Evidence map›Paper›PMID 29891314›Full record

ArticleCarbohydrate polymers2018

Ultra-high performance liquid chromatography-size exclusion chromatography (UPLC-SEC) as an efficient tool for the rapid and highly informative characterisation of biopolymers.

Natalia Perez-Moral, Jean-Michel Plankeele, Claire Domoney, Frederick J Warren

Open access · hybridAbstract read
In one paragraph

Article in Carbohydrate polymers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-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

5 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
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

4 authors at 3 institutions in 2 countries.

Natalia Perez-MoralFood and Health Programme, Quadram Institute Biosciences, Norwich, NR4 7UA, UK.
Jean-Michel PlankeeleWaters S.A.S., BP 608, 78056 Saint-Quentin, En Yvelines Cedex, France.
Claire DomoneyDepartment of Metabolic Biology, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UH, UK.
Frederick J WarrenFood and Health Programme, Quadram Institute Biosciences, Norwich, NR4 7UA, UK. Electronic address: fred.warren@quadram.ac.uk.
Quadram Institute · GBJohn Innes Centre · GBUniversité de Versailles Saint-Quentin-en-Yvelines · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Starch has a complex molecular structure, with properties dependent on the relative chain lengths and branching structure of its constituent molecules, which varies due to polymorphisms in starch biosynthetic genes, as well as environmental factors. Here we present the application of ultra-high performance size exclusion chromatography to the separation of starch chains from plant seeds. Several methods, have been used to analyse chain length distributions in starch, all with limitations in terms of analysis time, sample preparation and molecular weight range. Here we demonstrate that chain length distributions can be obtained with dramatically reduced analysis time using ultra-high performance size exclusion chromatography. The method may also show improvements in resolution of some fine structural features. Understanding links between starch fine structure and biosynthetic genes will allow bioengineering of starches with tailored properties. This technique may have application to the size separation and resolution of a range of biopolymers of value to the food, drink and pharmaceutical industries.

Indexed as

Chain length distributionMolecular structureSize exclusion chromatographyStarchUPLC

Identifiers

PMID29891314
PMCPMC6030444
OpenAlexW2804234699

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.