Evidence map›Paper›PMID 40133588›Full record

ArticleScientific reports2025

Exploring the classification and treatment of osteoporosis from the perspectives of natural medicines, molecular targets, and symptom clusters.

Yili Zhang, Xiangyun Guo, Kai Sun, Liang Wang, Siyuan Huang, Yiwen Gan, Jinran Qin, Qingqing Liu, Yan Li, Zikai Jin and 2 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

12 authors.

Yili Zhang *School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
Xiangyun Guo *School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
Kai Sun *Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China.
Liang Wang *School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
Siyuan HuangDepartment of Biochemistry, University of Oxford, South Parks Rd, Oxford, OX1 3QU, UK.
Yiwen GanSchool of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
Jinran QinSchool of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
Qingqing LiuSchool of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
Yan LiWangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China.
Zikai JinWangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China.
Liguo ZhuWangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China.
Xu WeiWangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, 100102, China. weixu.007@163.com.

Funding

National Natural Science Foundation of China 8220514
6 · The paper itself

Abstract

Osteoporosis (OP) is a metabolic bone disease characterized by reduced bone density and fragility, impairing quality of life. Traditional treatments often overlook symptoms like back and joint pain, increasing burden. This study aims to map relationships between natural medicines, targets, and symptom clusters, demonstrating their effectiveness in personalized OP treatment to enhance clinical strategies and self-assessment. We used compounds and targets, applying Summary data-based Mendelian Randomisation (SMR) analysis for biological process and molecular function enrichment. Additionally, we employed Phenome-Wide Association Studies (PheWAS) to select two natural drugs-Rhizoma Drynariae (RD) and Lycii Fructus (LF)-for case analysis. The study found that RD primarily improves symptoms such as indigestion, constipation, fatigue, polyuria, and depression, while LF significantly ameliorates symptoms related to the nervous and muscular systems, such as hoarseness, dizziness, vertigo, and fever symptoms. This analysis successfully differentiated two groups of symptoms and precisely constructed a logical chain among "natural Medicines-molecular tArGets-Illness-symptom Clusters" (MAGIC chain) achieving a refined classification of OP. The results of this study support the effectiveness of implementing personalized medical strategies in the treatment of OP, providing a scientific basis for the clinical application of natural medicines and patient self-management.

Indexed as

Biological ProductsDrugs, Chinese HerbalOsteoporosisHumansPrecision MedicineBiological ProductsDrugs, Chinese HerbalIllnessMolecular targetsNatural medicinesOsteoporosisSymptom clusters

Identifiers

PMID40133588
PMCPMC11937308

What Socratic 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 Socratic graph.