scholarly journals A SECURE STEGANOGRAPHY CREATION ALGORITHM FOR MULTIPLE FILE FORMATS

2019 ◽  
Vol 1 (01) ◽  
pp. 1-10 ◽  
Author(s):  
Vijayakumar T
Keyword(s):  
Image Processing ◽  
Skin Cancer ◽  
Cell Carcinoma ◽  
Early Stage ◽  
Normal Skin ◽  
Merkel Cell ◽  
Merkel Cell Tumor ◽  
File Formats ◽  
Processing Procedure ◽  
Processing Steps

Nowadays the skin cancer has become a more dangerous and an unpredictable disease among the humans. Nearly one million of people all over the world every year are been affected by the skin cancer and left with no treatment due to the lack of early diagnosis. Besides the usual types of cancer such as the melanoma, basal cell carcinoma and squamous cell carcinoma that could be identified easily there are certain types of unusual skin cancer such as the Merkel cell skin cancer that are rare and difficult to diagnose. As the identification of the Merkel cell skin cancer at the early stage would be very useful in deciding the necessary treatment for its cure, the paper has put forward preprocessing techniques to improve the image quality to make the further image processing procedure easy in the identification of the skin cancer. The proposed method applies the combined image enhancement and the restoration (CIEIR) on the input skin lesion images and makes it more presentable with the improved quality for the further image processing steps in the identification of the normal skin and the skin affected by the Merkel cell tumor. The CIEIR is implemented in the MATLAB and the parameters such as the PSNR, SSIM and the MSE are measured.

scholarly journals Identification of Polyomaviruses in Skin Cancers

Intervirology ◽  
2021 ◽  
pp. 96-102
Author(s):  
Pedro V.A. Costa ◽  
Patricia S. Ishiy ◽  
Paulo R.P. Urbano ◽  
Camila M. Romano ◽  
Stephen K. Tyring ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Normal Skin ◽  
Dermatofibrosarcoma Protuberans ◽  
Epidemiological Data ◽  
Skin Carcinogenesis ◽  
P Value ◽  
Merkel Cell ◽  
Cross Sectional ◽  
Skin Tumours ◽  
Skin Tumour

Background: Polyomaviruses (PyVs) were initially described in animals. They have also been detected in humans with some evidence that could play a role in skin carcinogenesis. Objectives: This study aimed to verify the presence of PyVs in different skin tumour samples and to make clinical correlations with patients’ epidemiological data from Clinics Hospital of Medical School of University of São Paulo, Brazil. Methods: This is a cross-sectional study. A random selection was performed of 120 patients with histopathological exams of different cutaneous neoplasms equally divided into 6 groups and 20 patients with normal skin. The available skin specimens were analysed with 2 different techniques of PCR (conventional and real time) for detection of PyV DNA. Concomitantly, retrospective analysis of the respective medical records for the collection of epidemiological data was done. Analyses suitable for categorical data were used to compare the proportion of patients in each group. Results: PyV DNA was found in 25.69% of the samples: 15% in basal cell carcinoma group, 15% in squamous cell carcinoma, 28.57% in melanoma, 15% in dermatofibrosarcoma protuberans, 13.33% in Kaposi sarcoma, 65% in Merkel cell carcinoma (MCC), and none in normal skin. Merkel cell PyV detection was statistically significant in MCC patients (p value <0.01), but no correlations were found between PyVs and others skin tumours. Conclusion: This study demonstrated the presence of PyVs in different skin tumours; however, no association of any PyVs found in any skin tumour with epidemiological data could be shown. Further studies are still needed to elucidate the mechanisms of PyVs in skin carcinogenesis.

scholarly journals Outcome of early stage Merkel carcinoma treated by exclusive radiation: a study of 53 patients

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Manon Dubois ◽  
Henry Abi Rached ◽  
Alexandre Escande ◽  
Frédéric Dezoteux ◽  
Franck Darloy ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Early Stage ◽  
Cox Model ◽  
Combined Treatment ◽  
Disease Free Survival ◽  
External Beam Radiation ◽  
Merkel Cell ◽  
Beam Radiation ◽  
Metastatic Relapse

