Evidence map›Paper›PMID 21639939›Full record

ArticleVirology journal2011

Alpha-1 antitrypsin is a potential biomarker for hepatitis B.

Xu-fei Tan, Shan-shan Wu, Shu-ping Li, Zhi Chen, Feng Chen

Open access · goldAbstract read
In one paragraph

Article in Virology journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

12 citing papers in PubMed, 22 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Xu-fei TanState Key Laboratory of Infectious Disease Diagnosis and Treatment, First Affiliated Hospital, College of Medicine, Zhejiang University, Zhejiang, China.
Shan-shan Wu
Shu-ping Li
Zhi Chen
Feng Chen
Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFunction exertion of specific proteins are key factors in disease progression, thus the systematical identification of those specific proteins is a prerequisite to understand various diseases. Though many proteins have been verified to impact on hepatitis, no systematical protein screening has been documented to hepatitis B virus (HBV) induced hepatitis, hindering the comprehensive understanding to this severe disease.

aimTo identify the major proteins in the progression of HBV infection from mild stage to severe stage.

methodsWe performed an integrated strategy by combining two-dimensional electrophoresis (2-DE), peptide mass fingerprinting (PMF) analysis, and tissue microarray techniques to screen the functional proteins and detect the localization of those proteins.

resultsInterestingly, MS/MS identification revealed the expression level of alpha-1 antitrypsin (AAT) was significantly elevated in serum samples from patients with severe chronic hepatitis. Immunoblotting with a specific AAT antibody confirmed that AAT is highly expressed in serum samples from patients with hepatic carcinoma and severe chronic hepatitis. Furthermore, we observed that AAT is with highest expression in normal tissue and cells, but lowest in hepatic carcinoma and severe chronic hepatitis tissues and cells, suggesting the specific secretion of AAT from tissues and cells to serum.

conclusionThese results suggest the possibility of AAT as a potential biomarker for hepatitis B in diagnosis.

Indexed as

alpha 1-AntitrypsinBiomarkersElectrophoresis, Gel, Two-DimensionalHepatitis BHumansMass SpectrometryMicroarray AnalysisSerumalpha 1-AntitrypsinBiomarkersSERPINA1 protein, human

Identifiers

PMID21639939
PMCPMC3120791
OpenAlexW2112618002

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.