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Record W4394771741 · doi:10.54680/fr24210110112

PERSPECTIVE: Targeted development and optimization of small-molecule ice recrystallization inhibitors (IRIs) for the cryopreservation of biological systems

2024· article· en· W4394771741 on OpenAlexaff
Leah E. McMunn, Ellyssa M. Walsh, Robert N. Ben

Bibliographic record

VenueCryoletters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCryopreservationRecrystallization (geology)Antifreeze proteinSmall moleculeChemistryCell biologyBiochemistryBiologyEmbryo

Abstract

fetched live from OpenAlex

Despite the routine use of cryopreservation for the storage of biological materials, its outcomes are often sub-optimal (including reduced post-thaw viability, recovery, and functionality) due to the damage caused by uncontrolled ice growth. Traditional cryoprotective agents (CPAs), including dimethyl sulfoxide (DMSO), fail to prevent damage caused by ice growth and concerns over CPA cytotoxicity have fostered an increased interest in developing improved CPAs and cryoprotection strategies. The inhibition of ice recrystallization by natural antifreeze (glyco)proteins [AF(G)Ps] to improve cryopreservation outcomes has been examined; however, the ice binding properties of these substances and their challenging large-scale production make them poor CPA candidates. Therefore, the development and deployment of biocompatible, small-molecule ice recrystallization inhibitors (IRIs) for use as CPAs is a worthwhile objective. Extensive structure-activity relationship studies on AF(G)Ps revealed that simple carbohydrate derivatives could inhibit ice recrystallization. It was later discovered that this activity could be fine-tuned by delicately balancing the molecule’s hydrophobicity and hydrophilicity. Current generation small-molecule IRIs have been meticulously designed to avoid binding to the surface of ice and subsequent biological testing (for both cytotoxicity and cryopreservation efficacy) has demonstrated significant improvements to the cryopreservation outcomes of several cell types. However, an individualized cell-specific approach for the simultaneous assessment of multiple cryopreservation outcomes is necessary to realize the full potential of IRIs as CPAs. This article provides a detailed overview of the development of small-molecule carbohydrate-based IRIs and highlights the crucial cell-specific biological considerations that must be taken into account when assessing cryopreservation outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.030
GPT teacher head0.237
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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Same venueCryoletters→Same topicPhysiological and biochemical adaptations→French-language works237,207→