Development of an Implantable Artificial Anal Sphincter by the Use of the Shape Memory Alloy
Bibliographic record
Abstract
In this study, we developed and assessed an artificial anal sphincter driven by an shape memory alloy actuator (AS-SMA). The performance characteristics of the device were analyzed with a measurement system. Assessment showed that the AS-SMA could generate a pressure of 55 mm Hg at an atmospheric temperature of 36 degrees C, and displacement of the SMA actuator was 7.5 mm when the temperature of the SMA plate was 55 degrees C. To evaluate opening and closing, we studied a piglet colostomy model, in which the AS-SMA was implanted around the colostomy in the extraperitoneal space. Flow control tests using living porcine intestine revealed that the AS-SMA could maintain fecal continence against an intestinal pressure of 75 mm Hg. The high pressure zone corresponding to the location of the device was demonstrated in a manometric examination. For 6 days after surgery, we activated the AS-SMA twice a day and observed the bowel movements. The animal experiment indicated that the AS-SMA is able to control the bowel movements of patients with fecal incontinence if several problems, such as burning of tissue around the device and compression injury of the intestine, are resolved.
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) | 0.000 | 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 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".