DG9-conjugated morpholino rescues phenotype in SMA mice by reaching the CNS via a subcutaneous administration
Bibliographic record
Abstract
Antisense oligonucleotide-mediated (AO-mediated) therapy is a promising strategy to treat several neurological diseases, including spinal muscular atrophy (SMA). However, limited delivery to the CNS with AOs administered intravenously or subcutaneously is a major challenge. Here, we demonstrate a single subcutaneous administration of cell-penetrating peptide DG9 conjugated to an AO called phosphorodiamidate morpholino oligomer (PMO) reached the CNS and significantly prolonged the median survival compared with unconjugated PMO and R6G-PMO in a severe SMA mouse model. Treated mice exhibited substantially higher expression of full-length survival of motor neuron 2 in both the CNS and systemic tissues compared with nontreated and unmodified AO-treated mice. The treatment ameliorated the atrophic musculature and improved breathing function accompanied by improved muscle strength and innervation at the neuromuscular junction with no signs of apparent toxicity. We also demonstrated DG9-conjugated PMO localized in nuclei in the spinal cord and brain after subcutaneous injections. Our data identify DG9 peptide conjugation as a powerful way to improve the efficacy of AO-mediated splice modulation. Finally, DG9-PMO is a promising therapeutic option to treat SMA and other neurological diseases, overcoming the necessity for intrathecal injections and treating body-wide tissues without apparent toxicity.
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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 | 0.001 |
| 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".