The importance of neuronal growth factors in the ovary
Bibliographic record
Abstract
The neurotrophin family consists of nerve growth factor (NGF), neurotrophin 3 (NT3) and neurotrophin 4/5 (NT4/5), in addition to brain-derived neurotrophic factor (BDNF) and the neuronal growth factors, glial cell line-derived neurotrophic factor (GDNF) and vasointestinal peptide (VIP). Although there are a few literature reviews, mainly of animal studies, on the importance of neurotrophins in the ovary, we aimed to provide a complete review of neurotrophins as well as neuronal growth factors and their important roles in normal and pathological processes in the ovary. Follicular assembly is probably stimulated by complementary effects of NGF, NT4/5 and BDNF and their receptors. The neurotrophins, GDNF and VIP and their receptors have all been identified in preantral and antral follicles of mammalian species, including humans. Transgenic mice with mutations in the genes encoding for Ngf, Nt4/5 and Bdnf and their tropomyosin-related kinase β receptor showed a reduction in preantral follicles and an abnormal ovarian morphology, whereas NGF, NT3, GDNF and VIP increased the in vitro activation of primordial follicles in rats and goats. Additionally, NGF, NT3 and GDNF promoted follicular cell proliferation; NGF, BDNF and VIP were shown to be involved in ovulation; VIP inhibited follicular apoptosis; NT4/5, BDNF and GDNF promoted oocyte maturation and NGF, NT3 and VIP stimulated steroidogenesis. NGF may also exert a stimulatory effect in ovarian cancer and polycystic ovarian syndrome (PCOS). Low levels of NGF and BDNF in follicular fluid may be associated with diminished ovarian reserve and high levels with endometriosis. More knowledge of the roles of neuronal growth factors in the ovary has important implications for the development of new therapeutic drugs (such as anti-NGF agents) for ovarian cancer and PCOS as well as various infertility problems, warranting further research.
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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 | 0.001 | 0.001 |
| 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".