Urine Sediment Analysis
Urine Sediment Analysis - Related Videos
07:58
Cell-Free DNA Integrity Analysis in Urine Samples
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Cited by 16 •
2017
A method for analyzing DNA integrity in the cell-free supernatant fraction of urine samples is proposed. The method is suitable for early detection of urological malignancies and has proven accurate for the early diagnosis of bladder cancer.
07:53
Actin Co-Sedimentation Assay; for the Analysis of Protein Binding to F-Actin
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Cited by 18 •
2008
Proteins bind to filamentous actin (F-actin) through distinct actin binding modules. In this video we demonstrate the procedure of actin co-sedimentation, which is an in vitro assay routinely used to analyze proteins or specific domains that bind F-actin.
01:32
Filtration and Urine Formation
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2019
The function of the kidneys is to filter, reabsorb, secrete, and excrete. Every day the kidneys filter nearly 180 liters of blood, initially removing water and solutes but ultimately returning nearly all filtrates into circulation with the help of osmoregulatory hormones. This process removes wastes and toxins but is also crucial to maintain water and electrolyte levels. Most of these functions are performed by the tiny but numerous nephrons contained within the kidneys. Blood enters the renal...
09:31
Preparation of Authigenic Pyrite from Methane-bearing Sediments for In Situ Sulfur Isotope Analysis Using SIMS
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Cited by 2 •
2017
Analyses of the sulfur isotopic composition (δ34S) of pyrite from methane-bearing sediments have typically focused on bulk samples. Here, we applied secondary ion mass spectroscopy to analyze the δ34S values of various pyrite generations to understand the diagenetic history of pyritization.
08:04
Soxhlet Extraction of Lipid Biomarkers from Sediment
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2023
Source: Laboratory of Jeff Salacup - University of Massachusetts Amherst Every lab needs standards that track the performance, accuracy, and precision of its instruments over time to ensure a measurement made today is the same as a measurement made a year from now (Figure 1). Because standards must test the performance of instruments over a long period of time, large volumes of the standards are often required. Many chemical standards can be purchased from retail scientific companies, like...
FAQs
Centrifugation concentrates suspended particles into a sediment, making cellular, crystalline, and microbial elements easier to examine than in an unconcentrated sample. The sediment is then resuspended so its contents can be distributed for observation. This concentration-resuspension sequence is central to the method because it prepares the sample for microscopy or automated image-based analysis.
Red blood cells can support assessment of bleeding, while white blood cells may indicate inflammation or infection. Casts provide information relevant to renal injury, and epithelial cells, crystals, and microorganisms add further detail about urinary tract or kidney conditions. Interpreting these categories together gives a broader picture than relying on a single sediment component.
Microscopy and automated image-based analyzers provide two observation routes after the sediment has been prepared. Microscopy supports identification of cellular, crystalline, and microbial components through visual examination, whereas automated imaging supports system-based analysis. Their inclusion in the same workflow shows how the method can connect laboratory observation with standardized, high-throughput urinalysis.
A typical sequence begins with a urine sample, followed by centrifugation to concentrate suspended solids. The resulting sediment is resuspended and then examined by microscopy or an automated image-based analyzer. This sequence links sample preparation with the later identification of red and white blood cells, casts, crystals, microorganisms, and other sediment components.
For engineering, findings from Urine Sediment Analysis help define the targets that biosensors, diagnostic devices, and automated urinalysis systems must handle. Because sediment may contain cells, casts, crystals, or microorganisms, designs must accommodate varied component types. The resulting systems can support standardized, high-throughput analysis of urinary health information.
Casts matter in this context because their identification can contribute to assessing renal injury. More broadly, distinguishing casts from red and white blood cells, epithelial cells, crystals, and microorganisms preserves the clinically relevant detail of the analysis. For engineered diagnostic workflows, maintaining those distinctions supports outputs that can inform kidney and urinary tract assessment.