Ultrasound biomicroscopy: a non-invasive approach for in vivo evaluation of oocytes and small antral follicles in mammals
Bibliographic record
Abstract
The use of ultrasonography has changed our understanding of the ovarian function in live animals. However, most of the studies that have used ultrasonography to image the ovary have provided data only of structures >1mm in diameter. The recent availability of high-resolution ultrasound technology with high-frequency transducers (25-70 MHz), offers the potential to examine the developmental dynamics of small antral follicles and the cumulus-oocyte complex (COC) in vivo. In this review we provide data from a series of studies performed by Veterinary Biomedical Sciences Laboratory describing the advantages and disadvantages, as well as image characteristics, of ultrasound biomicroscopy (UBM) to study ovarian biology in mammals. Data and images of small ovarian structures in rabbits, cattle, mice and humans are shown. The UBM technique allowed visualisation of small antral follicles ranging in size from 300 to 700 μm in all species examined, as well as COC within follicles in rabbits, cattle and humans. Furthermore, UBM permitted clear distinction of the follicular wall from the surrounding ovarian stroma in cattle and humans. At present, the limited depth of penetration of UBM restricts the use of this technique to an experimental setting. In that regard, further studies using UBM will probably result in a greater understanding of the pattern and control of early antral folliculogenesis and oogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".