High MUC2 production in goblet cells causes increased susceptibility to ER stress and apoptosis (151.4)
Bibliographic record
Abstract
MUC2, a large glycoprotein produced by goblet cells in the colon, forms a protective mucus blanket over the epithelium as the first line of host defense. During pathological conditions such as inflammatory bowel diseases, there is accelerated biosynthesis and secretion of MUC2. Surprisingly, little information is known on how MUC2 production is regulated and whether goblet cells undergo increased stress in response to high MUC2 biosynthesis and secretion. In this study we investigated the role of MUC2 in goblet cell stress using a high mucin producing cell line, HT29‐H, and a clone of HT29‐H (HT29‐L) in which MUC2 has been silenced using lentivirus shRNA. Cells were treated with tunicamycin and MG132, and markers for endoplasmic reticulum (ER) stress and apoptosis were quantified. Compared to HT29‐L cells, HT29‐H cells exhibited a greater dose‐and time‐dependent increase in ER stress markers GRP78, ATF4, CHOP, sXBP1 and AGR2 in response to both tunicamycin and MG132. ER stress also caused a decrease in phosphorylation of Akt and increased apoptosis in HT29‐H cells 6h after treatment. Phospho‐Akt in HT29‐L cells was however sustained, decreasing slightly only after 24h with less apoptosis compared to HT29‐H cells. Our findings indicate that MUC2 induces goblet cell stress and apoptosis which could subsequently lead to diminished mucus barrier function. Grant Funding Source : Supported by CIHR
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".