Dose Effects of Orally Administered Spirulina Suspension on Colonic Microbiota in Healthy Mice
Bibliographic record
Abstract
Oral supplemented nutraceuticals derived from food sources are surmised to improve the human health through interaction with the gastrointestinal bacteria. However, the lack of fundamental quality control and authoritative consensus (e.g. formulation, route of administration, dose and dosage regimen) of these non-medical yet bioactive compounds are one of the main practical issues resulting in inconsistent individual responsiveness and confounded clinical outcomes of consuming nutraceuticals. Herein, we studied the dose effects of widely used food supplement, microalgae spirulina (Arthrospira platensis), on the colonic microbiota and physiological responses in healthy male Balb/c mice. Based on the analysis of 16s rDNA sequencing, compared to the saline-treated group, oral administration of spirulina once daily for 24 consecutive days altered the diversity, structure and composition of colonic microbial community at the genus level. More importantly, the abundance of microbial taxa was markedly differentiated at the low (1.5 g/kg) and high (3.0 g/kg) dose of spirulina, among which the relative abundance of Clostridium XIVa, Desulfovibrio, Eubacterium, Barnesiella, Bacteroides and Flavonifractor were modulated at various degrees. Evaluation of serum biomarkers in mice at the end of spirulina intervention showed reduced the oxidative stress and the blood lipid levels and increased the level of appetite controlling hormone leptin in a dose-response manner, which exhibited the significant correlation with differentially abundant microbiota taxa in the cecum. These findings provide direct evidences of dose-related modulation of gut microbiota and physiological states by spirulina, engendering its future mechanistic investigation of spirulina as potential sources of prebiotics for beneficial health effects via the interaction with gut microbiota.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".