Evidence map›Paper›PMID 36755610›Full record

ArticleHeliyon2023

Damp-heat constitution influences gut microbiota and urine metabolism of Chinese infants.

Haihong Zhao, Yuhan Zong, Wenle Li, Yaqi Wang, Weibo Zhao, Xianghe Meng, Fan Yang, Jingwei Kong, Xiaoshan Zhao, Ji Wang

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

10 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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  4. Frontiers in pharmacology · 2025
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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

10 authors at 3 institutions in 1 country.

Haihong ZhaoNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Yuhan ZongNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Wenle LiNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Yaqi WangCollege of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, Zhejiang, China.
Weibo ZhaoNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Xianghe MengNeurology Department, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
Fan YangNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Jingwei KongNutrition and Metabolism Research Division, Innovation Center, Heilongjiang Feihe Dairy Co., Ltd., Beijing, 100015, China.
Xiaoshan ZhaoNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Ji WangNational Institute of Traditional Chinese Medicine Constitution and Preventive Treatment of Disease, Beijing University of Chinese Medicine, Beijing, 100029, China.
Beijing University of Chinese Medicine · CNCapital Medical University · CNZhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As an increasingly popular complementary and alternative approach for early detection and treatment of disease, traditional Chinese medicine constitution (TCMC) divides human beings into those with balanced constitution (BC) and unbalanced constitution, where damp-heat constitution (DHC) is one of the most unbalanced constitutions. Many studies have been carried out on the microscopic mechanism of constitution classification; however, most of these studies were conducted in adults and rarely in infants. Many diseases are closely related to intestinal microbiota, and metabolites produced by the interaction between microbiota and the body may impact constitution classification. Herein, we investigated the overall constitution distribution in Chinese infants, and analyzed the profiles of gut microbiota and urine metabolites of DHC to further promote the understanding of infants constitution classification. Methods: General information was collected and TCMC was evaluated by Constitutional Medicine Questionnaires. 1315 questionnaires were received in a cross-sectional study to investigate the constitution composition in Chinese infants. A total of 56 infants, including 30 DHC and 26 BC, were randomly selected to analyze gut microbiota by 16S rRNA sequencing and urine metabolites by UPLC-Q-TOF/MS method. Results: BC was the most common constitution in Chinese infants, DHC was the second common constitution. The gut microbiota and urine metabolites in the DHC group showed different composition compared to the BC group. Four differential genera and twenty differential metabolites were identified. In addition, the combined marker composed of four metabolites may have the high potential to discriminate DHC from BC with an AUC of 0.765. Conclusions: The study revealed the systematic differences in the gut microbiota and urine metabolites between infants with DHC and BC. Moreover, the differential microbiota and metabolites may offer objective evidences for constitution classification.

Indexed as

BiomarkerDamp-heat constitutionGut microbiotaInfantMetabolismTraditional Chinese medicine

Identifiers

PMID36755610
PMCPMC9900481
OpenAlexW4312112709

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.