Evidence map›Paper›PMID 34293192›Full record

ReviewElectrophoresis2021

Affinity monolith chromatography: A review of general principles and recent developments.

Saumen Poddar, Sadia Sharmeen, David S Hage

Abstract readReview
In one paragraph

Review in Electrophoresis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. 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

3 authors.

Saumen PoddarDepartment of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA.
Sadia SharmeenDepartment of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA.
David S HageDepartment of Chemistry, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA.ORCID 0000-0003-1145-5003

Funding

CHROMATOGRAPHIC STUDIES OF FUNCTIONAL PROTEOMICSR01DK069629 · NIDDK · UNIVERSITY OF NEBRASKA LINCOLN · PI HAGE, DAVID S · 2006 to 2017
$1.8M
NIDDK NIH HHS R01 DK069629
6 · The paper itself

Abstract

Affinity monolith chromatography (AMC) is a liquid chromatographic technique that utilizes a monolithic support with a biological ligand or related binding agent to isolate, enrich, or detect a target analyte in a complex matrix. The target-specific interaction exhibited by the binding agents makes AMC attractive for the separation or detection of a wide range of compounds. This article will review the basic principles of AMC and recent developments in this field. The supports used in AMC will be discussed, including organic, inorganic, hybrid, carbohydrate, and cryogel monoliths. Schemes for attaching binding agents to these monoliths will be examined as well, such as covalent immobilization, biospecific adsorption, entrapment, molecular imprinting, and coordination methods. An overview will then be given of binding agents that have recently been used in AMC, along with their applications. These applications will include bioaffinity chromatography, immunoaffinity chromatography, immobilized metal-ion affinity chromatography, and dye-ligand or biomimetic affinity chromatography. The use of AMC in chiral separations and biointeraction studies will also be discussed.

Indexed as

Chromatography, AffinityAdsorptionLigandsLigandsAffinity monolith chromatographyBioaffinity chromatographyChiral separationsImmobilized metal-ion affinity chromatographyImmunoaffinity chromatography

Identifiers

PMID34293192
PMCPMC9536602

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.