Re-evaluating the origins group 2 innate lymphoid cells through the lens of T-cell development
Bibliographic record
Abstract
The discovery of innate lymphoid cells (ILCs) has revolutionized our understanding of innate immunity and immune cell interactions at epithelial barrier sites. Their presence and maintenance are critical for modulating immune homeostasis, responding to injury or infection, and repairing damaged tissues. ILCs are remarkably similar to CD4+ T helper subsets in terms of function and transcription factors required for their development but are distinguished by their lack of antigen specific receptors. Despite their similarities, the absence of a surface TCR and presence of ILCs/precursors in adult bone marrow has led to speculation that ILCs and T cells develop separately from lineages that branch at the point of precursors within the bone marrow. Considering the common lineage markers and effector cytokine profiles shared between ILCs and T cells, it is surprising that the status of the TCR loci in ILCs was not fully explored at the time of their discovery. In this thesis, we demonstrate that a high proportion of peripheral tissue ILC2s have TCRγ chain gene rearrangements and TCRδ locus deletions. Detailed analyses of these loci show abundant frameshifts and premature stop codons that would encode non- functional TCR proteins. Collectively, these data argue that ILC2 can develop from T cells that fail to appropriately rearrange TCR genes, potentially within the thymus.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".