Abstract: Malignant Melanoma, known simply as Melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient death. When detected early, Melanoma is curable. In this paper we propose a deep learning model (Convolutional Neural Networks) in order to automatically classify skin lesion images as Malignant or Benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.
Abstract: In recent years, interest in ecogenetic and biomedical problems related to the effects on the population of radon and its daughter decay products has increased significantly. Of particular interest is the assessment of the consequence of irradiation at hazardous radon areas, which includes the Almaty region due to the large number of tectonic faults that enhance radon emanation. In connection with the foregoing, the purpose of this work was to study the genetic effects of exposure to supernormal radon doses on the alpha-radiation model. Irradiation does not affect the growth of the cell, but rather its ability to differentiate. In addition, irradiation can lead to somatic mutations, morphoses and modifications. These damages most likely occur from changes in the composition of the substances of the cell. Such changes are epigenetic since they affect the regulatory processes of ontogenesis. Variability in the expression of regulatory genes refers to conditional mutations that modify the formation of signs of intraspecific similarity. Characteristic features of these conditional mutations are the dominant type of their manifestation, phenotypic asymmetry and their instability in the generations. Currently, the terms “morphosis” and “modification” are used to describe epigenetic variability, which are maintained in Drosophila melanogaster cultures using linkaged X- chromosomes, and the mutant X-chromosome is transmitted along the paternal line. In this paper, we investigated the epigenetic effects of alpha particles, whose source in nature is mainly radon and its daughter decay products. In the experiment, an isotope of plutonium-238 (Pu238), generating radiation with an energy of about 5500 eV, was used as a source of alpha particles. In an experiment in the first generation (F1), deformities or morphoses were found, which can be called "radiation syndromes" or mutations, the manifestation of which is similar to the pleiotropic action of genes. The proportion of morphoses in the experiment was 1.8%, and in control 0.4%. In this experiment, the morphoses in the flies of the first and second generation looked like black spots, or melanomas on different parts of the imago body; "generalized" melanomas; curled, curved wings; shortened wing; bubble on one wing; absence of one wing, deformation of thorax, interruption and violation of tergite patterns, disruption of distribution of ocular facets and bristles; absence of pigmentation of the second and third legs. Statistical analysis by the Chi-square method showed the reliability of the difference in experiment and control at P ≤ 0.01. On the basis of this, it can be considered that alpha particles, which in the environment are mainly generated by radon and its isotopes, have a mutagenic effect that manifests itself, mainly in the formation of morphoses or deformities.
Abstract: Although skin cancers are prevalent worldwide, it is uncommon in Ha’il region in the Kingdom of Saudi Arabia, mostly non-melanoma sub-type. During a 4-year period from 2014 to 2017, out of a total of 120 cases of skin lesions, 29 non-melanoma cancers were retrieved from histopathology files obtained from King Khalid Hospital. As part of the study, all cases of skin cancer diagnosed during 2014 -2017 have been revised and the clinicopathological data recorded. The results show that Basal cell carcinoma (BCC) was the most common neoplasm (36%), followed by cutaneous lymphomas (mostly mycosis fungoides 25%), squamous cell carcinoma (SCC) (21%) and dermatofibrosarcoma protuberans (DFSP) (11%). Only one case of metastatic carcinoma was recorded. BCC nodular type was the most prevalent, with a mean age 57.6 years and mean size 2.73 cm. SCC was mostly grade 2, with mean size 1.9 cm and an older mean age of 72.3 cm. Increased size of lesion positively correlated with older age (p = 0.001). Non-melanoma skin cancer in Ha’il region is not frequently encountered. BCC is the most frequent followed by cutaneous T-cell lymphomas and SCC. The findings in this study were in accordance with other parts of, but much lower than other parts of the world.
Abstract: The development of Drugs Delivery System (DDS)
has been widely investigated in the last decades. In this paper, first a
general overview of traditional and modern wound dressing is
presented. This is followed by a review of what scientists have done
in the medical environment, focusing on the possibility to develop a
new alternative for DDS through transdermal pathway, aiming to
treat melanoma skin cancer.
