Antitumor and Immunostimulatory Activity of Two Chromones and Other Constituents from <i>Cassia Petersiana</i>
Bibliographic record
Abstract
Phytochemical and biological investigation of the leaves of Cassia petersiana afforded two new chromones (1, 2), in addition, to the known glyceryl-1-hexacosanoate (3) and stigmasterol-3-O-β-D-glucoside (4). The structures of the compounds were determined by comprehensive NMR studies, including DEPT, COSY, HMQC, HMBC and IR spectroscopy and MS. 1–4 were investigated against different types of cell lines, including solid tumor cells (Hep-G2, and MCF-7 cells) and leukemia (1301) cells for their cytotoxic effects. 1–3 possessed a dose-dependent cytotoxic effect against Hep-G2 cells, but in relatively high concentrations; 4 was the most cytotoxic with the lowest IC 50 value of 82.7 μM. The calculated IC 50 values against MCF-7 cells were 112.2 μM, 143.7 μM, 68.1 μM, and 114.3 μM for 1, 2, 3, and 4, respectively. The alteration in the macrophage proliferation index, using Raw 264.7 cells, was monitored. 1 and 3 were the highest stimulators of macrophage proliferation in a dose-dependent manner, whereas 2 and 4 showed a peak point of stimulation at 20 μM. The effect of these compounds on pre-induced NO was explored. 1–4 inhibited the LPS-induced NO, with inhibition percentages of 80.5%, 89.3%, 82.1%, and 92.1%, respectively, at a concentration of 20 μM. The antioxidant capacity of 1–4, using the DPPH assay was also investigated. 1–3 possessed weak scavenging activity; while 4 had an effective SC 50 value as low as 36 μM. These results indicated that 4 possessed the highest anti-tumor, immunoproliferative, macrophage proliferation, anti-inflammatory, and antioxidant activities.
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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".