Phytoglycoprotein (150 kDa) isolated from <i>Solanum nigrum </i>Linne has a preventive effect on dextran sodium sulfate‐induced colitis in A/J mouse
Bibliographic record
Abstract
The purpose of this study was to investigate the preventive effect of glycoprotein (SNL glycoprotein, 150 kDa) isolated from Solanum nigrum Linne fruits on dextran sulfate sodium (DSS, 3%)-induced colitis in A/J mice. To determine the physiological change by SNL glycoprotein, we first evaluated nitric oxide production, lactate dehydrogenase release and thiobarbituric acid reactive substances formation in the mice serum. After that, we tested the activity of inflammation-related signals such as transcriptional factor [nuclear factor-kappa B (NF-kappaB) and activator protein-1 (AP-1)], inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) in the mice colon tissues. Our results showed that SNL glycoprotein has a dose-dependent inhibitory effect on nitric oxide production, lactate dehydrogenase release, and thiobarbituric acid reactive substances formation. In the inflammation-related signal, our finding showed that SNL glycoprotein (20 mg kg(-1)) has a suppressive effect on activities of NF-kappaB (p50) and AP-1 (c-Jun), and regulates the expression of iNOS and COX-2 in the downstream of signal pathway. Taken together, the results in this study indicated that SNL glycoprotein has potential for prevention of colitis caused by DSS in A/J mice.
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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".