Abstract 3874: Galectin-3 Enhances Post Ischemic Angiogenesis Via Modulation Of Integrin And Akt Pathways.
Bibliographic record
Abstract
Introduction: As restoration of blood flow is critical for improved functional recovery following ischemic stroke, enhancing cerebral angiogenesis might be immensely helpful. Galectin-3 (gal-3) is a β-galactoside-binding lectin that plays key roles in inflammation, survival, and angiogenesis. Methods: We used transient middle cerebral artery occlusion (MCAO), oxygen-glucose deprivation (OGD) model, western blot analysis, RT-PCR, Immunofluorescence staining. Results: We currently report that intra-cerebroventricular infusion of recombinant gal-3 in rats subjected to transient MCAO increases the post-ischemic functional recovery. We further show that gal-3 mRNA and protein expression is up-regulated in vitro when activated microglial BV2 cells were subjected to either oxygen-glucose deprivation (OGD) or LPS (lipo-polysaccharide) stimulation. Immunofluorescence staining showed increased cytoplasmic gal-3 that is known to have pro-survival function. This increase in gal-3 is associated with increased number of pro-angiogenic structures in a 3D human vein umbilical cord endothelial (HUVEC) and microglia co-culture model. The pro-angiogenic effect of gal-3 was suppressed by treatment with gal-3 siRNA indicating the specific role of gal-3 in promoting angiogenesis. Exogenous gal-3 treatment further augmented the angiogenic potential of BV2 microglia cells. In addition, gal-3 increased survival of microglial BV2 cells, HUVEC, and neuro-progenitor cells. Gal-3 levels were also directly correlated with increased levels of Integrin-linked kinase 1(ILK1), pro-survival factor AKT and their down stream effector pro-angiogenic factors bFGF and MMP2. Conclusion: Taken together, our studies emphasize the importance of gal-3 in enhancing angiogenesis that is critical for neuron survival and neurogenesis in the post-stroke brain.
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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".