Protein Tyrosine Phosphatase 1B Deficiency Potentiates PERK/eIF2α Signaling in Brown Adipocytes
Bibliographic record
Abstract
BACKGROUND: Protein-tyrosine phosphatase 1B (PTP1B) is a physiological regulator of glucose homeostasis and body mass, and has been implicated in endoplasmic reticulum (ER) stress. Herein, we assess the role of PTP1B in ER stress in brown adipocytes, which are key regulators of thermogenesis and metabolic response. METHODOLOGY/PRINCIPAL FINDINGS: To determine the role of PTP1B in ER stress, we utilized brown adipose tissue (BAT) from mice with adipose-specific PTP1B deletion, and brown adipocytes deficient in PTP1B and reconstituted with PTP1B wild type (WT) or the substrate-trapping PTP1B D181A (D/A) mutant. PTP1B deficiency led to upregulation of PERK-eIF2α phosphorylation and IRE1α-XBP1 sub-arms of the unfolded protein response. In addition, PTP1B deficiency sensitized differentiated brown adipocytes to chemical-induced ER stress. Moreover, PERK activation and tyrosine phosphorylation were increased in BAT and adipocytes lacking PTP1B. Increased PERK activity resulted in the induction of eIF2α phosphorylation at Ser51 and better translatability of ATF4 mRNA in response to ER stress. At the molecular level, we demonstrate direct interaction between PTP1B and PERK and identify PERK Tyr615 as a mediator of this association. CONCLUSIONS: Collectively, the data demonstrate that PTP1B is a physiologically-relevant modulator of ER stress in brown adipocytes and that PTP1B deficiency modulates PERK-eIF2α phosphorylation and protein synthesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".