MétaCan
Menu
Back to cohort
Record W2807296086 · doi:10.1139/cjpp-2018-0160

Effects of CO<sub>2</sub> water-bath treatment on blood flow and angiogenesis in ischemic hind limb of diabetic rat

2018· article· en· W2807296086 on OpenAlexaffvenue
Yan‐Jun Xu, Vijayan Elimban, Sukhwinder K. Bhullar, Naranjan S. Dhalla

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsSt. Boniface Hospital
Fundersnot available
KeywordsMedicineHindlimbIschemiaDiabetes mellitusFemoral arteryBlood flowStreptozotocinLigationPeripheralArteryInternal medicineLimb ischemiaEndocrinologyAnesthesia

Abstract

fetched live from OpenAlex

The effects of CO 2 water-bath therapy on the hind limb of diabetic animals with or without peripheral ischemia were examined. Diabetes was induced in rats by administering streptozotocin (65 mg·kg −1 ), and the animals were then divided into 3 groups. After 4 weeks, peripheral ischemia was induced by ligation of the femoral artery for 2 weeks in 2 groups (diabetic ischemic) of diabetic rats, whereas the femoral artery was not occluded in the third group (diabetic). All these animals were subjected to water-bath therapy (with or without CO 2 mixing; 20 min·day −1 for 5 days·week −1 ) for a period of 4 weeks. Both peak and mean flows, unlike minimal flow, in diabetic ischemic limbs were increased about a twofold by CO 2 water-bath treatment. Morphological examination of hind limb tissue sections revealed about a twofold increase in the small artery count in diabetic ischemic animals upon CO 2 water-bath treatment. These results indicate that CO 2 water-bath therapy augments the blood flow and development of angiogenesis in the skeletal muscle of diabetic ischemic animals and thus may be of some benefit for the treatment of peripheral arterial disease in diabetes.

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 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 score0.006
Threshold uncertainty score0.457

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)0.0000.000

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 head0.006
GPT teacher head0.238
Teacher spread0.231 · 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

Citations12
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicAngiogenesis and VEGF in CancerFrench-language works237,207