Chronic nicotine induces hypoxia inducible factor-2α in perinatal rat adrenal chromaffin cells: role in transcriptional upregulation of K<sub>ATP</sub> channel subunit Kir6.2
Bibliographic record
Abstract
Fetal nicotine exposure causes impaired adrenal catecholamine secretion and increased neonatal mortality during acute hypoxic challenges. Both effects are attributable to upregulation of ATP-sensitive K(+) channels (K(ATP) channels) and can be rescued by pretreatment with the blocker, glibenclamide. Although use of in vitro models of primary and immortalized, fetal-derived rat adrenomedullary chromaffin cells (i.e., MAH cells) demonstrated the involvement of α7 nicotinic ACh receptor (nAChR) stimulation and the transcription factor, HIF-2α, the latter's role was unclear. Using Western blots, we show that chronic nicotine causes a progressive, time-dependent induction of HIF-2α in MAH cells that parallels the upregulation of K(ATP) channel subunit, Kir6.2. Moreover, a common HIF target, VEGF mRNA, was also upregulated after chronic nicotine. All the above effects were prevented during co-incubation with α-bungarotoxin (100 nM), a specific α7 nAChR blocker, and were absent in HIF-2α-deficient MAH cells. Chromatin immunoprecipitation (ChIP) assays demonstrated binding of HIF-2α to a putative hypoxia response element in Kir6.2 gene promoter. Specificity of this signaling pathway was validated in adrenal glands from pups born to dams exposed to nicotine throughout gestation; the upregulation of both HIF-2α and Kir6.2 was confined to medullary, but not cortical, tissue. This study has uncovered a signaling pathway whereby a nonhypoxic stimulus (nicotine) promotes HIF-2α-mediated transcriptional upregulation of a novel target, Kir6.2 subunit. The data suggest that the HIF pathway may be involved in K(ATP) channel-mediated neuroprotection during brain ischemia, and in the effects of chronic nicotine on ubiquitous brain α7 nAChR.
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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".