Hypothalamic‐pituitary gonadal axis and immune response imbalance during chronic filarial infections
Bibliographic record
Abstract
Bi-directional relationships operate between the hypothalamic-pituitary-gonadal axis and the immune system. Cytokines, peptide hormones and their shared receptors/ligands are used as a common biological language for communication within and between the immune and neuroendocrine systems. Such communication suggests an immunoregulatory role for the brain and a sensory function for the immune system. We used a radioimmunoassay to measure the concentrations of steroid hormones (cortisol, testosterone, estradiol and progesterone) and pituitary hormones [follicle stimulating hormone (FSH), luteinizing hormone (LH) human chorionic gonadotropin (HCG) and prolactin] in peripheral blood plasma from 78 young Gabonese women with chronic filarial infections. We used an enzyme-linked immunosorbent assay to determine the concentrations of four proinflammatory cytokines [tumor necrosis factor-alpha (TNF-alpha), gamma interferon (IFN-gamma), interleukin-1 (IL-1) and IL-6] in the same plasma samples. Progesterone was unchanged and all other steroid hormone plasma concentrations were lower in microfilaremic women than in amicrofilaremic women. The concentration of LH was higher in amicrofilaremic women, whereas the prolactin concentration was higher in microfilaremics. The plasma concentrations of TNF-alpha, IFN-gamma, IL-1 and IL-6 were higher in microfilaremic women. A strong negative correlation was found between the steroid and pituitary hormones and the pro-inflammatory cytokines. Conversely, a strong positive correlation was found between prolactin and the same cytokines. These data provide first evidence of immune system and hormonal system disturbance during chronic filarial infections and suggest that the observed imbalance should be taken into account in the diagnosis and treatment of filarial infections.
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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 | 0.000 |
| 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) | 0.001 | 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".