Distribution and localization of porcine calcium sensing receptor in different tissues of weaned piglets1
Bibliographic record
Abstract
Taste receptors including calcium sensing receptor (CaSR) are expressed in various animal tissues, and CaSR plays important roles in nutrient sensing and the physiology, growth, and development of animals. However, molecular distribution of porcine CaSR (pCaSR) in different tissues, especially along the longitudinal axis of the digestive tract in weaned piglets, is still unknown. In the present study, we investigated the distribution and localization of pCaSR in the different tissues including intestinal segments of weaned piglets. Six male pigs were anesthetized and euthanized. Different tissues such as intestinal segments were collected. The pCaSR mRNA abundance, protein abundance, and localization were measured by real-time PCR, Western blotting, and immunohistochemistry, respectively. The mRNA and protein of pCaSR were detected in the kidney, lung, liver, stomach, duodenum, jejunum, ileum, and colon. The pCaSR mRNA was much higher (five to 180 times) in the kidney when compared with other tissues (P < 0.05). The ileum had higher pCaSR mRNA and protein abundances than the stomach, duodenum, jejunum, and colon (P < 0.05). Immunohistochemical staining results indicated that the pCaSR protein was mostly located in the epithelia of the stomach, duodenum, jejunum, ileum, and colon. These results demonstrate that pCaSR is widely expressed in different tissues including intestinal segments in weaned piglets and the ileum has a higher expression level of pCaSR. Further research is needed to confirm the expression of CaSR in the different types of epithelial cells isolated from weaned piglets and characterize the functions of pCaSR, its potential ligands and cell signaling pathways related to CaSR activation in enteroendocrine cells and potentially in enterocytes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".