Effect of solvent concentration on the extraction kinetics and diffusivity of Cyclosporin A in the fungus <i>Tolypocladium inflatum</i>
Bibliographic record
Abstract
The kinetics of solid-liquid extraction and extraction yields of the immunosuppressant drug Cyclosporin A (CyA) from the mycelia of Tolypocladium inflatum were examined in this study. A 2 L stirred, baffled vessel was used to extract CyA from wet mycelia mass. Three different organic solvents were used, namely, methanol, acetone, and isopropanol at different concentrations in aqueous mixtures at room temperature. It was found that the best solvent was acetone at 50% v/v concentration achieving 100% extraction of CyA from the mycelia of T. inflatum. Although acetone proved to be the better solvent for CyA extraction, further studies were performed using methanol. A linear relationship was found between extraction yield of CyA and methanol concentration with 100% CyA extraction at 90% v/v methanol. The partition coefficients of CyA between the solid mycelia phase and the aqueous solvent phase were found to decrease exponentially with increasing methanol concentration. A liquid extraction model was developed based on the diffusion equation to correlate the kinetic data of CyA extraction from the solid mycelia of T. inflatum. Non-linear regression analysis of experimental data was used with the diffusion equation in order to calculate the effective diffusivities of CyA in the mycelia of T. inflatum. For all three organic solvents used, the effective diffusivities of CyA were found to be between 4.41 x 10(-15) and 6.18 x 10(-14) m(2)/s. This is the first time CyA effective diffusivities in T. inflatum are reported in the literature.
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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 | 0.001 |
| 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) | 0.001 | 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".