Potentiating effects of high-molecular weight fucoidan-agaricus mix (CUA) feeding on tumor vaccination
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Fucoidan is a series of sulfated polysaccharides derived from brown algae that mainly consist of L-fucose. Various biological activities of fucoidan such as anti-cancer and immune modulatory effects were reported, and our investigation with animal experiments and human trials demonstrated fucoidan from Cladosiphon okamuranus and Undaria pinnatifida effectively augmented anti-tumor immunity in combination with Agaricus blazei mycelium extract. In this study, we evaluated dietary effects of the two types of high-molecular weight fucoidans and the agaricus extract mix (CUA) on achievement of effective tumor vaccination with a tumor antigen gp70 expressed on colon-26 tumor cell line. Balb/c mice were immunized with 0.05 mg gp70 peptide emulsified in complete freund’s adjuvant and intake 1% CUA containing AIN93G diet for 4 weeks. This procedure totally enhanced systemic immune function because splenocytes from the vaccinated mice extensively proliferate in response to concanavalin A-stimulation. The NK cell activity and gp70 peptide-stimulated IFN-gamma production in splenocytes from the vaccinated mice were tended to augment by the CUA feeding. On the other hands, the CUA feeding potentiated the killing activity to colon-26 carcinoma of draining lymph node (LN) cells from the vaccinated mice in association with increase of gp70-specific CD8-positive T cell population. Furthermore, the expressions of MHC class II molecule (I-A/I-E) on CD11c-positive and F4/80-positive populations of LN cells from the vaccinated mice were elevated by the intake of CUA. These results suggested that the CUA feeding potentially support effective induction of anti-tumor immune function by vaccination with tumor antigen peptides.
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.
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) | 0.000 | 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) | 0.000 | 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 it