Pilot acute study of feedback-controlled retrograde peristalsis invoked by neural gastric electrical stimulation
Bibliographic record
Abstract
Neural gastric electrical stimulation (NGES) is a new method for invoking gastric contractions under microprocessor control. However, optimization of this technique using feedback mechanisms to minimize power consumption and maximize effectiveness has been lacking. The present pilot study proposes a prototype feedback-controlled neural gastric electric stimulator for the treatment of obesity. Both force-based and inter-electrode impedance-based feedback neurostimulators were implemented and tested. Four mongrel dogs (2 M, 2 F, weight 14.9 +/- 2.3 kg) underwent subserosal implantation of two-channel, 1 cm, bipolar electrode leads and two force transducers in the distal antrum. Two of the dogs were stimulated with a force feedback system utilizing the force transducers, and the other two animals were stimulated utilizing an inter-electrode impedance-based feedback system utilizing the proximal electrode leads. Both feedback systems were able to recognize erythromycin-driven contractions of the stomach and were capable of overriding them with NGES-invoked retrograde contractions which exceeded the magnitudes of the erythromycin-driven contractions by an average of 100.6 +/- 33.5% in all animals. The NGES-invoked contractions blocked the erythromycin-driven contractions past the proximal electrode pair and induced temporary gastroparesis in the vicinity of the distal force transducer despite the continuing erythromycin infusion. The amplitudes of the erythromycin-invoked contractions in the vicinity of the proximal force transducer decreased abruptly by an average of 47.9 +/- 6.3% in all four dogs after triggering-invoked retrograde contractions, regardless of the specific feedback-controlled mechanism. The proposed technique could be helpful for retaining food longer in the stomach, thus inducing early satiety and diminishing food intake.
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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 | 0.001 |
| 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 | 0.000 | 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 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".