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Peptidyl Arginine Deiminases and Neurodegenerative Diseases

2016· review· en· W2274079979 on OpenAlexafffund
R.K. Tu, H.M. Grover, Lakshmi P. Kotra

Bibliographic record

VenueCurrent Medicinal Chemistry · 2016
Typereview
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsArginineDiseaseCitrullineIsozymeBiochemistryNeurodegenerationEnzymeMedicineNeuroscienceChemistryBiologyComputational biologyPharmacologyPathologyAmino acid

Abstract

fetched live from OpenAlex

Peptidyl arginine deiminases (PADs) are a small group of isozymes that convert Arg residues on the surface of proteins into citrulline residues, typically as a part of posttranslational processing. PADs are present in most of the tissues, and the isozyme distribution is tissue-specific. In the past 15 years, it is becoming apparent that PADs are either upregulated or their catalytic activity is enhanced in certain disease conditions, including neurological diseases. In particular, hypercitrullinated proteins and elevated PAD activities are discovered in neurodegenerative conditions such as multiple sclerosis, Alzheimer's disease etc. This review article reviews the status of PAD enzymes as targets in neurodegenerative conditions, and briefly outlines the efforts in medicinal chemistry to identify PAD inhibitors for the treatment of various neurodegenerative conditions.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.379
Teacher spread0.329 · 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 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

Citations24
Published2016
Admission routes2
Has abstractyes

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