No interaction between tau and <scp>TDP</scp>‐43 pathologies in either frontotemporal lobar degeneration or motor neurone disease
Bibliographic record
Abstract
INTRODUCTION: Frontotemporal lobar degeneration (FTLD) is classified mainly into FTLD-tau and FTLD-TDP according to the protein present within inclusion bodies. While such a classification implies only a single type of protein should be present, recent studies have demonstrated dual tau and TDP-43 proteinopathy can occur, particularly in inherited FTLD. METHODS: We therefore investigated 33 patients with FTLD-tau (including 9 with MAPT mutation) for TDP-43 pathological changes, and 45 patients with FTLD-TDP (including 12 with hexanucleotide expansion in C9ORF72 and 12 with GRN mutation), and 23 patients with motor neurone disease (3 with hexanucleotide expansion in C9ORF72), for tauopathy. RESULTS: TDP-43 pathological changes, of the kind seen in many elderly individuals with Alzheimer's disease, were seen in only two FTLD-tau cases--a 70-year-old male with exon 10 + 13 mutation in MAPT, and a 73-year-old female with corticobasal degeneration. Such changes were considered to be secondary and probably reflective of advanced age. Conversely, there was generally only scant tau pathology, usually only within hippocampus and/or entorhinal cortex, in most patients with FTLD-TDP or MND. The extent of tau pathology in FTLD-TDP and MND, as with amyloid β protein, may relate to increased age and possession of Apolipoprotein ε4 allele. CONCLUSION: We find no predilection or predisposition towards an accompanying TDP-43 pathology in patients with FTLD-tau, irrespective of presence or absence of MAPT mutation, or that genetic changes associated with FTLD-TDP predispose towards excessive tauopathy. Where the two processes coexist, this is limited and probably causatively independent of each other.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".