Evidence map›Paper›PMID 27297056›Full record

ArticleProteomics2016

Can sugarcoated fingerprints be used to identify lurking viruses?

Tony Y Hu

Open access · greenAbstract readComment
In one paragraph

Article in Proteomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Tony Y HuDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, TX, USA.
Cornell University · US

Funding

Quantification of Circulating Antigens for Pediatric TB Diagnosis andTreatment MonitoringR01AI122932 · NIAID · METHODIST HOSPITAL RESEARCH INSTITUTE · PI HU, TONY Y. · 2016 to 2019
$1.8M
Real-time Detection of Active TB in HIV Exposed Children on CustomizedNanotrapR01AI113725 · NIAID · METHODIST HOSPITAL RESEARCH INSTITUTE · PI LABAER, JOSHUA · 2015 to 2018
$1.6M
NIAID NIH HHS R01 AI113725NIAID NIH HHS R01 AI122932
6 · The paper itself

Abstract

Comparative proteomics is increasingly used to detect biomarkers and therapeutic targets that differ between healthy and diseased populations; however, differences in posttranslational modifications have received less attention. In this issue, Yang et al. (Proteomics 2016, 16, 1872-1880) present data indicating that a glycoproteomics approach can detect N-glycosylated membrane protein differences between non-HIV-infected and latently infected human CD4(+) T-cell lines, identifying 172 proteins differentially expressed by these cells. Latently infected CD4(+) T cells are thought to represent the major barrier to eventual HIV cure, but do not express detectable levels of viral protein and have not been shown to express biomarkers that can distinguish them from the vastly more abundant uninfected CD4(+) T-cell population. The findings of Yang et al. suggest that glycoproteomic analyses may have untapped potential to identify novel biomarkers and therapeutic targets in cell populations not readily distinguishable be standard proteomic analyses.

Indexed as

HIV-1Virus LatencyCD4-Positive T-LymphocytesHIV InfectionsHumansProteomicsComparative glycoproteomicsGlycoproteomicsHIV-1 latencyN-glycoslylation

Identifiers

PMID27297056
PMCPMC5123435
OpenAlexW2441258758

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.