Bibliographic record
Abstract
Problem statement: Enzymes have vital roles in several industrial processes (foods, cosmetics, nutraceuticals and pharmaceuticals) due to their highly selective nature and high activity at very low concentrations.Recent efforts to identify new sources of useful enzymes have been concentrated on the marine environment because of the potential to make use of processing wastes.About 35-50% of the mass of the fish caught is a waste that is disposed off at sea or in landfills.The extraction of enzymes from fish processing waste can reduce environment problems and improve the economics of the fish industry.Collagenases are a group of enzymes that can be extracted from fish waste.Approach: Comprehensive reviews of the literature on the extraction, purification, characterization and use of collagenases was carried out.Results: Collagenases have different molecular weights based on their types and sources.They have the ability to break down the peptide bonds in collagen at physiological pH.They are classified into two types: serine and metallocollagenase.Collagenolytic activities have been shown at a wide range of temperatures (20-40°C) and pH (6-8).Many activators can be used to achive collagenase activity including 4-Aminophenylmercuric Acetate (APMA), trypsin, potassium or sodium thiocyanate, iodoacetamide and potassium iodide.Dithiothreitol (DTT), mercaptoethanol, ethylendiaminetetracetic acid, ophenanthroline and cysteine inactivate the enzyme.Collagenases enzymes can be extracted with a variety of techniques using different buffering systems (tris-HCl, sodium bicarbonate, calcium chloride and cacodylate).All techniques involve the use of ammonium sulphate fractionation and centrifugation to precipitate the enzyme.Collagenases are normally purified using chromatographic techniques such as gel-filtration, ion-exchange and affinity column chromatography.Collagenase can be assayed with a number of methods, including: colorimetric absorbance, viscometry, radioactivity and fluorescence spectroscopy.Collagenases are partly responsible for toughness in red meats and are used as tenderizers in food industry, have application in the fur and hide tanning to ensure uniform dying of leather, used in medicine to treat burns and ulcers, eliminate scar tissues, transplantation of organs.Conclusion: Understanding of the nature of the enzymes and identifying the most suitable resources and the methods for their extraction and purification will have significant impact on the fish processing, food and medical industries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".