Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Use of scanning electron microscopy and energy dispersive X-ray for urine analysis: A preliminary investigation

Microscopy Research and Technique, Volume 86, No. 10, Year 2023

Scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) are powerful tools to study the ultrastructure of numerous specimens and to determine their elemental composition, respectively. However, results have not yet been reported on their application to urine samples in routine clinical laboratory practice. Herein we investigate urine sediment by using SEM and EDX to detect and identify different urine components. A total of 206 urine samples from patients with and without urinary tract infections were analyzed using SEM and EDX. Microorganisms, crystals, epithelial cells, leukocytes, and erythrocytes were targeted in urine sediment samples. The identification of urine components was based on their morphology, size, contrast, and elemental composition. SEM-analysis allowed us to identify and classify microorganisms in urine sediments into the categories of gram-negative bacilli, cluster cocci, chain cocci, gram-negative bacilli, gram-positive bacilli, and yeasts. In addition, various types of epithelial cells such as renal, transitional, and squamous epithelial cells were found. Furthermore, leukocytes and erythrocytes were well identified, with the detection of various morphological forms of erythrocytes, such as dysmorphic and isomorphic erythrocytes. Using SEM–EDX analysis, calcium oxalate was the most frequently-identified crystal (92.0%), with prominent peaks of C, O, and Ca elements, followed by struvite (6%), with peaks of Mg, P, O, and N. These preliminary data suggest that the two complementary SEM–EDX analyses can be used to detect and identify microorganisms and crystals in urine samples. Further studies are still needed to apply SEM–EDX to urine sediment analysis. SEM–EDX analyses provided comparative results with the routine results, with accurate identification, high resolution and deep focus compared to the routine urinalysis SEM-analysis allowed us to identify and classify microorganisms in urine sediments into the categories of gram-negative bacilli, cluster cocci, chain cocci, gram-negative bacilli, gram-positive bacilli and yeasts. SEM–EDX analysis enabled the accurate identification of crystals based on both morphology and elemental composition.
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