Effect of polysaccharide extract SPSS1 from <i>Apostichopus japonicus</i> spermary on HepG2 cells via iTRAQ‐based proteome analysis
Bibliographic record
Abstract
In this study, polysaccharide extract was prepared from Apostichopus japonicus spermary and purified by ion-exchange chromatography and gel filtration chromatography. Two main fractions named SPSS1 and SPSS2 were obtained and analyzed by ultraviolet spectroscopy and mixed with KBr, respectively. Chemical components analysis proved that SPSS1 and SPSS2 were rich in sulfate. Monosaccharide analysis indicated that in addition to the high content of lactose in both kinds of polysaccharides, the highest content of monosaccharide in SPSS1 was galactose, while in SPSS2 it was fucose. Further, the antitumor study of SPSS1 was carried and the results showed that SPSS1 treatment inhibited the proliferation of HepG2 cells. Through the iTRAQ-based proteome analysis, there were 208 differential proteins between control tumor cells and SPSS1 treatment of tumor cells. Compared to control tumor cells, 135 proteins were upregulated and 73 proteins were downregulated in treatment tumor cells. PRACTICAL APPLICATIONS: Our study suggested that polysaccharide from sea cucumbers had the potential to be further developed as antitumor drugs.
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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".