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Record W1976393840 · doi:10.1159/000158461

Ultrastructural Changes in Mesenteric Arteries from Spontaneously Hypertensive Rats

2008· article· en· W1976393840 on OpenAlexaff
R.M.K.W. Lee, James B. Forrest, R. E. Garfield, E. E. Daniel

Bibliographic record

VenueBlood Vessels · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInternal elastic laminaMuscle hypertrophyElastinHyperplasiaAnatomyMesenteric arteriesMedicineBlood vesselSmooth muscleSpontaneously hypertensive ratInternal medicinePathologyChemistryBlood pressureArtery

Abstract

fetched live from OpenAlex

Morphometric measurements at the electron microscope level were carried out on three categories of mesenteric arteries representing elastic (superior mesenteric), muscular and arteriolar vessels, from 10- to 12-week-old spontaneously hypertensive rats (SHR) and age-matched Wistar-Kyoto normotensive rats (WKY). Changes were observed only in muscular and arteriolar vessels of SHR, mainly as thickening of the vessel wall due to hypertrophy of the media. In muscular arteries, hypertrophy of the endothelial cells, widening of the subendothelial space, increased volume of the internal elastic lamina (IEL), and both hyperplasia and hypertrophy of the smooth muscle cells (SMC) in the media contributed to the wall thickening. In arteriolar vessels, increase in the subendothelial space and IEL, and hyperplasia of the SMC in the media were involved in the increased thickness of the vessel wall. There was no difference in the collagen content in all vessels, but elastin was increased in the muscular and arteriolar vessels of SHR. Nerve density was also increased in arteriolar vessels of SHR. These changes, especially the increase of SMC in muscular and arteriolar vessels, may be related to the elevated blood pressure in SHR.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.244
Teacher spread0.227 · 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

Citations64
Published2008
Admission routes1
Has abstractyes

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