Abstract: Kigelia africana (Lam.) Benth. (Bignoniaceae) is a
reputed traditional remedy for various human ailments such as skin
diseases, microbial infections, melanoma, stomach troubles,
metabolic disorders, malaria and general pains. In spite of the fruit
being widely used for purposes related to its antibacterial and
antifungal properties, the chemical constituents associated with the
activity have not been fully identified. To elucidate the active
principles, we evaluated the antimicrobial activity of fruit extracts
and purified fractions against Staphylococcus aureus, Enterococcus
faecalis, Moraxella catarrhalis, Escherichia coli, Candida albicans
and Candida tropicalis. Shade-dried fruits were powdered and
extracted with hydroalcoholic (1:1) mixture by soaking at room
temperature for 72 h. The crude extract was further fractionated by
column chromatography, with successive elution using hexane,
dichloromethane, ethyl acetate, acetone and methanol. The
dichloromethane and ethyl acetate fractions were combined and
subjected to column chromatography to furnish a wax and oil from
the eluates of 20% and 40% ethyl acetate in hexane, respectively. The
GC-MS and GC×GC-MS results revealed that linoleic acid, linolenic
acid, palmitic acid, arachidic acid and stearic acid were the major
constituents in both oil and wax. The crude hydroalcoholic extract
exhibited the strongest activity with MICs of 0.125-0.5 mg/mL,
followed by the ethyl acetate (MICs = 0.125-1.0 mg/mL),
dichloromethane (MICs = 0.250-2.0 mg/mL), hexane (MICs = 0.25-
2.0 mg/mL), acetone (MICs = 0.5-2.0 mg/mL) and methanol (MICs =
1.0-2.0 mg/mL), whereas the wax (MICs = 2.0-4.0 mg/mL) and oil
(MICs = 4.0-8.0 mg/mL) showed poor activity. The study concludes
that synergistic interactions of chemical constituents could be
responsible for the antimicrobial activity of K. africana fruits, which
needs a more holistic approach to understand the mechanism of its
antimicrobial activity.
Abstract: Automatic segmentation of skin lesions is the first step
towards the automated analysis of malignant melanoma. Although
numerous segmentation methods have been developed, few studies
have focused on determining the most effective color space for
melanoma application. This paper proposes an automatic segmentation
algorithm based on color space analysis and clustering-based histogram
thresholding, a process which is able to determine the optimal
color channel for detecting the borders in dermoscopy images. The
algorithm is tested on a set of 30 high resolution dermoscopy images.
A comprehensive evaluation of the results is provided, where borders
manually drawn by four dermatologists, are compared to automated
borders detected by the proposed algorithm, applying three previously
used metrics of accuracy, sensitivity, and specificity and a new metric
of similarity. By performing ROC analysis and ranking the metrics,
it is demonstrated that the best results are obtained with the X and
XoYoR color channels, resulting in an accuracy of approximately
97%. The proposed method is also compared with two state-of-theart
skin lesion segmentation methods.
Abstract: Automatic segmentation of skin lesions is the first step
towards development of a computer-aided diagnosis of melanoma.
Although numerous segmentation methods have been developed,
few studies have focused on determining the most discriminative
and effective color space for melanoma application. This paper
proposes a novel automatic segmentation algorithm using color space
analysis and clustering-based histogram thresholding, which is able to
determine the optimal color channel for segmentation of skin lesions.
To demonstrate the validity of the algorithm, it is tested on a set of 30
high resolution dermoscopy images and a comprehensive evaluation
of the results is provided, where borders manually drawn by four
dermatologists, are compared to automated borders detected by the
proposed algorithm. The evaluation is carried out by applying three
previously used metrics of accuracy, sensitivity, and specificity and
a new metric of similarity. Through ROC analysis and ranking the
metrics, it is shown that the best results are obtained with the X and
XoYoR color channels which results in an accuracy of approximately
97%. The proposed method is also compared with two state-ofthe-
art skin lesion segmentation methods, which demonstrates the
effectiveness and superiority of the proposed segmentation method.