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Record W2593872179 · doi:10.1128/mbio.00140-17

New Mouse Model for Chronic Infections by Gram-Negative Bacteria Enabling the Study of Anti-Infective Efficacy and Host-Microbe Interactions

2017· article· en· W2593872179 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemBio · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsHost (biology)MicrobiologyGram-negative bacteriaBacteriaBiologyEscherichia coliEcologyGenetics

Abstract

fetched live from OpenAlex

ABSTRACT Only a few, relatively cumbersome animal models enable long-term Gram-negative bacterial infections that mimic human situations, where untreated infections can last for weeks. Here, we describe a simple murine cutaneous abscess model that enables chronic or progressive infections, depending on the subcutaneously injected bacterial strain. In this model, Pseudomonas aeruginosa cystic fibrosis epidemic isolate LESB58 caused localized high-density skin and soft tissue infections and necrotic skin lesions for up to 10 days but did not disseminate in either CD-1 or C57BL/6 mice. The model was adapted for use with four major Gram-negative nosocomial pathogens, Acinetobacter baumannii , Klebsiella pneumoniae , Enterobacter cloacae , and Escherichia coli . This model enabled noninvasive imaging and tracking of lux -tagged bacteria, the influx of activated neutrophils, and production of reactive oxygen-nitrogen species at the infection site. Screening antimicrobials against high-density infections showed that local but not intravenous administration of gentamicin, ciprofloxacin, and meropenem significantly but incompletely reduced bacterial counts and superficial tissue dermonecrosis. Bacterial RNA isolated from the abscess tissue revealed that Pseudomonas genes involved in iron uptake, toxin production, surface lipopolysaccharide regulation, adherence, and lipase production were highly upregulated whereas phenazine production and expression of global activator gacA were downregulated. The model was validated for studying virulence using mutants of more-virulent P. aeruginosa strain PA14. Thus, mutants defective in flagella or motility, type III secretion, or siderophore biosynthesis were noninvasive and suppressed dermal necrosis in mice, while a strain with a mutation in the bfiS gene encoding a sensor kinase showed enhanced invasiveness and mortality in mice compared to controls infected with wild-type P. aeruginosa PA14. IMPORTANCE More than two-thirds of hospital infections are chronic or high-density biofilm infections and difficult to treat due to adaptive, multidrug resistance. Unfortunately, current models of chronic infection are technically challenging and difficult to track without sacrificing animals. Here we describe a model of chronic subcutaneous infection and abscess formation by medically important nosocomial Gram-negative pathogens that is simple and can be used for tracking infections by imaging, examining pathology and immune responses, testing antimicrobial treatments suitable for high-density bacterial infections, and studying virulence. We propose that this mouse model can be a game changer for modeling hard-to-treat Gram-negative bacterial chronic and skin infections.

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.

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 score0.023
Threshold uncertainty score0.885

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 studies0.0010.000
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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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