The effect of female sexual hormones on the intestinal and serum cytokine response after traumatic brain injury: different roles for estrogen receptor subtypes
Bibliographic record
Abstract
The purpose of this study was to evaluate the effect of female sexual hormones on intestinal and serum cytokines following traumatic brain injury (TBI). Adult female rats were ovariectomized and distributed among the following 9 groups: (i) sham trauma, (ii) TBI (Marmarou's method), (iii) vehicle (dimethylsulfoxide) treated, (iv) estrogen (E2) treated, (v) progesterone (P) treated, (vi) treated with E2+P, (vii) propylpyrazole triol (PPT) treated, (viii) diarylpropionitrile (DPN) treated, and (ix) control. PPT and DPN are estrogen receptor αand β agonists, respectively. Serum and intestinal levels of interleukin (IL)-1β were increased by TBI (P < 0.001). The level of intestinal IL-1β was increased in the group treated with E2 (P < 0.001). There was a reduction in serum IL-1β (P < 0.01) and an increase in intestinal IL-1β level (P < 0.001) in the PPT-treated group compared with the vehicle-treated group. TBI reduced serum IL-6 (P < 0.01) and increased intestinal IL-6 (P < 0.001). Serum IL-6 was increased in the group treated with E2 (P < 0.001), P (P < 0.001), E2+P (P < 0.01), and DPN (P < 0.001) after TBI; however, intestinal IL-6 was higher in the E2-treated group compared with the vehicle-treated group (P < 0.01). Intestinal tumor necrosis factor α (TNF-α) was increased by TBI (P < 0.001). Progesterone decreased serum TNF-α (P < 0.01). Intestinal TNF-α in the E2 (P < 0.01), E2+P (P < 0.001), and PPT (P < 0.001) treatment groups was less than in the vehicle-treated group. In conclusion, estrogen influences the intestinal levels of proinflammatory cytokines, in particular TNF-α, mediated through estrogen receptor α.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".