Microprocessor controlled movement of solid colonic content using sequential neural electrical stimulation
Bibliographic record
Abstract
BACKGROUND AND AIMS: Invoked peristaltic contractions and movement of solid content have not been attempted in normal canine colon. The purpose of this study was to determine if movement of solid content through the colon could be produced by microprocessor controlled sequential stimulation. METHODS: The study was performed on six anaesthetised dogs. At laparotomy, a 15 cm segment of descending colon was selected, the proximal end closed with a purse string suture, and the distal end opened into a collecting container. Four sets of subserosal stimulating electrodes were implanted at 3 cm intervals. The segment of bowel was filled with a mixture of dog food and 50 plastic pellets before each of 2-5 random sessions of non-stimulated or stimulated emptying. Propagated contractions were generated using microprocessor controlled bipolar trains of 50 Hz rectangular voltage having 20 V (peak to peak) amplitude, 18 second stimulus duration, and a nine second phase lag between stimulation trains in sequential electrode sets. RESULTS: Electrical stimulation using the above mentioned parameters resulted in powerful phasic contractions that closed the lumen. By phase locking the stimulation voltage between adjacent sets of electrodes, propagated contractions could be produced in an aboral or orad direction. The number of evacuated pellets during the stimulation sessions was significantly higher than during the non-stimulated sessions (p<0.01). CONCLUSIONS: Microprocessor controlled electrical stimulation accelerated movement of colonic content suggesting the possibility of future implantable colonic stimulators.
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) | 0.001 | 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".