Gut peristalsis is governed by a multitude of cooperating mechanisms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Peristaltic motor activity of the gut is an essential activity to sustain life. In each gut organ, a multitude of overlapping mechanisms has developed to acquire the ability of coordinated contractile activity under a variety of circumstances and in response to a variety of stimuli. The presence of several simultaneously operating control systems is a challenge for investigators who focus on the role of one particular control activity since it is often not possible to decipher which control systems are operating or dominant in a particular situation. A crucial advantage of multiple control systems is that gut motility control can withstand injury to one or more of its components. Our efforts to increase understanding of control mechanism are not helped by recent attempts to eliminate proven control systems such as interstitial cells of Cajal (ICC) as pacemaker cells, or intrinsic sensory neurons, nor does it help to view peristalsis as a simple reflex. This review focuses on the role of ICC as slow-wave pacemaker cells and places ICC into the context of other control mechanisms, including control systems intrinsic to smooth muscle cells. It also addresses some areas of controversy related to the origin and propagation of pacemaker activity. The urge to simplify may have its roots in the wish to see the gut as a consequence of a single perfect design experiment whereas in reality the control mechanisms of the gut are the messy result of adaptive changes over millions of years that have created complementary and overlapping control systems. All these systems together reliably perform the task of moving and mixing gut content to provide us with essential nutrients.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it