Evidence map›Paper›PMID 35791598›Full record

ArticleSe pu = Chinese journal of chromatography2022

[Application progress of covalent organic framework materials in extraction of toxic and harmful substances].

Wenmin Zhang, Guancheng Liu, Wende Ma, Min Fang, Lan Zhang

Open access · greenAbstract read
In one paragraph

Article in Se pu = Chinese journal of chromatography, 2022. 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
0.5field-weighted citation impact, top 47% 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, 7 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Wenmin ZhangMinjiang Teachers College, Fuzhou 350108, China.
Guancheng LiuMinistry of Education Key Laboratory for Analytical Science of Food Safety and Biology, Fuzhou University, Fuzhou 350116, China.
Wende MaMinistry of Education Key Laboratory for Analytical Science of Food Safety and Biology, Fuzhou University, Fuzhou 350116, China.
Min FangMinjiang Teachers College, Fuzhou 350108, China.
Lan ZhangMinjiang Teachers College, Fuzhou 350108, China.
Minjiang University · CNFuzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxic and hazardous substances constitute a category of compounds that are potentially hazardous to humans, other organisms, and the environment. These substances include pesticides (benzoylureas, pyrethroids, neonicotinoids), persistent organic pollutants (polycyclic aromatic hydrocarbons, polychlorinated biphenyls, perfluorinated compounds), plasticizers (phthalate esters, phenolic endocrine disruptors), medicines (sulfonamides, non-steroid anti-inflammatory drugs, tetracyclines, fluoroquinone antibiotics), heterocyclic aromatic amines, algal toxins, and radioactive substances. Discharge of these toxic and harmful substances, as well as their possible persistence and bioaccumulation, pose a major risk to human health, often to the extent of being life-threatening. Therefore, it is important to analyze and detect toxic and hazardous substances in the environment, drinking water, food, and daily commodities. Sample pretreatment is an imperative step in most of the currently used analytical methods, especially in the analysis of trace toxic and harmful substances in complex samples. An efficient and fast sample pretreatment technology not only helps improve the sensitivity, selectivity, reproducibility, and accuracy of analytical methods, but also avoids contamination of the analytical instruments and even damages the performance and working life of instruments. Sample pretreatment techniques widely used in the extraction of toxic and hazardous substances include solid-phase extraction (SPE), solid-phase microextraction (SPME), and dispersed solid-phase extraction (DSPE). The adsorbent material plays a key role in these pretreatment techniques, thereby determining their selectivity and efficiency. In recent years, covalent organic frameworks (COFs) have attracted increasing attention in sample pretreatment. COFs represent an exciting new class of porous crystalline materials constructed via the strong covalent bonding of organic building units through a reversible condensation reaction. COFs present four advantages: (1) precise control over structure type and pore size by consideration of the target molecular structure based on the connectivity and shape of the building units; (2) post-synthetic modification for chemical optimization of the pore interior toward optimized interaction with the target; (3) straightforward scalable synthesis; (4) feasible formation of composites with magnetic nanoparticles, carbon nanotubes, graphene, silica, etc., which is beneficial to enhance the performance of COFs and meet the requirement of diverse pretreatment technologies. Because of the well-defined crystalline porous structures and tailored functionalities, COFs have excellent potential for use in target extraction. However, some issues need to be addressed for the application of COFs in the extraction of toxic and hazardous substances. (1) For the sample matrix, most of the reported COFs are highly hydrophobic, which limits their dispersibility in water-based samples, leading to poor extraction performance. COFs with good dispersibility in water-based samples are urgently required. (2) Besides, COFs rely on hydrophobic interaction, size repulsion,

Indexed as

Metal-Organic FrameworksNanotubes, CarbonHazardous SubstancesHumansReproducibility of ResultsWaterHazardous SubstancesMetal-Organic FrameworksNanotubes, CarbonWatercovalent organic frameworksmedicinespersistent organic pollutantspesticidesplasticizerreview

Identifiers

PMID35791598
PMCPMC9404040
OpenAlexW4284686761

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.