ReviewAdvances in microbial physiology2023
Bacterial metabolism and susceptibility to cell wall-active antibiotics.
Review in Advances in microbial physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 18 citations in OpenAlex.
- Synergistic Action of Antimicrobial Peptides and Antibiotics.International journal of molecular sciences · 2026Review
- Selenium nanoparticle loaded on PVA/chitosan biofilm synthesized from orange peels: antimicrobial and antioxidant properties for plum preservation.BMC chemistry · 2025Article
- Article
- Meat Quality Traits Using Gelatin-Green Tea Extract Hybrid Electrospun Nanofiber Active Packaging.Foods (Basel, Switzerland) · 2025Article
- Structure, Function, and Regulation of LytA: TheMicroorganisms · 2025Review
- Research Progress on the Antibacterial Activity of Natural Flavonoids.Antibiotics (Basel, Switzerland) · 2025Review
- A mutation in RNA polymerase imparts resistance to β-lactams by preventing dysregulation of amino acid and nucleotide metabolism.Cell reports · 2025Article
- Bacterial peptidoglycan as a living polymer.Current opinion in chemical biology · 2025Review
- Docosahexaenoic Acid-Driven Metabolic Reprogramming as an Attractive Anti-Infection Strategy to Potentiate β-Lactam Antibiotic Efficacy.Research (Washington, D.C.) · 2025Article
- Beyond antibiotics: exploring multifaceted approaches to combat bacterial resistance in the modern era: a comprehensive review.Frontiers in cellular and infection microbiology · 2025Review
- The role ofJournal of bacteriology · 2024Article
- Rhodamine 19 Alkyl Esters as Effective Antibacterial Agents.International journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Bacterial infections are increasingly resistant to antimicrobial therapy. Intense research focus has thus been placed on identifying the mechanisms that bacteria use to resist killing or growth inhibition by antibiotics and the ways in which bacteria share these traits with one another. This work has led to the advancement of new drugs, combination therapy regimens, and a deeper appreciation for the adaptability seen in microorganisms. However, while the primary mechanisms of action of most antibiotics are well understood, the more subtle contributions of bacterial metabolic state to repairing or preventing damage caused by antimicrobials (thereby promoting survival) are still understudied. Here, we review a modern viewpoint on a classical system: examining bacterial metabolism's connection to antibiotic susceptibility. We dive into the relationship between metabolism and antibiotic efficacy through the lens of growth rate, energy state, resource allocation, and the infection environment, focusing on cell wall-active antibiotics.
Indexed as
Identifiers
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.