Evidence map›Paper›PMID 41810130›Full record

ArticleCurrent research in microbial sciences2026

Layer-dependent modulation of

Kate C Blanco, Paul de Figueiredo, Jace A Willis, Leonardo De Boni, Letícia P Martinelli, Vladislav V Yakovlev, Vanderlei S Bagnato

Abstract read
In one paragraph

Article in Current research in microbial sciences, 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

7 authors.

Kate C BlancoDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77840, USA.
Paul de FigueiredoCollege of Medicine, Texas A&M University, College Station, TX 77840, USA.
Jace A WillisDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77840, USA.
Leonardo De BoniSão Carlos Institute of Physics, University of São Paulo, São Carlos 13566-590, Brazil.
Letícia P MartinelliSão Carlos Institute of Physics, University of São Paulo, São Carlos 13566-590, Brazil.
Vladislav V YakovlevDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77840, USA.
Vanderlei S BagnatoDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77840, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bacterial biofilms display pronounced spatial heterogeneity, generating, yet how these effects are distributed across biofilm layers and how surviving cells respond after treatment remain poorly understood. Methods: Results: Light-induced oxidative stress altered post-treatment growth dynamics and impaired the ability of surviving cells to re-establish structured biofilms. Photosensitizer penetration was strongly layer-dependent and influenced by S biofilm maturation and complexity, resulting in spatially heterogeneous photodynamic effects. These effects differentially impacted cells located in superficial versus deeper biofilm regions. Conclusion: These findings demonstrate that photodynamic treatment modulates S. aureus biofilm behavior in a layer-dependent manner, weakening protective niches without requiring complete eradication. By disrupting biofilm microenvironments associated with tolerance and persistence, light-induced oxidative stress limits biofilm recovery and provides a mechanistic basis for photodynamic strategies aimed at controlling biofilm re-establishment.

Indexed as

Biofilm modulationLayer-dependent responsesLight-induced oxidative stressPhotodynamic effectsPost-treatment behaviorS. aureus biofilms

Identifiers

PMID41810130
PMCPMC12968421

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.