Source of hematopoietic progenitor cells determines their capacity to generate innate lymphoid cells ex vivo
Bibliographic record
Abstract
Background aims The success of allogeneic hematopoietic cell transplantation (HCT) as therapy for hematologic conditions is negatively impacted by the occurrence of graft-versus-host disease (GVHD). Tissue damage, caused, for example, by chemotherapy and radiotherapy, is a key factor in GVHD pathogenesis. Innate lymphoid cells (ILCs) are important mediators of tissue repair and homeostasis. The presence of ILCs before, and enhanced ILC reconstitution after, allogeneic HCT is associated with a reduced risk to develop mucositis and GVHD. However, ILC reconstitution after allogeneic HCT is slow and often incomplete. A way to replenish the pool of ILC relies on the differentiation of hematopoietic progenitor cells (HPCs) into ILC. Methods We developed an ex vivo stromal cell–containing culture system to study the capacity of HPCs to differentiate into all mature helper ILC subsets. Results ILC development depended on the source of HPCs. ILCs developed at high frequencies from umbilical cord blood– and fetal liver–derived HPC and at low frequencies when HPCs were obtained from allogeneic or autologous adult HCT grafts or healthy adult bone marrow. Although all helper ILC subsets could be generated from adult HPC sources, development of tissue protective ILC2 and NKp44 + ILC3 was notoriously difficult. Conclusions Our data suggest that slow ILC recovery after allogeneic HCT may be related to an intrinsic incapability of adult HPC to develop into ILC.
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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) | 0.002 | 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".