Shikonin Derivatives Protect Immune Organs from Damage and Promote Immune Responses <i>In Vivo</i> in Tumour‐bearing Mice
Bibliographic record
Abstract
Shikonin, a major component of Lithospermum erythrorhizon and Arnebia euchroma, exhibits antiinflammatory, immunomodulatory and antitumour activities. Although many recent studies have focused on the antitumour effects of shikonin, the exact mechanisms underlying its antitumour and immunomodulatory effects in tumour-bearing mice remain unclear. The aim of the present study was to investigate the antitumour and immunomodulatory effects of shikonin derivatives (ShD) in tumour-bearing mice. Swiss mice inoculated with hepatoma HepA(22) or sarcoma 180 (S(180)) cells were treated with ShD or 5-fluorouracil (5Fu). Survival time, immune organs, natural killer cell activity, lymphocytes, lymphocyte transformation and interleukin (IL)-2 production were analysed. ShD significantly prolonged the survival (median survival time prolonged by >7 days) of tumour-bearing mice in a dose-dependent manner, inhibited the growth of transplantable neoplasms (inhibitory rate, > 33%), and recovered (at [ShD] = 2.5 mg/kg/day) or increased (at [ShD] > 5 mg/kg/day) the number of CD3- and CD19-positive cells. ShD also played a role in protecting the immune organs from damage and reversed or enhanced immune responses, as noted by the nearly normal thymic structure; enlarged splenic corpuscles; and improved natural killer cell activity, lymphocyte transformation and IL-2 production in ShD-treated mice. ShD reduced the tumour load of tumour-bearing mice and protected the immune organs against tumour-induced damage and immune function impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".