have different roles in pericyte tone depending on the pericyte location. This has important implications for how pericytes influence vasomotion and neurovascular coupling, which are central processes in CBF regulation. This work also provides the first evidence of TRPC3 channel activity in pericytes in vivo , furthering our understanding of the diverse signaling pathways within these brain mural cells.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.239
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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