Background: Oral squamous cell carcinoma is the most prevalent malignant neoplasm of the oral cavity which results from accumulated genetic and epigenetic alterations. It is not always inexorable and may be reversible if early intervention in the process can occur to prevent further genetic mutation and disease progression. The FHIT gene is a tumor suppressor gene located in FRA3B region which is the most active common fragile site, where DNA damage leading to aberrant transcripts and translocations frequently occur. The WWOX is a tumor suppressor gene that plays a central role in tumor suppression through transcriptional repression and apoptosis, with its apoptotic function the more prominent of the two. This study aimed to evaluate and compare the immunohistochemical expression of FHIT and WWOX in normal oral mucosa, oral epithelial dysplasia and oral squamous cell carcinoma and to correlate the expression of the mentioned markers with the clinicopathological features and to show the expression of studied markers with each other. Materials and methods: Fifty formalin-fixed, paraffin embedded tissue blocks (10 cases of normal oral mucosa, 19 cases of oral epithelial dysplasia, and 21 cases of oral squamous cell carcinoma) were included in this study. Immunohistochemical staining was performed using anti FHIT polyclonal antibody, and anti WWOX polyclonal antibody. Results: Positive IHC of FHIT was detected with high score in all cases of NOM, 16 cases (84%) of OED and 18 cases (86%) of OSCC. For WWOX expression positive IHC detected with high score in all cases (100%) of NOM, 14 cases (74%) of OED and 15 cases (71%) of OSCC. There was statistically highly significant correlation of both markers in OED and non significant correlation in OSCC, with significant differences among studied groups. Conclusions: These results signifying both markers cooperative tumor suppressive role and potential pathological transition from normal oral mucosa to dysplastic epithelium and subsequently cause malignant oral lesions.
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حظيت السمية الخلوية للمستخلصات النباتية باهتمام كبير في السنوات الأخيرة لتقييم نشاطها ضد الأورام. تركز الوقاية الكيميائية من السرطان على السمية الخلوية للمستخلصات النباتية لتكون سامة تجاه خطوط الخلايا السرطانية دون أن تؤثر على الخلايا الطبيعية. الهدف من هذه الدراسة هو تقييم السمية الخلوية لمستخلصي الزنجبيل و أوراق الزيتون ومزيجهما بنسبة 1: 1 تجاه خطوط خلايا RD وتقدير فعالية هذه المسخلصات ضد الاجهاد التا
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The present study aimed to evaluate sera TGF- ?1 concentration in patients with urinary bladder carcinoma (UBC). All malignant of them was transitional cell carcinoma (TCC) type , patients with urinary bladder disorders (UBD ) and healthy control , and to study the correlation between sera TGF-?1 levels and tumor stages and grades in UBC patients . A direct ELISA test was used to quantify the seraTGF-?1 concentrations in sera of 58 patients with urinary bladder carcinoma UBC of different grades (G) and stages (T) all malignant of them was transitional cell carcinoma (TCC) type , 15 from patients with UBD and 15 healthy subjects . Sera levels of TGF-?1 were elevated in patients with UBC and UBD compared to healthy (P ? 0
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The aim of this paper is to introduce and study some of the Fibrewise minimal regular,Fibrewise maximal regular, Fibrewise minimal completely regular, Fibrewise maximal completely regular, Fibrewise minimal normal, Fibrewise maximal normal, Fibrewise minimal functionally normal, and Fibrewise maximal functionally normal. This is done by providing some definitions of the concepts and examples related to them, as well as discussing some properties and mentioning some explanatory diagrams for those concepts.
The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
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