Dexmedetomidine suppresses gap junctional intercellular communication and attenuates the sensitivity of gliocytoma to temozolomid (LB642)
Bibliographic record
Abstract
Dexmedetomidine(DEX), an alpha‐2 adrenergic agonist which can affect cell‐to‐cell gap junctions(GJ), is used as an adjuvant analgesic and sedatives in patients with cancer pain, especially in neural cancer patients who concomitantly receiving chemotherapy. GJ may increase the sensitivity of tumor cells to chemotherapeutic agents (Oncol Rep. 2014;31:540‐550). It is unknown whether or not DEX may affect the sensitivity of gliocytoma (U87 cell, which richly expresses the GJ protein Connexin43) to temozolomide (TEM, an anticancer agent for gliocytoma) and if DEX exerts its effect via affecting GJ. U87 cells were treated with TEM, respectively at high density (which form GJ) or low density (without GJ formation), for 1 hour in the absence or presence of 3 hours DEX pretreatment prior to applying TEM. TEM toxicity (i.e., reduction of clonogenic cell survival), was assayed by “Standard Clony‐forming assay” and GJ function was examined by “Parachute” dye‐coupling assay. TEM toxicity was greater at high density than at low density cells (P<0.01), while either oleamide (a GJ inhibitor) or Cx43 siRNA reduced TEM toxicity. Similarly, DEX reduced GJ function and compromised TEM treatment effects, manifested as increases in clonogenic cell survivals at high but not at low cell density. We concluded that DEX reduced TEM cytotoxicity through inhibiting GJ function in gliocytoma. Grant Funding Source : supported by departmental development fund and Supported by Science and Technology Planning Project of Guangdong Province(2010B060900089)
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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) | 0.001 | 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".