Cardiovascular changes after pneumonia in a dual disease mouse model
Bibliographic record
Abstract
Residual inflammation in cardiovascular organs is thought to be one of the catalysts for the increased risk of cardiovascular complications seen following pneumonia. To test this hypothesis, we investigated changes in plaque characteristics and inflammatory features in ApoE-/- mouse aorta and heart following pneumonia. Male ApoE-/- mice were fed a high fat diet for 8 weeks before intranasal inoculation with either Streptococcus pneumoniae serotype 4 (test group) or phosphate buffered saline (control group). Mice were sacrificed at 2-, 7- and 28-days post-challenge. Changes in plaque burden and characteristics in aortic root and thoracic aorta were characterized by Oil red O and Trichrome stains. Inflammatory changes were investigated by FDG-PET imaging and immunofluorescence staining. We found TIGR4-infected mice present with increased plaque presence in the aortic root and thoracic aorta at 2- and 28-days post-inoculation, respectively. Aortic wall remodelling was also more pronounced in mice challenged with pneumococci at 28 days post-inoculation. Aortic root plaques of infected mice had reduced collagen and smooth muscle cells, consistent with an unstable plaque phenotype. Pneumonia alters plaque burden, plaque characteristics, and aortic wall remodelling in ApoE-/- mice. These effects caused by Streptococcus pneumoniae TIGR4, may contribute to the increased risk of cardiovascular complications seen in survivors of this infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".