Screening chronic myeloid leukemia neutrophils using a novel 3-Dimensional Spectral Gradient Mapping algorithm on hyperspectral images.

Background and objective Early diagnosis of chronic myeloid leukemia (CML) is important for effective treatment. The high spectral and spatial resolution of hyperspectral cellular or tissue images coupled with image analysis algorithms may provide avenues to detect and diagnose diseases early. Many algorithms have been used to analyze medical hyperspectral image data, each having their own strengths and short-comings. We present a novel 3-Dimensional Spectral Gradient Mapping (3-D SGM) method to analyze hyperspectral image cubes of CML versus healthy blood smears. Methods In the present study, we analyzed 13 hyperspectral image cubes of CML and healthy neutrophils. The 3-D SGM algorithm was compared to the conventional Windowed Spectral Angle Mapping (Windowed SAM) method. The 3-D SGM exploited the spectral information of the image cube together with the inter-band and inter-pixel data by extracting the 3-D gradient vector from each pixel. The Windowed SAM determined the similarity between the averaged window of a 2×2 training pixel group and the test pixel, in the multidimensional spectral angle. Results The specificity measure of 3-D SGM (97.7%) was superior to Windowed SAM (72.7%) at ruling out the presence of the disease, making it potentially ideal for screening patients. The positive likelihood ratio value of 3-D SGM (16.70) was superior in diagnosing the presence of the disease (i.e., positive test for CML) versus Windowed SAM (2.26). An accuracy value of 84.2% was achieved with 3-D SGM versus only 70.2% for Windowed SAM. Conclusion The new method is efficient and robust for analyzing hyperspectral images of CML versus healthy neutrophils. It has the potential to be developed into an inexpensive, minimally invasive method for screening CML, and could directly facilitate early diagnosis and treatment of the disease.

A comparative evaluation of resin- and varnish-based surface protective agents on glass ionomer cement - a spectrophotometric analysis.

Objectives: To evaluate and compare the effectiveness of resin- and varnish-based surface protective agents on Glass Ionomer Cement (GIC). The different surface protective agents used were: Vaseline®, GC Fuji VARNISH™ (varnish), G-Coat Plus™ (resin) and EQUIA® Coat (resin). Method: Thirty-six identical specimens of GIC were made. Six specimens were used in preparation of standard solution and remaining thirty were divided into five groups with six specimens in each group. Each test specimen was coated with one of the surface protecting agent except for the control group. The specimens were immersed separately into 1 ml of 0.05% methylene blue solution for 24 h and then rinsed with deionised water and further immersed into tubes containing 1 ml of 65% nitric acid. Specimens, once completely dissolved in nitric acid solution, were filtered and centrifuged. The supernatant was used to determine the absorbance using a spectrophotometer. The effectiveness of the surface protecting agents for the GIC was recorded in micrograms of dye per specimen, where low values indicate good protection. Result: Tukey HSD test revealed that GC Fuji VARNISH™ (varnish; mean = 21.25 µg/ml), G-Coat Plus™ (resin; mean = 30.39 µg/ml) and EQUIA® Coat (resin; mean = 9.32 µg/ml) were statistically not significantly different to each other and were effective in protecting the surface of GIC. Significance: The study found that there was a statistically significant difference between control and GC Fuji VARNISH™, G-Coat Plus™ and EQUIA® Coat. The three agents were found to be equally effective in protecting the surface of GIC.

HPSE-1 expression and functionality in differentiating neural cells.

The study of cellular differentiation encompasses many vital parts of biology and medicine. Heparan sulfate proteoglycans (HSPG) are essential and ubiquitous macromolecules associated with the cell surface and extracellular matrix (ECM) of a wide range of cells and tissues. Heparan sulfate chains (HS) of HSPG bind and sequester a multitude of extracellular ligands, including growth factors, cytokines, chemokines, enzymes, and lipoproteins. Enzymatic degradation of HS is therefore involved in processes such as cell proliferation, migration, and differentiation. Heparanase (HPSE-1) is an HS degradative enzyme associated with inflammation and lipid metabolism and is a critical molecular determinant in cancer metastasis. The enzyme acts as an endo-beta-D-glucuronidase, which degrades HS at specific intrachain sites, resulting in HS fragments of discrete molecular weights that retain biological function. HPSE-1's relevance as the only example of cloned/purified mammalian HS degradative enzyme led us to investigate its functionality in human olfactory epithelium (HOE) cells as a paradigm for HPSE-1's roles in neural cell differentiation. We provide the first evidence of 1) HPSE-1 presence in HOE cells and 2) a highly significant increase of HPSE-1 mRNA and enzyme activity in differentiating vs. proliferating HOE cells. Our data suggest that an augmented HPSE-1 activity may represent a physiological mechanism involved in neural cellular differentiation.