T<scp>he</scp> B<scp>iochemistry and</scp> P<scp>hysiology of</scp> M<scp>etallic</scp> F<scp>luoride:</scp> A<scp>ction,</scp> M<scp>echanism, and</scp> I<scp>mplications</scp>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fluoride is a well-known G protein activator. Activation of heterotrimeric GTP-binding proteins by fluoride requires trace amounts of Al3+ or Be2+ ions. AlFx mimics a gamma-phosphate at its transition state in a Galpha protein and is therefore able to inhibit its GTPase activity. AlFx also forms complexes with small GTP-binding proteins in the presence of their GTPase-activating proteins (GAP). As phosphate analogs, AlFx or BeFx affect the activity of a variety of phosphoryl transfer enzymes. Most of these enzymes are fundamentally important in cell signal transduction or energy metabolism. Al3+ and F- tend to form stable complexes in aqueous solution. The exact structure and concentration of AlFx depend on the pH and the amount of F- and Al3+ in the solution. Humans are exposed to both F and Al. It is possible that Al-F complexes may be formed in vivo, or formed in vitro prior to their intake by humans. Al-F complexes may play physiological or pathological roles in bone biology, fluorosis, neurotoxicity, and oral diseases such as dental caries and periodontal disease. The aim of this review is to discuss the basic chemical, biochemical, and toxicological properties of metallic fluoride, to explore its potential physiological and clinical implications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.174 |
| Meta-epidemiology (narrow) | 0.008 | 0.007 |
| Meta-epidemiology (broad) | 0.019 | 0.004 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 it