Vascularized Muscle Flap to Reduce Wound Breakdown During Flexible Electrode-Mediated Functional Electrical Stimulation After Peripheral Nerve Injury
Bibliographic record
Abstract
The success of devices delivering functional electrical stimulation (FES) has been hindered by complications related to implants including skin breakdown and subsequent wound dehiscence. Our hypothesis was that a vascularized muscle flap along the dorsal surface of an epimysial electrode would prevent skin breakdown during FES therapy to treat atrophy of the gastrocnemius muscle during peripheral nerve injury. Resection of a tibial nerve segment with subsequent electrode implantation on the dorsal surfaces of the gastrocnemius muscle was performed on ten Lewis rats. In five rats, the biceps femoris (BF) muscle was dissected and placed along the dorsal surface of the electrode (Flap group). The other five animals did not undergo flap placement (No Flap group). All animals were treated with daily FES therapy for 2 weeks and degree of immune response and skin breakdown were evaluated. The postoperative course of one animal in the No Flap group was complicated by complete wound dehiscence requiring euthanasia of the animal on postoperative day 4. The remaining 4 No Flap animals showed evidence of ulceration at the implant by postoperative day 7. The 5 animals in the Flap group did not have ulcerative lesions. Excised tissue at postoperative day 14 examined by histology and In Vivo Imaging System (IVIS) showed decreased implant-induced inflammation in the Flap group. Expression of specific markers for local foreign body response were also decreased in the Flap group.
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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".