Additional file 1 of Lipoxins A4 and B4 inhibit glial cell activation via CXCR3 signaling in acute retinal neuroinflammation
Bibliographic record
Abstract
Additional file 1: Table S1. Antibodies Used. Figure S1. High magnification images of cell marker staining. A) Representative retinal staining at 1 day following intravitreal LPS challenge, shown at higher magnification to better demonstrate cell morphology of GFAP, F4-80, and GR-1. B) Representative retinal staining for ramified or amoeboid microglial morphology following staining for Iba1 or CD68. (scale bars represent 20 μm). Figure S2. LPS challenge did not induce an apparent T-cell response. Representative negative staining for CD4- and CD3-positive T cells in retinal sections at three days following intravitreal LPS treatment showed no signal in the retina. A parallel stained section from a retina three days after exposure to the potent oxidative stressor paraquat (PQ) is presented as a positive control (arrows, scale bars represent 100 μm). Figure S3. LPS treatment results in significant RGC loss after three weeks. A) Brn3a staining in retinas over a time course showed no clear reduction in RGC density compared to control until a 21 day time point (d21) after LPS injection (scale bars represent 100 μm). B) Corresponding quantification after 21 days reveals a small, but significant loss of RGCs at three weeks following LPS-induced retinal inflammation (*p <0.05, bars represent SE, GCL; ganglion cell layer). Figure S4. LXA4, LXB4 or Amg487 treatment alone do not induce retinal inflammation markers. Retinal staining for A)GFAP, B) Iba1, or C) F4-80, do not show any difference at two days following treatment, compared to vehicle alone (scale bars represent 100 μm).
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.908 | 0.189 |
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".