Selective Enhancement of the Uptake and Bioactivity of a TAT-conjugated Peptide Inhibitor of Glycogen Synthase Kinase-3
Bibliographic record
Abstract
The use of cell-penetrating peptides as transduction vectors is a promising approach to deliver peptides and proteins into cells. However, the uptake and bioavailability of trans-activating transcriptor (TAT)-conjugated molecules vary depending on the cell type and the cargo. This study aimed to determine whether a low-voltage electrical pulse can enhance the TAT-mediated delivery of peptide cargoes in different cell types. In TF-1 and mouse embryonic stem cells, the uptake of a novel detachable TAT-conjugated glycogen synthase kinase-3 (GSK-3) peptide inhibitor was enhanced by an order of magnitude without affecting the cell viability. A similar increase in uptake was achieved in primary mouse bone marrow cells while maintaining >80% of their viability. Interestingly, under these low-voltage conditions, the uptake of a control peptide not conjugated to TAT was not significantly increased. A T-cell factor/lymphoid enhancer factor (TCF/LEF) luciferase reporter assay was also used to assess the bioactivity of the TAT construct. The results indicated that cells loaded with a low-voltage electrical pulse had a twofold increase in TCF/LEF activity, which was equivalent to a level of GSK-3 inhibition similar to that of cells treated with 20 mmol/l lithium or 500 nmol/l (2'Z,3'E)-6-bromoindirubin-3'-oxime. These results demonstrate the usefulness of low-voltage electrical pulses to enhance the uptake and bioactivity of TAT-conjugated molecules in different cell types.
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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 | 0.000 |
| 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".