Abnormal Regenerative Responses and Impaired Axonal Outgrowth after Nerve Crush in TDP-43 Transgenic Mouse Models of Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Tar DNA binding protein 43 (TDP-43) mislocalization and aggregation is a hallmark of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar dementia. Moreover, TDP-43 mRNA was found to be upregulated by ∼2.5-fold in the spinal cord of sporadic ALS subjects. Here we have examined the effects of nerve injury in new transgenic mouse models overexpressing by approximately threefold wild-type or mutant (G348C) TDP-43 species. Four weeks after axonal crush of sciatic nerve, TDP-43 transgenic mice remained paralyzed at the injured limb unlike control mice, which had regained most of their normal mobility. In contrast to normal mice, TDP-43 transgenic mice exhibited sustained elevation of TDP-43 cytoplasmic levels in motor neurons after nerve crush, and the relocalization of TDP-43 to the nucleus was delayed by several weeks. After crush, peripherin and ubiquitin levels remained also significantly elevated in TDP-43 transgenic mice compared with control mice. Analysis of the sciatic nerve at 11 d after nerve crush showed that the number of regenerating axons in the distal portion of the lesion was considerably reduced in TDP-43 transgenic mice, especially in TDP-43(G348C) mice, which exhibited a reduction of ∼40%. In addition, markers of neuroinflammation were detected at much higher levels in TDP-43 transgenic mice. These results suggest that a deregulation of TDP-43 expression in ALS is a phenomenon that can affect the regenerative responses to neuronal injury and regrowth potential of axons.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".