Adenylate Gradients and Ar:O2 Effects on Legume Nodules: I. Mathematical Models
Bibliographic record
Abstract
Mathematical models were developed to test the likelihood that large cytosolic adenylate concentration gradients exist across the bacteria-infected cells of legume nodules. Previous studies hypothesized that this may be the case to account for the unusually low adenylate energy charge (AEC; 0.65) measured in the plant fraction of metabolically active nodules (M.M. Kuzma, H. Winter, P. Storer, I. Oresnik, C.A. Atkins, D.B. Layzell [1999] Plant Physiol 119: 399-407). Simulations coupled leghemoglobin-facilitated O(2) diffusion into the infected cell, through bacteroid nitrogenase activity, with the ATP demand for transport and ammonia assimilation in the plant fraction of ureide- and amide-producing nodules. Although large cytosolic adenylate gradients were predicted to exist in both nodule types, amide nodules were predicted to have steeper AEC gradients (0.82-0.52) than ureide nodules (0.82-0.61). The differences were attributed to an additional ATP demand for Asn synthesis in the amide nodule. Simulations for nodules transferred to an Ar:O(2) atmosphere predicted a major reduction in the magnitude of adenylate gradients and an increase in the AEC of the plant fraction. Results were consistent with a number of experimental studies and were used to propose an experimental test of the models.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".