Technologies for Vitrification Based Cryopreservation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cryopreservation is a unique and practical method to facilitate extended access to biological materials. Because of this, cryopreservation of cells, tissues, and organs is essential to modern medical science, including cancer cell therapy, tissue engineering, transplantation, reproductive technologies, and bio-banking. Among diverse cryopreservation methods, significant focus has been placed on vitrification due to low cost and reduced protocol time. However, several factors, including the intracellular ice formation that is suppressed in the conventional cryopreservation method, restrict the achievement of this method. To enhance the viability and functionality of biological samples after storage, a large number of cryoprotocols and cryodevices have been developed and studied. Recently, new technologies have been investigated by considering the physical and thermodynamic aspects of cryopreservation in heat and mass transfer. In this review, we first present an overview of the physiochemical aspects of freezing in cryopreservation. Secondly, we present and catalog classical and novel approaches that seek to capitalize on these physicochemical effects. We conclude with the perspective that interdisciplinary studies provide pieces of the cryopreservation puzzle to achieve sustainability in the biospecimen supply chain.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it