The cervical cancer considered as the fourth female prevalent disease worldwide, it was once the most extensively recognized female cancer two in many low-income countries. Human Cytomegalovirus (HCMV) exhibits broader tropism and can cause infection in most of the human body organs. Although, human cytomegalovirus HCMV is not yet considered an oncogenic virus, there is increased evidences of HCMV infection implication in malignant diseases of different cancer types. The present study aims to evaluate the effect of CMV infection on the development of HPV16 positive cervical cancinoma. The current retrospective study enrolled a number of paraffinized cervical cancer tissues .included 30 cervical carcinomatous tissues and 10 biopsies from an

The purpose of this study was to measure serum levels of insulin-like growth factor-binding protein (IGFBP7), Insulin-like Growth Factor 1 (IGF-1), Growth Hormone (GH), Interleukin 6 (IL-6) and insulin in acromegaly patients and healthy controls. The acromegaly group had 60 patients, while the population group had 30 people who had never had acromegaly before. The concentration of IGFBP7, IGF-1, GH, IL-6, and insulin were determined. The results of the present study indicate that IGFBP7 level in the acromegaly group was significantly lower (1.690.07 ng/mL vs. 2.740.12 ng/mL, respectively, p = 0.001). IGF-1, GH, IL-6, and insulin concentrations were also significantly higher in acromegaly patients. The diagnostic accuracy (2.194) was exce

Background: The primary stability of the dental implant is a crucial factor determining the ability to initiate temporary implant-supported prosthesis and for subsequent successful osseointegration, especially in the maxillary non-molar sites. This study assessed the reliability of the insertion torque of dental implants by relating it to the implant stability quotient values measured by the Osstell device. Material and methods: This study included healthy, non-smoker patients with no history of diabetes or other metabolic, or debilitating diseases that may affect bone healing, having non-restorable fractured teeth and retained roots in the maxillary non-molar sites. Primary dental implant stability was evaluated using a torque ratc

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This research was interested in studying the phrase “I don’t know” in the Lisan al-Arab dictionary, and Lisan al-Arab was based on collecting its material from five dictionaries, including: Tahdhib al-Lugha, al-Muqamah, al-Sahih, and the footnotes of Ibn Berri, al-Nihaya and Gharib al-Hadith. The objection to this phrase, and the discussion of its various implications among linguists and the clarification of the closest and most famous content to it according to the data presented to the researcher in his research journey, and to reach this goal, the research division into a preface, five demands and a conclusion and followed the list of sources and references. To define the lexicon of Lisan al-Ar

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a