ArticleTissue engineering. Part C, Methods2025
Optimization of Cytometry by Time-of-Flight Staining for Peripheral Blood and Bone Marrow Samples.
Article in Tissue engineering. Part C, Methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed.
- Immune profiling in orthopaedic diseases using mass cytometry : a narrative review of applications and future directions.Bone & joint research · 2026Article
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Authors and funding
9 authors.
Funding
Abstract
Cytometry by time-of-flight (CyTOF) enables comprehensive immune profiling for translational research. However, challenges such as signal variability, nonspecific binding, and antibody incompatibility can compromise data quality. This study presents an optimized CyTOF staining protocol for human peripheral blood mononuclear cells and bone marrow aspiration concentrate samples, addressing these challenges by refining antibody conjugation with polymer X8, saponin use, and fixation protocols. Preliminary data indicate improved staining for key markers (CD14, CD16, and CD19), enhancing signal consistency and clarity. These findings advance the utility of CyTOF in orthopaedic research and immune profiling for diseases such as osteonecrosis of the femoral head.
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Registered trials
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.