Evidence mapPaperPMID 42558368Full record

ReviewFrontiers in endocrinology2026

Molecular mechanisms and translational prospects in osteoporosis.

Ping Xie, Jie Cai, Zhengjie Yu, Junjie Zhou, Jianping Wang

Abstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ping XieState Key Laboratory of New Targets Discovery and Drug Development for Major Diseases, Ganzhou, China.
Jie CaiState Key Laboratory of New Targets Discovery and Drug Development for Major Diseases, Ganzhou, China.
Zhengjie YuState Key Laboratory of New Targets Discovery and Drug Development for Major Diseases, Ganzhou, China.
Junjie ZhouState Key Laboratory of New Targets Discovery and Drug Development for Major Diseases, Ganzhou, China.
Jianping WangState Key Laboratory of New Targets Discovery and Drug Development for Major Diseases, Ganzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoporosis is the most prevalent chronic metabolic bone disease, affecting approximately 200 million individuals worldwide. With the rapid acceleration of global aging, osteoporosis has emerged as a major global health challenge, significantly increasing the occurrence rate of fractures and the associated medical burden. In recent years, considerable progress has been made in understanding the molecular mechanisms underlying osteoporosis, including bone remodeling, osteoblast-osteoclast communication, and signaling pathways such as RANKL/RANK/OPG and Wnt/β-catenin. These mechanistic studies have been translated into clinical applications. Emerging therapies, including targeted biologics and precision medicine approaches, offer novel strategies and methods for future prevention and treatment. This review summarizes recent advances in research, with a particular focus on therapeutic agents and mechanistic studies of osteoporosis. Following the mainline of "mechanism-target-translation," this review proposes new research perspectives and approaches, and provides an outlook on future research directions for the disease, aiming to promote the development of more effective diagnostic and therapeutic strategies.

Indexed as

Bone RemodelingOsteoporosisTranslational Research, BiomedicalAnimalsHumansOsteoblastsOsteoclastsSignal Transductionbone remodelingmolecular mechanismsosteoporosisresearch progresstherapeutic targets

Identifiers

PMID42558368
PMCPMC13437411

What Socratic holds

Textmetadata
LicenceCC BY
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.