Evidence map›Paper›PMID 27063869›Full record

ReviewJournal of fluorescence2016

Signal Improvement Strategies for Fluorescence Detection of Biomacromolecules.

Chengxin Luan, Zixue Yang, Baoan Chen

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of fluorescence, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
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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

3 authors at 2 institutions in 1 country.

Chengxin LuanDepartment of Hematology and Oncology (Key Department of Jiangsu Medicine), Zhongda Hospital, School of Medicine, Southeast University, Dingjiaqiao 87, Gulou District, Nanjing, 210009, Jiangsu Province, People's Republic of China.
Zixue YangSchool of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Baoan ChenDepartment of Hematology and Oncology (Key Department of Jiangsu Medicine), Zhongda Hospital, School of Medicine, Southeast University, Dingjiaqiao 87, Gulou District, Nanjing, 210009, Jiangsu Province, People's Republic of China. cba8888@hotmail.com.
Zhongda Hospital Southeast University · CNSoutheast University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For analysis of biomacromolecules, a sensitive, specified and reliable method is indispensable. Fluorescent dyes or fluorophores have been widely used as mediums to obtain readout signals in various assays or bioimaging because of their versatilities such as biocompatibility. Those fluorescent dyes based techniques manipulate many molecular interactions for analysis of biomacromolecules including antibody-protein interaction, base complementation, glycan-lectin interaction, etc. The strategies to manipulate those molecular interactions are various and always updating due to the development of biotechnological tools and instruments. In this minireview, we summarize the state of the art of signal improvement techniques for fluorescence detection of biomacromolecules especially proteins and nucleic acids. We focus on the principle and mechanism of those techniques for fluorescence detection of biomacromolecules. We also discuss the future trend of the techniques for fluorescence detection of biomacromolecules.

Indexed as

AnimalsFluorescent DyesHumansLimit of DetectionMacromolecular SubstancesSpectrometry, FluorescenceFluorescent DyesMacromolecular SubstancesBiomacromoleculeFluorescenceSignal improvementSignal-to-noise ratio

Identifiers

PMID27063869
OpenAlexW2317541087

What OpenQuestion holds

Textmetadata
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.