Involvement of cannabinoid-1 and cannabinoid-2 receptors in septic ileus
Bibliographic record
Abstract
BACKGROUND Cannabinoid (CB) receptors are involved in the regulation of gastrointestinal (GI) motility under physiological and pathophysiological conditions. We aimed to characterize the possible influence of CB(1) and CB(2) receptors on motility impairment in a model of septic ileus. METHODS Lipopolysaccharide (LPS) injections were used to mimic pathophysiological features of septic ileus. Spontaneous jejunal myoelectrical activity was measured in rats in vivo, and upper GI transit was measured in vivo by gavaging of a charcoal marker into the stomach of mice, in absence or presence of LPS, and CB(1) and CB(2) receptor agonists and antagonists. Tumour necrosis factor (TNF)-alpha and interleukin (IL)-6 levels were measured using enzyme-linked immunosorbent assay. Histology was performed with haematoxylin-eosin staining. KEY RESULTS Lipopolysaccharide treatment significantly reduced amplitude and frequency of myoelectric spiking activity and GI transit in vivo in a dose-dependent manner. TNF-alpha and IL-6 were increased in LPS-treated animals and histology showed oedema and cell infiltration. Both, the CB(1) agonist HU210 and the CB(2) agonist JWH133 reduced myoelectrical activity whereas the CB(1) antagonist AM251 caused an increase of myoelectrical activity. Pretreatment with AM251 or AM630 prevented against LPS-induced reduction of myoelectrical activity, and also against the delay of GI transit during septic ileus in vivo. CONCLUSIONS & INFERENCES The LPS model of septic ileus impairs jejunal myoelectrical activity and delays GI transit in vivo. Antagonists at the CB(1) receptor or the CB(2) receptor prevent the delay of GI transit and thus may be powerful tools in the future treatment of septic ileus.
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".