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Record W4407808112 · doi:10.3390/pathogens14030210

Inflammatory Responses to Non-Typeable Haemophilus influenzae Clinical Isolates from Invasive and Non-Invasive Infections

2025· article· en· W4407808112 on OpenAlexafffund
Brenda Huska, Marina Ulanova

Bibliographic record

VenuePathogens · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsNOSM University
FundersCanadian Immunization Research Network
KeywordsHaemophilus influenzaeImmunologyImmune systemInnate immune systemBiologyToll-like receptorSepsisDiseaseMeningitisInflammationAcquired immune systemMicrobiologyMedicineAntibioticsPathology

Abstract

fetched live from OpenAlex

(NTHi) is often asymptomatically carried in the upper airways but can cause a wide spectrum of disease conditions, from local respiratory tract infections to invasive disease such as sepsis or meningitis. The factors driving NTHi's transition from benign carriage to severe systemic disease remain poorly understood. It is unknown whether NTHi strains associated with invasive or non-invasive disease differ in their capacity to trigger inflammatory responses in innate immune cells. To address this question, we have used an in vitro infection model of human THP-1 cells differentiated to macrophages. To evaluate inflammatory responses, we studied the expression of 3 prototypic pro-inflammatory molecules, ICAM-1, TNF-α, and IL-1β. The role of lipooligosaccharide in triggering inflammatory responses was assessed using inhibition of Toll-like receptor 4 signaling. Our experiments demonstrated that NTHi strains isolated from cases of invasive and non-invasive infections were similarly able to induce strong activations of macrophage pro-inflammatory responses. Our findings support the hypothesis that the development of invasive versus non-invasive NTHi disease may be more significantly influenced by the adaptive immune response than the innate immune response.

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)0.001
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 score0.539
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.001

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 head0.019
GPT teacher head0.290
Teacher spread0.271 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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