The distribution of the proteoglycan FORSE‐1 in the developing mouse central nervous system
Bibliographic record
Abstract
Glycosylation is a major post-translational modification in which a carbohydrate known as a glycan is enzymatically attached to target proteins which regulate protein folding and stability. Glycans are strongly expressed in the developing nervous system where they play multiple roles during development. The importance of these glycan epitopes in neural development is highlighted by a group of conditions known as congenital disorders of glycosylation which lead to psychomotor difficulties, mental retardation, lissencephaly, microencephaly and epilepsy. One of these glycan epitopes, known as Lewis X, is recognised by the FORSE-1 antibody and is regionally expressed in the developing nervous system. In this study, we report the regional and temporal expression patterns of FORSE-1 immunolabelling during the periods of neurogenesis, gliogenesis and axonogenesis in developing mouse nervous system. We demonstrate the localisation of FORSE-1 on subsets of neuroepithelial cells and radial glial cells, and in compartments corresponding to axon tract formation. These spatial, temporal and regional expression patterns are suggestive of roles in the determination of different cell lineages and in the patterning of white matter during development, and help provide insights into the neuroanatomical regions affected by congenital disorders of glycosylation.
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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 | 0.001 | 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) | 0.001 | 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".