Protease activities of <i>Acanthamoeba polyphaga</i> and <i>Acanthamoeba castellanii</i>
Bibliographic record
Abstract
Acanthamoeba spp. are free-living amoebae that cause amoebic granulomatous encephalitis, skin lesions, and ocular amoebic keratitis in humans. Several authors have suggested that proteases could play a role in the pathogenesis of these diseases. In the present work, we performed a partial biochemical characterization of proteases in crude extracts of Acanthamoeba spp. and in conditioned medium using 7.5% SDS-PAGE copolymerized with 0.1% m/v gelatin as substrate. We distinguished a total of 17 bands with proteolytic activity distributed in two species of Acanthamoeba. The bands ranged from 30 to 188 kDa in A. castellanii and from 34 to 144 kDa in A. polyphaga. Additionally, we showed that the pattern of protease activity differed in the two species of Acanthamoeba when pH was altered. By using protease inhibitors, we found that the proteolytic activities belonged mostly to the serine protease family and secondly to cysteine proteases and that the proteolytic activities from A. castellanii were higher than those in A. polyphaga. Furthermore, aprotinin was found to inhibit crude extract protease activity on Madin-Darby canine kidney (MDCK) monolayers. These data suggest that protease patterns could be more complex than previously reported.
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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) | 0.000 | 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".