<i>Streptococcus pneumoniae</i>and<i>Staphylococcus aureus</i>Pneumonia Induce Distinct Metabolic Responses
Bibliographic record
Abstract
Pneumonia is an infection of the lower respiratory tract caused by microbial pathogens. Two such pathogens, Streptococcus pneumoniae and Staphylococcus aureus, are the most common causes of community-acquired and hospital-acquired pneumonia respectively. Each expresses strains highly resistant to penicillin and other antibiotics, and a significant number of people succumb to infection by these pathogens every year. Urinary metabolite changes in a C57Bl/6 mouse model with lung infection from either S. pneumoniae or S. aureus were characterized using multivariate targeted profiling data obtained from (1)H NMR spectra. Marked changes in the urinary metabolite profile occurred within 24 h after infection with either pathogen. Specifically, significant decreases in TCA cycle intermediates, coupled with increases in fucose, creatine, and taurine were observed in the urine of S. pneumoniae-treated mice. Infection with S. aureus resulted in the decrease of a number of urinary metabolites including 1-methylnicotinamide, 3-methyl-2-oxovalerate, 2-oxoisocaproate, N-isovaleroylglycine and others. Disturbances in gut-derived microbial metabolites were also observed. Analysis of metabolic trajectory data indicated that, as the mice recovered from infection, their urinary metabolic profile became similar to that of the preinfected state. These results underline the potential of metabolomics as a tool for diagnosis, health monitoring, and drug development, and show its usefulness for understanding microbial-host interactions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".