Liposomes as Gene Delivery Vectors for Human Placental Cells
Bibliographic record
Abstract
Nanomedicine as a therapeutic approach for pregnancy-related diseases could offer improved treatments for the mother while avoiding side effects for the fetus. In this study, we evaluated the potential of liposomes as carriers for small interfering RNAs to placental cells. Three neutral formulations carrying rhodamine-labelled siRNAs were evaluated on an in vitro model, i.e., human primary villous cytotrophoblasts. siRNA internalization rate from lipoplexes were compared to the one in the presence of the lipofectamine reagent and assessed by confocal microscopy. Results showed cellular internalization of nucleic acid with all three formulations, based on two cationic lipids, either DMAPAP or CSL-3. Moreover, incubation with DMAPAP+AA provided a rate of labelled cells as high as with lipofectamine (53 ± 15% and 44 ± 12%, respectively) while being more biocompatible. The proportion of cells which internalized siRNA were similar when using DMAPAP/DDSTU (16 ± 5%) and CSL-3 (22 ± 5%). This work highlights that liposomes could be a promising approach for gene therapy dedicated to pregnant patients.
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 | 0.000 | 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 | 0.000 |
| 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".