Effect of a seashell protein Haishengsu on cell growth and expression of apoptosis genes in leukemia K562 cells
Bibliographic record
Abstract
OBJECTIVES: To investigate the effect of a seashell protein Haishengsu (HSS), an extract from a shellfish Tegillarca granosa, on cell growth and the expression of apoptosis genes in leukemia K562 cells. METHODS: Cultured K562 cells were treated with HSS at various concentrations (10-40 mg/L). The cell cycle, cell growth and the expression of apoptosis suppressor gene bcl-2 and apoptosis promoting gene bax were evaluated. RESULTS: HSS, 20mg/L, inhibited cell cycle in the G0/G1 and S phases. HSS, 20mg/L, also inhibited the growth of K562 cells over time. Expression of bcl-2 gene in the HSS 20mg/L (58.8%+/-4.7%) and HSS 40 mg/L group (26.6%+/-2.1%) were lower than in the control group (91.0+/-8.7%, P < 0.01). Expression of bax gene in the HSS 20mg/L (77.7+/-3.6%) and 40 mg/L group (90.6+/-3.7%) were higher than in the control group (10.9+/-6.6%, P < 0.01). CONCLUSION: HSS suppresses leukemia K562 cell growth by inhibiting the G0/G1 and S phases of the cell cycle. It also induces apoptosis in these leukemia cells by reducing the expression of apoptosis suppressor gene bcl-2, and increasing the expression of apoptosis promoting gene bax. Further studies are required to investigate the clinical efficacy of HSS in leukemia.
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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".