Lung-brain crosstalk: Behavioral disorders and neuroinflammation in septic survivor mice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although studies have suggested an association between lung infections and increased risk of neuronal disorders (e.g., dementia, cognitive impairment, and depressive and anxious behaviors), its mechanisms remain unclear. Thus, an experimental mice model of pulmonary sepsis was developed to investigate the relationship between lung and brain inflammation. Male Swiss mice were randomly assigned to either pneumosepsis or control groups. Pneumosepsis was induced by intratracheal instillation of Klebsiella pneumoniae, while the control group received a buffer solution. The model's validation included assessing systemic markers, as well as tissue vascular permeability. Depression- and anxiety-like behaviors and cognitive function were assessed for 30 days in sepsis survivor mice, Inflammatory profiles, including cytokine levels (lungs, hippocampus, and prefrontal cortex) and microglial activation (hippocampus), were examined. Pulmonary sepsis damaged distal organs, caused peripheral inflammation, and increased vascular permeability in the lung and brain, impairing the blood-brain barrier and resulting in bacterial dissemination. After sepsis induction, we observed an increase in myeloperoxidase activity in the lungs (up to seven days) and prefrontal cortex (up to 24 h), proinflammatory cytokines in the hippocampus and prefrontal cortex, and percentage of areas with cells positive for ionized calcium-binding adaptor molecule 1 (IBA-1) in the hippocampus. Also, depression- and anxiety-like behaviors and changes in short-term memory were observed even 30 days after sepsis induction, suggesting a crosstalk between inflammatory responses of lungs and brain.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it