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Record W3012944770 · doi:10.1139/cjpp-2019-0537

Temperature-dependent effects on CO<sub>2</sub> water bath therapy induced changes in blood flow and vascularity in hind limb ischemia

2020· article· en· W3012944770 on OpenAlexaffvenue
Vijayan Elimban, Yan‐Jun Xu, Sukhwinder K. Bhullar, Naranjan S. Dhalla

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2020
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsSt. Boniface Hospital
Fundersnot available
KeywordsBlood flowHindlimbIschemiaMedicineFemoral arteryVascularityArteryCardiologyAnesthesiaLimb ischemiaInternal medicineEndocrinologySurgery

Abstract

fetched live from OpenAlex

To test if magnitudes of the beneficial actions of CO2 water bath therapy on blood flow and vascular density are dependent upon temperature, ischemia in the hind limb of rats was induced by occluding the left femoral artery for 2 weeks and the animals were exposed to water bath therapy with or without CO2 at 34 or 41 °C for 4 weeks (20 min treatment each day for 5 days/week). CO2 water bath therapy at 34 °C increased peak, minimal, and mean blood flow by 190%–600% in the ischemic limb. On the other hand, CO2 water bath treatment at 41 °C increased these parameters of blood flow by 37%, 55%, and 41%, respectively, in the ischemic limb. The small blood vessel count, an index of vascular density, in the ischemic limb was increased by CO2 water bath therapy at 34 and 41 °C by 32% and 122%, respectively. No changes in the ischemic animals by CO2 water bath therapy at 34 or 41 °C were observed in the heart rate, R–R interval, and plasma lipid or glucose levels. These data indicate that the beneficial effect of CO2 water bath therapy at 34 °C on blood flow in the ischemic muscle is greater whereas that on vascular density is smaller than changes in these parameters at 41 °C.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.271
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 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

Citations3
Published2020
Admission routes2
Has abstractyes

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