Additional file 1 of Pericytes as mediators of infiltration of macrophages in multiple sclerosis
Bibliographic record
Abstract
Additional file 1: Figure S1. Pericytes localized within GFAP+ reactive astrocytes in EAE. D16 EAE cerebellum (cbm) tissues (lower panel) were analyzed for GFAP+ astrocyte (green) and PDGFRβ+ pericyte (red) staining to investigate differences in these cells as a part of the neurovascular unit (NVU). When compared with naïve cerebellum (upper panel), reactive astrocytes in EAE cerebellum appear to wrap around the PDGFRβ+ cells in an inflamed capillary venule. Scale 50 µm. Figure S2. Pericyte proliferation is not altered upon IL-1β and IFNγ or CSPG treatments. A. Primary mouse pericytes were seeded at 7,500 cells in a 96-well plate and treated with either 10 ng/mL IL-1β + IFNγ or 10 µg/mL CSPG and stained for DAPI and Ki67 to identify proliferating cells. B. Graphs denote %Ki67+ DAPI+ cells in response to treatment. Data are represented as mean ± SD. Figure S3. Characterization of mouse pericytes in vitro. Primary murine pericytes (passage 6) were seeded at 7500 cells in 96-well plates and stained for PDGFRβ (red) and NG2 (green) after 24 h in cultures. These cells were found to express both these markers. Figure S4. Pericyte induced macrophage migration in vitro. Using the Boyden chamber assay, we investigated migration of bone marrow derived macrophages (BMDMs) in response to supernatants from LPS-treated pericytes. Data points represent technical replicates in untreated and LPS-treated conditions. Data are represented as mean ± SD. **p < 0.01.
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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 | 0.002 |
| 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) | 0.547 | 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".