The p110δ isoform of PI3K modulates TLR4 signalling and is crucial for survival from endotoxin and <i>Escherichia coli</i> infection (P4023)
Bibliographic record
Abstract
Abstract Sepsis, a systemic immune response to severe bacterial infection, is a leading cause of death in critical care medicine caused by dysregulated immune response to bacteria endotoxin LPS which is recognised by TLR4. The p110δ isoform of PI3K is expressed mostly on leukocytes and has been shown to be important in leukocyte recruitment to sites of inflammation and infection. We report that pharmacological or genetic inhibition of p110δ signalling led to increased expression of TLR4 upon LPS stimulation an effect which was not observed for p110α and p110β. Differential cell counting showed higher numbers of inflammatory cells in the peritoneum of p110δ knock-in [p110δ(D910A)] mice compared to wild type mice. Macrophages from p110δ(D910A) mice induced higher proinflammatory cytokines compared to WT mice in response to LPS. In addition, absence of p110δ activity led to mortality in an otherwise non lethal dose of LPS accompanied by exaggerated production of proinflammatory cytokines. We authenticate our findings by showing that p110δ(D910A) mice are unable to recover from a non lethal dose of Escherichia coli infection. Thus modulation of p110δ signalling is a potential therapeutic target in acute inflammation and sepsis
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
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 | 0.001 |
| 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".