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Record W2121567540 · doi:10.1093/infdis/jir657

Sex-Based Differences in Susceptibility to Respiratory and Systemic Pneumococcal Disease in Mice

2011· article· en· W2121567540 on OpenAlexaff
Aras Kadioglu, Anna Maria Cuppone, Claudia Trappetti, Thomas List, Adriano Spreafico, Gianni Pozzi, Peter W. Andrew, Marco R. Oggioni

Bibliographic record

VenueThe Journal of Infectious Diseases · 2011
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsInstitute of Infection and Immunity
FundersAstraZeneca
KeywordsPneumococcal diseaseRespiratory systemImmunologyMedicineDiseaseStreptococcus pneumoniaeRespiratory diseaseSystemic diseasePneumococcal infectionsBiologyImmunopathologyInternal medicineMicrobiologyLungAntibiotics

Abstract

fetched live from OpenAlex

Systemic infection with Streptococcus pneumoniae was investigated in male and female mice in models of invasive pneumonia and sepsis. Male mice were found to be more susceptible to infection, exhibiting greater weight loss, marked decrease in body temperature, and a significantly higher mortality rate compared with female mice. For pneumonia, there were significant differences in survival rates. Female mice cleared their lung infections over time, whereas male mice, compared with female mice, had significantly increased numbers of colony-forming units in early stages of infection accompanied by higher levels of neutrophil recruitment in the first 24 hours after infection. Importantly, there were significant increases in proinflammatory cytokine levels during both sepsis and pneumonia in male compared with female mice. These cytokines were indicative of T-helper 1-type responses. The data presented here describe surprising differences in survival rates, neutrophil recruitment, and proinflammatory cytokine levels, indicating a sex-based difference in susceptibility to respiratory and systemic pneumococcal disease.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), 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

Citations111
Published2011
Admission routes1
Has abstractyes

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