Engineering baculovirus gene delivery platforms for treating atherosclerotic progression
Bibliographic record
Abstract
A single cut sets off a cascading signal in our body to initiate healing.This happens every day without us realizing it.Only when these finely regulated system dysfunctions do we realize, arising in an infection or disease.This is also the case with atherosclerosis, plaque build-up within the arteries causing serious complications.Atherosclerosis is on the rise, affecting a growing number of younger individuals, leading to a diminished quality of life, substantial pain, and numerous serious accompanying comorbidities.Accumulation of fatty deposits, endothelial cell dysfunction, and inflammation causes the artery to close and constrict blood flow causing significant health problems such as limb ischemia and chronic wounds.Typically, a metal stent forces the artery open, successfully saving millions of lives.However, stents further damage the artery and can lead to in-stent restenosis and thrombosis.But what if we could bypass this dysfunction and injury by providing the proper genes your artery needs to recover?Baculoviruses, extracted from insect cells, have the potential to do just this.These biosafe, non-replicative, non-integrative, low-cost vectors can effectively be engineered to express human genes.The baculovirus gene delivery system was found to be safe with no signs of inflammation, hemolysis, thrombosis, genotoxicity, or cytotoxicity.The baculovirus safety and gene expression can be further improved by encapsulating the baculovirus in an engineered biocompatible and biodegradable polymer.A baculovirus polymer hydrogel system was developed to control and sustain baculovirus delivery.The three genes selected (ADAMTS13, NOS3, and VEGFA) showed favourable properties including angiogenic, prolific for endothelial cells, and regulatory for smooth muscle cells.The genes also prevented reactive oxygen species (ROS) production in both cell types and C-reactive protein (CRP) production in endothelial cells.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".