Evidence map›Paper›PMID 41720464›Full record

ArticleACS biomaterials science & engineering2026

Biomaterial Screening Identifies Enhanced Osteogenic and Angiogenic Potential of Mn-Doped Calcium Phosphate Coatings.

Maria Eischen-Loges, Zeineb Tahmasebi Birgani, Yousra Alaoui Selsouli, Virginie Joris, Lars Eijssen, Nadia Roumans, Hoon Suk Rho, Martijn van Griensven, Vanessa L S LaPointe, Pamela Habibović

Abstract read
In one paragraph

Article in ACS biomaterials science & engineering, 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.

Maria Eischen-LogesDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.ORCID 0000-0002-2785-4263
Zeineb Tahmasebi BirganiDepartment of Complex Tissue Regeneration, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.ORCID 0000-0003-3899-922X
Yousra Alaoui SelsouliDepartment of Complex Tissue Regeneration, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Virginie JorisDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Lars EijssenDepartment of Translational Genomics, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands.
Nadia RoumansDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Hoon Suk RhoDepartment of Complex Tissue Regeneration, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Martijn van GriensvenDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.ORCID 0000-0001-5104-9881
Vanessa L S LaPointeDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.ORCID 0000-0002-0887-7443
Pamela HabibovićDepartment of Instructive Biomaterial Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands.ORCID 0000-0001-8249-5155

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Synthetic biomaterials such as calcium phosphate (CaP) ceramics are promising substitutes for autologous bone grafts, as they are easy to produce, cost-effective and closely resemble the mineral component of natural bone. However, their performance in bone repair and regeneration is often inferior to their biological counterparts, which highlights the need for further optimization and improvement. Incorporating inorganic additives has previously been shown as a promising approach to improve the performance of synthetic biomaterials, without compromising their synthetic character. Here, a library of carbonated apatite coatings with inorganic additives such as copper, magnesium, manganese, strontium, and zinc was established. Human mesenchymal stem cells (hMSCs) were seeded on these coatings. A CaP coating with high (1000 μM) manganese incorporation (CaMnP1000) stood out as material inducing a superior osteogenic response in hMSCs, based on a protein multiplex assay containing markers related to osteogenesis, angiogenesis and inflammation. Specifically, the levels of osteopontin, bone morphogenetic protein-2, matrix metalloproteinase-13 and tenascin-C were increased relative to the control group, as well as mRNA transcripts related to early and late osteogenic gene expression (

Indexed as

AngiogenesisCalcium PhosphatesCoated Materials, BiocompatibleManganeseNeovascularization, PhysiologicOsteogenesisCell DifferentiationCells, CulturedHumansMesenchymal Stem Cellscalcium phosphateCalcium PhosphatesCoated Materials, BiocompatibleManganeseangiogenic potentialCalcium phosphate biomaterialshuman mesenchymal stem cellsinorganic additivesmanganeseosteogenic differentiation

Identifiers

PMID41720464
PMCPMC12976998

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Registered trials

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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.