Abstract Purpose Early stage Merkel cell carcinoma (MCC) is a rare and aggressive primary skin cancer. The standard of care for MCC is broad excision and adjuvant external beam radiation therapy (EBRT). However, for some patients, anesthesia is contraindicated, while others run the risk of serious aesthetic sequelae. In such cases, exclusive radiotherapy is an interesting alternative to surgery. Though limited data is available, this study evaluates exclusive radiotherapy for MCC, using data from the largest retrospective study to date. Methods All patients who were followed in our center between 1989 and 2019 for histologically proven early stage MCC were included in the study. They were treated either by surgery with a 2-cm clear margin followed by adjuvant radiotherapy (RT) or by exclusive RT. Survival rates with adjuvant and exclusive EBRT were analyzed using Cox model and Fine and Gray model depending on the type of survival. p value < 0.05 was considered significant. Results Eighty-four patients treated for MCC were included. Fifty-three of them (63.1%) were treated by exclusive RT, and 31 (36.9%) had surgical excision followed by adjuvant RT. Local relapse rate was 13.7% (95% CI 8.0–43.7) in the RT monotherapy group (group A) and 25.8% (95% CI 10.3–56.2) in the surgery + RT group (group B) (p = 0.42). No statistical difference was found for nodal relapse (p = 0.81), metastatic relapse (p = 0.10), disease free survival (p = 0.83) or overall survival (p = 0.98). Conclusion Our study suggests that exclusive radiotherapy for early Merkel cell carcinoma leads to a similar oncological outcome as combined treatment, with fewer aesthetic sequelae. The approach is interesting for elderly patients with comorbidities or patients for whom surgery would cause significant functional or aesthetic sequelae.

scholarly journals Characterization of the Merkel Cell Carcinoma miRNome

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Matthew S. Ning ◽  
Annette S. Kim ◽  
Nripesh Prasad ◽  
Shawn E. Levy ◽  
Huiqiu Zhang ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Normal Skin ◽  
Merkel Cell ◽  
Tissue Samples ◽  
Qrt Pcr ◽  
Skin Cancers ◽  
Next Generation Sequencing Ngs

MicroRNAs have been implicated in various skin cancers, including melanoma, squamous cell carcinoma, and basal cell carcinoma; however, the expression of microRNAs and their role in Merkel cell carcinoma (MCC) have yet to be explored in depth. To identify microRNAs specific to MCC (MCC-miRs), next-generation sequencing (NGS) of small RNA libraries was performed on different tissue samples including MCCs, other cutaneous tumors, and normal skin. Comparison of the profiles identified several microRNAs upregulated and downregulated in MCC. For validation, their expression was measured via qRT-PCR in a larger group of MCC and in a comparison group of non-MCC cutaneous tumors and normal skin. Eight microRNAs were upregulated in MCC: miR-502-3p, miR-9, miR-7, miR-340, miR-182, miR-190b, miR-873, and miR-183. Three microRNAs were downregulated: miR-3170, miR-125b, and miR-374c. Many of these MCC-miRs, the miR-183/182/96a cistron in particular, have connections to tumorigenic pathways implicated in MCC pathogenesis.In situhybridization confirmed that the highly expressed MCC-miR, miR-182, is localized within tumor cells. Furthermore, NGS and qRT-PCR reveal that several of these MCC-miRs are highly expressed in the patient-derived MCC cell line, MS-1. These data indicate that we have identified a set of MCC-miRs with important implications for MCC research.

scholarly journals Skin Cancer Recognition Using SVM Image Processing Technique

2020 ◽  
pp. 11-15
Author(s):  
Rahul Chand Thakur ◽  
◽  
Vaibhav Panwar ◽  
Keyword(s):  
Image Processing ◽  
Skin Cancer ◽  
Supervised Learning ◽  
Detection System ◽  
Early Stage ◽  
Image Features ◽  
The Body ◽  
Image Processing Technique ◽  
Support Vector ◽  
Skin Cells

Skin cancer is considered as commonest cause of death among humans in today's world. This type of cancer shows non uniform or patchy growth of skin cells that most commonly occurs on of the certain parts of body which are more likely exposed to the light, but it can occur anywhere on the body. The majority of skin cancers can be treated if detected early. As a result, finding skin cancer early and easily will save a patient's life. Early detection of skin cancer at an early stage is now possible thanks to modern technologies. Biopsy procedure [1] is a systematic method for diagnosis skin cancer. It is achieved by extracting skin cells, after which the sample is sent to different laboratories for examination. It's a very long (in terms of time) and painful process. For primitive detection of skin cancer disease, we proposed a skin cancer detection system based on svm. It is more helpful to patients. Various methods of image processing and the supervised learning algorithm called Support Vector Machine (SVM) are used in the identification process. Epiluminescence microscopy is taken using an image and particular to several preprocessing techniques which are used in the reduction of sound artifacts and improvise quality of images. Segmentation is done by using certain thresholding techniques like OTSU. The GLCM technique must be used to remove certain image features. These characteristics are fed into the classifier as input. The Supervised learning model called (SVM) is used to distinguish data sets. It determines whether a picture is cancerous or not.

