The Forgotten History of Bacteriophages in Bulgaria: An Overview and Molecular Perspective on Their Role in Addressing Antibiotic Resistance and Therapy
Bibliographic record
Abstract
Bacteriophages, often referred to as "bacteria eaters," have gained renewed interest as a powerful alternative to traditional antibiotics, particularly in addressing antibiotic-resistant bacterial infections. The present review summarizes data collected in Bulgaria during the 1960s, 1970s, and 1980s, drawing connections between past findings and present-day understanding of cytotoxicity and the clinical validation of bacteriophage applications. Its sections describe phage structure, mechanisms of action, and historical findings both globally and within the Bulgarian context, while also highlighting emerging trends and applications. The cited studies delve into the past through contemporary research contributions related to "Bulgarian phages", a topic that remains underexplored in existing literature. The role of phages in medical microbiology is discussed alongside the challenges of therapeutic implementation, with particular focus on insights gained from the Bulgarian experience. In conclusion, by fostering international collaborations, investing in infrastructure, and establishing supportive policies, bacteriophage therapy can emerge as a critical tool for managing bacterial infections and reducing the global burden of antibiotic resistance in the future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".