Myeloid PTEN Promotes Inflammation but Impairs Bactericidal Activities during Murine Pneumococcal Pneumonia
Bibliographic record
Abstract
Phosphatidylinositol 3-kinase has been described as an essential signaling component involved in the chemotactic cell influx that is required to eliminate pathogens. At the same time, PI3K was reported to modulate the immune response, thus limiting the magnitude of acute inflammation. The precise role of the PI3K pathway and its endogenous antagonist phosphatase and tensin homolog deleted on chromosome 10 (PTEN) during clinically relevant bacterial infections is still poorly understood. Utilizing mice lacking myeloid cell-specific PTEN, we studied the impact of PTEN on the immune response to Streptococcus pneumoniae. Survival analysis disclosed that PTEN-deficient mice displayed less severe signs of disease and prolonged survival. The inflammatory response to S. pneumoniae was greatly reduced in macrophages in vitro and in vivo. Unexpectedly, neutrophil influx to the lungs was significantly impaired in animals lacking myeloid-cell PTEN, whereas the additional observation of improved phagocytosis by alveolar macrophages lacking PTEN ultimately resulted in unaltered lung CFUs following bacterial infection. Together, the absence of myeloid cell-associated PTEN and consecutively enhanced PI3K activity dampened pulmonary inflammation, reduced neutrophil influx, and augmented phagocytic properties of macrophages, which ultimately resulted in decreased tissue injury and improved survival during murine 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
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) | 0.001 | 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".