MétaCan
Menu
Back to cohort
Record W2049371898 · doi:10.2174/1389557053175416

Transglutaminases as Targets for Pharmacological Inhibition

2005· review· en· W2049371898 on OpenAlexaff
Jolanta Wodzinska

Bibliographic record

VenueMini-Reviews in Medicinal Chemistry · 2005
Typereview
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsApotex (Canada)
Fundersnot available
KeywordsTissue transglutaminaseAutoantibodyBiologyCell biologyImmunologyMedicineEnzymeBiochemistryAntibody

Abstract

fetched live from OpenAlex

Transglutaminases (TGases), a family of enzymes that catalyze the formation of epsilon-(gamma-glutamyl)lysine isopeptide linkage, play an important physiological role in hemostasis, wound healing, assembly and remodeling of the extracellular matrix, cell signaling and apoptosis. Although many members of this class of enzymes have been known for decades, their role in various physiological and pathological processes is still a subject of substantial research and debate. Convincing evidence exists that TGases are involved in formation of cytotoxic proteinatious aggregates in Alzheimer's, Huntington's and other neurodegenerative diseases. However, it is not clear if elevated levels of TGases play a causative or protective role in several of these processes. Increased or defective TGase activity is a factor in cortical cataract formation, lamellar ichtyosis and fibrosis. TGase creates epitopes for the production of autoantibodies in celiac disease and possibly other autoimmune diseases. Another TGase, Factor XIIIa, is involved in the etiology of vascular diseases. Modulation of TGase activity through its selective inhibition may have therapeutic benefit in a wide variety of diseases. This paper will examine TGases as targets for the development of new therapeutics and review the progress in discovery of selective inhibitors of these enzymes.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.106
GPT teacher head0.406
Teacher spread0.301 · 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.

Study designNot applicable
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

Citations23
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueMini-Reviews in Medicinal ChemistrySame topicBlood properties and coagulationFrench-language works237,207