Heterogeneity of thymic output in the elderly and its association with sex and smoking
Bibliographic record
Abstract
BACKGROUNDThymic involution with age leads to reduced T cell output and impaired adaptive immunity. However, the extent to which thymic activity persists later in life and how this contributes to immunological aging remains unclear. This study aimed to assess the presence and function of thymic tissue in older adults and identify factors influencing residual thymopoiesis.METHODSPatients aged 50 or older undergoing cardiothoracic surgery were recruited. Thymic structures within mediastinal adipose tissue were evaluated using histology, immunofluorescence, flow cytometry, T cell receptor (TCR) sequencing, and RNA sequencing. Recent thymic emigrants (RTEs) were quantified in peripheral blood and correlated with transcriptomic, epigenetic, and TCR repertoire data. Primary outcomes included thymic tissue identification, RTE frequency, and immune correlates.RESULTSFunctional thymic tissue was identified in mediastinal adipose tissue of older individuals. The frequency of CD31+CD4+ T cells (RTEs) positively correlated with the presence of thymic tissue. Thymic output showed substantial heterogeneity and was influenced by sex and smoking history. Thymic activity was associated with increased TCR repertoire diversity, improved immune protection against infections, and reduced epigenetic aging. Detailed profiling uncovered functional and phenotypic heterogeneity within naive CD4+ T cell subsets shaped by thymic activity.CONCLUSIONThis study demonstrates that thymic function can persist into later life and is modulated by factors such as sex and smoking. These findings suggest that thymic activity during aging is heterogeneous and influenced by more than chronological age alone, with potential implications for immune competence in older adults.
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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) | 0.000 | 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".