Systemic Inflammation in C57BL/6J Mice Receiving Dietary Aluminum Sulfate; Up-Regulation of the Pro-Inflammatory Cytokines IL-6 and TNFα, C-Reactive Protein (CRP) and miRNA-146a in Blood Serum
Bibliographic record
Abstract
A number of experimental investigations utilizing different murine species have previously reported: (i) that standard mouse-diets supplemented with physiologically realistic amounts of neurotoxic metal salts substantially induce pro-inflammatory signaling in a number of murine tissues; (ii) that these diet-stimulated changes may contribute to a systemic inflammation (SI), a potential precursor to neurodegenerative events in both the central and the peripheral nervous system (CNS, PNS); and (iii) that these events may ultimately contribute to a chronic and progressive inflammatory neurodegeneration, such as that which is observed in Alzheimer’s disease (AD) brain. In these experiments we assayed for markers of SI in the blood serum of C57BL/6J mice after 0, 1, 3 and 5 months of exposure to a standard mouse diet that included aluminum-sulfate in the food and drinking water, compared to agematched controls receiving magnesium-sulfate or no additions. The data indicate that the SI markers that include the pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor alpha (TNFα), the acute phase reactive protein C-reactive protein (CRP) production and a triad of pro-inflammatory microRNAs (miRNA-9, miRNA-125b and miRNA-146a) all increase in the serum after aluminum-sulfate exposure. For the first time these results suggest that ad libitum exposure to aluminum-sulfate at physiologically realistic concentrations, as would be found in the human diet over the long term, may predispose to SI and the potential development of chronic, progressive, inflammatory neurodegeneration with downstream pathogenic consequences.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".