<i>In vitro</i> structural determination and analysis of full‐length aggregated TDP‐43 protein
Bibliographic record
Abstract
Background TDP-43 protein has been causally linked to amyotrophic lateral sclerosis (ALS), most often in the form of amyloid-like aggregates and characterized by changes in structural conformations that induce pathogenesis. Methods Our research has shown that TDP-43 adopts β-sheet structures throughout in vitro aggregation, as it yields ThT-positive results. Further, these aggregating conditions have identified amyloid-like fibrils and other aggregates through morphological analyses using transmission electron microscopy (TEM) and the presence of insoluble particulates via turbidity. This study characterized the misfolding of TDP-43 in vitro, mimicking biologically-relevant aggregated TDP-43. Results Data indicate that wild-type, full-length TDP-43 aggregates under agitated, temperature-controlled environmental conditions and results in a fibrillar-forming, ThT-positive yield. After incubation at 37 °C, TDP-43 had aggregated significantly, showing fibril formation synonymous to similar literature on ALS-type TDP-43 proteins. Further research should focus the influence of post-translational modifications (PTMs) on TDP-43 aggregation. Conclusions This study demonstrates the feasibility of studying TDP-43 aggregates in vitro and provides a valuable model for future aggregation and pathogenicity studies for TDP-43 and other, similar proteins.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".