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Record W2022022610 · doi:10.3109/10428190009113379

Matrix Metalloproteinases and Their Tissue Inhibitors - Expression, Role and Regulation in Human Malignant Non-Hodgkin's Lymphomas

2000· review· en· W2022022610 on OpenAlexafffund
Anna E. Kossakowska, Stefan J. Urbanski, Anna Janowska‐Wieczorek

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2000
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtease and Inhibitor Mechanisms
Canadian institutionsCanadian Blood ServicesCalgary Laboratory ServicesUniversity of AlbertaUniversity of Calgary
FundersMedical Research Council CanadaUlster UniversityCanadian Blood Services
KeywordsMatrix metalloproteinaseCancer researchLymphomaMedicineBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Human malignant non-Hodgkin's lymphomas (NHL) represent a heterogeneous group of neoplasms, which vary in their clinical behavior and pathophysiology. Matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) have been shown to play a role in the pathophysiology and clinical aggressiveness of human NHL. In this setting, MMP-9 and TIMP-1 appear to be the most important members of the MMP and TIMP families, and overexpression of both correlates with a poor clinical outcome of patients with NHL. MMP-9 and TIMP-1, however, act through different mechanisms and are produced by different cell types. Expression of both is upregulated by interleukin-6 (IL-6), a cytokine that is known as one of the factors involved in the pathophysiology of human NHL. In this review we summarize the complex regulation of MMP and TIMP expression in human NHL and propose a mechanism by which MMP-9, TIMP-1 and IL-6 may influence the biology of these tumors.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0020.000
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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations40
Published2000
Admission routes2
Has abstractyes

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