[Application of Hepatocyte Growth Factor for Amyotrophic Lateral Sclerosis].
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is an adult onset neurodegenerative disorder characterized by the death of upper and lower motor neurons. About 10% of all ALS cases are familial, and we have identified SOD1 and FUS mutations as the most common causes in a consecutive series of 111 familial ALS pedigrees in Japan (Nishiyama A, 2017). From studies of the TDP43, FUS, and C9orf72 genes, perturbations of RNA processing can be highly adverse in motor neurons. Hepatocyte growth factor (HGF) is one of the most potent survival-promoting factors for motor neurons. We administered human recombinant HGF (hrHGF) by continuous intrathecal delivery to transgenic rats at onset of paralysis for 4 weeks. Intrathecal administration of hrHGF attenuated motor neuron degeneration and prolonged the duration of the disease by 63% (Ishigaki A, 2007). To translate this strategy to human treatment, we induced a contusive cervical spinal cord injury in the common marmoset, a primate, and then administered hrHGF intrathecally. We conducted a first-in-human phase I trial of intrathecal hrHGF in 15 Japanese patients with ALS (Warita H, 2019). Based on the results, we are conducting a phase II trial of intrathecal hrHGF for patients with ALS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.010 | 0.005 |
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".