Evidence map›Paper›PMID 34684890›Full record

ReviewMolecules (Basel, Switzerland)2021

Research Progress of NMR in Natural Product Quantification.

Zhi-Fan Wang, Yu-Lin You, Fei-Fei Li, Wen-Ru Kong, Shu-Qi Wang

Open access · goldAbstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 54 citations in OpenAlex.

  1. Differentiation of Plant and Animal-Derived Cholesterol Using irm-Magnetic resonance in chemistry : MRC · 2026
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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 1 institution in 1 country.

Zhi-Fan WangSchool of Pharmacy Sciences, Shandong University, 44# West Wenhua Road, Jinan 250012, China.
Yu-Lin YouSchool of Pharmacy Sciences, Shandong University, 44# West Wenhua Road, Jinan 250012, China.ORCID 0000-0002-2523-2292
Fei-Fei LiSchool of Pharmacy Sciences, Shandong University, 44# West Wenhua Road, Jinan 250012, China.
Wen-Ru KongSchool of Pharmacy Sciences, Shandong University, 44# West Wenhua Road, Jinan 250012, China.
Shu-Qi WangSchool of Pharmacy Sciences, Shandong University, 44# West Wenhua Road, Jinan 250012, China.ORCID 0000-0002-5764-8161
Shandong University · CN

Funding

the Key Research and Development Project of Shandong Province 2017GSF218049the Young Scholars Program of Shandong University 2018WLJH93
6 · The paper itself

Abstract

In the fields of medicine and health, traditional high-performance liquid chromatography or UV-visible spectrophotometry is generally used for substance quantification. However, over time, nuclear magnetic resonance spectroscopy (NMR) has gradually become more mature. Nuclear magnetic resonance spectroscopy has certain advantages in the quantitative analysis of substances, such as being nondestructive, having a high flux and short analysis time. Nuclear magnetic resonance spectroscopy has been included in the pharmacopoeiae of various countries. In this paper, the principle of nuclear magnetic resonance spectroscopy and the recent progress in the quantitative study of natural products by NMR are reviewed, and its application in the quantitative study of natural products is proposed. At the same time, the problems of using NMR alone to quantify natural products are summarized and corresponding suggestions are put forward.

Indexed as

Biological ProductsChromatography, High Pressure LiquidEvaluation Studies as TopicMagnetic Resonance SpectroscopyBiological Productsnatural productsquantitative analysisquantitative nuclear magnetic resonance (qNMR)

Identifiers

PMID34684890
PMCPMC8541192
OpenAlexW3205325152

What OpenQuestion holds

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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.