Metabolic homeostasis and tissue renewal are dependent on β1,6GlcNAc-branched N-glycans
Bibliographic record
Abstract
Golgi beta1,6-N-acetylglucosaminyltransferase V (Mgat5) produces beta1,6GlcNAc-branched N-glycans on glycoproteins, which increases their affinity for galectins and opposes loss from the cell surface to constitutive endocytosis. Oncogenic transformation increases Mgat5 expression, increases beta1,6GlcNAc-branched N-glycans on epidermal growth factor and transforming growth factor-beta receptors, and enhances sensitivities to ligands, cell motility, and tumor metastasis. Here, we demonstrate that Mgat5(-/-) mouse embryonic fibroblasts (MEFs) display reduced sensitivity to anabolic cytokines and reduced glucose uptake and proliferation. Mgat5(-/-) mice are also hypoglycemic, resistant to weight gain on a calorie-enriched diet, hypersensitive to fasting, and display increased oxidative respiration and reduced fecundity. Serum-dependent activation of the extracellular response kinase (growth) and Smad2/3 (arrest) pathways in Mgat5(-/-) MEFs and bone marrow cells reveals an imbalance favoring arrest. Mgat5(-/-) mice have fewer muscle satellite cells, less osteogenic activity in bone marrow, and accelerated loss of muscle and bone mass with aging. Our results suggest that beta1,6GlcNAc-branched N-glycans promote sensitivity to anabolic cytokines, and increase fat stores, tissue renewal, and longevity.
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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) | 0.000 | 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 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".