Bibliographic record
Abstract
Since their discovery, antimicrobial agents have revolutionized the treatment of infectious disease. However, increased use of these agents contributed to the development of microbial resistance almost immediately, rendering these treatments less effective, or often useless. Despite considerable pressures on the scientific community, few new classes of antimicrobial agents have been discovered since the antibiotic era (1950-1970). Microbes’ astonishing ability to adapt to antibiotics has posed a serious threat to the modern health care system. In order to reduce the prevalence of resistance and develop new antimicrobial agents, it is crucial to understand the origins of antibiotics, the development of resistance through evolutionary mechanisms, and the biochemical mode of action of antibiotics along with their associated resistance pathways. This review investigates the various mechanisms of antibiotic resistance, from both an evolutionary and biochemical standpoint. Microbes are able to adapt and mutate at unparalleled rates through mechanisms such as horizontal gene transfer and high reproduction rates. Acquired resistance mechanisms include modifying enzymes, point mutations in the target site of antibiotics, and reduced uptake of antibiotics. This paper concludes by considering responses to the current crisis in microbial resistance, such as preventative measures and the development of new antibiotics.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".