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The Morphological & Biomechanical Characteristics of the Ligamentum Mucosum and its Potential Role in Anterior Knee Pain

2016· article· en· W4389008625 on OpenAlexaff
Madeleine E. Norris, Tim Burkhart, Marjorie Johnson, Martin Sandig, Thomas Smallman, Alan Getgood

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsFowler Kennedy Sport Medicine ClinicHealth Sciences CentreLawson Health Research InstituteWestern University
Fundersnot available
KeywordsAnatomyTrichromeInfrapatellar fat padMasson's trichrome stainCadaveric spasmJoint capsuleMedicineKnee JointIntraclass correlationFemurOsteoarthritisH&E stainPathologyStainingSurgery

Abstract

fetched live from OpenAlex

Introduction The ligamentum mucosum (LM), or infrapatellar plica, is a non‐isometric structure of the knee joint that traverses from the intercondylar notch of the femur to the infrapatellar fat pad. The LM is composed of dense regular connective tissue, of which four different morphologies have been identified: separate, vertical septum, split, and fenestrated. Microscopically, pathological LM appears fibrotic and calcified, which can lead to impingement, and ultimately may be implicated in the pathogenesis of anterior knee pain. The specific aims of this study are to investigate the anatomical relationship of the LM to neighboring structures, determine whether the histological characteristics of the LM further define its function and its potential role in proprioception, and lastly to perform an in vitro biomechanical analysis of the LM under normal physiological loading. Methodology Fresh‐frozen cadaveric knee specimens (n=14) were dissected to reveal the structures of the joint capsule and to identify the morphology of the ligamentum mucosum. With the knee at 90° flexion, four measurements were recorded in order to examine the important relationships within the joint capsule. The intraclass correlation coefficient was calculated to determine the consistency and reproducibility of the measurements recorded. Maintaining the proximal and distal attachments, two specimens were harvested for histological analysis using standard hematoxylin and eosin, Masson's trichrome for collagen, and mono‐clonal mouse anti‐human neurofilament protein to identify neurons and peripheral nerve endings. Results Overall, 64% of the knees had a LM present. With respect to morphology, 50% of the 14 specimens had a separate type, 14% had a vertical septum type, and the remaining specimens had no LM present, which is consistent with known classification systems. The histological analysis confirmed the LM to be ligamentous, thus being composed of dense regular connective tissue. Preliminary immunohistochemistry results are inconclusive at this time for evidence of peripheral nerves and nerve endings, and the biomechanical properties of LM have yet to be determined. Discussion The role of LM in anterior knee pain is not well documented; however, studies have shown that excising the LM can relieve idiopathic anterior knee pain. With a decrease in elasticity, pathological LM may result in patellar maltracking and instability, ultimately triggering anterior knee pain. Future biomechanical testing will utilize an Instron materials testing machine to load the ligaments under tension at a constant velocity in order to determine the force at which the specimen fails. Thus, the findings from this study can be implemented in models of anterior knee pain, more specifically models of patellar instability and maltracking, to determine the proprioceptive and pathogenic mechanisms of the ligamentum mucosum.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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 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
Published2016
Admission routes1
Has abstractyes

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