Bibliographic record
Abstract
For almost 30 years, the cell-surface protein CD34 has been widely used as a marker to assist in the identification and Summary isolation of hematopoietic stem cells (HSCs) and progenitors in preparation for bone-marrow transplantation. In addition, it has increasingly been used as a marker to help identify other tissue-specific stem cells, including muscle satellite cells and epidermal precursors. Despite its utility as a stem-cell marker, however, the function of CD34 has remained remarkably elusive. This is probably because: (1) it is subject to a range of tissue-specific post-transcriptional and post-translational modifications that are expected to alter its function dramatically; (2) the simple interpretation of CD34 gain- and loss-of-function experiments has been confounded by the overlapping expression of the two recently discovered CD34-related proteins podocalyxin and endoglycan; and (3) there has been a glaring lack of robust in vitro and in vivo functional assays that permit the structural and functional analysis of CD34 and its relatives. Here, we provide a brief review of the domain structure, genomic organization, and tissue distribution of the CD34 family. We also describe recent insights from gain- and loss-of-function experiments and improved assays, which are elucidating a fascinating role for these molecules in cell morphogenesis and migration.
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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 | 0.001 | 0.001 |
| 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".