scholarly journals Merkel cell carcinoma (MCC) – neuroendocrine skin cancer

2019 ◽  
Vol 69 (3-4) ◽  
pp. 111-116
Author(s):  
Monika Dudzisz-Śledź ◽  
Marcin Zdzienicki ◽  
Piotr Rutkowski
Keyword(s):  
Skin Cancer ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Merkel Cell

scholarly journals Melanoma Skin Cancer Detection

2019 ◽  
Vol 9 (1) ◽  
pp. 4073-4076
Keyword(s):  
Image Processing ◽  
Skin Cancer ◽  
Cancer Detection ◽  
Normal Skin ◽  
Cancer Growth ◽  
Melanoma Cancer ◽  
Skin Malignancy ◽  
Image Investigation ◽  
Skin Cancer Detection ◽  
Melanoma Skin

Skin cancer growth is viewed as one of the most Hazardous type of the Cancers found in Humans. Nowadays skin cancer is found in different kinds for example Melanoma, Basal and Squamous cell Carcinoma among which Melanoma is the generally flighty. The detection of Melanoma disease in beginning period can be helpful for cure it. Computer vision can play big role in Portrayal Analysis also it has been examined by many existing frameworks. In this paper, we present a Computer helped strategy for the recognition of Melanoma Skin Cancer utilizing Image Processing instruments. The contribution to the framework is the skin lesion picture and after that by applying novel picture preparing strategies, it investigates it to finish up about the nearness of skin malignancy. The Lesion Image investigation instruments checks for the different Melanoma parameters Like Asymmetry, Border, Color, Diameter,(ABCD) and so on by surface, size and shape examination for picture division and highlight stages. The extricated highlight parameters are utilized to characterize the picture as Normal skin and Melanoma cancer growth injury.

scholarly journals Merkel Cell Polyomavirus Small T Antigen Mediates Microtubule Destabilization To Promote Cell Motility and Migration

2014 ◽  
Vol 89 (1) ◽  
pp. 35-47 ◽  
Author(s):  
Laura M. Knight ◽  
Gabriele Stakaityte ◽  
Jennifer, J. Wood ◽  
Hussein Abdul-Sada ◽  
David A. Griffiths ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Cell Motility ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Tumor Antigen ◽  
Molecular Mechanisms ◽  
T Antigen ◽  
Merkel Cell Polyomavirus ◽  
Merkel Cell ◽  
Potential Link

ABSTRACTMerkel cell carcinoma (MCC) is an aggressive skin cancer of neuroendocrine origin with a high propensity for recurrence and metastasis. Merkel cell polyomavirus (MCPyV) causes the majority of MCC cases due to the expression of the MCPyV small and large tumor antigens (ST and LT, respectively). Although a number of molecular mechanisms have been attributed to MCPyV tumor antigen-mediated cellular transformation or replication, to date, no studies have investigated any potential link between MCPyV T antigen expression and the highly metastatic nature of MCC. Here we use a quantitative proteomic approach to show that MCPyV ST promotes differential expression of cellular proteins implicated in microtubule-associated cytoskeletal organization and dynamics. Intriguingly, we demonstrate that MCPyV ST expression promotes microtubule destabilization, leading to a motile and migratory phenotype. We further highlight the essential role of the microtubule-associated protein stathmin in MCPyV ST-mediated microtubule destabilization and cell motility and implicate the cellular phosphatase catalytic subunit protein phosphatase 4C (PP4C) in the regulation of this process. These findings suggest a possible molecular mechanism for the highly metastatic phenotype associated with MCC.IMPORTANCEMerkel cell polyomavirus (MCPyV) causes the majority of cases of Merkel cell carcinoma (MCC), an aggressive skin cancer with a high metastatic potential. However, the molecular mechanisms leading to virally induced cancer development have yet to be fully elucidated. In particular, no studies have investigated any potential link between the virus and the highly metastatic nature of MCC. We demonstrate that the MCPyV small tumor antigen (ST) promotes the destabilization of the host cell microtubule network, which leads to a more motile and migratory cell phenotype. We further show that MCPyV ST induces this process by regulating the phosphorylation status of the cellular microtubule-associated protein stathmin by its known association with the cellular phosphatase catalytic subunit PP4C. These findings highlight stathmin as a possible biomarker of MCC and as a target for novel antitumoral therapies.

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