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Inhibition of NOS Does Not Affect Oxygen Dependent Capillary Blood Flow Response In Vivo

2017· article· en· W4389017927 on OpenAlexaff
Graham Fraser, Stephanie Milkovich, Christopher G. Ellis

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsWestern UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsChemistryAnatomyBlood flowNitric oxideSalineNitric oxide synthaseAnesthesiaInternal medicineMedicine

Abstract

fetched live from OpenAlex

Objective To determine if nitric oxide (NO) plays a significant role in regulating blood flow, in response to changing oxygen (O 2 ) conditions within skeletal muscle capillaries. Methods Five male Sprague‐Dawley rats, 140 – 190g rats were anaesthetized with pentobarbital, tracheotomized, ventilated, and maintained in a normotensive state. A laparotomy was performed and the left common iliac was catheterized with a cannula advanced retrograde to the distal abdominal aorta. The extensor digitorum longus muscle was blunt dissected and reflected onto a glass cover slip (dose response), or permeable membrane above a gas exchange chamber (O 2 response) set within a microscope stage. The muscle was bathed in warm saline and isolated from the air via polyvinylidene chloride film and a glass coverslip. Dose response was determined in 3 animals by injecting a nitric oxide synthase inhibitor, L‐NMMA, in logarithmic increasing concentrations ranging from 10 −5 to 1 mg/kg into the iliac artery. O 2 dependent blood flow responses were determined in 2 animals. Gas concentrations (N 2 , CO 2 , and O 2 ) within the exchange chamber were dynamically controlled using mass flow valves connected to a computer. The muscle was allowed to equilibrate for 30 minutes at 5% CO 2 , 5% O 2 and 90% N 2 . O 2 concentrations at the surface of the muscle were oscillated from 7%–12%‐2%–7% in a square‐wave with each level maintained for 60s. CO 2 was held at a constant 5% with N 2 composing the balance of gas within the exchange chamber. Video sequences of capillary blood flow at 10× magnification were recorded in multiple fields in each animal. Videos were analyzed offline using custom software written in MATLAB yielding frame‐by‐frame measurements of capillary velocity, hematocrit and red blood cell supply rate (SR). Results Capillary blood flow dose response for L‐NMMA was measured in 178 capillaries under baseline, and increasing concentrations of L‐NMMA. All L‐NMMA concentrations caused a significant decrease in SR compared to vehicle () with a 42% reduction at 10 −2 mg/kg; higher doses did not result in a further decrease of SR. The time dependent O 2 blood flow response was measured in 58 capillaries under baseline conditions and after infusion of 10 −2 mg/kg L‐NMMA (). An average phase lag of 20 s was observed in the SR response to O 2 concentration changes in the chamber under both conditions. Phase lag was partially due to the intrinsic time delay of the gas delivery system. Average SR under 7% O 2 concentration was 45% lower with L‐NMMA compared to control. High O 2 caused a decrease in SR of 53% for control vs. 60% under L‐NMMA, normalized to the baseline mean SR at 7% O 2 . Low O 2 caused an increase in SR of 14% and 47% with control and L‐NMMA respectively. Post oscillation, 7% O 2 restored average SR to 93% and 100% of baseline in control and L‐NMMA respectively. Conclusion Alteration of tissue surface O 2 causes an O 2 dependent capillary blood flow response to both low and high O 2 challenges that is preserved following the introduction of a nitric oxide synthase inhibitor. This suggests that NO does not play a significant role in regulating blood flow, in response to changing O 2 conditions within skeletal muscle capillaries.

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 score0.005

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 head0.017
GPT teacher head0.262
Teacher spread0.245 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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