Evidence map›Paper›PMID 16281978›Full record

ArticleProteome science2005

Application of protein lysate microarrays to molecular marker verification and quantification.

Anitha Ramaswamy, E Lin, Iou Chen, Rahul Mitra, Joel Morrisett, Kevin Coombes, Zhenlin Ju, Mini Kapoor

Abstract read
In one paragraph

Article in Proteome science, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Microfluidic Western blotting.Proceedings of the National Academy of Sciences of the United States of America · 2012
    Article
  5. Protein microarrays for systems biology.Acta biochimica et biophysica Sinica · 2011
    Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
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

8 authors.

Anitha RamaswamyDepartment of Molecular Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. pinkas@hotmail.com
E Lin
Iou Chen
Rahul Mitra
Joel Morrisett
Kevin Coombes
Zhenlin Ju
Mini Kapoor

Funding

LESION QUANTIFICATION IN HUMAN CAROTID ATHEROSCLEROSISR01HL063090 · NHLBI · BAYLOR COLLEGE OF MEDICINE · PI MORRISETT, JOEL DAVID · 2002 to 2005
$1.3M
NHLBI NIH HHS R01 HL063090
6 · The paper itself

Abstract

This study presents the development and application of protein lysate microarray (LMA) technology for verification of presence and quantification of human tissue samples for protein biomarkers. Sub-picogram range sensitivity has been achieved on LMA using a non-enzymatic protein detection methodology. Results from a set of quality control experiments are presented and demonstrate the high sensitivity and reproducibility of the LMA methodology. The optimized LMA methodology has been applied for verification of the presence and quantification of disease markers for atherosclerosis. LMA were used to measure lipoprotein [a] and apolipoprotein B100 in 52 carotid endarterectomy samples. The data generated by LMA were validated by ELISA using the same protein lysates. The correlations of protein amounts estimated by LMA and ELISA were highly significant, with r2 > or = 0.98 (p < or = 0.001) for lipoprotein [a] and with r2 > or = 0.94 (p < or = 0.001) for apolipoprotein B100. This is the first report to compare data generated using proteins microarrays with ELISA, a standard technology for the verification of the presence of protein biomarkers. The sensitivity, reproducibility, and high-throughput quality of LMA technology make it a potentially powerful technology for profiling disease specific protein markers in clinical samples.

Identifiers

PMID16281978
PMCPMC1334216

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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.