Evidence map›Paper›PMID 25038825›Full record

ArticleNature medicine2014

A plasmonic chip for biomarker discovery and diagnosis of type 1 diabetes.

Bo Zhang, Rajiv B Kumar, Hongjie Dai, Brian J Feldman

Open access · greenAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
14.2field-weighted citation impact, top 1% of its field
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

58 citing papers in PubMed, 178 citations in OpenAlex.

  1. Article
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  3. Gold nanoparticle-loaded TiOMikrochimica acta · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Bo Zhang1] Stanford University, Stanford, California, USA. [2] Department of Chemistry, Stanford University School of Humanities and Sciences, Stanford, California, USA. [3].ORCID 0000000307434816
Rajiv B Kumar1] Stanford University, Stanford, California, USA. [2] Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA. [3].
Hongjie Dai1] Stanford University, Stanford, California, USA. [2] Department of Chemistry, Stanford University School of Humanities and Sciences, Stanford, California, USA.
Brian J Feldman1] Stanford University, Stanford, California, USA. [2] Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA. [3] Program in Regenerative Medicine, Stanford University, Stanford, California, USA.
Stanford University · US

Funding

Stanford Global Health Consortium: Innovation, Design, Evaluation, and ActionRC4TW008781 · FIC · STANFORD UNIVERSITY · PI BARRY, MICHELE · 2010 to 2010
$8.1M
Using Components of the Circadian Clock to Regulate Stem Cell Fate DecisionsDP2OD006740 · OD · STANFORD UNIVERSITY · PI FELDMAN, BRIAN J · 2010 to 2010
$2.4M
Carbon Nanotubes as Multi-functional Spectroscopic Markers and Delivery Agents foR01CA135109 · NCI · STANFORD UNIVERSITY · PI DAI, HONGJIE · 2008 to 2012
$1.6M
CCR NIH HHS 1 RC4 TW008781-01FIC NIH HHS RC4 TW008781NCI NIH HHS 5R01CA135109-02NCI NIH HHS R01 CA135109NIH HHS DP2 OD006740NIH HHS DP2OD006740
6 · The paper itself

Abstract

Type 1 diabetes (T1D) is an autoimmune disease, whereas type 2 diabetes (T2D) results from insulin resistance and beta cell dysfunction. Previously, the onset of these two separate diseases was easily distinguished, with children being most at risk for T1D and T2D occurring in overweight adults. However, the dramatic rise in obesity, coupled with the notable increase in T1D, has created a large overlap in these previously discrete patient populations. Delayed diagnosis of T1D can result in severe illness or death, and rapid diagnosis of T1D is critical for the efficacy of emerging therapies. However, attempts to apply next-generation platforms have been unsuccessful for detecting diabetes biomarkers. Here we describe the development of a plasmonic gold chip for near-infrared fluorescence-enhanced (NIR-FE) detection of islet cell-targeting autoantibodies. We demonstrate that this platform has high sensitivity and specificity for the diagnosis of T1D and can be used to discover previously unknown biomarkers of T1D.

Indexed as

AutoantibodiesBiomarkersDiabetes Mellitus, Type 1GoldHumansIslets of LangerhansSensitivity and SpecificitySpectroscopy, Near-InfraredSurface Plasmon ResonanceAutoantibodiesBiomarkersGold

Identifiers

PMID25038825
PMCPMC4736508
OpenAlexW2022179089

What OpenQuestion holds

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Registered trials

None linked

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.