Natural Variation in Testosterone is Associated With Hypoalgesia in Healthy Women
Bibliographic record
Abstract
OBJECTIVE: Sex differences in pain are well established, with women reporting greater incidence of clinical pain and heightened responsivity to experimental pain stimuli relative to men. Sex hormones (ie, estrogens, progestins, androgens) could contribute to extant differences in pain sensitivity between men and women. Despite this, there has been limited experimental research assessing the relationship between pain and sex hormones. The purpose of this study was to extend previous research and examine the association between sex hormones and nociceptive processing in healthy women. MATERIALS AND METHODS: A total of 40 healthy women were tested during the mid-follicular, ovulatory, and late-luteal phases of the menstrual cycle (testing order counterbalanced). Salivary estradiol, progesterone, and testosterone were collected at each testing session and pain was examined from electrocutaneous threshold/tolerance, ischemia threshold/tolerance, and McGill Pain Questionnaire-Short Form ratings of noxious stimuli. Nociceptive flexion reflex threshold was assessed as a measure of spinal nociception. RESULTS: Overall, there were no significant menstrual phase-related differences in pain outcomes. Nonetheless, variability in testosterone (and to a lesser degree estradiol) was associated with pain; testosterone was antinociceptive, whereas estradiol was pronociceptive. No hormone was associated with nociceptive flexion reflex threshold. DISCUSSION: Although future research is needed to replicate and extend these findings to clinical populations (ie, chronic pain, premenstrual dysphoric disorder), results from the present study indicate that menstrual phase-related changes in sex hormones have minimal influence on experimental pain. However, individual differences in testosterone may play a protective role against pain in healthy women.
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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 | 0.001 |
| 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) | 0.001 | 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".