Bibliographic record
Abstract
Pseudomonas aeruginosa is intrinsically resistant to a variety of antimicrobials and can develop resistance during anti-pseudomonal chemotherapy both of which compromise treatment of infections caused by this organism. Resistance to multiple classes of antimicrobials (multidrug resistance) in particular is increasingly common in P. aeruginosa, with a number of reports of pan-resistant isolates treatable with a single agent, colistin. Acquired resistance in this organism is multifactorial and attributable to chromosomal mutations and the acquisition of resistance genes via horizontal gene transfer. Mutational changes impacting resistance include upregulation of multidrug efflux systems to promote antimicrobial expulsion, derepression of ampC, AmpC alterations that expand the enzyme's substrate specificity (i.e., extended-spectrum AmpC), alterations to outer membrane permeability to limit antimicrobial entry and alterations to antimicrobial targets. Acquired mechanisms contributing to resistance in P. aeruginosa include β-lactamases, notably the extended-spectrum β-lactamases and the carbapenemases that hydrolyze most β-lactams, aminoglycoside-modifying enzymes, and 16S rRNA methylases that provide high-level pan-aminoglycoside resistance. The organism's propensity to grow in vivo as antimicrobial-tolerant biofilms and the occurrence of hypermutator strains that yield antimicrobial resistant mutants at higher frequency also compromise anti-pseudomonal chemotherapy. With limited therapeutic options and increasing resistance will the untreatable P. aeruginosa infection soon be upon us?
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".