Evidence map›Paper›PMID 33488227›Full record

ArticleTurkish journal of chemistry2020

A novel molecular imprinting polymer for the selective adsorption of D-arabinitol from spiked urine.

Yuni Retnaningtyas, Ganden Supriyanto, Ni Nyoman Tri Puspaningsih, Roedi Irawan, Siswandono Siswodihardjo

Open access · bronzeAbstract read
In one paragraph

Article in Turkish journal of chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 57% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Yuni RetnaningtyasFaculty of Pharmacy, University of Jember, Jember Indonesia.ORCID https://orcid.org/0000-0003-0725-9560
Ganden SupriyantoDepartment of Chemistry, Faculty of Science and Technology, University of Airlangga, Surabaya Indonesia.ORCID https://orcid.org/0000-0002-8881-4871
Ni Nyoman Tri PuspaningsihDepartment of Chemistry, Faculty of Science and Technology, University of Airlangga, Surabaya Indonesia.ORCID https://orcid.org/0000-0001-5835-1653
Roedi IrawanDepartment of Pediatrics, Faculty of Medicine, University of Airlangga, Surabaya Indonesia.ORCID https://orcid.org/0000-0001-5999-4773
Siswandono SiswodihardjoDepartment of Pharmaceutical Chemistry, Facultyof Pharmacy, University of Airlangga, Surabaya Indonesia.ORCID https://orcid.org/0000-0002-9579-8929
Airlangga University · IDUniversitas Jember · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this research, molecular imprinting polymers (MIPs) for D-arabinitol were synthesized using a bulk polymerization method through a noncovalent approach. The MIPs were prepared by using D-arabinitol as a template, acrylamide as a functional monomer, ethylene glycol dimethacrylateas cross-linker, benzoyl peroxide as an initiator and dimethyl sulfoxideas a porogen. MIPS was synthesized in several formulas with a different molar ratio of template to functional monomers and cross-linker. Fourier-transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) were used to characterize the MIPs produced. A batch rebinding assay was used to test the binding efficiency of each formula. Batch rebinding test results revealed that MIPsF3 with a molar ratio of the template: monomer and crosslinker ratio respectively (1: 4: 25) had the highest binding capacity at 1.56 mgg

Indexed as

bulk polymerizationD-arabinitolMIPsnoncovalentselective adsorption

Identifiers

PMID33488227
PMCPMC7751933
OpenAlexW3123470127

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.