Raja 42, a novel gamma lactam compound, is effective against Clostridioides difficile
Bibliographic record
Abstract
Clostridioides difficile infection (CDI) is the primary cause of hospital-acquired diarrhea, and responsible for over 500,000 enteric infections a year in the United States alone. Although most patients with CDI are successfully treated with metronidazole or vancomycin, the high rate of recurrence is still a serious problem, in which case these antibiotics are usually not very effective. The primary objective of this research is to develop a potentially effective therapeutic agent against C. difficile that are resistant to metronidazole or vancomycin. The susceptibility to metronidazole and vancomycin was examined with 194 C. difficile clinical isolates. Sixty of these isolates chosen based on a variety of criteria were examined for their susceptibility against the 4-chloro-1-piperidin-1ylmethyl-1H-indole-2,3-dione compound (Raja 42), a novel isatin-benzothiazole analogue containing a gamma-lactam structure, as we previously found that this novel compound is effective against a variety of different bacteria. Most of the 60 isolates were resistant to ceftriaxone and ciprofloxacin, raising the possibility that they might have been exposed previously to these or structurally similar antibiotics (e.g., β-lactam and quinolone compounds). Among the isolates, 48 (80%) and 54 (90%) were susceptible to metronidazole and vancomycin, respectively. Raja 42 was found to be effective against most of the isolates, especially so against metronidazole-resistant C. difficile. Most importantly, five isolates that show resistance to metronidazole and vancomycin were sensitive to Raja 42. Thus, Raja 42, a gamma lactam antibiotic, has the potential to effectively control C. difficile strains that are resistant to metronidazole and vancomycin.
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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) | 0.000 | 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) | 0.001 | 0.001 |
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".