Evidence map›Paper›PMID 42427765›Full record

ArticlebioRxiv : the preprint server for biology2026

A high throughput platform for measuring and predicting vitrification behavior in multicomponent aqueous solutions.

Nima Ahmadkhani, Cameron Sugden, Euihyun Lee, Carlos R Baiz, Duncan Brown, Nolan Drummond, Alec Snyder, Matthew Uden, Adam Z Higgins

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Nima AhmadkhaniSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA.
Cameron SugdenSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA.
Euihyun LeeDepartment of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA.
Carlos R BaizDepartment of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA.
Duncan BrownSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA.
Nolan DrummondSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA.
Alec SnyderSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA.
Matthew UdenDepartment of Psychology, The University of Texas at Austin, Austin, TX 78712, USA.
Adam Z HigginsSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA.

Funding

Protein structure and dynamics in ultra-heterogeneous environments-RenewalR35GM133359 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Carlos Raul Baiz · 2019 to 2026
$1.8M
NIGMS NIH HHS R35 GM133359
6 · The paper itself

Abstract

Cryopreservation depends critically on suppression of ice formation by cryoprotective agents (CPAs), but limited data is available on the CPA concentration required for vitrification (Cv). Here, we introduce a high-throughput 384-well platform that integrates automated liquid handling, randomized plate layouts, and a binary-search strategy to rapidly determine Cv across hundreds of formulations. Relative to conventional methods, this approach increases throughput by ~50-fold, compressing a year of measurements into one week, while markedly reducing manual labor. Across ~200 CPA compositions, we demonstrate that environmental boundary conditions strongly influence vitrification behavior: plates sealed with silicone mats exhibited lower Cv than open plates, indicating that sealed configurations promote vitrification. Further, the data reveal a decrease in Cv with increasing CPA molecular weight, consistent with enhanced ice suppression by larger molecules. We also present a simple mixture model that accurately predicts Cv for a broad range of CPA formulations, including mixtures containing up to seven CPAs (R

Indexed as

384-well plate assayCryopreservationCryoprotectantGlass FormationHigh-throughput screeningIce FormationMixture modelingVitrification

Identifiers

PMID42427765
PMCPMC13345240

What OpenQuestion holds

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LicenceCC BY-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.