Kinase Activity Profiling of Gram-Negative Pneumonia
Bibliographic record
Abstract
Pneumonia is a severe disease with high morbidity and mortality. A major causative pathogen is the Gram-negative bacterium Klebsiella (K.) pneumoniae. Kinases play an integral role in the transduction of intracellular signaling cascades and regulate a diverse array of biological processes essential to immune cells. The current study explored signal transduction events during murine Gram-negative pneumonia using a systems biology approach. Kinase activity arrays enable the analysis of 1,024 consensus sequences of protein kinase substrates. Using a kinase activity array on whole lung lysates, cellular kinase activities were determined in a mouse model of K. pneumoniae pneumonia. Notable kinase activities also were validated with phospho-specific Western blots. On the basis of the profiling data, mitogen-activated protein kinase (MAPK) signaling via p42 mitogen-activated protein kinase (p42) and p38 mitogen-activated protein kinase (p38) and transforming growth factor β (TGFβ) activity were reduced during infection, whereas v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) (SRC) activity generally was enhanced. AKT signaling was represented in both metabolic and inflammatory (mitogen-activated protein kinase kinase 2 [MKK], apoptosis signal-regulating kinase/mitogen-activated protein kinase kinase kinase 5 [ASK] and v-raf murine sarcoma viral oncogene homolog B1 [b-RAF]) context. This study reaffirms the importance of classic inflammation pathways, such as MAPK and TGFβ signaling and reveals less known involvement of glycogen synthase kinase 3β (GSK-3β), AKT and SRC signaling cassettes in pneumonia.
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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".