Erucamide regulates retinal neurovascular crosstalk
Bibliographic record
Abstract
Abstract Neurovasculoglial crosstalk is critical in establishing and maintaining a functional neurovascular unit. Breakdown in the unit is central to many neurodegenerative disorders of the CNS of which the retina is a component. A growing literature indicated that primary fatty acid amides (PFAMs) can regulate this crosstalk between vasculature and neuronal tissues. In this study we describe a central role for erucamide, a 22:1 mono-unsaturated omega-9 fatty acid amide, in degenerating retinal tissues. Using high-resolution global mass spectrometry-based metabolomics, we cataloged metabolites in murine models of retinal degeneration and show that while PFAMs, in general, are highly dysregulated, erucamide is the one most significantly diminished during photoreceptor atrophy. Using rodent models of retinal degeneration and novel organosilane-modified porous silicon nanoparticles (pSiNPs) for the in vivo delivery of erucamide, we demonstrate that erucamide activates CD11b+ myeloid cells, leading to the upregulation of angiogenic and neurotrophic cytokines that stabilize retinal degeneration. We identified TMEM19 as a novel binding protein for erucamide that is crucial for human iPSC-derived macrophage precursor cells activation and subsequent neurotrophic and angiogenic factor production. These findings reveal a previously unknown PFAM pathway that is modulated during retinal degenerative diseases, demonstrating that erucamide or functional analogues and their action through TMEM19 may be useful as a therapeutic alternative to neuroprotective and stem cell-based approaches for the treatment of retinal degenerative diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".