Adenylate-driven equilibration of both ribo- and deoxyribonucleotides is under magnesium control: Quantification of the Mg2+-signal
Bibliographic record
Abstract
Nucleoside mono-, di- and triphosphates (NMP, NDP, and NTP) and their deoxy-counterparts (dNMP, dNDP, dNTP) are involved in energy metabolism and are the building blocks of RNA and DNA, respectively. The production of NTP and dNTP is carried out by several NMP kinases (NMPK) and NDP kinases (NDPK). All NMPKs are fully reversible and use defined Mg-free and Mg-complexed nucleotides in both directions of their reactions, with Mg 2+ controlling the ratios of Mg-free and Mg-complexed reactants. Their activities are driven by adenylates produced by adenylate kinase which controls the direction of NMPK and NDPK reactions, depending on the energy status of a cell. This enzymatic machinery is localized in the cytosol, mitochondria, and plastids, i.e. compartments with high energy budgets and where (except for cytosol) RNA and DNA synthesis occur. Apparent equilibrium constants of NMPKs, based on total nucleotide contents, are [Mg 2+ ]-dependent. This allows for an indirect estimation of internal [Mg 2+ ], which constitutes a signal of the energetic status of a given tissue/cell/compartment. Adenylates contribute the most to this Mg 2+ -signal, followed by uridylates, guanylates, and cytidylates, with deoxynucleotides’ contribution deemed negligible. A method to quantify the Mg 2+ -signal, using nucleotide datasets, 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".