Sex hormones have pervasive effects on thymic epithelial cells
Bibliographic record
Abstract
The goal of our study was to evaluate at the systems-level, the effect of sex hormones on thymic epithelial cells (TECs). To this end, we sequenced the transcriptome of cortical and medullary TECs (cTECs and mTECs) from three groups of 6 month-old mice: males, females and males castrated at four weeks of age. In parallel, we analyzed variations in the size of TEC subsets in those three groups between 1 and 12 months of age. We report that sex hormones have pervasive effects on the transcriptome of TECs. These effects were exquisitely TEC-subset specific. Sexual dimorphism was particularly conspicuous in cTECs. Male cTECs displayed low proliferation rates that correlated with low expression of Foxn1 and its main targets. Furthermore, male cTECs expressed relatively low levels of genes instrumental in thymocyte expansion (e.g., Dll4) and positive selection (Psmb11 and Ctsl). Nevertheless, cTECs were more abundant in males than females. Accumulation of cTECs in males correlated with differential expression of genes regulating cell survival in cTECs and cell differentiation in mTECs. The sexual dimorphism of TECs highlighted here may be mechanistically linked to the well-recognized sex differences in susceptibility to infections and autoimmune diseases.
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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".