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Record W4414902753 · doi:10.1139/cjpp-2024-0383

Finding a link between the TRPV4 ion channel and angiogenesis: a potential therapeutic target for vascular remodeling

2025· article· en· W4414902753 on OpenAlexaffvenue
Gabriel Malka, Vanessa Salucci, Andreas Bergdahl

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsConcordia University
Fundersnot available
KeywordsTRPV4AngiogenesisAgonistTransient receptor potential channelAntagonistTherapeutic angiogenesisBlood vesselTRPC1Voltage-dependent calcium channel

Abstract

fetched live from OpenAlex

Angiogenesis, the formation of new blood vessels, is crucial in ischemic heart disease to improve blood supply to the heart. Meanwhile, in cancer, inhibiting angiogenesis can limit tumor growth by reducing oxygen and nutrients. Calcium ions, key in cellular functions like proliferation and migration, play an important role in this process. Transient Receptor Potential Cation Channel, Vanilloid Subfamily Member 4 (TRPV4), a calcium-permeable channel, is highly expressed in endothelial cells lining blood vessels. This study explored the connection between TRPV4 and angiogenesis using an aortic ring assay. Aortic rings from 3-day-old C57Bl/6 pups were exposed to TRPV4 agonist (GSK1016790) and antagonist (HC067047) and standard growth media (control) after which maximal length and number of new sprouts were measured. The study found that the antagonist significantly reduced the number and length of new micro vessels, while the agonist increased sprout length. These findings highlight TRPV4's role in vascular remodeling, suggesting it could be a therapeutic target for treating diseases related to impaired blood flow and abnormal angiogenesis.

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 score0.003
Threshold uncertainty score0.009

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.293
Teacher spread0.258 · 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
Published2025
Admission routes2
Has abstractyes

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