GABA Dysfunction and Its Consequences in Women with Polycystic Ovary Syndrome
Bibliographic record
Abstract
Background and Objective: The GABA system plays an important role in the development, maturation, and function of gonadotropin-releasing hormone (GnRH)-secreting neurons, as well as in the coordination of reproductive and metabolic signals. Considering the emerging evidence in this area, dysfunction of the GABA system may be involved in the development of polycystic ovary syndrome (PCOS). The aim of this study is to summarize the available evidence on dysfunction of the GABA system and its implications for women with PCOS. Methods: This systematic review was conducted using the keywords Gamma-Aminobutyric Acid (GABA), GABAergic pathway, PCOS and their related MeSH and searching for English articles from 2000 to 2023 in WOS, Embase, Scopus and PubMed databases. Articles that conducted clinical research on the relationship between GABA supplementation or the GABA pathway and PCOS were identified as relevant articles. The quality of the studies was assessed using the Newcastle-Ottawa tool. Findings: A total of 260 articles were found in the initial search, of which only 7 were selected. There is evidence that GABA and PCOS are associated, but the causal direction and underlying mechanism are unclear. Some studies have shown that PCOS alters the levels or function of GABA in the blood or brain, leading to psychological and physiological consequences. On the other hand, GABA dysfunction affects amino acid metabolism and GnRH hormone signaling, helping to improve PCOS symptoms. Conclusion: Based on the results of this study, GABA may play an important role in the pathophysiology of PCOS by regulating GnRH neurons and GABA inputs to them. GABA is also a signaling molecule in various tissues and organs outside the brain, and GABA pathways may affect GnRH neuron function and PCOS development through different mechanisms.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".