Klf4 protects thymus integrity during late pregnancy
Bibliographic record
Abstract
Pregnancy causes abrupt thymic atrophy. This atrophy is characterized by a severe decrease in the number of all thymocyte subsets and qualitative (but not quantitative) changes in thymic epithelial cells (TECs). Pregnancy-related thymic involution is triggered by progesterone-induced functional changes affecting mainly cortical TECs (cTECs). Remarkably, this severe involution is rapidly corrected following parturition. We postulated that understanding the mechanisms of pregnancy-related thymic changes could provide novel insights into signaling pathways regulating TEC function. When we analyzed genes whose expression in TECs was modified during late pregnancy, we found a strong enrichment in genes bearing KLF4 transcription factor binding motifs. We, therefore, engineered a Psmb11-iCre : Klf4 lox/lox mouse model to study the impact of TEC-specific Klf4 deletion in steady-state conditions and during late pregnancy. Under steady-state conditions, Klf4 deletion had a minimal effect on TEC subsets and did not affect thymic architecture. However, pregnancy-induced thymic involution was much more pronounced in pregnant females lacking Klf4 expression in TECs. These mice displayed a substantial ablation of TECs with a more pronounced loss of thymocytes. Transcriptomic and phenotypic analyses of Klf4 -/- TECs revealed that Klf4 maintains cTEC numbers by supporting cell survival and preventing epithelial-to-mesenchymal plasticity during late pregnancy. We conclude that Klf4 is essential for preserving TEC’s integrity and mitigating thymic involution during late pregnancy.
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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 | 0.001 |
| 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".