Anthrax-protective effects of yeast beta 1,3 glucans.
Bibliographic record
Abstract
CONTEXT: The recent events increasing the threat of bioterrorism have prompted a widespread search for defenses against this peril. OBJECTIVE: To evaluate the anthrax-protective effect of beta1,3-glucan immune modulators (PGG-glucan and WGP beta glucan) in an experimental animal model. DESIGN: Beta1,3-glucan immune modulators were administered by subcutaneous injection to Balb/c mice 2 days prior to anthrax challenge. WGP beta glucan was administered by daily oral gavage for 7 days prior to challenge, or in drinking water for 10 days postchallenge with a lethal dose of Bacillus anthracis spores. Survival, survival time, and microbial bioburden relative to an infected, untreated control group were assessed. RESULTS: A single injected dose of PGG-glucan or WGP beta glucan immune modulators given 2 days before challenge significantly: (a) increased the survival rate of infected mice (2.5-fold), (b) diminished the bacterial load in the lungs of infected mice (4-8-fold), and (c) increased the proportion of bacteria-free animals 10 days after challenge (2-fold). In mice prophylactically administered oral WGP beta glucan for 1 week prior to infection, survival increased from 50% to 100%; therapeutic administration of oral WGP beta glucan for 10 days postinfection increased survival from 30% up to 90% in treatment groups. CONCLUSIONS: These results demonstrate the potential for beta1,3-glucan immune modulators to provide a significant degree of protection against anthrax, a potential biological warfare (BW) agent in a mouse model of anthrax infection. Further studies are needed to optimize protection, evaluate activity in combination with other treatment options, demonstrate activity in a validated primate model of infection, and determine if protection is effective against other potential BW agents.
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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) | 0.001 | 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 | 0.000 |
| 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".