Morphological patterns of angiogenesis in ovarian follicle capillary networks. A scanning electron microscopy study of corrosion cast
Bibliographic record
Abstract
To describe the morphological characteristics of the ovarian follicle (F) capillary neoformation and regression, the angiogenic figures were studied by means of scanning electron microscopy of corrosion casts in developing and mature F of rabbit, pig, and cow. Developing F showed gradual neoformation of thecal capillaries characterized by budding and then sprouting, likely from preexisting interstitial vessels. Postcapillary venules frequently showed vasoconstriction rings (sphincters). Vasodilation followed capillary elongation. Mature F, in addition to vessel elongation and dilation, also presented infolding of dilated capillary walls, followed by capillary duplication and sinusoidalization. Periovulatory F mainly showed functional changes, such as capillary dilation, signs of iperpermeabilization, and ischemia, the latter being limited to the apical follicular area. Vessel regression was characterized by thinning of capillaries and presence of avascular areas within the atretic F wall at any stage. This study showed two main types of angiogenic patterns. (a) longitudinal elongation (in series, sprouting angiogenesis) characterizing the initial phase of F development and (b) parallel duplication (in parallel, infolding or intussusceptive angiogenesis), ending in capillary lateral replication or splitting, secondary to functional microvascular changes. Indirect evidence of the establishment of postcapillary resistances contributing to capillary remodeling, was also shown. It is concluded that the sequence of capillary neoformation in mammalian ovarian F occurs in six steps: (1) budding, (2) sprouting (and elongation), (3) dilation, (4) infolding (intussusception), (5) duplication (splitting and elongation), and (6) sinusoidalization. Capillary regression hits F at any stage and characterizes F atresia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".