Evidence map›Paper›PMID 35154341›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

An Objective Diagnosis Model with Integrated Metabolic and Immunity Parameters for Phlegm-Dampness Constitution.

Yanchun Huang, Shanshan Guo, Jun Yang, Yangfan Tang, Xinghua Zhu, Sichong Ren

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Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.6field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Yanchun HuangDepartment of Laboratory Medicine, The First People's Hospital of Longquanyi District, Chengdu, West China Longquan Hospital Sichuan University, Chengdu 610100, China.
Shanshan GuoCenter for Translational Medicine, Sichuan Academy of Traditional Chinese Medicine, Translational Chinese Medicine Key Laboratory of Sichuan Province, Chengdu 610041, China.
Jun YangDepartment of Laboratory Medicine, The First People's Hospital of Longquanyi District, Chengdu, West China Longquan Hospital Sichuan University, Chengdu 610100, China.
Yangfan TangCenter for Translational Medicine, Sichuan Academy of Traditional Chinese Medicine, Translational Chinese Medicine Key Laboratory of Sichuan Province, Chengdu 610041, China.
Xinghua ZhuDepartment of Laboratory Medicine, The First People's Hospital of Longquanyi District, Chengdu, West China Longquan Hospital Sichuan University, Chengdu 610100, China.
Sichong RenCenter for Translational Medicine, Sichuan Academy of Traditional Chinese Medicine, Translational Chinese Medicine Key Laboratory of Sichuan Province, Chengdu 610041, China.ORCID https://orcid.org/0000-0001-7311-4314
Sichuan University · CNSichuan Academy of Traditional Chinese Medicine · CNFirst Affiliated Hospital of Chengdu Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccording to Chinese constitutional theory, people can be divided into nine constitutions, which represent distinctive vulnerability to different diseases such as metabolic syndrome, atherosclerosis, and immunity-related disease, and so forth in modern medicine, phlegm-dampness constitution (PDC) is one of the nine constitutions, which is susceptible to metabolic syndrome (MS) and atherosclerosis that associate with lipid metabolism and immunity dysregulation closely.

objectivesIn this study, we aimed to investigate the metabolic and immunity profiles of phlegm-damp constitution (PDC), including metabolites, lymphocytes distribution, and inflammatory cytokines.

methodsA total of 74 patients with PDC and 66 individuals with gentle constitution (GC) were enrolled in this study. We utilized biochemical methods to detect metabolic parameters, flow cytometry to survey T/B/NK/NKT lymphocyte subgroups distribution, and ELISA to assay inflammatory cytokines.

resultsThe subjects with PDC had higher GLU, AI TC, TG, and LDL-C and lower HDL-C levels. The immunity profile indicated that PDC subjects had higher percentage of WBCs, neutrophils, lymphocytes, B cells, and natural killer T cells compared with subjects with GC (

conclusionPhlegm-damp constitution was prone to hyperglycemia and hyperlipidemia syndrome, promoting the occurrence and progression of metabolic-related diseases. Interestingly, proinflammatory cells and cytokines were activated in the PDC group as well. Our findings could offer a profile of early screening indicators to identify high-risk patients of metabolic- and immunity-related diseases from Chinese constitution.

Identifiers

PMID35154341
PMCPMC8837425
OpenAlexW4210622631

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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.