ArticleMethods in molecular biology (Clifton, N.J.)2023
Quantitative Analysis of Microscopy Data to Evaluate Bacterial Responses to Antibiotic Treatment.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- The Dual Mode of Antibacterial Action of the Synthetic Small Molecule DCAP Involves Lipid II Binding.Journal of the American Chemical Society · 2024Article
- Double-Labeling Method for Visualization and Quantification of Membrane-Associated Proteins inInternational journal of molecular sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microscopy is a powerful method to evaluate the direct effects of antibiotic action on the single cell level. As with other methodologies, microscopy data is obtained through sufficient biological and technical replicate experiments, where evaluation of the sample is generally followed over time. Even if a single antibiotic is tested for a defined time, the most certain outcome is large amounts of raw data that requires systematic analysis. Although microscopy is a helpful qualitative method, the recorded information is stored as defined quantifiable units, the pixels. When this information is transferred to diverse bioinformatic tools, it is possible to analyze the microscopy data while avoiding the inherent bias associated to manual quantification. Here, we briefly describe methods for the analysis of microscopy images using open-source programs, with a special focus on bacteria exposed to antibiotics.
Indexed as
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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.