HeLa cell segmentation using digital image processing

Computational cell segmentation is a vital area of research, particularly in the analysis of images of cancer cells. The use of cell lines, such as the widely utilized HeLa cell line, is crucial for studying cancer. While deep learning algorithms have been commonly employed for cell segmentation, their resource and data requirements can be impractical for many laboratories. In contrast, image processing algorithms provide a promising alternative due to their effectiveness and minimal resource demands. This article presents the development of an algorithm utilizing digital image processing to segment the nucleus and shape of HeLa cells. The research aims to segment the cell shape in the image center and accurately identify the nucleus. The study uses and processes 300 images obtained from Serial Block-Face Scanning Electron Microscopy (SBF-SEM). For cell segmentation, the morphological operation of erosion was used to separate the cells, and through distance calculation, the cell located at the center of the image was selected. Subsequently, the eroded shape was employed to restore the original cell shape. The nucleus segmentation uses parameters such as distances and sizes, along with the implementation of verification stages to ensure accurate detection. The accuracy of the algorithm is demonstrated by comparing it with another algorithm meeting the same conditions, using four segmentation similarity metrics. The evaluation results rank the proposed algorithm as the superior choice, highlighting significant outcomes. The algorithm developed represents a crucial initial step towards more accurate disease analysis. In addition, it enables the measurement of shapes and the identification of morphological alterations, damages, and changes in organelles within the cell, which can be vital for diagnostic purposes.

The behavior of arsenic accumulation in onion (Allium cepa) structures by irrigation water: effect of phosphates and arsenic on the total bioactive compounds and antioxidant capacity

The presence of arsenic (As) in irrigation water is a threat to agricultural crops as well as human health. The presence of arsenic and phosphorous in irrigation water influences the behavior of bioaccumulation, biotransfer, and total bioactive compounds in the distinct parts of the onion structure. The present work evaluates the behavior of the bioaccumulation and biotransfer of As in the structures of onion (Allium cepa) through a composite central design and response surface method. The factors employed include the concentration of arsenic (V) and phosphate (V) in the nutritive solution. Additionally, this study analyzes the behavior of the effect that the induced stress has on the total bioactive compounds (phenols and flavonoids) and antioxidant capacity (ABTS and DPPH) in the onion roots. The results showed that the physiological properties, bioaccumulation factors, As transference, and the total bioactive compounds in the onion structure are affected by the competition of As and phosphates (P(V)) in the irrigation water. For concentrations of As and phosphorous of 450 μg L-1 and 0.30 mg L-1 respectively in irrigation water, there are negative effects on the equatorial diameter of the bulb (DE), length, weight of the leaf, and weight of the bulb. Besides, the transference and bioaccumulation factors range from 0.02 to 0.22 and from 2.15 to 7.81, respectively, suggesting that the plant has the ability to accumulate As but exhibits a low translocation ability of As from the root to aerial organs. Besides, it is found for central concentrations of As and phosphorous (450 μg L-1 and 0.30 mg L-1, respectively) in irrigation water, a greater production occurs in total phenolic compounds and antioxidant capacity (ABTS and DPPH) as a response to the stress generated by As.