Evidence map›Paper›PMID 29588653›Full record

ReviewChinese medicine2018

Approaches in studying the pharmacology of Chinese Medicine formulas: bottom-up, top-down-and meeting in the middle.

Tao Huang, Linda L D Zhong, Chen-Yuan Lin, Ling Zhao, Zi-Wan Ning, Dong-Dong Hu, Man Zhang, Ke Tian, Chung-Wah Cheng, Zhao-Xiang Bian and 1 more

Abstract readReview
In one paragraph

Review in Chinese medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Integration strategy of network pharmacology in Traditional Chinese Medicine: a narrative review.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2022
    Review
  3. Review
  4. Article
  5. 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

11 authors.

Tao Huang1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Linda L D Zhong1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Chen-Yuan Lin1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Ling Zhao1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Zi-Wan Ning1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Dong-Dong Hu1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Man Zhang1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Ke Tian1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Chung-Wah Cheng2Hong Kong Chinese Medicine Clinical Study Centre, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
Zhao-Xiang Bian1Institute of Brain and Gut Research, School of Chinese Medicine, Hong Kong Baptist University, Room 307, Jockey Club School of Chinese Medicine, 7 Baptist University Road, Kowloon, Hong Kong, Hong Kong SAR China.
for MZRW Research Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigating the pharmacology is key to the modernization of Chinese Medicine (CM) formulas. However, identifying which are the active compound(s) of CM formulas, which biological entities they target, and through which signaling pathway(s) they act to modify disease symptoms, are still difficult tasks for researchers, even when equipped with an arsenal of advanced modern technologies. Multiple approaches, including network pharmacology, pharmaco-genomics, -proteomics, and -metabolomics, have been developed to study the pharmacology of CM formulas. They fall into two general categories in terms of how they tackle a problem: bottom-up and top-down. In this article, we compared these two different approaches in several dimensions by using the case of MaZiRenWan (MZRW, also known as Hemp Seed Pill), a CM herbal formula for functional constipation. Multiple hypotheses are easy to be proposed in the bottom-up approach (e.g. network pharmacology); but these hypotheses are usually false positives and hard to be tested. In contrast, it is hard to suggest hypotheses in the top-down approach (e.g. pharmacometabolomics); however, once a hypothesis is proposed, it is much easier to be tested. Merging of these two approaches could results in a powerful approach, which could be the new paradigm for the pharmacological study of CM formulas.

Indexed as

Bottom-upChinese medicine formulaFocused network pharmacologyPharmacometabolomicsTop-down

Identifiers

PMID29588653
PMCPMC5863461

What OpenQuestion holds

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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.