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Record W2044182035 · doi:10.1159/000183024

Ultrastructure of Normal Rabbit Mesentery

2008· article· en· W2044182035 on OpenAlexaff
Lázaro Gotloib, George E. Digenis, Sol Rabinovich, Alan Medline, Dimitrios G. Oreopoulos

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsUltrastructureVesicleMesothelial CellElectron microscopePathologyMesotheliumLymphatic systemAnatomyBasement membraneGlycocalyxMesenteryEndotheliumBiologyCell biologyMedicineChemistryMembraneBiochemistryEndocrinology

Abstract

fetched live from OpenAlex

The ultrastructure of the mesentery was examined by electron microscope (EM) after in vivo fixation in 7 normal rabbits. In 1, the fixation was performed after intravenous injection of an electron-dense tracer (iron dextran) and intraperitoneal infusion of dialysate 4.25% for 1 h. We studied morphometric data of what is considered to be the active peritoneal dialysis membrane, i.e. capillary endothelial cells, interstitium and mesothelial cells. The mesothelial cells are flattened and overlapping with tight junctions between them. They lie on a continuous basement membrane and they contain numerous intracytoplasmic vesicles, separated or in clusters. The mesenteric microvessels were mainly true capillaries of continuous type and postcapillary venules. Capillary lymphatics and larger lymphatic channels (lacunae) seem to be more extensive than the blood capillaries and venules. The endothelial cells contain many vesicles. The interstitium consists of bundles of collagen, fibroblasts and occasional macrophages. The electron-dense tracer was found in the vesicles of the mesothelial cells suggesting that vesicular transport may play an important part in the transportation of at least molecules of a certain size.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.025
GPT teacher head0.280
Teacher spread0.255 · 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.

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

Citations72
Published2008
Admission routes1
Has abstractyes

Explore more

Same venue˜The œNephron journals/Nephron journalsSame topicDialysis and Renal Disease ManagementFrench-language works237,207