Identification of CD44 as a cell surface marker for Müller glia precursor cells
Bibliographic record
Abstract
In the retina, both neurons and glia differentiate from a common progenitor population. CD44 cell surface antigen is a hyaluronic acid receptor expressed on mature Müller glial cells. We found that in the developing mouse retina, expression of CD44 was transiently observed at or around birth in a subpopulation of c-kit-positive retinal progenitor cells. During in vitro culture, purified CD44/c-kit-positive retinal progenitor cells exclusively differentiated into Müller glial cells and not into neurons, suggesting that CD44 marks a subpopulation of retinal progenitor cells that are fated to become glia. Over-expression of CD44 inhibited the extension of processes by Müller glial cells and neurons. Notch signaling is known to be involved in the specification of retinal progenitors into a glial fate. Activation of Notch signaling increased the number of CD44-positive cells, and treatment with the Notch signal inhibitor, DAPT, at early, but not later, stages of retinal development abolished both CD44-positive cells and Müller glial cells. Together, CD44 was identified as an early cell surface marker of the Müller glia lineage, and Notch signalling was involved in commitment of retinal progenitor cells to CD44 positive Müller glial precursor cells.
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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 | 0.001 | 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".