Sulfatase‐mediated manipulation of the astrocyte‐Schwann cell interface
Bibliographic record
Abstract
Schwann cell (SC) transplantation following spinal cord injury (SCI) may have therapeutic potential. Functional recovery is limited however, due to poor SC interactions with host astrocytes and the induction of astrogliosis. Olfactory ensheathing cells (OECs) are closely related to SCs, but intermix more readily with astrocytes in culture and induce less astrogliosis. We previously demonstrated that OECs express higher levels of sulfatases, enzymes that remove 6-O-sulfate groups from heparan sulphate proteoglycans, than SCs and that RNAi knockdown of sulfatase prevented OEC-astrocyte mixing in vitro. As human OECs are difficult to culture in large numbers we have genetically engineered SCs using lentiviral vectors to express sulfatase 1 and 2 (SC-S1S2) and assessed their ability to interact with astrocytes. We demonstrate that SC-S1S2s have increased integrin-dependent motility in the presence of astrocytes via modulation of NRG and FGF receptor-linked PI3K/AKT intracellular signaling and do not form boundaries with astrocytes in culture. SC-astrocyte mixing is dependent on local NRG concentration and we propose that sulfatase enzymes influence the bioavailability of NRG ligand and thus influence SC behavior. We further demonstrate that injection of sulfatase expressing SCs into spinal cord white matter results in less glial reactivity than control SC injections comparable to that of OEC injections. Our data indicate that sulfatase-mediated modification of the extracellular matrix can influence glial interactions with astrocytes, and that SCs engineered to express sulfatase may be more OEC-like in character. This approach may be beneficial for cell transplant-mediated spinal cord repair. GLIA 2016 GLIA 2017;65:19-33.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".