158 The Identification of Pig Calcium-sensing Receptor (pCaSR) Expression in Porcine Intestinal Enterocytes
Bibliographic record
Abstract
Abstract Enterocytes play important roles in nutrient absorption, while the intestinal porcine enterocyte cell line (IPEC-J2) is a non-transformed and permanent commercial cell line. The calcium-sensing receptor (CaSR) has been identified as calcium ions and L-amino acids sensor in the gut and studies have demonstrated that the CaSR is involved in nutrient digestion and absorption, as well as gut barrier function. Although the expression of CaSR on the basal membrane of the villus has been found in other animal species, its expression in porcine enterocytes (pCaSR) has not been investigated to date. To investigate the expression of pCaSR in isolated porcine enterocytes and IPEC-J2, cell sorting of ileal enterocytes by fluorescence-activated cell sorting (FACS) based on sucrase-isomaltose as enterocytes marker were performed to obtain pure porcine enterocytes. The digital droplet PCR (ddPCR), immunofluorescence staining, and Western blotting were applied for the detection of pCaSR expression at the gene and protein levels, respectively. Our results showed that about 3.3% of upper epithelial cells were characterized and sorted as pure porcine enterocytes, while the other cells were negative to the enterocytes marker. In addition, neither the isolated porcine enterocytes nor the IPEC-J2 expressed the pCaSR. In summary, pure porcine enterocytes could be obtained by using FACS with the sucrase-isomaltase as enterocytes marker but pCaSR is not expressed in either isolated porcine enterocytes or IPEC-J2, which provides new insights for future work exploring the role of pCaSR in the intestine.
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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 | 0.000 | 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 | 0.001 |
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".