On the Architecture of the Gram-Negative Bacterial Murein Sacculus
Bibliographic record
Abstract
The peptidoglycan network of the murein sacculus must be porous so that nutrients, waste products, and secreted proteins can pass through. Using Escherichia coli and Pseudomonas aeruginosa as a baseline for gram-negative sacculi, the hole size distribution in the peptidoglycan network has been modeled by computer simulation to deduce the network's properties. By requiring that the distribution of glycan chain lengths predicted by the model be in accord with the distribution observed, we conclude that the holes are slits running essentially perpendicular to the local axis of the glycan chains (i. e., the slits run along the long axis of the cell). This result is in accord with previous permeability measurements of Beveridge and Jack and Demchik and Koch. We outline possible advantages that might accrue to the bacterium via this architecture and suggest ways in which such defect structures might be detected. Certainly, large molecules do penetrate the peptidoglycan layer of gram-negative bacteria, and the small slits that we suggest might be made larger by the bacterium.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".