Influence of androgens on the innate immune system
Bibliographic record
Abstract
BACKGROUND: Sexual dimorphism is observed in the occurrence, course, and severity of human disease. The difference in immune response between males and females can in part be attributed to sexual genotype. However, immunological differences can also be explained by endocrine-immune interactions. Specifically, androgens possess the ability of directly modulating the development and function of immune cells. Although androgens generally contribute to immunosuppressive effects, this is not necessarily always the case. AIM: The aim of the review is to uncover the role of androgens in shaping the innate immune response. MATERIAL & METHODS: Authors included papers in this review which discussed the impact of androgens on specific innate immune cells. RESULTS: Androgens modulate the innate immune response through various mechanisms. However, there is conflicting evidence in the literature regarding the interplay betwen androgens and the innate immune system. DISCUSSION: Conflicting evidence presented in this review could in part be explained by the limitations present in interpreting results. CONCLUSION: This review is of great importance for our understanding of occurence and mechanism of human inflammatory disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".