Evidence map›Paper›PMID 29184498›Full record

ArticleFrontiers in pharmacology2017

Development of the Digital Arthritis Index, a Novel Metric to Measure Disease Parameters in a Rat Model of Rheumatoid Arthritis.

Maria A Lim, Brenton Louie, Daniel Ford, Kyle Heath, Paulyn Cha, Joe Betts-Lacroix, Pek Yee Lum, Timothy L Robertson, Laura Schaevitz

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

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  7. Analytical chemistry · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Maria A LimVium Inc., San Mateo, CA, United States.
Brenton LouieCapella Biosciences Inc., Palo Alto, CA, United States.
Daniel FordVium Inc., San Mateo, CA, United States.
Kyle HeathVium Inc., San Mateo, CA, United States.
Paulyn ChaVium Inc., San Mateo, CA, United States.
Joe Betts-LacroixVium Inc., San Mateo, CA, United States.
Pek Yee LumCapella Biosciences Inc., Palo Alto, CA, United States.
Timothy L RobertsonVium Inc., San Mateo, CA, United States.
Laura SchaevitzVium Inc., San Mateo, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite a broad spectrum of anti-arthritic drugs currently on the market, there is a constant demand to develop improved therapeutic agents. Efficient compound screening and rapid evaluation of treatment efficacy in animal models of rheumatoid arthritis (RA) can accelerate the development of clinical candidates. Compound screening by evaluation of disease phenotypes in animal models facilitates preclinical research by enhancing understanding of human pathophysiology; however, there is still a continuous need to improve methods for evaluating disease. Current clinical assessment methods are challenged by the subjective nature of scoring-based methods, time-consuming longitudinal experiments, and the requirement for better functional readouts with relevance to human disease. To address these needs, we developed a low-touch, digital platform for phenotyping preclinical rodent models of disease. As a proof-of-concept, we utilized the rat collagen-induced arthritis (CIA) model of RA and developed the Digital Arthritis Index (DAI), an objective and automated behavioral metric that does not require human-animal interaction during the measurement and calculation of disease parameters. The DAI detected the development of arthritis similar to standard

Indexed as

3rs strategiescollagen induced arthritiscontinuous monitoring platformsdrug discovery screeningphenotypic screeningrheumatoid arthritis (RA)rodent models of disease

Identifiers

PMID29184498
PMCPMC5694443

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.