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Record W2063045581 · doi:10.1093/ecam/nek001

The Use of Gene Expression Analysis and Proteomic Databases in The Development of a Screening System To Determine The Value of Natural Medicinal Products

2006· article· en· W2063045581 on OpenAlexafffund
Sidney Katz, Robert Harris, Jeffrey Lau, Adeline Chau

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2006
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchWater CorporationEuropean Bioinformatics Institute
KeywordsGene expressionWestern blotGeneBiologyComputational biologyDatabaseGeneticsComputer science

Abstract

fetched live from OpenAlex

A rapid throughput screening system involving gene expression analysis was developed in order to investigate the potential of bioactive chemicals contained in natural health products as effective drug therapy, in particular the ability of these chemicals to alleviate the inflammatory response in human airway epithelial cells. A number of databases were searched to retrieve the information needed to properly analyze the gene expression profiles obtained. The gene expression of human bronchial epithelial cells infected with rhinovirus and/or exposed to platelet activating factor was analyzed. Following analysis of the gene expression data the total number of expressed proteins that may potentially act as a marker for monitoring the modulation of airway inflammation was narrowed to 19. Further studies will involve selecting antibodies for these proteins, culturing airway epithelial cells in the presence of extracts of natural health products, extracting the proteins and identifying them by western blot analysis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.121
GPT teacher head0.333
Teacher spread0.213 · 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 designBench or experimental
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

Citations15
Published2006
Admission routes2
Has abstractyes

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