Bibliographic record
Abstract
One of a number of critical roles played by NO· as a chemical weapon (generated by the immune system) is to neutralize pathogens. However, the virulence of pathogens depends on the production activity of reductants to detoxify NO·. Broad reactivity of NO· makes it complicated to predict the fate of NO· inside bacteria and its effects on the treatment of any infection. Here, we present a mathematical model of biofilm response to NO·, as a stressor. The model is comprised of a PDE system of highly nonlinear reaction-diffusion equations that we study in computer simulations to determine the positive and negative effects of key parameters on bacterial defenses against NO·. From the reported results, we conjecture that the oscillatory behavior of NO· under a microaerobic regime is a temporal phenomenon and does not give rise to a spatial pattern. It is also shown computationally that decreasing the initial size of the biofilm colony negatively impacts the functionality of reducing agents that deactivate NO·. Whereas nutrient deprivation results in the development of biofilms with heterogeneous structure, its effect on the activity of NO· reductants depends on the oxygen availability, biofilm size, and the amount of NO·.
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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 | 0.001 | 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) | 0.002 | 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".