Thymic Mesenchymal Cells Have a Distinct Transcriptomic Profile
Bibliographic record
Abstract
In order to understand the role of mesenchymal cells (MCs) in the adult thymus, we performed whole transcriptome analyses of primary thymic, bone, and skin MCs. These three MC populations shared expression of 2850 core MC genes involved in generic processes including interactions with tissue-resident macrophages. Moreover, we discovered that 2036 genes were differentially expressed, by at least 5-fold, in the three MC populations. Genes preferentially expressed in thymic MCs are instrumental in clearance of apoptotic thymocytes by macrophages, maintenance of a noninflammatory milieu, and attraction-expansion of thymocyte progenitors. Thymic and bone MCs share other sets of differentially expressed genes implicated in resolution of inflammation and expansion of hematolymphoid progenitors. Consistent with the fact that thymic and skin MCs have to support epithelial cells, they express at higher levels genes mediating epithelial cell adhesion to basement membrane and mesenchymal-epithelial cross-talk. Differentially expressed genes preferentially expressed by bone MCs are connected to formation and remodeling of bone, whereas those preferentially expressed in skin MCs are involved in skin and hair follicle homeostasis. We conclude that MCs from different organs display substantial heterogeneity and that the transcriptome of thymic MCs is exquisitely suited for interactions with epithelial and hematolymphoid cells in an environment with a high apoptosis rate.
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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 | 0.001 | 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 | 0.000 |
| 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".