Evidence map›Paper›PMID 42105139›Full record

ArticleMolecular diversity2026

Rapid evaluation of the comprehensive quality of paeonol/cyclodextrin supramolecular complexes using CASSA based on near-infrared spectroscopy combined with artificial intelligence.

Bo-Yao Zhang, Xin-Li Li, Cheng Qian, Si-Min Xue, Zhi-Tong Zhang, Si-Yi Liu, Guo Zhang, Guo-Ping Peng, Ning Ding, Yun-Feng Zheng

Abstract read
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In one paragraph

Article in Molecular diversity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Bo-Yao Zhang *National Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Xin-Li Li *National Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Cheng QianNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Si-Min XueNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Zhi-Tong ZhangNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Si-Yi LiuNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Guo ZhangNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Guo-Ping PengNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China.
Ning DingNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China. dingning@njucm.edu.cn.
Yun-Feng ZhengNational Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine, Nanjing, 211100, China. zyunfeng@njucm.edu.cn.

Funding

National Natural Science Foundation of China 81473390
6 · The paper itself

Abstract

Supramolecular complexes of volatile components and cyclodextrin are widely used to improve the stability of volatile compounds. However, the quality assessment of these complexes remains challenging. In this study, paeonol/cyclodextrin complexes were prepared and characterized using FT-NIR spectroscopy. Using the NIR spectra of samples with different paeonol inclusion states (fully encapsulated, partially encapsulated, and unencapsulated), an SVM model was developed to classify the inclusion state, and a PLSR model was used to quantify the paeonol content. The SVM model achieved 100% accuracy, and the PLSR model had an R

Indexed as

AcetophenonesArtificial IntelligenceCyclodextrinsSpectroscopy, Near-InfraredSupport Vector MachineAcetophenonesCyclodextrinspaeonolArtificial intelligence algorithmsCASSACyclodextrinFT-NIRSupramolecular complexes

Identifiers

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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.