Novel Apoplastic Antifreeze Proteins of Deschampsia antarctica as Enhancer of Common Cell Freezing Media for Cryobanking of Genetic Resources, a Preliminary Study
Bibliographic record
Abstract
Antifreeze proteins (AFPs) are natural biomolecules found in cold-adapted organisms that lower the freezing point of water, allowing survival in icy conditions. These proteins have the potential to improve cryopreservation techniques by enhancing the quality of genetic material postthaw. Deschampsia antarctica, a freezing-tolerant plant, possesses AFPs and is a promising candidate for cryopreservation applications. In this study, we investigated the cryoprotective properties of AFPs from D. antarctica extracts on Atlantic salmon spermatozoa. Apoplastic extracts were used to determine ice recrystallization inhibition (IRI), thermal hysteresis (TH) activities and ice crystal morphology. Spermatozoa were cryopreserved using a standard cryoprotectant medium (C+) and three alternative media supplemented with apoplastic extracts. Flow cytometry was employed to measure plasma membrane integrity (PMI) and mitochondrial membrane potential (MMP) postthaw. Results showed that a low concentration of AFPs (0.05 mg/mL) provided significant IRI activity. Apoplastic extracts from D. antarctica demonstrated a cryoprotective effect on salmon spermatozoa, with PMI comparable to the standard medium. Moreover, samples treated with apoplastic extracts exhibited a higher percentage of cells with high MMP. These findings represent the first and preliminary report that suggests that AFPs derived from apoplastic extracts of D. antarctica have the potential to serve as cryoprotectants and could allow the development of novel freezing media.
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) | 0.000 | 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".