Antimicrobial Resistance in<i>Campylobacter</i>
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
This chapter provides a review of prevalence and trends of resistance in Campylobacter jejuni and Campylobacter coli isolated from humans in different parts of the world and a more thorough description of the mechanisms of resistance, origin, spread, and clinical consequences of resistance. Aminoglycosides exhibit rapid and significant bactericidal effects in vitro and should initially be included for the treatment of Campylobacter bacteremia in patients who appear very ill. The only mechanism of chloramphenicol resistance identified in Campylobacter occurs through modification of chloramphenicol by chloramphenicol acetyltransferase, which prevents its binding to the ribosome. The majority of contacts between Tet(O) and the ribosome are mediated by the rRNA, and one interaction with ribosomal protein S12. Most of the antimicrobials used in veterinary medicine are tetracyclines and macrolides, which result in high and continuous selective pressure for the animal-colonizing bacteria, ultimately resulting in the acquisition of antimicrobial resistance genes. Investigation into the mechanisms of action of antimicrobials, as well as the transfer of resistance determinants, is necessary to gain effective control of antimicrobial resistance. Epidemiological and microbiological studies show that poultry is the most important source for quinolone-susceptible and quinolone-resistant Campylobacter infections in humans. Trends over time for macrolide resistance show stable low rates in most countries, and macrolides should remain the drug class of choice for C. jejuni and C. coli enteritis.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 it