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Record W2233585229 · doi:10.1039/c5fd00168d

High spatial resolution (1.1 μm and 20 nm) FTIR polarization contrast imaging reveals pre-rupture disorder in damaged tendon

2016· article· en· W2233585229 on OpenAlexafffund
Richard Wiens, Catherine Rui Jin Findlay, Samuel G. Baldwin, Laurent Kreplak, J. Michael Lee, Samuel P. Veres, Kathleen Gough

Bibliographic record

VenueFaraday Discussions · 2016
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsSaint Mary's UniversityDalhousie UniversityUniversity of WinnipegUniversity of Manitoba
FundersInstitute of Musculoskeletal Health and ArthritisNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchDalhousie UniversityResearch Manitoba
KeywordsTendonFourier transform infrared spectroscopyMaterials scienceBiomedical engineeringPolarization (electrochemistry)Image resolutionNuclear magnetic resonanceOpticsChemistryBiophysicsAnatomyPhysicsBiologyMedicinePhysical chemistry

Abstract

fetched live from OpenAlex

Collagen is a major constituent in many life forms; in mammals, collagen appears as a component of skin, bone, tendon and cartilage, where it performs critical functions. Vibrational spectroscopy methods are excellent for studying the structure and function of collagen-containing tissues, as they provide molecular insight into composition and organization. The latter is particularly important for collagenous materials, given that a key feature is their hierarchical, oriented structure, organized from molecular to macroscopic length scales. Here, we present the first results of high-resolution FTIR polarization contrast imaging, at 1.1 μm and 20 nm scales, on control and mechanically damaged tendon. The spectroscopic data are supported with parallel SEM and correlated AFM imaging. Our goal is to explore the changes induced in tendon after the application of damaging mechanical stress, and the consequences for the healing processes. The results and possibilities for the application of these high-spatial-resolution FTIR techniques in spectral pathology, and eventually in clinical applications, are discussed.

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)0.000
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 score0.232
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.245
Teacher spread0.239 · 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".

Quick stats

Citations29
Published2016
Admission routes2
Has abstractyes

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