Effect of Gonadal Hormones on Neurotransmitters Implicated in the Pathophysiology of Obsessive-Compulsive Disorder: A Critical Review
Bibliographic record
Abstract
Obsessive-compulsive disorder (OCD) is a relatively common neuropsychiatric disorder affecting between 1.6 and 3.2% of the population. A number of studies have previously reported increased incidence of OCD, or exacerbation of preexisting symptoms in females during reproductive events. Since these periods are known to involve fluctuating levels of gonadal hormones, these steroids have been suggested to be involved in modulating the course of the disorder. However, to date, only a few studies have measured hormone levels and obsessive-compulsive (OC) symptoms concurrently; thus, direct evidence for this relationship is limited. In turn, investigations into neurotransmission in OC individuals have been more extensive, and have implicated the serotonergic, dopaminergic, and glutamatergic neurotransmitter systems in OCD pathology. There is evidence suggesting that reproductive hormones estrogens and progesterone can modulate neurotransmission in the aforementioned signaling pathways by regulating the expression of receptors and channels, as well as the synthesis and release of the neurotransmitter itself. Overall, estrogen and progesterone appear to enhance serotonin signaling, which has been associated with improved OC symptoms. The effect of the gonadal hormones in dopaminergic and glutamatergic signaling is much more variable, highlighting the need for further research in this field. The existing evidence shows that gonadal hormones can have profound impacts on neurotransmission in the brain, leading to the conclusion that the hormonal fluctuations during reproductive events are a plausible factor contributing to the change in OCD course during these times.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".