Bacteria and PAMPs activate nuclear factor κB and Gro production in a subset of olfactory ensheathing cells and astrocytes but not in Schwann cells
Bibliographic record
Abstract
The primary olfactory nerves provide uninterrupted conduits for neurotropic pathogens to access the brain from the nasal cavity, yet infection via this route is uncommon. It is conceivable that olfactory ensheathing cells (OECs), which envelope the olfactory nerves along their entire length, provide a degree of immunological protection against such infections. We hypothesized that cultured OECs would be able to mount a biologically significant response to bacteria and pathogen-associated molecular patterns (PAMPs). The response of OECs to Escherichia coli (E. coli) and various PAMPs was compared to that of Schwann cells (SCs), astrocytes (ACs), and microglia (MG). A subset of OECs displayed nuclear localization of nuclear factor kappaB), an inflammatory transcription factor, after treatment with E. coli (20% +/- 5%), lipopolysacchride (33% +/- 9%), and Poly I:C (25% +/- 5%), but not with peptidoglycan or CpG oligonucleotides. ACs displayed a similar level of activation to these treatments, and in addition responded to peptidoglycan. The activation of OECs and ACs was enhanced by coculture with MG (56% +/- 16% and 85% +/- 13%, respectively). In contrast, SCs did not respond to any treatment or to costimulation by MG. Immunostaining for the chemokine Gro demonstrated a functional response that was consistent with NF kappaB activation. OECs expressed mRNA for Toll-like receptors (TLRs) 2 and 4, but only TLR4 protein was detected by Western blotting and immunohistochemistry. The results demonstrate that OECs possess the cellular machinery that permits them to respond to certain bacterial ligands, and may have an innate immune function in protecting the CNS against infection.
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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".