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Record W2768824645

Immunolocalization of proteoglycan 4 and hyaluronan on articular cartilage

2013· article· en· W2768824645 on OpenAlexaffvenue
Rachel Malone

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2013
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCartilageChemistryAggrecanProteoglycanPrimary and secondary antibodiesParaformaldehydeMolecular biologyGlycosaminoglycanImmunohistochemistrySynovial fluidMatrix (chemical analysis)AntibodyAnatomyPathologyArticular cartilageOsteoarthritisBiochemistryImmunologyChromatographyBiologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION Articular cartilage is a tissue that is designed to reduce friction and be resistant to wear [1]. Proteoglycan 4 (PRG4), a mucin-like glycoprotein, is a lubricating molecule that is found in synovial fluid (SF) [2]. SF also has hyaluronan (HA), a glycosaminoglycan that forms large aggregates with proteoglycans like aggrecan [3]. Friction tests have shown that PRG4 and HA exhibit synergistic effects while lubricating cartilage [4]. HA and PRG4 have both been singularly visualized on the surface of cartilage using immunohistochemistry (IHC). The objective of this project was to co-visualize PRG4 and HA on the surface of articular cartilage. METHODS Cartilage disks (6 mm diameter) were harvested from the femoral groove of mature bovine knees. Samples were either immediately snap frozen (fresh) in OCT embedding medium or were shaken overnight in phosphate buffered saline (PBS) at 4°C to remove SF, and then soaked in 200 μL bovine SF (bSF), or PBS. These samples were then snap frozen in OCT. Samples were sliced (5 μm) and placed on slides for IHC. Slides were washed in PBS, and then fixed with paraformaldehyde. They were washed again, and endogenous peroxidase activity was blocked with H 2 O 2 . Nonspecific binding was blocked with normal goat serum. Monoclonal mouse antibody 4D6 was used as the primary antibody for PRG4 and biotinylated-HA binding protein (HABP) was used to detect HA [5.6]. Alexa Fluor 594 goat anti-mouse antibodies and streptavidin PE were used as secondary agents to label the PRG4 and HA, respectively [6]. Slides were sealed with DAPI VectaShield. The slides were imaged with a Zeiss LSM 780 confocal microscope using the 405 nm (DAPI), 488 nm (HA) and 594 nm lasers (PRG4). RESULTS HA and PRG4 were co-localized on the surface of fresh cartilage. The binding was shown to be specific, since PRG4 and HA were not observed on samples that did not receive HABP or 4D6. After shaking and soaking in PBS, neither PRG4 or HA were observed on the surface indicating that shaking successfully removed SF from the surface. HA and PRG4 were observed on the shaken samples soaked in bSF, indicating the surface could be repleted with PRG4 and HA. Figure 1. Image of the surface of: fresh sample (a), fresh sample with no secondary agents (b), shake-PBS soaked (c), and shake-bSF soaked (d). Cells labeled blue. PRG4 red, HA green. Overlap between HA and PRG4 is orange/yellow. DISCUSSION AND CONCLUSIONS These results demonstrate that PRG4 and HA are co-localized on the surface of articular cartilage. The signal for PRG4 and HA is specific, and SF can be removed and repleted via shaking and soaking samples. Additional IHC work is required, with PRG4, HA, and PRG4+HA soaks, to determine the order of deposition of PRG4 and HA on the surface of articular cartilage. Further surface interaction assays could also contribute to the understanding of the PRG4+HA interaction. REFERENCES 1. Buckwalter & Mankin. J Bone Joint Surg . 79A : 612-32, 1997. 2. Drewniak E, et al. A& R. 64 : 465–473, 2012. 3. Pearl A, et al. Clin Sports Med. 24 : 1-12. 2005. 4. Schmidt T, et al. A&R . 56 : 882-891, 2007. 5. Abubacker S, et al. Osteoarthritis and Cartilage . 21 : 186-189, 2013. 6. de la Motte & Drazba. J Histochem Cytochem . 59 :252–257, 2011.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.323
Teacher spread0.291 · 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 designBench or experimental
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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Citations1
Published2013
Admission routes2
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