Differential gene expression of human stem progenitor cells derived from early stages of in utero human hematopoiesis
Bibliographic record
Abstract
Hematopoietic stem progenitor cells (HSPCs) are highly enriched in a rare subset of Lin-CD34+CD38- cells. Independent of stage of human development, HSPC function segregates to the subset of Lin-CD34+CD38- cells. However, fetal-derived HSPCs demonstrate distinct self-renewal and differentiation capacities compared with their adult counterparts. Here, to characterize the molecular nature of fetal HSPCs, suppressive subtractive hybridization was used to compare gene expression of HSPCs isolated from fetal blood (FB-HSPCs) versus adult mobilized peripheral blood (MPB-HSPCs). We identified 97 differentially expressed genes that could be annotated into distinct groups that include transcription factors, cell cycle regulators, and genes involved in signal transduction. Candidate regulators, such as Lim only domain-2 (LMO2), nuclear factor-kappa B (NF-kappaB), tripartite motif 28 (Trim28), and N-myc protooncogene (MYCN), and a novel homeobox gene product were among transcripts that were found to be differentially expressed and could be associated with specific proliferation and differentiation properties unique to FB-HSPCs. Interestingly, the majority of genes associated with signal transduction belong to Ras pathway, highlighting the significance of Ras signaling in FB-HSPCs. Genes differentially expressed in FB-HSPCs versus adult MPB-HSPCs were verified using quantitative real-time polymerase chain reaction (Q-PCR). This approach also resulted in the identification of a transcript that is highly expressed in FB-HSPCs but not detectable in more differentiated Lin-CD34+CD38+ FB progenitors. Our investigation represents the first study to compare phenotypically similar, but functionally distinct, HSPC populations and to provide a gene profile of unique human HSPCs with higher proliferative capacity derived from early in utero human blood development.
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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) | 0.001 | 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".