Evidence map›Paper›PMID 26557869›Full record

ReviewEvidence-based complementary and alternative medicine : eCAM2015

Recent Advance in Applications of Proteomics Technologies on Traditional Chinese Medicine Research.

Qing Ji, Fangshi Zhu, Xuan Liu, Qi Li, Shi-Bing Su

Open access · hybridAbstract readReview
In one paragraph

Review in Evidence-based complementary and alternative medicine : eCAM, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

21 citing papers in PubMed, 52 citations in OpenAlex.

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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 2 institutions in 1 country.

Qing JiResearch Center for Traditional Chinese Medicine Complexity System, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China ; Department of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Fangshi ZhuJiangsu Provincial Academy of Traditional Chinese Medicine, Nanjing 210028, China.
Xuan LiuDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Qi LiDepartment of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Shi-Bing SuResearch Center for Traditional Chinese Medicine Complexity System, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Shanghai University of Traditional Chinese Medicine · CNJiangsu Provincial Academy of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteomics technology, a major component of system biology, has gained comprehensive attention in the area of medical diagnosis, drug development, and mechanism research. On the holistic and systemic theory, proteomics has a convergence with traditional Chinese medicine (TCM). In this review, we discussed the applications of proteomic technologies in diseases-TCM syndrome combination researches. We also introduced the proteomic studies on the in vivo and in vitro effects and underlying mechanisms of TCM treatments using Chinese herbal medicine (CHM), Chinese herbal formula (CHF), and acupuncture. Furthermore, the combined studies of proteomics with other "-omics" technologies in TCM were also discussed. In summary, this report presents an overview of the recent advances in the application of proteomic technologies in TCM studies and sheds a light on the future global and further research on TCM.

Identifiers

PMID26557869
PMCPMC4629032
OpenAlexW2115547357

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.