ReviewScience (New York, N.Y.)2016
Multidrug evolutionary strategies to reverse antibiotic resistance.
Review in Science (New York, N.Y.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 345 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
345 citing papers in PubMed, 733 citations in OpenAlex.
- Predicting resistance evolution to guide antibiotic development.Nature reviews. Microbiology · 2026Review
- Quantifying antibiotic susceptibility and inoculum effects using transient dynamics of Pseudomonas aeruginosa.PLoS computational biology · 2026Article
- TACTIC: A transfer learning framework to predict drug interactions in emerging pathogens.Cell reports methods · 2026Article
- Fangchinoline drives NOS2-dependent host immunity to restrict intracellular enteric pathogens.iScience · 2026Article
- Impaired Membrane Energetics Underlies Collateral Sensitivity to Amphenicols During Meropenem Resistance Evolution inMicroorganisms · 2026Article
- CRISPR/Cas system as a novel therapeutic strategy to combat multi-drug-resistant bacteria.Archives of microbiology · 2026Review
- Acquired mutations in transcriptional regulatorAntimicrobial agents and chemotherapy · 2026Article
- A microfluidic hollow-fiber infection model (µHFIM): monitoring bacterial response to dynamic drug treatment with single-cell resolution.Microsystems & nanoengineering · 2026Article
- Using Machine Learning to Design Effective Antimicrobial Dosing Regimens.Computers & chemical engineering · 2026Article
- Advancements in Technologies Targeting Horizontal Gene TransferRoutes to Control Drug Resistance Evolution.ACS bio & med chem Au · 2026Review
- Transcription attenuation amplifies collateral vulnerabilities in rifampicin-resistant Mycobacterium tuberculosis.Nature microbiology · 2026Article
- The Spermidine Synthase Gene as a Reporter of Transcription Inhibition inInternational journal of molecular sciences · 2026Article
- Two Worlds, One Battle: How Bacteria and Malignancies Converge on Drug Resistance.International journal of molecular sciences · 2026Review
- Synergistic Inhibitory Effect and Mechanism of Action of Cinnamaldehyde-Carvacrol Nanoemulsion on the Staphylococcus aureus and Escherichia coli Mixed Biofilms Formation.MicrobiologyOpen · 2026Article
- Uncovering actionable trade-offs of antifungal resistance in a yeast pathogen.Molecular systems biology · 2026Article
- The Role of Combination Antibiotic Therapy in Combatting Drug-ResistantAntibiotics (Basel, Switzerland) · 2026Review
- Robust antibiotic sensitization of pathogenic Pseudomonas aeruginosa via negative hysteresis in the cell envelope.Nature communications · 2026Article
- Sequential Phage Delivery Can Outperform Cocktails by Delaying Cross-Resistance Evolution.Viruses · 2026Article
- Bayesian network models to assess antimicrobial resistance patterns of Streptococcus suis isolated from swine production systems in the United States between 2014-2021.PLoS computational biology · 2026Article
- Cryptic phenotypic variation emerges rapidly during the adaptive evolution of a carbapenemase.Nature ecology & evolution · 2026Article
285 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Antibiotic treatment has two conflicting effects: the desired, immediate effect of inhibiting bacterial growth and the undesired, long-term effect of promoting the evolution of resistance. Although these contrasting outcomes seem inextricably linked, recent work has revealed several ways by which antibiotics can be combined to inhibit bacterial growth while, counterintuitively, selecting against resistant mutants. Decoupling treatment efficacy from the risk of resistance can be achieved by exploiting specific interactions between drugs, and the ways in which resistance mutations to a given drug can modulate these interactions or increase the sensitivity of the bacteria to other compounds. Although their practical application requires much further development and validation, and relies on advances in genomic diagnostics, these discoveries suggest novel paradigms that may restrict or even reverse the evolution of resistance.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.