Evidence map›Paper›PMID 41907475›Full record

ArticlePeerJ2026

Optimizing

Jie Li, Xinyi Sun, Changqing Yan, Weiwei Zhao, Dandan Liu, Yang Liu, Shuguo Zheng

Abstract read
In one paragraph

Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Jie Li *Department of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
Xinyi Sun *Department of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
Changqing YanDepartment of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
Weiwei ZhaoDepartment of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
Dandan LiuDepartment of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
Yang LiuDepartment of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.
Shuguo ZhengDepartment of Preventive Dentistry, Peking University School and Hospital of Stomatology, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Osteoclasts are multinucleated cells essential for bone resorption and remodeling. In healthy bone remodeling, osteoclast activity is tightly coupled with osteoblast activity, but this coupling is disrupted in a range of pathological conditions, such as Paget's disease of bone and delayed healing of fatigue fractures. Methods: In this study, we compared three methods for inducing osteoclast differentiation from mouse bone marrow-derived monocyte/macrophage (BMMs). Method 1 involved direct isolation of BMMs, Method 2 differentiated BMMs into bone marrow-derived macrophages (BMDM), and Method 3 incorporated Ficoll-Paque density gradient centrifugation prior to M-CSF-induced BMDM differentiation. For osteoclast differentiation, all three methods employed a complete medium containing 30 ng/mL M-CSF and 50 ng/mL RANKL. After first using TRAP staining, bone resorption assays, F-actin ring staining, quantitative reverse transcription polymerase chain reaction (RT-qPCR), and Western blot to identify the optimal plating density for each method, we then applied the same assays to compare osteoclastogenesis efficiency across the three methods at their optimal densities. Results: We found that Method 2, which involved differentiating BMMs into BMDM, yielded the highest proportion of live cells and osteoclast precursors, and exhibited the most efficient osteoclast differentiation. The optimal cell density for osteoclastogenesis was 2.8 ∼ 5.6 × 10 Conclusions: This study highlights the importance of precursor cell purity and seeding density in osteoclast differentiation. Method 2 (BMMs to BMDM) provides a simplified and effective approach for

Indexed as

Bone Marrow CellsCell DifferentiationMacrophagesOsteoclastsOsteogenesisAnimalsBone ResorptionCell CountCells, CulturedMacrophage Colony-Stimulating FactorMiceMice, Inbred C57BLRANK LigandMacrophage Colony-Stimulating FactorRANK LigandBone marrow-derived macrophages (BMDM)Bone marrow-derived monocyte/macrophage (BMMs)Cell densityFlow cytometryOsteoclastogenesis

Identifiers

PMID41907475
PMCPMC13032752

What OpenQuestion holds

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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 OpenQuestion graph.