Receptor Trafficking via the Perinuclear Recycling Compartment Accompanied by Cell Division Is Necessary for Permanent Neurotensin Cell Sensitization and Leads to Chronic Mitogen-activated Protein Kinase Activation
Bibliographic record
Abstract
Most G protein-coupled receptors are internalized after interaction with their respective ligand, a process that subsequently contributes to cell desensitization, receptor endocytosis, trafficking, and finally cell resensitization. Although cellular mechanisms leading to cell desensitization have been widely studied, those responsible for cell resensitization are still poorly understood. We examined here the traffic of the high affinity neurotensin receptor (NT1 receptor) following prolonged exposure to high agonist concentration. Fluorescence and confocal microscopy of Chinese hamster ovary, human neuroblastoma (CHP 212), and murine neuroblastoma (N1E-115) cells expressing green fluorescent protein-tagged NT1 receptor revealed that under prolonged treatment with saturating concentrations of neurotensin (NT) agonist, NT1 receptor and NT transiently accumulated in the perinuclear recycling compartment (PNRC). During this cellular event, cell surface receptors remained markedly depleted as detected by both confocal microscopy and (125)I-NT binding assays. In dividing cells, we observed that following prolonged NT agonist stimulation, NT1 receptors were removed from the PNRC, accumulated in dispersed vesicles inside the cytoplasm, and subsequently reappeared at the cell surface. This NT binding recovery allowed for constant cell sensitization and led to a chronic activation of mitogen-activated protein kinases p42 and p44. Under these conditions, the constant activation of NT1 receptor generates an oncogenic regulation. These observations support the potent role for neuropeptides, such as NT, in cancer progression.
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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 | 0.000 |
| 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".