Olfactory ensheathing cells of the lamina propria in vivo and in vitro
Bibliographic record
Abstract
Olfactory ensheathing cells (OECs) continuously support the regeneration of olfactory receptor neurons (ORNs). In addition, OECs promote regeneration of neurons within the CNS in a number of transplantation paradigms, but details of exactly how they support regeneration remain elusive. The majority of studies using OECs to promote regeneration have thus far focused on understanding the cell biology of OECs purified from the olfactory bulb (OB). Here we show that a population of OECs similar to those obtained from the OB is present in the lamina propria (LP) beneath the olfactory epithelium (OE). These OECs are the first glial cells encountered by the axons of developing ORNs as they exit the OE and display distinct and variable expression of p75, S100beta, GFAP, and O4, characteristic markers of bulb OECs. Once purified in vitro, they display Schwann cell-like and astrocyte-like properties and expand rapidly. In addition to resembling OB-OECs, LP-OECs also express a unique combination of developmentally important proteins-CD 44, beta1 integrin, P200, Notch 3, NG2, VEGF, and PACAP and CREB binding protein (CBP/p300)-not previously reported in OB-OECs. These data suggest that LP-OECs, like OB-OECs, are a developmentally distinct class of glia that are capable of both immature and mature function, depending on environmental stimuli, within the adult nervous system.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".