Sepsis shapes the human γδ TCR repertoire in an age‐ and pathogen‐dependent manner
Bibliographic record
Abstract
Sepsis affects 25 million children per year globally, leading to 2.9 million deaths and substantial disability in survivors. Extensive characterization of interactions between the host and bacteria in children is required to design novel preventive and therapeutic strategies tailored to this age group. Vγ9Vδ2 T cells are the first T cells generated in humans. These cells are defined by the expression of Vγ9Vδ2 T-cell receptors (TCRs, using the TRGV9 and TRDV2 gene segments), which react strongly against the prototypical bacterial phosphoantigen HMBPP. We investigated this reactivity by analyzing the TCR δ (TRD) repertoire in the blood of 76 children (0-16 years) with blood culture-proven bacterial sepsis caused by HMBPP-positive Escherichia coli or by HMBPP-negative Staphylococcus aureus or by HMBPP-negative Streptococcus pneumoniae. Strikingly, we found that S. aureus, and to a lesser extent E. coli but not S. pneumoniae, shaped the TRDV2 repertoire in young children (<2 years) but not in older children or adults. This dichotomy was due to the selective expansion of a fetal TRDV2 repertoire. Thus, young children possess fetal-derived Vγ9Vδ2 T cells that are highly responsive toward specific bacterial pathogens.
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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) | 0.002 | 0.001 |
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".