The Queuine Micronutrient: Charting a Course from Microbe to Man
Bibliographic record
Abstract
Micronutrients from the diet and gut microbiota are essential to human health and wellbeing. Arguably, among the most intriguing and enigmatic of these micronutrients is queuine, an elaborate 7-deazaguanine derivative made exclusively by eubacteria and salvaged by animal, plant and fungal species. In eubacteria and eukaryotes, queuine is found as the sugar nucleotide queuosine within the anticodon loop of transfer RNA isoacceptors for the amino acids tyrosine, asparagine, aspartic acid and histidine. The physiological requirement for the ancient queuine molecule and queuosine modified transfer RNA has been the subject of varied scientific interrogations for over four decades, establishing relationships to development, proliferation, metabolism, cancer, and tyrosine biosynthesis in eukaryotes and to invasion and proliferation in pathogenic bacteria, in addition to ribosomal frameshifting in viruses. These varied effects may be rationalized by an important, if ill-defined, contribution to protein translation or may manifest from other presently unidentified mechanisms. This article will examine the current understanding of queuine uptake, tRNA incorporation and salvage by eukaryotic organisms and consider some of the physiological consequence arising from deficiency in this elusive and lesser-recognized micronutrient.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".