Extensive Involvement of Autophagy in Alzheimer Disease: An Immuno-Electron Microscopy Study
Bibliographic record
Abstract
The accumulation of lysosomes and their hydrolases within neurons is a well-established neuropathologic feature of Alzheimer disease (AD). Here we show that lysosomal pathology in AD brain involves extensive alterations of macroautophagy, an inducible pathway for the turnover of intracellular constituents, including organelles. Using immunogold labeling with compartmental markers and electron microscopy on neocortical biopsies from AD brain, we unequivocally identified autophagosomes and other prelysosomal autophagic vacuoles (AVs), which were morphologically and biochemically similar to AVs highly purified from mouse liver. AVs were uncommon in brains devoid of AD pathology but were abundant in AD brains particularly, within neuritic processes, including synaptic terminals. In dystrophic neurites, autophagosomes, multivesicular bodies, multilamellar bodies, and cathepsin-containing autophagolysosomes were the predominant organelles and accumulated in large numbers. These compartments were distinguishable from lysosomes and lysosomal dense bodies, previously shown also to be abundant in dystrophic neurites. Autophagy was evident in the perikarya of affected neurons, particularly in those with neurofibrillary pathology where it was associated with a relative depletion of mitochondria and other organelles. These observations provide the first evidence that macroautophagy is extensively involved in the neurodegenerative/regenerative process in AD. The striking accumulations of immature AV forms in dystrophic neurites suggest that the transport of AVs and their maturation to lysosomes may be impaired, thereby impeding the suspected neuroprotective functions of autophagy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".