Amyloid ß<sub>1–42</sub> Peptide Induces Galectin-1<sup>S8</sup> O-GlcNAcylation to Lead Microglia Migration
Bibliographic record
Abstract
Protein O-GlcNAcylation has been associated with neurodegenerative diseases such as Alzheimer´s disease (AD). O-GlcNAcylation of Amyloid Precursor Protein (APP) regulates both the trafficking and the processing of the APP through the amyloidogenic pathway, resulting in the release and aggregation of the Aβ1-42 peptide. Microglia clear Aβ aggregates and dead cells to maintain brain homeostasis. Here, using LC-MS/MS we reveal that the Aβ1-42 peptide modifies the microglia O-GlcNAcome. We have identified 55 proteins, focusing our research on Galectin-1 protein, since it is a very versatile protein from a functional point of view. Combining biochemical with genetic approaches we demonstrate that Aβ1-42 peptide specifically targets Galectin-1S8 O-GlcNAcylation via OGT. In addition, this Gal-1-O-GlcNAcylated form, in turn, controls human microglia migration. Given the importance of microglia migration in the progression of AD, this study reports the relationship between Aβ1-42 peptide and Serine 8- O-GlcNAcylation of Galectin to drive microglial migration
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".