Microcircuit formation following transplantation of mouse embryonic stem cell-derived neurons in peripheral nerve
Bibliographic record
Abstract
Motoneurons derived from embryonic stem cells can be transplanted in the tibial nerve, where they extend axons to functionally innervate target muscle. Here, we studied spontaneous muscle contractions in these grafts 3 mo following transplantation. One-half of the transplanted grafts generated rhythmic muscle contractions of variable patterns, either spontaneously or in response to brief electrical stimulation. Activity generated by transplanted embryonic stem cell-derived neurons was driven by glutamate and was modulated by muscarinic and GABAergic/glycinergic transmission. Furthermore, rhythmicity was promoted by the same transmitter combination that evokes rhythmic locomotor activity in spinal cord circuits. These results demonstrate that there is a degree of self-assembly of microcircuits in these peripheral grafts involving embryonic stem cell-derived motoneurons and interneurons. Such spontaneous activity is reminiscent of embryonic circuit development in which spontaneous activity is essential for proper connectivity and function and may be necessary for the grafts to form functional connections with muscle. NEW & NOTEWORTHY This manuscript demonstrates that, following peripheral transplantation of neurons derived from embryonic stem cells, the grafts are spontaneously active. The activity is produced and modulated by a number of transmitter systems, indicating that there is a degree of self-assembly of circuits in the grafts.
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 | 0.001 |
| 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".