Amyloid β1–42 Oligomers Induce Galectin–1S8 O–GlcNAcylation Leading to Microglia Migration
Bibliographic record
Abstract
Protein O–GlcNAcylation has been associated with neurodegenerative diseases such as Alzheimer’s disease (AD). The O–GlcNAcylation of the 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 clears Aβ aggregates and dead cells to maintain brain homeostasis. Here, using LC-MS/MS, we revealed that the Aβ1–42 oligomers modify the microglia O-GlcNAcome. We 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 demonstrated that Aβ1–42 oligomers specifically target Galectin–1S8 O–GlcNAcylation via OGT. In addition to this, the 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 the Aβ1–42 oligomers and Serine 8–O–GlcNAcylation of Galectin–1 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 | 0.000 |
| 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".