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Record W2287581582 · doi:10.2174/187221307780979892

Vcsa1 Gene Peptides for the Treatment of Inflammatory and Allergic Reactions

2007· review· en· W2287581582 on OpenAlexaff
Katherine Morris, Byron Kuo, Mark D. Wilkinson, Joseph S. Davison, A. Dean Befus, R. D. Mathison

Bibliographic record

VenueRecent Patents on Inflammation & Allergy Drug Discovery · 2007
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsPentapeptide repeatPeptideGenePeptide sequenceSubmandibular glandBiologyBiochemistryProhormoneAllergic inflammationChemistryInflammationImmunologyHormoneEndocrinology

Abstract

fetched live from OpenAlex

The recently emerged Vcsa1 gene is one member of the variable coding sequence (VCS) multigene family of Rattus norvegicus. This gene encodes the precursor prohormone SMR1 (submandibular rat-1), which on enzymatic processing gives rise to several 5 to 11 amino acid peptides that modulate a variety of physiological functions. The analgesic pentapeptide sialorphin and anti-inflammatory heptapeptide submandibular gland peptide-T (TDIFEGG) are the most intensively studied. Although the Vcsa1 gene and its protein product are unique to rats, TDIFEGG or a derivative acts on all species examined to date, including human cells, in functions related to allergic reactions and inflammation. In this review, the patent and academic literature on SMR1 and its natural peptides and their derivatives are reviewed for consideration of biological targets and relevance to the development of novel therapeutic agents. The VCS gene family is discussed and we speculate on possible human homologs of these potent anti-inflammatory rat-derived peptides. The biologically active peptide products of SMR1 are considered and the mechanism of action and structure-activity relationships of the anti-inflammatory submandibular gland peptide-T and its derivatives are discussed.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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 head0.063
GPT teacher head0.334
Teacher spread0.271 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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