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Record W3173512342 · doi:10.1096/fasebj.21.6.lb109-b

Histamine levels during postexercise hypotension assessed by skeletal muscle microdialysis in inactive limbs

2007· article· en· W3173512342 on OpenAlexaff
Jennifer L. McCord, John R. Halliwill, Cara J. Weisbrod, David A. MacLean

Bibliographic record

VenueThe FASEB Journal · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsNOSM University
FundersAmerican Historical Association
KeywordsMicrodialysisHistamineBicepsSkeletal muscleInternal medicineEndocrinologyChemistryInterstitial fluidMedicineAnesthesiaAnatomyCentral nervous system

Abstract

fetched live from OpenAlex

The activation of histamine receptors in skeletal muscle has been implicated as a major mediator of postexercise hypotension. The purpose of this study was to examine the role that histamine plays in postexercise hypotension in humans. Histamine detection by microdialysis was tested by infusing compound 48–80 (a mast cell degranulator) through microdialysis probes inserted into the biceps muscle of resting humans. Interstitial histamine levels increased (P<0.05) from 2.46±.96 pre‐infusion to 6.81±0.74 ng/ml post‐infusion, confirming our ability to measure changes in endogenous histamine concentrations. Subsequently, six subjects had microdialysis probes inserted into their biceps muscle (inactive) 75 min prior to lower limb cycling exercise at 60% Vo 2 peak for 60 min. Dialysate histamine concentrations were 2.22±0.21 before, 1.71±0.19 during, and 1.09±0.18 ng/ml after exercise and were not significantly different across time. These data indicate that muscle interstitial histamine levels do not increase during or following exercise in inactive limb muscles. Therefore, the next step will be to examine whether histamine levels are altered in the active limb muscles during the postexercise period by directly measuring histamine concentrations via microdialysis in the exercised muscle. Supported by AHA 0555623Z.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.592
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.241
Teacher spread0.224 · 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.

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
Published2007
Admission routes1
Has abstractyes

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