Phrenic nerve stimulation mitigates hippocampal and brainstem inflammation in an ARDS model
Bibliographic record
Abstract
Rationale: In porcine healthy-lung and moderate acute respiratory distress syndrome (ARDS) models, groups that received phrenic nerve stimulation (PNS) with mechanical ventilation (MV) showed lower hippocampal apoptosis, and microglia and astrocyte percentages than MV alone. Objectives: Explore whether PNS in combination with MV for 12 h leads to differences in hippocampal and brainstem tissue concentrations of inflammatory and synaptic markers compared to MV-only animals. Methods: Compare tissue concentrations of inflammatory markers (IL-1α, IL-1β, IL-6, IL-8, IL-10, IFN-γ, TNFα and GM-CSF), pre-synaptic markers (synapsin and synaptophysin) and post-synaptic markers (disc-large-homolog 4, N-methyl-D-aspartate receptors 2A and 2B) in the hippocampus and brainstem in three groups of mechanically ventilated pigs with injured lungs: MV only (MV), MV plus PNS every other breath (MV + PNS50%), and MV plus PNS every breath (MV + PNS100%). MV settings in volume control were tidal volume 8 ml/kg, and positive end-expiratory pressure 5 cmH2O. Moderate ARDS was achieved by infusing oleic acid into the pulmonary artery. Measurements and Main Results: Hippocampal concentrations of GM-CSF, N-methyl-D-aspartate receptor 2B, and synaptophysin were greater in the MV + PNS100% group compared to the MV group, p = 0.0199, p = 0.0175, and p = 0.0479, respectively. The MV + PNS100% group had lower brainstem concentrations of IL-1β, and IL-8 than the MV group, p = 0.0194, and p = 0.0319, respectively; and greater brainstem concentrations of IFN-γ and N-methyl-D-aspartate receptor 2A than the MV group, p = 0.0329, and p = 0.0125, respectively. Conclusion: In a moderate-ARDS porcine model, MV is associated with hippocampal and brainstem inflammation, and phrenic nerve stimulation on every breath mitigates that inflammation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".