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Record W4414296668 · doi:10.1002/mabi.202500452

Biohybrid Living Material with Antibacterial and Regenerating Properties Based on Probiotic Bacteria Stress Metabolism Modulation

2025· article· en· W4414296668 on OpenAlexaff
Alina V. Lokteva, Kristina O. Baskakova, Erik R. Gandalipov, Nikita Serov, Mariia A. Mikhailova, Elena I. Koshel

Bibliographic record

VenueMacromolecular Bioscience · 2025
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Ozone Research
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsStaphylococcus aureusWound healingRegeneration (biology)Antibacterial activityIn vivoBacteriaProbioticOxidative stressAntibacterial agent

Abstract

fetched live from OpenAlex

Wound healing is an intricate process that involves various biochemical pathways at each stage of tissue regeneration. Wound therapy is a series of distinct treatment stages that has a limited efficacy if wounds are of complex etiologies. A modern approach to this problem may be the development of bifunctional adaptive biohybrid systems that can concurrently affect pathogens' growth, inflammation, and tissue regeneration. We have developed biohybrid living material with antibacterial and regenerating properties based on induced hormesis by oxidative stress onto probiotic bacteria with prolonged synthesis of hydrogen peroxide, increased antibacterial action, and regeneration of the burn wound. Material demonstrates almost complete wound healing with a wound area difference 3-4 times with natural healing in vivo burn wound model for 21 days, antibacterial activity against wound antibiotic-resistance pathogens Escherichia coli K12 and Staphylococcus aureus ATCC 29213 in 4 and 5-fold, respectively in co-cultivation model, and has no toxicity to human skin fibroblasts and β-hemolysis in the in vitro model. Our findings promise the improving tissue regeneration of burn wounds, therapy against antibiotic-resistance pathogens by eliminating antibiotics, and other classical bactericides.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.250
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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