Exploring Iron Deposition Patterns Using Light and Electron Microscopy in the Mouse Brain Across Aging and Alzheimer's Disease Pathology Conditions
Bibliographic record
Abstract
ABSTRACT Alzheimer's disease (AD) involves cognitive decline, possibly via multiple concurrent pathologies associated with iron accumulation. To investigate if iron accumulation in AD is more likely due to pathological iron‐rich compartments, or a compensatory response of iron within oligodendrocytes to disease progression, we sought to quantify iron‐rich staining (via Perl's diaminobenzidine; DAB). Healthy wild‐type (WT) and APP Swe ‐PS1Δe9 (APP‐PS1; amyloid‐beta overexpressing) male mice were examined during middle age, at 14 months. The frontal cortex, a brain region affected over the course of dementia progression, was investigated. Iron‐rich compartments were found across genotypes, including oligodendrocytes and immune cells at the blood–brain barrier, and exclusively amyloid plaques in the APP‐PS1 genotype. A semi‐automated approach was employed to quantify the staining intensity of iron‐rich compartments with light microscopy. Mouse frontal cortex of each genotype was also assessed qualitatively and ultrastructurally with scanning electron microscopy, to novelly discern and confirm iron‐rich staining (via Perl's DAB). We found parenchymal iron staining corresponding to oligodendrocytes, pericytes, astrocytes, microglia and/or infiltrating macrophages, and amyloid plaques; increased iron deposition and clustering were detected in middle‐aged male APP‐PS1 versus WT frontal cortex, supporting that AD pathology may involve greater brain iron levels and local clustering. Unexpectedly, iron‐rich cells were enriched at the central nervous system (CNS) interface and perivascular space in control and APP‐PS1 mouse models, with ultrastructural examination revealing examples of these cells loaded with many secretory granules containing iron. Together, our results provide novel exploration and confirmation of iron‐rich cells/compartments in scanning electron microscopy and reinforce literature that iron deposition is relatively increased in AD over healthy cognitive aging and involves greater local clusters of iron burden. Increased iron burden along the aging trajectory, regardless of cognitive status, may also be attributed to novelly discovered iron‐rich cells secreting granules along the CNS border. image
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".