Stimulatory effect of aerosil on algal growth
Bibliographic record
Abstract
Unicellular green alga represents not only a convenient model for its biochemical and physiological studies but also a sensitive system to test the effects of various environmental factors. Algae cells of two strains, SA-3 strain (exsymbiotic from Paramecium bursaria) and Chlorella vulgaris c-27, were asynchronously cultured in the presence of 0.01% Aerosil A-300. Aerosil effects on algae were monitored at logarithmic and stationary phases of their growth by flow cytometry and microscopic counting of algal numbers. The growth patterns of algae were evaluated by their forward light scatter versus fluorescence of endogenous chlorophyll (FL3-height) signal distributions. Although aerosil itself did not cause any direct effects on algal morphology, it affected the growth patterns and the numbers of algae of both strains. Their growth patterns were remarkably altered in the late logarithmic phase cultures (6-day cultures). However, a significant increase of cell numbers was found in the stationary phase cultures (9- and 12-day cultures). While C. vulgaris c-27 demonstrated an increase of cell numbers by approximately 11% in the 9- and 12-day cultures, the amounts of SA-3 cells in the 9- and 12-days cultures were increased by 16% and 35%, respectively. Our study shows aerosil in its colloidal form stimulates proliferation of algae mainly via an acceleration of their life cycles. The stimulatory effect of silica on the growth of algae, the mechanism of which remains to be clarified, might have a practical (e.g., ecological) interest for regulation of algal expansion.
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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) | 0.000 | 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".