Beta Endorphin Levels in PCOS Women: Relationship With Insulin Secretion
Bibliographic record
Abstract
Background : An understanding of the relationship between beta endorphin ( Beta ) with insulin, glucose and gonadotropins may explain how non-pharmacologic treatment options such as exercise and acupuncture may be beneficial to women with Polycystic Ovary Syndrome (PCOS). The objective was to examine the correlation of Beta with insulin, glucose and gonadotropins, controlling for exercise and body mass index (BMI). Methods : 40 untreated women with a confirmed diagnosis of PCOS (NIH criteria) were tested. Height, exercise frequency and exercise intensity were self-reported; weight was measured by nurses. Blood samples were collected for the biological measures of interest. The setting was an academic US medical center. Statistical analyses consisted of Spearman correlations and partial correlations with an alpha = 0.05. The main outcome measures included plasma Beta, insulin and glucose (fasting and AUC) from a 2-hour oral glucose tolerance test, serum gonadotropins. Results : The mean Beta level was 7.92 pmol / mL (sd = 4.0, range 1.92 - 18.7, 25% / 75% interquartile range 4.56 - 11.29). Beta was associated with log e AUC-insulin (P = 0.04) after adjustment for exercise as measured via energy equivalents; this correlation was unaffected by additional control of BMI. No relationship between Beta and luteinizing hormone, the luteinizing hormone / follicle stimulating hormone ratio, or glucose was seen after accounting for BMI and exercise. Conclusion : Beta was positively correlated with AUC-insulin after accounting for exercise. Future studies could investigate the affects of Beta -potentiating therapies, such as exercise and acupuncture, in women with PCOS to determine how these changes in Beta are related to insulin / glucagon balance. doi:10.4021/jem62w
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".