Evidence map›Paper›PMID 30271145›Full record

ArticleInternational journal of nanomedicine2018

A novel absorption spectrometric method, based on graphene nanomaterials, for detection of hepatocellular carcinoma-specific T lymphocyte cells.

Jianmeng Zhu, Yiping Li, Lei Li, Jian Wang, Hongqin Wang, Wenzhong Hong, Ke Hao, Yadan Xue, Bingyu Chen, Zhen Wang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of nanomedicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
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

10 authors at 3 institutions in 1 country.

Jianmeng ZhuDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Yiping LiDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Lei LiDepartment of Pathophysiology, School of Basic Medical Science, Southern Medical University, Guangzhou, Zhejiang, China.
Jian WangDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Hongqin WangDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Wenzhong HongDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Ke HaoDepartment of Blood Transfusion, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Yadan XueDepartment of Blood Transfusion, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Bingyu ChenDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Zhen WangDepartment of Clinical Laboratory, Chun'an First People's Hospital (Zhejiang Provincial People's Hospital Chun'an Branch), Hangzhou, Zhejiang Province, China, chenbingyu@hmc.edu.cn, wangzhen@hmc.edu.cn.
Zhejiang Provincial People's Hospital · CNHangzhou Medical College · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDetection of antigen-specific cytotoxic T lymphocytes (CTLs) is the foundation for understanding hepatocellular carcinoma immune pathology and hepatocellular carcinoma immunotherapy. However, the classical method for labeling CTLs, major histocompatibility complex (MHC)-peptide tetramer, has drawbacks and needs further improvement. MATERIALS AND

methodsHere, as a new detection probe, a graphene-based MHC-peptide multimer was developed for sensitively and selectively identifying hepatocellular carcinoma-specific T-cells. To assess its detection efficiency, reduced graphene oxide (RGO) was functionalized with hemin and streptavidin to prepare a functionalized HRGO-streptavidin complex. Biotinylated MHC-peptide monomer was subsequently constructed onto HRGO to generate a detection probe for CTL labeling. The number of T-cells was detected through the reaction between HRGO and tetramethylbenzidine.

resultsUsing HRGO/MHC-peptide multimers, the number of T-cells was efficiently detected in both the induction system in vitro and in peripheral blood of patients.

conclusionHRGO/MHC-peptide multimers methodology has application prospects in the detection of antigen peptide-specific T cells.

Indexed as

BiotinylationCarcinoma, HepatocellularCase-Control StudiesGraphiteHumansLiver NeoplasmsMajor Histocompatibility ComplexNanostructuresPeptide FragmentsSpectrophotometryStreptavidinT-Lymphocytes, CytotoxicTumor Cells, CulturedGraphitePeptide FragmentsStreptavidincytotoxic T lymphocytesgrapheneheminhepatocellular carcinomamajor histocompatibility complex multimertetramer

Identifiers

PMID30271145
PMCPMC6154735
OpenAlexW2890913822

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.