Impact of natural mutations on the riboflavin transporter 2 and their relevance to human riboflavin transporter deficiency 2
Bibliographic record
Abstract
Abstract Riboflavin transporter deficiency 2 (RTD2) is a rare neurological disorder caused by mutations in the Solute carrier family 52 member 2 (Slc52a2) gene encoding human riboflavin transporter 2 (RFVT2). This transporter is ubiquitously expressed and mediates tissue distribution of riboflavin, a water‐soluble vitamin that, after conversion into FMN and FAD, plays pivotal roles in carbohydrate, protein, and lipid metabolism. The 3D structure of RFVT2 has been constructed by homology modeling using three different templates that are equilibrative nucleoside transporter 1 (ENT1), Fucose: proton symporter, and glucose transporter type 5 (GLUT5). The structure has been validated by several approaches. All known point mutations of RFVT2, associated with RTD2, have been localized in the protein 3D model. Six of these mutations have been introduced in the recombinant protein for functional characterization. The mutants W31S, S52F, S128L, L312P, C325G, and M423V have been expressed in E. coli, purified, and reconstituted into proteoliposomes for transport assay. All the mutants showed impairment of function. The Km for riboflavin of the mutants increased from about 3 to 9 times with respect to that of WT, whereas Vmax was only marginally affected. This agrees with the improved outcome of most RTD2 patients after administration of high doses of riboflavin.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".