Foe turned friend: multiple functional roles attributable to hyper-activating stem cell factor receptor mutant in regeneration of the haematopoietic cell compartment
Bibliographic record
Abstract
OBJECTIVES: Stem cell factor receptor, c-kit, is considered to be the master signalling molecule of haematopoietic stem cells. It develops the orchestral pattern of haematopoietic cell lineages, seen by its varying degree of omnipresence in progenitors, lineage committed and mature cells. We have investigated the effect of over-expressing c-kit on early recovery of the haematopoietic compartment, in irradiated hosts. MATERIALS AND METHODS: Normal bone marrow cells (BMCs) were transfected with Kit(wt) (wild-type c-kit) or its variant Kit(mu) (asp814tyr) by electroporation. Lethally irradiated mice were transplanted with normal or transfected congeneic BMCs. The effect of ectopic expression of c-kit on haematopoietic cell recovery was determined by analysing donor-derived cells. Furthermore, effects of both types of c-kit over-expression on progenitor and lineage-committed cells were examined by flow cytometric analysis of Sca-1 and lineage-committed (Lin(+)) cells respectively. RESULTS: Hyper-activating Kit(mu) significantly improved recovery of the haematopoietic system in irradiated hosts. In vivo results showed that the donor-derived c-kit(+) cell population was increased to more than 3-fold in the case of Kit(mu)-transfected cells compared to normal and Kit(wt) over-expressing BMCs. In general, survival of progenitor and committed cell was improved in the Kit(mu) over-expressing system compared to the other two cohorts. CONCLUSION: These results suggest that recruitment of the hyper-activating variant of c-kit (Kit(mu)) lead to early recovery of the bone marrow of lethally irradiated mice.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".