Protein-Energy Malnutrition Developing after Global Brain Ischemia Induces an Atypical Acute-Phase Response and Hinders Expression of GAP-43
Bibliographic record
Abstract
Protein-energy malnutrition (PEM) is a common post-stroke problem. PEM can independently induce a systemic acute-phase response, and pre-existing malnutrition can exacerbate neuroinflammation induced by brain ischemia. In contrast, the effects of PEM developing in the post-ischemic period have not been studied. Since excessive inflammation can impede brain remodeling, we investigated the effects of post-ischemic malnutrition on neuroinflammation, the acute-phase reaction, and neuroplasticity-related proteins. Male, Sprague-Dawley rats were exposed to global forebrain ischemia using the 2-vessel occlusion model or sham surgery. The sham rats were assigned to control diet (18% protein) on day 3 after surgery, whereas the rats exposed to global ischemia were assigned to either control diet or a low protein (PEM, 2% protein) diet. Post-ischemic PEM decreased growth associated protein-43, synaptophysin and synaptosomal-associated protein-25 immunofluorescence within the hippocampal CA3 mossy fiber terminals on day 21, whereas the glial response in the hippocampal CA1 and CA3 subregions was unaltered by PEM. No systemic acute-phase reaction attributable to global ischemia was detected in control diet-fed rats, as reflected by serum concentrations of alpha-2-macroglobulin, alpha-1-acid glycoprotein, haptoglobin, and albumin. Acute exposure to the PEM regimen after global brain ischemia caused an atypical acute-phase response. PEM decreased the serum concentrations of albumin and haptoglobin on day 5, with the decreases sustained to day 21. Serum alpha-2-macroglobulin concentrations were significantly higher in malnourished rats on day 21. This provides the first direct evidence that PEM developing after brain ischemia exerts wide-ranging effects on mechanisms important to stroke recovery.
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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) | 0.000 | 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) | 0.001 | 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".