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Record W7133077932

Analysis of gene expression in human articular cartilage

2002· dissertation· W7133077932 on OpenAlexfundno aff
Hongwei Zhang

Bibliographic record

VenueTSpace · 2002
Typedissertation
Language
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsExpressed sequence tagcDNA libraryComplementary DNAGeneGene expressionCartilageOsteoarthritisMicroarray
DOInot available

Abstract

fetched live from OpenAlex

Osteoarthritis (OA), a common joint disease affecting mainly the middle-aged and elderly, is characterized by a progressive loss of articular cartilage. Currently, there is no effective therapy for OA, and disease-modifying therapies await identification of novel diagnostic and therapeutic targets. Our hypothesis is that expressed sequence tags (ESTs) and microarrays can be used to identify differences in gene expression profiles between embryonic, normal and diseased cartilage. Documenting these differences will allow us to identify key genes of relevance in OA, information that is an essential prerequisite for developing disease-modifying therapies for cartilage injury and disease. We first constructed a cDNA library from fetal cartilage and analyzed 5,603 ESTs. Of these, 3,420 ESTs matched known genes and represented 1,370 unique genes. Collagen type II, alpha 1 (COL2A1) was the most abundant gene. 127 novel ESTs (with no match) were discovered. One of these, FCR0572, was further studied and mapped to chromosome 9p21-22. Its mRNA was expressed in five fetal tissues. We then constructed cDNA libraries from mild and severe OA cartilage. Over 7000 ESTs were obtained from each library. Non-redundant analysis of ESTs with known gene matches resulted in 1,612 and 1,677 unique genes in mild and severe OA, respectively. By calculating relative EST frequency levels, we identified several differentially expressed genes, such as proteoglycan 4 (or megakaryocyte stimulating factor, MSF). Genes highly expressed in both mild and severe OA were also identified. One of these genes, beta-2 microglobulin (B2M), was further studied for its role in OA. We found that B2M levels in synovial fluid were significantly higher in OA joints than in normal joints. We then demonstrated that OA cartilage in vitro could produce B2M. At a concentration of 10 μg/ml, B2M showed an inhibitory effect on OA chondrocyte proliferation. Furthermore, we explored the effects of B2M on chondrocyte gene expression by using cDNA microarrays. Collagen type III, alpha 1 was one of the genes up-regulated two-fold by B2M. Our results demonstrate that EST-based approach and microarray are powerful tools for exploring cartilage biology and diseases at a molecular level.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.319
Teacher spread0.300 · 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 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".

Quick stats

Citations0
Published2002
Admission routes1
Has abstractyes

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