First- vs. Second-Generation Autologous Platelet Concentrates and Their Implications for Wound Healing: Differences in Proteome and Secretome.

IF 3.8 3区 医学 Q2 ENGINEERING, BIOMEDICAL Bioengineering Pub Date : 2024-11-20 DOI:10.3390/bioengineering11111171
Hanna L Stiller, Natarajan Perumal, Caroline Manicam, Emily R Trzeciak, Julia Todt, Kerstin Jurk, Andrea Tuettenberg, Sven Schumann, Eik Schiegnitz, Sebastian Blatt
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Abstract

Differences in cell count and growth factor expression between first- and second-generation autologous platelet concentrates (APCs) have been well described. The debate over which formula best supports wound healing in various surgical procedures is still ongoing. This study aims to assess the whole proteome assembly, cell content, immunological potential and pro-angiogenic potential of second-generation APC, Platelet-Rich Fibrin (PRF) vs. first-generation APC, Platelet-Rich Plasma (PRP). The global proteome of the APCs was analyzed using nano-liquid chromatography mass spectrometry. Blood cell concentrations were determined by an automated cell counter. The effect of APCs on macrophage polarization was analyzed by flow cytometry. A yolk sac membrane (YSM) assay was used to monitor the neo-vessel formation and capillary branching in vivo. Cell count analysis revealed a higher number/concentration of leukocytes in PRF vs. PRP. Incubation of macrophages with PRP or platelet-free plasma (PFP) did not induce a significant pro-inflammatory state but led to a shift to the M0/M2 phenotype as seen in wound healing for all tested formulas. Label-free proteomics analysis identified a total of 387 proteins from three biological replicates of the respective designated groups. PRF induced increased formation of neo-vessels and branching points in vivo in comparison to PRP and PFP (each p < 0.001), indicating the enhanced pro-angiogenic potential of PRF. Overall, PRF seems superior to PRP, an important representative of first-generation formulas. Inclusion of leucocytes in PRF compared to PRP suggested rather an anti-inflammatory effect on macrophages. These results are important to support the versatile clinical applications in regenerative medicine for second-generation autologous platelet concentrates to optimize wound healing.

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第一代与第二代自体血小板浓缩物及其对伤口愈合的影响:蛋白质组和分泌组的差异。
第一代和第二代自体血小板浓缩物(APCs)在细胞数量和生长因子表达方面的差异已被充分描述。关于哪种配方最能支持各种外科手术中的伤口愈合的争论仍在继续。本研究旨在评估第二代自体血小板浓缩物(Platelet-Rich Fibrin,PRF)与第一代自体血小板浓缩物(Platelet-Rich Plasma,PRP)的全蛋白质组组合、细胞含量、免疫潜能和促血管生成潜能。使用纳米液相色谱质谱法分析了 APC 的全蛋白质组。血细胞浓度由自动细胞计数器测定。流式细胞术分析了 APCs 对巨噬细胞极化的影响。卵黄囊膜(YSM)试验用于监测体内新血管的形成和毛细血管的分支。细胞计数分析显示,PRF 中的白细胞数量/浓度高于 PRP。用 PRP 或无血小板血浆 (PFP) 培养巨噬细胞不会诱发明显的促炎状态,但会导致 M0/M2 表型的转变,这在所有测试配方的伤口愈合中都能看到。无标记蛋白质组学分析从各指定组的三个生物重复中鉴定出了共 387 个蛋白质。与 PRP 和 PFP 相比,PRF 能诱导体内新血管和分支点的形成(各 p < 0.001),这表明 PRF 具有更强的促血管生成潜能。总体而言,PRF 似乎优于 PRP,是第一代配方的重要代表。与 PRP 相比,PRF 中含有白细胞,这表明 PRF 对巨噬细胞具有抗炎作用。这些结果对于支持第二代自体血小板浓缩物在再生医学领域的广泛临床应用以优化伤口愈合非常重要。
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来源期刊
Bioengineering
Bioengineering Chemical Engineering-Bioengineering
CiteScore
4.00
自引率
8.70%
发文量
661
期刊介绍: Aims Bioengineering (ISSN 2306-5354) provides an advanced forum for the science and technology of bioengineering. It publishes original research papers, comprehensive reviews, communications and case reports. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. All aspects of bioengineering are welcomed from theoretical concepts to education and applications. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, four key features of this Journal: ● We are introducing a new concept in scientific and technical publications “The Translational Case Report in Bioengineering”. It is a descriptive explanatory analysis of a transformative or translational event. Understanding that the goal of bioengineering scholarship is to advance towards a transformative or clinical solution to an identified transformative/clinical need, the translational case report is used to explore causation in order to find underlying principles that may guide other similar transformative/translational undertakings. ● Manuscripts regarding research proposals and research ideas will be particularly welcomed. ● Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. ● We also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds. Scope ● Bionics and biological cybernetics: implantology; bio–abio interfaces ● Bioelectronics: wearable electronics; implantable electronics; “more than Moore” electronics; bioelectronics devices ● Bioprocess and biosystems engineering and applications: bioprocess design; biocatalysis; bioseparation and bioreactors; bioinformatics; bioenergy; etc. ● Biomolecular, cellular and tissue engineering and applications: tissue engineering; chromosome engineering; embryo engineering; cellular, molecular and synthetic biology; metabolic engineering; bio-nanotechnology; micro/nano technologies; genetic engineering; transgenic technology ● Biomedical engineering and applications: biomechatronics; biomedical electronics; biomechanics; biomaterials; biomimetics; biomedical diagnostics; biomedical therapy; biomedical devices; sensors and circuits; biomedical imaging and medical information systems; implants and regenerative medicine; neurotechnology; clinical engineering; rehabilitation engineering ● Biochemical engineering and applications: metabolic pathway engineering; modeling and simulation ● Translational bioengineering
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First- vs. Second-Generation Autologous Platelet Concentrates and Their Implications for Wound Healing: Differences in Proteome and Secretome. Proteoglycans Enhance the Therapeutic Effect of BMSC Transplantation on Osteoarthritis. Improving Brain Metabolite Detection with a Combined Low-Rank Approximation and Denoising Diffusion Probabilistic Model Approach. A Unified Multi-Task Learning Model with Joint Reverse Optimization for Simultaneous Skin Lesion Segmentation and Diagnosis. AI-Driven Prediction of Symptom Trajectories in Cancer Care: A Deep Learning Approach for Chemotherapy Management.
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