Evidence map›Paper›PMID 38405502›Full record

ArticleACS omega2024

Preparation, Characterization, and Bioactivity Evaluation of Lambda-Cyhalothrin Microcapsules for Slow-Controlled Release System.

Liying Wang, Juan Liu, Chong Gao, Xinxin Yan, Junzhi Liu

Abstract read
In one paragraph

Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Liying WangInstitute of Functional Molecules, Shenyang University of Chemical Technology, Shenyang 110142, China.ORCID https://orcid.org/0000-0003-3422-7409
Juan LiuInstitute of Functional Molecules, Shenyang University of Chemical Technology, Shenyang 110142, China.
Chong GaoInstitute of Functional Molecules, Shenyang University of Chemical Technology, Shenyang 110142, China.
Xinxin YanInstitute of Functional Molecules, Shenyang University of Chemical Technology, Shenyang 110142, China.
Junzhi LiuInstitute of Functional Molecules, Shenyang University of Chemical Technology, Shenyang 110142, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The utilization of interfacial polymerization in the preparation of microcapsules with a slow-controlled release has been shown to effectively improve pesticide efficacy and reduce environmental pollution. In this study, polyurea microcapsules loaded with lambda-cyhalothrin were prepared by an interfacial polymerization method using modified isocyanate (MDI) as the wall material and GT-34 as the initiator. The microcapsules were fully characterized by optical microscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis, etc., and release behaviors were investigated. The results indicated that the microcapsules had a smooth surface and uniform distribution, the average particle size of the microcapsules was 1.97 μm, and the encapsulation efficiency of lambda-cyhalothrin microcapsules could reach 91.48%. Compared with other commercial formulations, the microcapsules exhibited an excellent sustained release property (>7 days) in a 50% acetonitrile aqueous solution (v/v). Subsequently, in vitro release studies showed that the lambda-cyhalothrin microcapsules could consistently control the release of the core materials at different pH, temperature, and MDI addition amount conditions. The release of lambda-cyhalothrin microcapsules was in accordance with the first-order model release, which was mainly by the Fickian diffusion mechanism. Furthermore, the biological activity on

Identifiers

PMID38405502
PMCPMC10882664

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Registered trials

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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.