Ranaspumin Protein Characterization and Applications for Both Environmental and Medical Purposes
Bibliographic record
Abstract
The Túngara frog (Engystomops pustulosus) from Central America creates a bio-foam that protects their young from dehydration, microbial degradation, and even predators during early development. The foam is composed of unique proteins known as Ranaspumin 1-6 (RSN 1-6). These RSN proteins have been synthetically synthesized and verified with Circular Dichroism (CD) to determine their critical micelle concentration, antimicrobial properties, and stability at varying temperatures and pH ranges. Throughout these characterizations, RSN 2 was determined to establish/produce antimicrobial properties, express stability at temperatures between 20 – 60oC, and express stability at a pH range of 5-8. Therefore, RSN 2 was isolated and utilized for medical and environmental applications. With the addition of RSN 2, the separation of aromatics was achieved in tar-sands with the assistance of a Tangential Flow Filtration (TFF) system. With only three passes through the TFF system, the RSN 2 solution isolated approximately 35% of the aliphatic region, and approximately 70% of the aromatic region. Finally, RSN 2 was implemented into an organ preservation solution for organ transplant surgery. By observing two different biomarkers, including Cardiolipin (CL) and alkali metals/alkaline earth metals for a change in concentration to verify organ viability. Resulting in the RSN 2 solution as well as a 50:50 solution composed of RSN 2 and a ‘gold standard' solution, has the potential to replace the on the market preservation solutions. Therefore, a simple bio-foam such as RSN 2 has the potential to advance both the medical and environmental fields.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".