In-vitro and In-vivo Anti-Candidal Effect of Cnidoscolus aconitifolius Leaves Extracts
Bibliographic record
Abstract
Candidiasis is an opportunistic infection caused by pathogens of the genus Candida. Due to the increase in antifungal resistance by Candida species, there is a need for alternatives in its treatment. Cnidoscolus aconitifolius is a medicinal plant with vast nutritional and antimicrobial properties. This study evaluated the in-vitro and in-vivo anti-candidal effect of Cnidoscolus aconitifolius (spinach tree) leaves extract. Clinical isolates of Candida albicans, Candida krusei, Candida tropicalis, Candida dublinensis, Candida glabrata, and Candida parapsilosis were used in this study and Cold maceration technique was employed in the plant extraction process, to obtain its ethanolic, methanolic, and aqueous extract. The agar well diffusion method and 2-fold dilution process -to obtain 250 mg/ml to 15.625mg/ml of the extracts -were used for the antimicrobial sensitivity test and three weeks old female Wistar rats infected with 20µl of standardized C. albicans were used for the in-vivo evaluation. Statistical analysis was done using Statistical package for Social Sciences (SPSS) version 22. In-vitro assay revealed ethanolic extract as the most potent extract with the highest inhibition zone diameter of 12.67±1.15c, 11.67±1.15c, and 12.33±0.58c at 250mg/ml against C. tropicalis, C. krusei2, and C. parapsilosis respectively. C. parapsilosis was the most sensitive to all the extracts. In-vivo, the disappearance of disease symptoms and progressive decrease in rats Candida burden- from 6.35×103 CFU/ml obtained after infection to 2.15×103CFU/ml after treatment revealed the ability of the plant to treat candidiasis. The study suggests that extract of Cnidoscolus aconitifolius leaves could act individually or synergistically as effective drug candidates in the treatment of candidiasis; thus if its individual antifungal constituents are purified, this plant could be the next major anti-candidal agent.
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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 | 0.000 |
| 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".