Co-Transcriptomes of Initial Interactions In Vitro between Streptococcus Pneumoniae and Human Pleural Mesothelial Cells
Bibliographic record
Abstract
Streptococcus pneumoniae (Spn) is a major causative organism of empyema, an inflammatory condition occurring in the pleural sac. In this study, we used human and Spn cDNA microarrays to characterize the transcriptional responses occurring during initial contact between Spn and a human pleural mesothelial cell line (PMC) in vitro. Using stringent filtering criteria, 42 and 23 Spn genes were up-and down-regulated respectively. In particular, genes encoding factors potentially involved in metabolic processes and Spn adherence to eukaryotic cells were up-regulated e.g. glnQ, glnA, aliA, psaB, lytB and nox. After Spn initial contact, 870 human genes were differentially regulated and the largest numbers of significant gene expression changes were found in canonical pathways for eukaryotic initiation factor 2 signaling (60 genes out of 171), oxidative phosphorylation (32/103), mitochondrial dysfunction (37/164), eIF4 and p70S6K signaling (28/142), mTOR signaling (27/182), NRF2-mediated oxidative stress response (20/177), epithelial adherens junction remodeling (11/66) and ubiquitination (22/254). The cellular response appeared to be directed towards host cell survival and defense. Spn did not activate NF-kB or phosphorylate p38 MAPK or induce cytokine production from PMC. Moreover, Spn infection of TNF-α pre-stimulated PMC inhibited production of IL-6 and IL-8 secretion by >50% (p<0.01). In summary, this descriptive study provides datasets and a platform for examining further the molecular mechanisms underlying the pathogenesis of empyema.
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How this classification was reachedexpand
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, unvalidatedMachine predicted; a candidate call from one teacher head, 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".