Evidence map›Paper›PMID 38339180›Full record

ArticleInternational journal of molecular sciences2024

Comprehensive Similarity Algorithm and Molecular Dynamics Simulation-Assisted Terahertz Spectroscopy for Intelligent Matching Identification of Quorum Signal Molecules (N-Acyl-Homoserine Lactones).

Lintong Zhang, Xiangzeng Kong, Fangfang Qu, Linjie Chen, Jinglin Li, Yilun Jiang, Chuxin Wang, Wenqing Zhang, Qiuhua Yang, Dapeng Ye

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2024. 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
0.9field-weighted citation impact, top 30% 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, 5 citations in OpenAlex.

  1. 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

10 authors at 2 institutions in 1 country.

Lintong ZhangCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xiangzeng KongCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Fangfang QuCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Linjie ChenCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Jinglin LiFujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing, Fuzhou University, Fuzhou 350108, China.
Yilun JiangCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Chuxin WangCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Wenqing ZhangCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Qiuhua YangFisheries Research Institute of Fujian, Fuzhou 350025, China.
Dapeng YeCenter for Artificial Intelligence in Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Fujian Agriculture and Forestry University · CNFuzhou University · CN

Funding

Educational Scientific Research Project for Middle-aged and Young teachers of Fujian Provincial Department of Education (science and technology category), China JAT200020Educational Scientific Research Project for Middle-aged and Young teachers of Fujian Provincial Department of Education (science and technology category), China JAT220066Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing, Fuzhou University, China FPKLTFDIS202302Natural Science Foundation of Fujian Province, China 2021J05116Natural Science Foundation of Fujian Province, China 2023J01079
6 · The paper itself

Abstract

To investigate the mechanism of aquatic pathogens in quorum sensing (QS) and decode the signal transmission of aquatic Gram-negative pathogens, this paper proposes a novel method for the intelligent matching identification of eight quorum signaling molecules (N-acyl-homoserine lactones, AHLs) with similar molecular structures, using terahertz (THz) spectroscopy combined with molecular dynamics simulation and spectral similarity calculation. The THz fingerprint absorption spectral peaks of the eight AHLs were identified, attributed, and resolved using the density functional theory (DFT) for molecular dynamics simulation. To reduce the computational complexity of matching recognition, spectra with high peak matching values with the target were preliminarily selected, based on the peak position features of AHL samples. A comprehensive similarity calculation (CSC) method using a weighted improved Jaccard similarity algorithm (IJS) and discrete Fréchet distance algorithm (DFD) is proposed to calculate the similarity between the selected spectra and the targets, as well as to return the matching result with the highest accuracy. The results show that all AHL molecular types can be correctly identified, and the average quantization accuracy of CSC is 98.48%. This study provides a theoretical and data-supported foundation for the identification of AHLs, based on THz spectroscopy, and offers a new method for the high-throughput and automatic identification of AHLs.

Indexed as

Acyl-ButyrolactonesTerahertz SpectroscopyLactonesMolecular Dynamics SimulationMolecular StructureQuorum SensingAcyl-ButyrolactonesLactonesGram-negative pathogensmolecular dynamics simulationquorum signaling moleculesspectral similarity calculationterahertz spectroscopy

Identifiers

PMID38339180
PMCPMC10855763
OpenAlexW4391556785

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.