White matter changes in the perforant path area in patients with amyotrophic lateral sclerosis
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to test the hypothesis that white matter degeneration of the perforant path - as part of the Papez circuit - is a key feature of amyotrophic lateral sclerosis (ALS), even in the absence of frontotemporal dementia (FTD) or deposition of pTDP-43 inclusions in hippocampal granule cells. METHODS: We used diffusion Magnetic Resonance Imaging (dMRI), polarized light imaging (PLI) and immunohistochemical analysis of post mortem hippocampus specimens from controls (n = 5) and ALS patients (n = 14) to study white matter degeneration in the perforant path. RESULTS: diffusion Magnetic Resonance Imaging demonstrated a decrease in fractional anisotropy (P = 0.01) and an increase in mean diffusivity (P = 0.01) in the perforant path in ALS compared to controls. PLI-myelin density was lower in ALS (P = 0.05) and correlated with fractional anisotropy (r = 0.52, P = 0.03). These results were confirmed by immunohistochemistry; both myelin (proteolipid protein, P = 0.03) and neurofilaments (SMI-312, P = 0.02) were lower in ALS. Two out of the fourteen ALS cases showed pTDP-43 pathology in the dentate gyrus, but with comparable myelination levels in the perforant path to other ALS cases. CONCLUSION: We conclude that degeneration of the perforant path occurs in ALS patients and that this may occur before, or independent of, pTDP-43 aggregation in the dentate gyrus of the hippocampus. Future research should focus on correlating the degree of cognitive decline to the amount of white matter atrophy in the perforant path.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".