Hirsch Sigal, Porat Ziv, Dror Ishai, Shilo Yaniv, Berkowitz Brian
Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel.
Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel.
PLoS One. 2025 May 22;20(5):e0324271. doi: 10.1371/journal.pone.0324271. eCollection 2025.
There is a notable scarcity of information concerning particulate matter in urine. This study presents an initial investigation that uses flow cytometry to determine the particulate content in the urine of healthy individuals, focusing on particles within a diameter range of 0.33-70 µm. Imaging flow cytometry was combined with fluorescent tagging and a birefringence technique to characterize particulate matter in terms of concentration, type, and size. This method enabled the identification and quantification of total particles within a sample, as well as the characterization of specific subtypes, including lipid-associated particles, protein aggregates, lipid-protein complexes, particles containing calcium (such as calcium oxalate crystals), DNA-containing particles (including cells and bacteria), and crystalline structures. Benchmark ranges for particulate matter present in urine were categorized according to subgroups that account for the influence of age, gender, and time of sampling, yielding valuable insights into the total number of particles traversing the human urinary tract daily. Significantly, the analysis here suggests that approximately 320 × 106 particles may pass through the urinary tract each day. Examination of a range of potential correlations among samples indicated that the total particle concentrations remained statistically similar. More specifically, there were no significant concentration differences in urine samples relative to sampling time, gender, or age. These findings provide valuable insights into the variability of urinary particulate matter and lay the groundwork for future, larger-scale studies. Ultimately, this research contributes to understanding urinary tract function and may potentially lead to identifying novel markers for various health conditions.
关于尿液中的颗粒物，目前存在明显的信息匮乏。本研究进行了初步调查，利用流式细胞术测定健康个体尿液中的颗粒物含量，重点关注直径范围在0.33 - 70 µm的颗粒。成像流式细胞术与荧光标记和双折射技术相结合，从浓度、类型和大小方面对颗粒物进行表征。该方法能够识别和量化样品中的总颗粒，以及特定亚型的特征，包括脂质相关颗粒、蛋白质聚集体、脂蛋白复合物、含钙颗粒（如草酸钙晶体）、含DNA颗粒（包括细胞和细菌）以及晶体结构。根据考虑年龄、性别和采样时间影响的亚组对尿液中存在的颗粒物基准范围进行分类，从而对每天通过人体尿道的颗粒总数有了有价值的认识。值得注意的是，此处的分析表明每天约有320×10⁶个颗粒可能通过尿道。对一系列样本间潜在相关性的检查表明，总颗粒浓度在统计学上保持相似。更具体地说，尿液样本在采样时间、性别或年龄方面没有显著的浓度差异。这些发现为尿液颗粒物的变异性提供了有价值的见解，并为未来更大规模的研究奠定了基础。最终，这项研究有助于理解尿道功能，并可能潜在地导致识别各种健康状况的新型标志物。
