Evidence map›Paper›PMID 38099525›Full record

ArticleCombinatorial chemistry & high throughput screening2024

Proteomic Analysis Based on TMT Regarding the Therapeutic Action of

Hui Su, Binghan Yan, Ruochong Wang, Zhichao Li, Zhanwang Xu, Haipeng Xue, Guoqing Tan

Open access · hybridAbstract read
In one paragraph

Article in Combinatorial chemistry & high throughput screening, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

7 authors at 3 institutions in 1 country.

Hui SuShandong University of Traditional Chinese Medicine, Jinan, Shandong, China.ORCID 0000-0003-4458-0193
Binghan YanShandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Ruochong WangBeijing University of Traditional Chinese Medicine, Beijing, China.
Zhichao LiShandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Zhanwang XuShandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Haipeng XueAffiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Guoqing TanShandong University of Traditional Chinese Medicine, Jinan, Shandong, China.ORCID 0000-0001-7793-3835
Shandong University of Traditional Chinese Medicine · CNAffiliated Hospital of Shandong University of Traditional Chinese Medicine · CNBeijing Hospital of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary osteoporosis has increasingly become one of the risk factors affecting human health, and the clinical effect and action mechanism of traditional Chinese medicine in the treatment of primary osteoporosis have been widely studied. Previous studies have confirmed that in traditional Chinese medicine (TCM), Drynaria rhizome has a role in improving bone density. In this study, a tandem mass tag (TMT)-based proteomic analysis was conducted to derive potential targets for

methodsThe model group (OVX) and experimental group (OVXDF) for menopausal osteoporosis were established using the universally acknowledged ovariectomy method, and the OVXDF group was given 0.48g/kg Rhizoma Drynariae solution by gavage for 12 weeks. After 12 weeks, femurs of rats selected for this study were examined with a bone mineral density (BMD) test, Micro-CT, ELISABiochemical testing, hematoxylin and eosin (HE) staining, and immunohistochemistry. A certain portion of the bone tissue was studied with a TMT-based proteomic analysis and functional and pathway enrichment analysis. Finally, key target genes were selected for Western blotting for validation.

resultsThe comparison of the OVXDF and OVX groups indicated that Drynaria rhizome could improve bone density. In the TMT-based proteomic analysis, the comparison of these two groups revealed a total of 126 differentially expressed proteins (DEPs), of which 62 were upregulated and 64 were downregulated. Further, by comparing the differential genes between the OVXDF and OVX groups and between the OVX and SHAM groups, we concluded that the 27 differential genes were significantly changed in the rats selected for the osteoporosis model after Drynaria rhizome intragastric administration. The gene ontology (GO) enrichment analysis of DEPs showed that molecular function was mainly involved in biological processes, such as glucose metabolism, carbohydrate metabolism, immune responses, and aging. A Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEPs revealed that multiple differential genes were enriched in the estrogen and peroxisome proliferator-activated receptor (PPAR) signaling pathways. Relationships with nitrogen metabolism, glycerophospholipid metabolism, secretion systems, and tumor diseases were also observed. Western blotting was consistent with the analysis.

conclusionsWe used TMT-based proteomics to analyze the positive effects of TCM Drynaria rhizome, which can regulate related proteins through the unique roles of multiple mechanisms, targets, and pathways. This treatment approach can regulate oxidative stress, improve lipid metabolism, reduce the inflammatory response mechanism, and improve bone density. These benefits highlight the unique advantages of TCM in the treatment of primary osteoporosis.

Indexed as

Disease Models, AnimalDrugs, Chinese HerbalOsteoporosisPolypodiaceaeProteomicsRats, Sprague-DawleyRhizomeAnimalsBone DensityFemaleMedicine, Chinese TraditionalOvariectomyRatsTandem Mass SpectrometryDrugs, Chinese Herbalosteoporosisproteomic analysis.ratsRhizoma drynariaetherapeutic actionTMT

Identifiers

PMID38099525
PMCPMC11348476
OpenAlexW4389802489

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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.