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Record W4390952230 · doi:10.24041/ejmr2023.40

STRUCTURAL CHARACTERISTICS AND FUNCTIONAL INSIGHTS INTO TSP-4: IMPLICATIONS FOR CARDIOVASCULAR HEALTH

2023· article· en· W4390952230 on OpenAlexaff
Mr. Ale Eba

Bibliographic record

VenueEra s journal of medical research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsThrombospondinAngiogenesisAdipogenesisBiomarkerInflammationADAMTSThrombospondin 1BioinformaticsCoronary artery diseaseDiseaseMedicineExtracellular matrixBiologyCancer researchMesenchymal stem cellPathologyMatrix metalloproteinaseImmunologyCell biologyGeneticsInternal medicineMetalloproteinase

Abstract

fetched live from OpenAlex

Thrombospondin-4 (TSP-4) is a multidomain protein with unique functions within the thrombospondin family. It plays a works in tissue repair, cell-to-matrix conveying, and various physiological processes. TSP-4 differs structurally from other family members and is associated with a common single nucleotide polymorphism (SNP), A387P, linked to cardiovascular disorders. Its functions include tissue remodeling, regeneration, proliferation, adhesion, migration, angiogenesis, inflammation, and adipogenesis. The A387PSNPin TSP-4 increases the risk of these cardiovascular conditions and affects angiogenesis, inflammation, and adipogenesis. TSP-4 has clinical applications as a marker for various tissues and pathological disorders. Its expression levels differentiate cell origins, making it a biomarker for articular cartilage, tendon progenitor cells, and more. In heart-related conditions, TSP-4 serves as a marker for cardiac overload and coronary artery disease. Additionally, TSP-4 expression is associated with osteoarthritis severity, suggesting its potential as a biomarker for this condition. Overall, understanding TSP-4's diverse functions and its role in cardiovascular pathology provides insights into its clinical relevance and diagnostic potential, making it a promising target for further research and therapeutic interventions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.091
GPT teacher head0.423
Teacher spread0.332 · 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 designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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