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Record W4404524854 · doi:10.1159/000542663

Perfusion Staining Methods for Visualization of Intact Microvascular Networks in Whole Mount Skeletal Muscle Preparations

2024· article· en· W4404524854 on OpenAlex
Barbara Hyde-Lay, Mackenzie Charter, Coral L. Murrant

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Vascular Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSkeletal muscleCremaster muscleAnatomyMicrocirculationWheat germ agglutininPerfusionMicrovesselStainingChemistryBiologyBiochemistryAngiogenesisLectinMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Visualization of the intact microvascular network in skeletal muscle requires labeling the entire network in whole mount preparations where muscle fibre length can be set to near optimal but the tools to do this are not clear. METHODS: We intravascularly injected CD-1 mice with different fluorescently labelled lectins (fluorescent isolectin GS-IB4 [ISO], wheat germ agglutinin [WGA], lycopersicon esculentum [LYCO]) or FITC-labelled gel. Soleus, extensor digitorum longus, diaphragm, gluteus maximus and cremaster muscles were excised, pinned at optimal sarcomere length and viewed using fluorescence microscopy. RESULTS: WGA and LYCO were effective at labeling the entire vascular network with WGA labeling capillaries more brightly. ISO labelled the arteriolar vasculature and early segments of the capillaries but not the full length of the capillaries or the venular network. FITC-labelled gel was effective at labelling the microvascular network but not all small vessels were consistently labelled. The pattern of staining for each labelling method was similar across all muscle fibre-types tested. CONCLUSIONS: WGA was optimal for perfusion labeling and visualization of the intact microvascular network in whole mount skeletal muscle preparations and can be used in combination with ISO to distinguish the arteriolar and venous sides of the network. INTRODUCTION: Visualization of the intact microvascular network in skeletal muscle requires labeling the entire network in whole mount preparations where muscle fibre length can be set to near optimal but the tools to do this are not clear. METHODS: We intravascularly injected CD-1 mice with different fluorescently labelled lectins (fluorescent isolectin GS-IB4 [ISO], wheat germ agglutinin [WGA], lycopersicon esculentum [LYCO]) or FITC-labelled gel. Soleus, extensor digitorum longus, diaphragm, gluteus maximus and cremaster muscles were excised, pinned at optimal sarcomere length and viewed using fluorescence microscopy. RESULTS: WGA and LYCO were effective at labeling the entire vascular network with WGA labeling capillaries more brightly. ISO labelled the arteriolar vasculature and early segments of the capillaries but not the full length of the capillaries or the venular network. FITC-labelled gel was effective at labelling the microvascular network but not all small vessels were consistently labelled. The pattern of staining for each labelling method was similar across all muscle fibre-types tested. CONCLUSIONS: WGA was optimal for perfusion labeling and visualization of the intact microvascular network in whole mount skeletal muscle preparations and can be used in combination with ISO to distinguish the arteriolar and venous sides of the network.

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.

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)0.004
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.450
Teacher spread0.413 · 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