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Record W4417177674 · doi:10.1016/j.mex.2025.103754

Application of a thermoelectric cooling approach for localized hypothermia in a murine model

2025· article· en· W4417177674 on OpenAlexafffund
Kosala D. Waduthanthri, Gregory S. Korbutt, Andrew R. Pepper, Larry D. Unsworth

Bibliographic record

VenueMethodsX · 2025
Typearticle
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsDiabetes CanadaUniversity of Alberta
FundersAlberta Diabetes FoundationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsJuvenile Diabetes Research Foundation Canada
KeywordsThermoelectric coolingThermoelectric effectHypothermiaTemperature controlThermoelectric generatorHyperthermiaWater cooling

Abstract

fetched live from OpenAlex

Achieving localized and adjustable hypothermia is critical for various clinical and experimental applications, including reducing oxidative stress, modulating inflammatory responses, and enabling temperature-triggered drug delivery. However, existing cooling techniques such as ice packs, and cryogenic sprays limitations in precision, efficiency, duration, and cooling capacity. In this study, we used a commercially available thermoelectric cooling module to construct a simple and low-cost cooling system, and applied it in a preclinical mouse model to achieve focal hypothermia at a subcutaneous transplant site.•The system, assembled using a TES1-4903 thermoelectric module, a heat sink, and a power supply, achieved rapid temperature reduction rates. At 5 V, the subcutaneous temperature decreased at an average rate of ∼1.5 °C/s during the first 10 s, reaching a stable temperature of ∼8 °C within 120 s. At 2 V, the average rate was ∼0.4 °C/s, stabilizing at ∼17 °C over the same period.•The system demonstrated precise temperature control with minimal variability, maintaining temperature steps of <2 °C and ensuring a stable temperature range.•Compared to literature, our system highlights the utility of thermoelectric modules for biomedical cooling applications, demonstrating faster and safer subcutaneous hypothermia with more precise temperature control than other approaches.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.378
Teacher spread0.343 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes2
Has abstractyes

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