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Record W2098814720 · doi:10.1152/ajpheart.00383.2002

Deficiency in endothelial nitric oxide synthase impairs myocardial angiogenesis

2002· article· en· W2098814720 on OpenAlexaff
Xue Zhao, Xiangru Lu, Qingping Feng

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2002
Typearticle
Languageen
FieldMedicine
TopicNitric Oxide and Endothelin Effects
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
Fundersnot available
KeywordsEnosAngiogenesisMatrigelInternal medicineEndocrinologyNitric oxide synthaseIn vivoNeovascularizationNitric oxideMedicineBiologyChemistry

Abstract

fetched live from OpenAlex

We recently demonstrated that mice deficient in endothelial nitric oxide (NO) synthase (eNOS) have congenital septal defects and postnatal heart failure. However, the mechanisms by which eNOS affects heart development are not clear. We hypothesized that deficiency in eNOS impairs myocardial angiogenesis. Myocardial capillary densities were measured morphometrically in neonatal mouse hearts. In vitro tube formation on Matrigel was investigated in cardiac endothelial cells. In vivo myocardial angiogenesis was performed by implanting Matrigel in the left ventricular myocardium. Myocardial capillary densities and VEGF mRNA expression were decreased in neonatal eNOS(-/-) compared with neonatal wild-type mice (P < 0.01). Furthermore, in vitro tube formation from cardiac endothelial cells and in vivo myocardial angiogenesis were attenuated in eNOS(-/-) compared with wild-type mice (P < 0.01). In vitro tube formation was inhibited by N(G)-nitro-l-arginine methyl ester in wild-type mice and restored by a NO donor, diethylenetriamine-NO, in eNOS(-/-) mice (P < 0.05). In conclusion, deficiency in eNOS decreases VEGF expression and impairs myocardial angiogenesis and capillary development. Decreased myocardial angiogenesis may contribute to cardiac abnormalities during heart development in eNOS(-/-) mice.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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 designObservational
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

Citations110
Published2002
Admission routes1
Has abstractyes

Explore more

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