Electrically Controlled Delivery of Cargo into Single Human Neural Stem Cell
Bibliographic record
Abstract
Nanoprobe-based techniques have emerged as an efficient tool for the manipulation and analysis of single cells. Here, we report a powerful whole-electrical single-cell manipulation tool that enables rapid and controllable delivery of cargo into single neural stem cells with precision monitoring of the cell penetration process using a conductive nanoprobe. The highly electrically sensitive nanoprobes that were fabricated and the indium tin oxide electrode-integrated cell chip were found to be very effective for monitoring the cell penetration process via current changes that appear as spike-like negative currents. Moreover, the assembly of cargoes onto the nanoprobes was controllable and could reach its maximum load in a very short period of time (<10 min) based on the same electrical system that was used for monitoring cell penetration and without the need for any complex chemical linkers or mediators. Even more remarkably, the cargo assembled on the surface of the nanoprobe was successfully released in a very short period of time (<10 s), regardless of the surrounding intracellular or extracellular environments. The monitoring of cell penetration, assembly of quantum dots (QDs), and release of QDs into the intracellular environment were all accomplished using our whole-electrical system that combined a conductive nanoprobe with cell chip technology. This is a novel technology, which can eliminate complex and time-consuming steps owing to chemical modifications, as well as reduce the time needed for the delivery of cargo into the cell cytosol/nucleus during cell penetration, which is very important for reducing cell damage.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".