Relationships between Ultrasonographic Image Attributes, Histomorphology and Proliferating Cell Nuclear Antigen Expression of Bovine Antral Follicles and Corpora Lutea <i>ex situ</i>
Bibliographic record
Abstract
The aim of this study was to examine the relationships between quantitative ultrasonographic image characteristics, histological attributes and cell proliferating ability of bovine antral follicles and corpora lutea (CL) ex situ. Bovine ovaries (n = 30) from animals at various reproductive states (metoestrus-early dioestrus, n = 8; mid-dioestrus, n = 12; oestrous phase of peripubertal heifers, n = 6; and pregnancy, n = 4) were collected at the slaughterhouse. High-resolution ultrasonographic images of the ovaries were obtained in the water bath, digitized and subjected to computerized image analyses. The analyses utilized line and spot techniques designed to determine pixel values of the follicular wall (the largest follicles >2 mm in diameter in each ovary) and CL, respectively. Individual ovarian structures were dissected and processed for histology and immunohistochemical detection of proliferating cell nuclear antigen (PCNA). The mean follicular diameter was negatively correlated with total cell density (r = -0.45, p < 0.05), granulosa layer thickness (r = -0.67, p < 0.001) and the percentage of PCNA-positive cells (r = -0.57, p < 0.001). Numerical pixel values and heterogeneity of the follicular wall were positively correlated with total cell density (r = 0.42, p < 0.05 and r = 0.62, p < 0.05; respectively), granulosa layer thickness (both r = 0.39, p < 0.05), and the percentage of PCNA-positive cells (r = 0.54, p < 0.01 and r = 0.69, p < 0.001, respectively). Estimates of cell density and proliferating cell index were not correlated with the ultrasonographic image attributes of CL. We conclude that follicular size and echotextural variables, as determined by computer-assisted image analysis of ovaries ex situ, are reliable markers of the histophysiological properties of bovine antral follicles, but the ultrasonographic characteristics are not indicative of cell density and proliferation in the bovine CL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".