Sodium Ion Cycle in Bacterial Pathogens: Evidence from Cross-Genome Comparisons
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
Analysis of the bacterial genome sequences shows that many human and animal pathogens encode primary membrane Na+ pumps, Na+-transporting dicarboxylate decarboxylases or Na+ translocating NADH:ubiquinone oxidoreductase, and a number of Na+ -dependent permeases. This indicates that these bacteria can utilize Na+ as a coupling ion instead of or in addition to the H+ cycle. This capability to use a Na+ cycle might be an important virulence factor for such pathogens as Vibrio cholerae, Neisseria meningitidis, Salmonella enterica serovar Typhi, and Yersinia pestis. In Treponema pallidum, Chlamydia trachomatis, and Chlamydia pneumoniae, the Na+ gradient may well be the only energy source for secondary transport. A survey of preliminary genome sequences of Porphyromonas gingivalis, Actinobacillus actinomycetemcomitans, and Treponema denticola indicates that these oral pathogens also rely on the Na+ cycle for at least part of their energy metabolism. The possible roles of the Na+ cycling in the energy metabolism and pathogenicity of these organisms are reviewed. The recent discovery of an effective natural antibiotic, korormicin, targeted against the Na+ -translocating NADH:ubiquinone oxidoreductase, suggests a potential use of Na+ pumps as drug targets and/or vaccine candidates. The antimicrobial potential of other inhibitors of the Na+ cycle, such as monensin, Li+ and Ag+ ions, and amiloride derivatives, is discussed.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 it