<i>Spirulina platensis</i> ameliorates arsenic-mediated uterine damage and ovarian steroidogenic disorder
Bibliographic record
Abstract
Novel, non-invasive, painless oral therapeutic agents are needed to replace the painful conventional treatment of arsenic-associated health hazards with metal chelators. Our aim was to examine the effect of spirulina ( Spirulina platensis ( Geitler, 1925 )) on arsenic-mediated uterine toxicity. Female Wistar rats were divided equally into four experimental treatment groups: control group, sodium arsenite group (1.0 mg/100 g body mass), spirulina placebo group (20 mg/100 g body mass), and sodium arsenite + spirulina group. In contrast with the control group, spectrophotometric and electrozymographic evaluation revealed that rats that ingested arsenic for 8 d showed significant diminution of the activities of superoxide dismutase, catalase, and peroxidase ( p < 0.001). Mutagenic uterine DNA breakage and tissue damage were prominent following arsenic consumption by the rats. Oral delivery of spirulina resulted in a significant amelioration of arsenic-induced adverse oxidative stress and genotoxic state of rats. A significant low-signaling ( p < 0.001) of gonadotropins and estradiol was also noted in the arsenic-treated rats, which was terminated by spirulina; this arsenic-primed adverse effect was significant ( p < 0.05, p < 0.01). The spirulina treatment mechanism could be associated with augmentation of the antioxidant defense system that protects the arsenic-mediated pathological state of the uterus.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".