Modular Transcriptional Networks of the Host Pulmonary Response during Early and Late Pneumococcal Pneumonia
Bibliographic record
Abstract
Streptococcus pneumoniae (Spneu) remains the most lethal bacterial pathogen and the dominant agent of community-acquired pneumonia. Treatment has perennially focused on the use of antibiotics, albeit scrutinized due to the occurrence of antibiotic-resistant Spneu strains. Immunomodulatory strategies have emerged as potential treatment options. Although promising, immunomodulation can lead to improper tissue functions either at steady state or upon infectious challenge. This argues for the availability of tools to enable a detailed assessment of whole pulmonary functions during the course of infection, not only those functions biased to the defense response. Thus, through the use of an unbiased tissue microarray and bioinformatics approach, we aimed to construct a comprehensive map of whole-lung transcriptional activity and cellular pathways during the course of pneumococcal pneumonia. We performed genome-wide transcriptional analysis of whole lungs before and 6 and 48 h after Spneu infection in mice. The 4,000 most variable transcripts across all samples were used to assemble a gene coexpression network comprising 13 intercorrelating modules (clusters of genes). Fifty-four percent of this whole-lung transcriptional network was altered 6 and 48 h after Spneu infection. Canonical signaling pathway analysis uncovered known pathways imparting protection, including IL17A/IL17F signaling and previously undetected mechanisms that included lipid metabolism. Through in silico prediction of cell types, pathways were observed to enrich for distinct cell types such as a novel stromal cell lipid metabolism pathway. These cellular mechanisms were furthermore anchored at functional hub genes of cellular fate, differentiation, growth and transcription. Collectively, we provide a benchmark unsupervised map of whole-lung transcriptional relationships and cellular activity during early and late pneumococcal pneumonia.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".