Evidence map›Paper›PMID 41805841›Full record

ReviewOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2026

Molecular-level understanding of the aging bone and regeneration mechanisms using computational methods.

Filip Stojceski, Harry Zaverdas, Andrea Danani, Alessia Mengoni, Mario Ledda, Giuseppe Falvo D'Urso Labate, Athanasios Kalogeras, Konstantinos Theofilatos, Seferina Mavroudi, Gianvito Grasso

Abstract readReview
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In one paragraph

Review in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 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

10 authors.

Filip StojceskiDalle Molle Institute for Artificial Intelligence, USI-SUPSI, Polo Universitario Lugano - Campus Est, Via La Santa, Lugano-Viganello, 6962, Switzerland.
Harry ZaverdasInSyBio PC, Patras, 265 04, Greece.
Andrea DananiDalle Molle Institute for Artificial Intelligence, USI-SUPSI, Polo Universitario Lugano - Campus Est, Via La Santa, Lugano-Viganello, 6962, Switzerland.
Alessia MengoniInstitute of Translational Pharmacology, National Research Council, Via Fosso del Cavaliere 100, Rome, 00133, Italy.
Mario LeddaInstitute of Translational Pharmacology, National Research Council, Via Fosso del Cavaliere 100, Rome, 00133, Italy.
Giuseppe Falvo D'Urso LabateCellex S.R.L, Piazzale Delle Belle Arti, 2, Rome, Italy.
Athanasios KalogerasIndustrial Systems Institute, Athena Research Center, Patras, 265 04, Greece.
Konstantinos TheofilatosInSyBio PC, Patras, 265 04, Greece.
Seferina MavroudiInSyBio PC, Patras, 265 04, Greece.
Gianvito GrassoDalle Molle Institute for Artificial Intelligence, USI-SUPSI, Polo Universitario Lugano - Campus Est, Via La Santa, Lugano-Viganello, 6962, Switzerland. gianvito.grasso@supsi.ch.ORCID http://orcid.org/0000-0002-7761-222X

Funding

HORIZON EUROPE Marie Sklodowska-Curie Actions 101131255Staatssekretariat für Bildung, Forschung und Innovation 23.0086
6 · The paper itself

Abstract

Bone degeneration diseases, such as osteoporosis, are skeletal disorders characterized by diminished bone mass and increased susceptibility to fractures and represent a growing global health challenge, particularly in aging populations. The development of effective therapeutic strategies necessitates a deep understanding of the complex biological processes underlying bone remodeling, regeneration, and homeostasis. To address these challenges, computational approaches have played a crucial role in advancing our understanding of bone biology and improving therapeutic strategies. This review explores these contributions across three main areas: (1) elucidating the structural organization and interactions within the bone matrix, particularly between collagen and hydroxyapatite; (2) investigating the regulatory roles of non-collagenous proteins, such as bone morphogenetic proteins, osteocalcin, osteopontin, and fibronectin, in bone mineralization; and (3) facilitating drug discovery and development for bone regeneration by targeting key pathways and molecules, including sclerostin, RANKL, and estrogen receptors. Molecular dynamics and docking have helped identify and optimize natural and synthetic therapeutic agents for these critical pathways. Additionally, we apply bioinformatics tools to analyze bone regeneration and degeneration pathways, emphasizing the need for more accurate computational techniques to reconstruct their interactome. As these techniques continue to evolve, integrating advancements in machine learning, molecular dynamics, and multi-scale modeling, their potential to bridge the gap between experimental research and clinical application is becoming increasingly apparent. A multidisciplinary approach that combines computational predictions with experimental validation and clinical data is poised to drive the development of personalized and effective osteoporosis therapies, ultimately reducing the global burden of this debilitating disease.

Indexed as

Aging boneBone matrixComputational methodsMolecular DynamicsOsteoporosis treatmentsRegeneration mechanisms

Identifiers

What OpenQuestion holds

Textmetadata
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.