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Role of voltage‐dependent calcium channels in stretch‐induced lymphatic vessel contractions

2013· article· en· W3170679186 on OpenAlexaff
Stewart S Lee, Pierre‐Yves von der Weid

Bibliographic record

VenueThe FASEB Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicLymphatic System and Diseases
Canadian institutionsUniversity of Calgary
FundersNational Institutes of Health
KeywordsMibefradilLymphatic systemNifedipineChemistryVoltage-dependent calcium channelElectrophysiologyAnatomyCalcium channelDiltiazemCalciumInternal medicineMedicinePathology

Abstract

fetched live from OpenAlex

Lymph drainage maintains tissue fluid homeostasis and facilitates immune response. It is promoted by phasic contractions of lymphatic vessels, which increase in rate with increase in luminal pressure. The contractions depend on activation of voltage‐dependent calcium channel (VDCC), which have not been characterized in lymphatic vessels. We used pressure‐ and wire‐myography, electrophysiology, PCR and immunofluorescence imaging to investigate the electrophysiological properties of L‐type and T‐type VDCCs and their role on stretch‐induced lymphatic contractions. Members of the VDCC family were expressed at the messenger RNA and protein level in rat mesenteric lymphatic vessels. The stretch‐induced increase in force was significantly attenuated in the presence of L‐type VDCC blockers nifedipine and diltiazem, while the T‐type VDCC blockers mibefradil and nickel significantly decreased the stretch‐induced increase in contraction frequency. Furthermore, nifedipine and diltiazem depolarized, while mibefradil and nickel hyperpolarized lymphatic muscle membrane potential. Our data suggest a delineating role of VDCCs in stretch‐induced lymphatic vessel contractions. We propose that activation of T‐type VDCC depolarizes membrane potential, regulating the frequency of lymphatic contractions via opening of L‐type VDCCs, which drive the strength of contractions. Supported by NIH

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.024
GPT teacher head0.274
Teacher spread0.250 · 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 teacher head, not a consensus.

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

Citations1
Published2013
Admission routes1
Has abstractyes

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