Effect of Metal Ions, Solvents and Surfactants on the Activity of Protease from Aspergillus niger KIBGE-IB36
Bibliographic record
Abstract
Metal ions greatly impact on the enzymatic activity, they may form strong interaction by forming coordinate bond with enzyme-substrate at the catalytic site which may activate, inhibit or stabilized the enzyme molecules. In this study, extracellular protease from Aspergillus niger KIBGE-IB36 was precipitated with 40% ammonium sulfate. It was revealed that K+, Ba2+, Na+, Mg2+ Zn2+, Ca2+ boosted the protease activity whereas, Cs+, Mn2+, Cu2+, Ni2+, V2+, Co2+, Hg2+ and Al3+ showed to be inhibitor of protease. Dimethyl sulfoxide (5.0 mM) and methanol (5.0 mM) showed catalytic activity while ethanol at same concentration exhibited inhibitory effect. Protease activity augmented with Tween 80, while SDS, Triton X-100, EDTA and PMSF exhibited inhibitory effect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".