High throughput method for simultaneous screening of membrane permeability and toxicity for discovery of new cryoprotective agents
Bibliographic record
Abstract
Cryoprotective agent (CPA) toxicity is the most limiting factor impeding cryopreservation of critically needed tissues and organs for transplantation and medical research. This limitation is in part due to the challenge of rapidly screening compounds to identify candidate molecules that are highly membrane permeable and non-toxic at high concentrations. Such a combination would facilitate rapid CPA permeation throughout the sample, enabling ice-free cryopreservation with minimal toxicity. This study presents a new method for rapidly assessing the cell membrane permeability and toxicity of candidate CPAs. The new method enables ~ 100 times faster permeability measurement than previous methods, while also allowing assessment of CPA toxicity using the same 96-well plate. We tested five commonly used CPAs and 22 less common ones at both 4 °C and room temperature, with 23 of them passing the screening process based on their favorable toxicity and permeability properties. Considering its advantages such as high throughput measurement of membrane permeability along with simultaneous toxicity assessment, the presented method holds promise as an effective initial screening tool to identify new CPAs for cryopreservation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".