Positive Florbetapir PET Amyloid Imaging in a Subject with Frequent Cortical Neuritic Plaques and Frontotemporal Lobar Degeneration with TDP43-Positive Inclusions
Bibliographic record
Abstract
Abnormal neuronal accumulation and modification of TAR DNA binding protein 43 (TDP-43) have recently been discovered to be defining histopathological features of particular subtypes of frontotemporal dementia and amyotrophic lateral sclerosis, and are also common in aging, particularly coexisting with hippocampal sclerosis and Alzheimer's disease pathology. This case report describes a 72 year old Hispanic male with no family history of neurological disease, who presented at age 59 with obsessive behavior, anxiety, agitation, and dysphasia. Positron emission tomography imaging using the amyloid ligand 18F florbetapir (Amyvid) was positive. Postmortem examination revealed frequent diffuse and neuritic amyloid plaques throughout the cerebral cortex, thalamus, and striatum, Braak stage II neurofibrillary degeneration, and frequent frontal and temporal cortex TDP-43-positive neurites with rare nuclear inclusions. The case is unusual and instructive because of the co-existence of frequent cortical and diencephalic amyloid plaques with extensive TDP-43-positive histopathology in the setting of early-onset dementia and because it demonstrates that a positive cortical amyloid imaging signal in a subject with dementia does not necessarily establish that Alzheimer's disease is the sole cause.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".