Evidence map›Paper›PMID 41753758›Full record

ArticleMicroorganisms2026

Investigation of the Mechanisms of Transition of Gram-Negative Bacterial Cells into Induced Anabiosis Using Computational Methods of Classical Molecular Dynamics.

Ksenia Tereshkina, Eduard Tereshkin, Licheng Zhang, Petr Zaytsev, Vladislav Kovalenko, Yuriy Litti, Olga S Sokolova, Yurii Krupyanskii, Nataliya Loiko

Abstract read
In one paragraph

Article in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Ksenia TereshkinaSemenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia.ORCID 0000-0003-1165-5224
Eduard TereshkinSemenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia.ORCID 0000-0001-6091-7476
Licheng ZhangFaculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia.
Petr ZaytsevFaculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia.
Vladislav KovalenkoSemenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia.ORCID 0000-0001-9851-8358
Yuriy LittiWinogradsky Institute of Microbiology, Fundamentals of Biotechnology Federal Research Center, Russian Academy of Sciences, 117312 Moscow, Russia.ORCID 0000-0002-5457-4603
Olga S SokolovaFaculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia.ORCID 0000-0003-4678-232X
Yurii KrupyanskiiSemenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, 119991 Moscow, Russia.
Nataliya LoikoWinogradsky Institute of Microbiology, Fundamentals of Biotechnology Federal Research Center, Russian Academy of Sciences, 117312 Moscow, Russia.ORCID 0000-0001-5204-007X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studying the mechanisms by which Gram-negative heterotrophic bacteria transition from active metabolism to dormancy is an important task, as it is directly related to the problem of bacterial antibiotic resistance and the spread of nosocomial infections. Using electron microscopy, microbiology, and molecular modeling, we investigated the dose-dependent mechanisms of action of 4-hexylresorcinol (4HR), a chemical analog of the anabiosis autoinducer, on the cell membranes of Gram-negative bacteria (using

Indexed as

4-hexylresorcinolbacterial antibiotic resistancebacterial cell survivalclassical molecular dynamicsdormant cellsEscherichia colimembrane of Gram-negative cells

Identifiers

PMID41753758
PMCPMC12943714

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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.