Synergetic effects and inhibition mechanisms of the polysaccharide‐selenium nanoparticle complex in human hepatocarcinoma cell proliferation
Bibliographic record
Abstract
BACKGROUND: Active components from natural fungal products have shown promising potential as anti-tumor therapeutic agents. In the search for anti-tumor agents, research to overcome the drawbacks of high molecular weight and low bioavailability of pure polysaccharides, polysaccharide-conjugated selenium nanoparticles (SeNPs) has attracted much attention. RESULTS: A novel polysaccharide-selenium nanoparticle complex was produced, in which SeNPs were decorated with polysaccharide obtained from fermented mycelia broth of Lactarius deliciosus (FLDP). Transmission electron microscope, dynamic light scattering, and X-ray photoelectron spectroscopy were utilized to characterize the FLDP-SeNPs; and human hepatocarcinoma cell line (HepG2) was used to assess growth inhibition efficacy. The FLDP-SeNPs that were prepared had a spherical shape with the smallest mean diameter of 32 nm. The FLDP-SeNPs showed satisfactory dispersibility and stability after combination, demonstrating that a reliable consolidated structure had formed. The results revealed that FLDP-SeNPs had notable growth inhibition effects on HepG2 cells. They reduced the membrane potential of mitochondria significantly, increased the generation of reactive oxygen species, enhanced levels of both Caspase-3 and Caspase-9, and led to the nucleus in a wrinkled form. CONCLUSION: The FLDP-SeNPs could exert a synergetic toxicity reduction and inhibition enhancement effect on HepG2 cells by inducing early apoptosis, through mitochondria-mediated cytochrome C-Caspases and reactive oxygen species-induced DNA damage pathways. These results indicate that FLDP-SeNP treatment of HepG2 cells induced early apoptosis with synergetic efficacy, showing that FLDP-SeNPs can be useful as natural anti-tumor agents. © 2024 Society of Chemical Industry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".