Nucleic-acid based gene therapeutics: delivery challenges and modular design of nonviral gene carriers and expression cassettes to overcome intracellular barriers for sustained targeted expression
Bibliographic record
Abstract
The delivery of nucleic acid molecules into cells to alter physiological functions at the genetic level is a powerful approach to treat a wide range of inherited and acquired disorders. Biocompatible materials such as cationic polymers, lipids, and peptides are being explored as safer alternatives to viral gene carriers. However, the comparatively low efficiency of nonviral carriers currently hampers their translation into clinical settings. Controlling the size and stability of carrier/nucleic acid complexes is one of the primary hurdles as the physicochemical properties of the complexes can define the uptake pathways, which dictate intracellular routing, endosomal processing, and nucleocytoplasmic transport. In addition to nuclear import, subnuclear trafficking, posttranscriptional events, and immune responses can further limit transfection efficiency. Chemical moieties, reactive linkers or signal peptide have been conjugated to carriers to prevent aggregation, induce membrane destabilization and localize to subcellular compartments. Genetic elements can be inserted into the expression cassette to facilitate nuclear targeting, delimit expression to targeted tissue, and modulate transgene expression. The modular option afforded by both gene carriers and expression cassettes provides a two-tier multicomponent delivery system that can be optimized for targeted gene delivery in a variety of settings.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".