Bibliographic record
Abstract
Biotin is a water-soluble B-complex vitamin and is well-known as a co-factor for 5 indispensable carboxylases. Holocarboxylase synthetase (HLCS) catalyzes the biotinylation of carboxylases and other proteins, whereas biotinidase catalyzes the release of biotin from biotinylated peptides. Previous studies have reported that nutritional biotin deficiency and genetic defects in either HLCS or biotinidase induces cutaneous inflammation and immunological disorders. Since biotin-dependent carboxylases involve various cellular metabolic pathways including gluconeogenesis, fatty acid synthesis, and the metabolism of branched-chain amino acids and odd-chain fatty acids, metabolic abnormalities may play important roles in immunological and inflammatory disorders caused by biotin deficiency. Transcriptional factors, including NF-κB and Sp1/3, are also affected by the status of biotin, indicating that biotin regulates immunological and inflammatory functions independently of biotin-dependent carboxylases. An in-vivo analysis with a murine model revealed the therapeutic effects of biotin supplementation on metal allergies. The novel roles of biotinylated proteins and their related enzymes have recently been reported. Non-carboxylase biotinylated proteins induce chemokine production. HLCS is a nuclear protein involved in epigenetic and chromatin regulation. In this review, comprehensive knowledge on the regulation of immunological and inflammatory functions by biotin and its potential as a therapeutic agent is discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".