Age-related remodeling of the glycocalyx drives T cell exhaustion
Bibliographic record
Abstract
Abstract Cell surface glycans, termed the glycocalyx, are essential regulators of cellular signaling and thus cellular development and functions, but how aging impacts the glycocalyx remains poorly understood. Here, using immune cells as a model system for studying the relationship between aging and glycocalyx remodeling, we show that α2,6-linked sialic acid – a terminal glycan epitope typically associated with inhibitory signaling – becomes downregulated in T cells from older animals. This downregulation is tightly correlated with age-associated accumulation of effector T cells, which are decorated with little to no α2,6-linked sialic acids. T cell aging renders older individuals more vulnerable to infections and cancers. To understand the role of α2,6-linked sialic acids in T cell physiology, we generated a mouse model with T cell-specific deletion of the sialyltransferase gene St6gal1 . The chronic depletion of α2,6-linked sialic acids led to naïve T (T N ) cells expansion in the periphery and premature T cell exhaustion. As a result, these mice were less able to control acute Listeria infection and chronic tumor growth. Blockade of the PD-1 pathway can partially restore the ability of St6gal1 -deficient T cells to control tumor growth. Together, these data suggest that α2,6-linked sialic acids are critical for maintaining long-term T cell responsiveness, and the loss of α2,6-linked sialic acids may directly contribute to age-related T cell exhaustion.
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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 | 0.001 |
| 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".