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Record W2404927434 · doi:10.1093/femspd/ftw048

Host resistance to intranasal<i>Acinetobacter baumannii</i>reinfection in mice

2016· article· en· W2404927434 on OpenAlexaff
Hongyu Qiu, Zack Li, Rhonda KuoLee, Greg Harris, Xiaoling Gao, Hongbin Yan, H. Howard Xu, Wangxue Chen

Bibliographic record

VenuePathogens and Disease · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsBrock UniversityNational Research Council Canada
Fundersnot available
KeywordsAcinetobacter baumanniiMicrobiologyNasal administrationBiologyHost (biology)BacteriaChemistryVirologyGeneticsPseudomonas aeruginosa

Abstract

fetched live from OpenAlex

Acinetobacter baumannii is a major causative agent of healthcare-associated infection and develops multidrug resistance rapidly. However, little is known in the host defense mechanisms against this infection. In this study, we examined if mice recovered from a previous intranasal A. baumannii infection (recovered mice) are fully protected against a subsequent reinfection. We found that, despite the presence of specific serum IgG and mucosal IgA responses prior to the reinfection, the recovered mice were only marginally better protected against intranasal challenge with low doses of homologous or heterologous A. baumannii strains than the naïve mice. Post-challenge immune and inflammatory (cells and cytokines) responses were generally comparable between recovered and naïve mice although the recovered mice produced significantly higher amounts of IFN-γ and IL-17 and had higher percentages and numbers of resident lung CD44(hi)CD62L(-)CD4(+) and CD19(+) B lymphocytes. Taken together, our results suggest that mice recovered from a previous A. baumannii infection remain susceptible to reinfection, indicating the complexity of immune protection mechanism for this Gram-negative, multidrug-resistant emerging pathogen.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.406

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 head0.005
GPT teacher head0.222
Teacher spread0.217 · 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 designObservational
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

Citations6
Published2016
Admission routes1
Has abstractyes

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