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Examination Of Facial Reflex Vasodilation In Young And Older Females Using Laser Speckle Contrast Imaging.

2025· article· en· W4414226318 on OpenAlexaffabout
Caroline Li-Maloney, Gregory W. McGarr, Kelli E. King, Glen P. Kenny

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2025
Typearticle
Languageen
FieldMedicine
TopicInfrared Thermography in Medicine
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsVasodilationDermatomeReflexPerfusionForearmBlood flowFacial nerveLaser Doppler velocimetry

Abstract

fetched live from OpenAlex

Aging is known to attenuate reflex forearm cutaneous vasodilation during passive heating. However, it is unknown whether facial reflex vasodilation is also impaired with aging in females who may report greater facial flushing with menopause. Facial skin is also innervated by various spinal nerves (dermatomes) and varies in microvascular density over the surface, which could influence cutaneous vasodilation differently across facial regions during passive heating. PURPOSE: To explore how facial reflex cutaneous vasodilation in response to whole-body passive heating in females is modulated across dermatomes and by age using laser speckle contrast imaging (LCSI). METHODS: 10 young (23 ± 3 years) and 10 older (70 ± 3 years) females underwent passive heating via a water-perfused suit to raise core temperature to 1.0 °C above baseline (36.9 °C ± 0.29). Steady-state heating was maintained for 60 minutes (+0.98 °C ± 0.08). LSCI was used to measure facial skin blood flux (quantified in perfusion units) at baseline and end-heating. Imaging flux was measured over the entire face and partitioned into regions of interest (~20mm2) to evaluate vasodilator responses across specific facial landmarks (eyelids, nose, lips), dermatomes (V1, V2, V3) and the left and right sides of the face. RESULTS: There was a significant main effect of heating on blood perfusion for the whole face pooled across age groups (+104% [87.3,121], P < 0.001). There was a significantly greater response to heating for skin corresponding to dermatome V2 (+99.4% [ 43.1, 155.8], P < 0.001) and the lower lip (+97.5% [1.32, 193.6], P = 0.03) relative to the whole face. There was no significant difference in responses to heating between the left and right sides of the face, nor any significant differences between age groups with respect to the whole face or partitioned regions of the face. CONCLUSION: LSCI captured the effect of whole-body passive heating on facial vasodilation in young and older females. Reflex vasodilation was not uniform across the face. It was greater in regions with higher nerve fiber and capillary density. These findings warrant further investigation into the influence of skin tissue characteristics on facial cutaneous vasodilation. Supported by: Natural Sciences and Engineering Research Council of Canada

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.002
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 head0.017
GPT teacher head0.308
Teacher spread0.292 · 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 designObservational
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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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