Synthesis of a novel photoactivatable glucosylceramide cross-linker
Bibliographic record
Abstract
The biosynthesis of glucosylceramide (GlcCer) is a key rate-limiting step in complex glycosphingolipid (GSL) biosynthesis. To further define interacting partners of GlcCer, we have made a cleavable, biotinylated, photoreactive GlcCer analog in which the reactive nitrene is closely apposed to the GlcCer head group, by substituting the native fatty acid with d, l-2-aminohexadecanoic acid. Two amino-GlcCer diastereomer cross-linkers (XLA and XLB) were generated. XLB proved an effective lactosylceramide (LacCer) synthase substrate while XLA was inhibitory. Both probes specifically bound and cross-linked the GlcCer binding protein, glycolipid transfer protein (GLTP), but not other GSL binding proteins (Shiga toxin and cholera toxin). GlcCer inhibited GLTP cross-linking. Both GlcCer cross-linkers competed with microsomal nitrobenzoxadiazole (NBD)-GlcCer anabolism to NBD-LacCer. GLTP showed marked, ATP-dependent enhancement of cell-free intact microsomal LacCer synthesis from endogenous or exogenous liposomal GlcCer, supporting a role in the transport/membrane translocation of cytosolic and extra-Golgi GlcCer. GLTP was specifically labeled by either XLA or XLB GlcCer cross-linker during this process, together with a (the same) small subset of microsomal proteins. These cross-linkers will serve to probe physiologically relevant GlcCer-interacting cellular proteins.
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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 | 0.001 |
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".