Polysaccharide-rich extract from Polygonatum sibiricum protects hematopoiesis in bone marrow suppressed by triple negative breast cancer
Bibliographic record
Abstract
Polysaccharide is one of main components in Polygonatum sibiricum (PS), which is an herbal medicine widely used in East Asia. Polysaccharides from Polygonatum sibiricum has been shown to exhibit multiple biological activities, such as anti-diabetes, anti-inflammation, antioxidant, immunity modulation, and anticancer. Since hematopoietic system is one of determinant factors in cancer control, we here explored the effect of polysaccharide-rich extract from Polygonatum sibiricum (PREPS) on hematopoiesis in the mice bearing triple negative breast cancer (TNBC). We found that the 4T1 TNBC tumor significantly increased myeloid cells in peripheral blood, bone marrow and spleen, while decreasing bone marrow hematopoietic stem and progenitor cells (HSPCs), indicative of an inhibition of medullary hematopoiesis. When 4T1 TNBC tumor-bearing mice were treated with PREPS, the percentage of myeloid cells within tumor-infiltrating immune cells was reduced. In addition, PREPS also inhibited hematopoietic cell expansion in the spleen, which was induced by TNBC tumors. Importantly, PREPS markedly increased HSPCs and common lymphoid progenitors in the bone marrow that had been suppressed by TNBC tumors. These findings suggest that PREPS protect hematopoiesis inhibited by TNBC tumors in the bone marrow. Although PREPS alone did not achieve statistical significance in the suppression of TNBC tumor growth, it may have a long-lasting anti-tumor effect to assist TNBC therapies by sustaining hematopoiesis and lymphoid regeneration in bone marrow.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 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".