Synergy of a virulent phage (φAB182) with antibiotics leading to successful elimination of biofilms formed by MDR <i>Acinetobacter baumannii</i>
Bibliographic record
Abstract
Emergence of multiple drug resistant (MDR) strains of Acinetobacter baumannii and a withering drug discovery pipeline necessitates the search for effective alternatives to replace or synergize with currently used antibiotics. In this report, we have described the synergy assessment of a virulent Acinetobacter baumannii phage φAB182 with a wide range of antibiotics. Myophage φAB182 was isolated from sewage against MDR A. baumannii and exhibited maximum stability at 25 °C and pH 7. It also had a short latent period of 9 min with a large burst size of 287. The phylogenetic analysis of its major capsid protein gene indicated an 84.15% similarity to the lytic A. baumannii phage Acj9. In the presence of antibiotics, phage φAB182 showed the highest synergy ( p < 0.0001) with colistin, followed by polymixin B, ceftazidime and cefotaxime and this synergistic effect was further validated by time kill kinetics. The combined action of phage φAB182 with colistin, polymixin B, ceftazidime and cefotaxime was also synergistic for the eradication of biofilms formed by A. baumannii as measured by MBECcombination/MBECantibiotic values (<0.25). We thus propose bacteriophage φAB182 as a potential antibacterial candidate in combination therapy. The findings from this study strongly support the use of phage antibiotic synergy for the successful treatment of biofilm forming MDR A. baumannii infections.
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) | 0.000 | 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 | 0.000 |
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 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".