Evidence map›Paper›PMID 28250795›Full record

ReviewEvidence-based complementary and alternative medicine : eCAM2017

The Use of Omic Technologies Applied to Traditional Chinese Medicine Research.

Dalinda Isabel Sánchez-Vidaña, Rahim Rajwani, Man-Sau Wong

Registry-linked trialAbstract readReview
In one paragraph

Review in Evidence-based complementary and alternative medicine : eCAM, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04843865 (A Systemic Approach to Study the Traditional Chinese Medicine as an Adjuvant Treatment in Breast Cancer Patients), which is not on this map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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.

NCT04843865 narecruitingnot on this mapstarted 2022, after this paper: background citation

A Systemic Approach to Study the Traditional Chinese Medicine as an Adjuvant Treatment in Breast Cancer Patients

TypeinterventionalSponsorUniversiti Tunku Abdul RahmanRan2022 to 2024Enrolled30ConditionsBreast Cancer, Musculoskeletal PainArmsChinese Herbs
3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Comparative Proteomic Analysis ofMolecules (Basel, Switzerland) · 2020
    Article
  5. Article
  6. Article
  7. Article
  8. 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

3 authors.

Dalinda Isabel Sánchez-VidañaDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.ORCID 0000-0002-2150-0341
Rahim RajwaniDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
Man-Sau WongDepartment of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.ORCID 0000-0002-0729-8618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural products represent one of the most important reservoirs of structural and chemical diversity for the generation of leads in the drug development process. A growing number of researchers have shown interest in the development of drugs based on Chinese herbs. In this review, the use and potential of omic technologies as powerful tools in the modernization of traditional Chinese medicine are discussed. The analytical combination from each omic approach is crucial for understanding the working mechanisms of cells, tissues, organs, and organisms as well as the mechanisms of disease. Gradually, omic approaches have been introduced in every stage of the drug development process to generate high-quality Chinese medicine-based drugs. Finally, the future picture of the use of omic technologies is a promising tool and arena for further improvement in the modernization of traditional Chinese medicine.

Identifiers

PMID28250795
PMCPMC5307000

What OpenQuestion holds

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Registered trials

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.