CLARITY reveals dynamics of ovarian follicular architecture and vasculature in three-dimensions
Bibliographic record
Abstract
Abstract Optimal distribution of heterogeneous organelles and cell types within an organ is essential for physiological processes. Unique for the ovary, hormonally regulated folliculogenesis, ovulation, luteal formation/regression and associated vasculature changes lead to tissue remodeling during each reproductive cycle. Using the CLARITY approach and marker immunostaining, we identified individual follicles and corpora lutea in intact ovaries. Monitoring lifetime changes in follicle populations showed age-dependent decreases in total follicles and percentages of advanced follicles. Follicle development from primordial to preovulatory stage was characterized by 3 × 10 5 -fold increases in volume, decreases in roundness, and decreased clustering of same stage follicles. Construction of follicle-vasculature relationship maps indicated age- and gonadotropin-dependent increases in vasculature and branching surrounding follicles. Heterozygous mutant mice with deletion of hypoxia-response element in the vascular endothelial growth factor A (VEGFA) promoter showed defective ovarian vasculature and decreased ovulatory responses. Unilateral intrabursal injection of axitinib, an inhibitor of VEGF receptors, retarded neo-angiogenesis that was associated with defective ovulation in treated ovaries. Our approach uncovers unique features of ovarian architecture and essential roles of vasculature in organizing follicles to allow future studies on normal and diseased human ovaries. Similar approaches could also reveal roles of neo-angiogenesis during embryonic development and tumorigenesis.
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 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 | 0.001 | 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) | 0.001 | 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".