Defining the role of lipids and metabolic factors as risk factors for prostate cancer incidence and aggressiveness

Prostate Cancer (PCa) is the second most common cancer and among the top causes of cancer-related mortality among men. In recent years there has been a growing debate about the effect of metabolic factors (diabetes, hypertension, and hyperlipidaemia) and obesity on prostate cancer risk and aggressiveness. This thesis aims to uncover the role of metabolic factors, sex hormones, and obesity as risk factors for prostate cancer incidence and aggressiveness, and how the metabolic factors and sex hormones are important confounders in prostate cancer risk assessment and screening models. It also aims to review how assessing different aspects of obesity including peri-prostatic fat influences prostate cancer incidence and aggressiveness. The thesis consists of five chapters: • Chapter 1 is a literature review and it includes; * Section 1 an introduction to prostate cancer risk factors. * Section 2 a summary of prostate cancer as a metabolic disease. * Section 3 a summary of the debate around prostate cancer screening. * Section 4 a summary of the debate around the role of sex hormones in prostate cancer pathogenesis. * Section 5 (published review) a review on the role of periprostatic versus subcutaneous fat and its association with prostate cancer risk. • Chapter 2 (published research): describes the inverse relationship between obesity and PSA levels and the underlying mechanisms • Chapter 3 (research submitted for publication) describes how obesity attenuates prostate cancer screening and leads to an underestimation of prostate cancer risk. • Chapter 4 (research prepared for publication) describes how metabolic factors may attenuate prostate cancer screening efficacy. • Chapter 5 (research submitted for publication) describes the association between sex hormones and prostate cancer characteristics at the time of diagnosis. The research work done through this project and as part of this thesis, have shown that: • Obesity leads to lower PSA levels through two main mechanisms, first; the change in the sex hormone levels among men with obesity (mainly the increase in the estradiol-to-testosterone ratio), second; the increase in the plasma volume among men with obesity. • The lowers levels of PSA among men with obesity (especially moderate and severe obesity) could lead to underestimation of prostate cancer risk and potentially delay prostate cancer diagnosis. • Metabolically healthy men (those without diabetes, hypertension or obesity) appear to benefit from prostate cancer screening in terms of reducing their risk of prostate cancer-specific mortality, in comparison to those who have one or more of these conditions. • Sex hormones (mainly the higher estradiol-to-testosterone ratio) are associated with a higher Gleason score at the time of diagnosis. The results of this project give opportunities to introduce and identify new risk reduction modalities and interventions, as well as identify factors that may attenuate the efficacy of prostate cancer screening. The effect of these factors needs to be confirmed in randomised controlled trials. Longer term, applying the results of this project in clinical practice may refine the implementation and/or interpretation prostate cancer screening, and improve the available risk reduction interventions.Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 201

Ektopowa grasica : rzadki przypadek masy szyjnej u noworodka

Background: A defective migration of the thymus during fetal life leads to the remnant tissue, situated along the path of descent, forming an abnormal mass. Case Report: The case of a neonate with an upper lateral neck mass is presented. Ultrasonography, CT, and MRI could only localize this mass as lying deeply and laterally within the parotid-submandibular area. The exact nature of the mass was suggested only after histopathology, which revealed normal thymic tissue. Conclusion: Though a rare entity, ectopic thymus should be considered in the differential diagnosis of neck masses in young patients. In view of occasional neoplastic transformation, it is important to localize and recognize ectopic thymic tissue

Suppression of Mobile Phone Radiation in Human Head Using Metamaterial

This paper investigates the effect of radio frequency waves emitted by cellular phone antennas on the human head by using a 3D human head model to assess the specific absorption rate (SAR) in various human tissues. The simulation of SAR was performed using a PIFA (Planar Inverted-F Antenna) modelled in HFSS (High Frequency Structure Simulator) operating in the cellular frequency bands. To reduce the electromagnetic coupling between the mobile phone antenna and the human head, metamaterials were inserted at various locations in the vicinity of the antenna and study the effects of the metamaterial on the SAR level. The SAR in the human head was reduced by positioning the metamaterial between the PIFA antenna and the human head, with the metamaterial operating at a scale smaller than the wavelength of the antenna's operating frequency. The metamaterial structures exhibit resonance through internal capacitance and inductance, and a stop band was designed to align with the antenna's operating frequency band

Investigation of Environmental and Biological Effects of Rare Earth Elements (REEs) with a Special Focus on Industrial and Mining Pollutions in Iran: A Review

The present article is a review study on the types of rare earth elements (REEs), environmental and biological effects as well as the sources of emission of these elements as pollution in nature. The purpose of this study is to provide a vision in environmental planning and control of pollution caused by REEs. The evaluation of rare earth elements was studied in human life and its environmental and biological effects, which have particular importance and are entering the life cycle through industrial and mining pollution sources. Since mining activities intensify the dispersion of these elements in the environment and the existence of industrial factories located around urban drainage system plays a unique role in creating and spreading pollution caused by rare earth elements; As a result, two case studies were conducted on two mining and industrial areas. The first case is the Choghart mine in Yazd province as an example of mining pollution,and the second case study is performed on the Kor river as an example of industrial pollution which is caused by industrial activities around it, Then the results are well explained to show both two environments of litho and hydro. Due to this fact that produced environmental pollution can cause exchange pollutant compounds with the surrounding environment besides its long-lasting destructive effects; It can cause irreversible biological effects on living organisms. By targeting this evaluation, several techniques can be proposed to prevent the entry and dispersal of rare earth elements from pollution sources besides methods to reduce the damage of these elements to the ecosystem

Mental Health State Classification Using Facial Emotion Recognition and Detection

Analyzing and understanding emotion can help in various aspects, such as realizing one’s attitude, behavior, etc. By understanding one’s emotions, one's mental health state can be calculated, which can help in the medical field by classifying whether one is mentally stable or not. Facial Recognition is one of the many fields of computer vision that utilizes convolutional networks or Conv Nets to perform, train, and learn. Conv Nets and other machine learning algorithms have evolved to adapt better to larger datasets. One of the advancements in Conv Nets and machines is the introduction of various Conv architectures like VGGNet. Thus, this study will present a mental health state classification approach based on facial emotion recognition. The methodology comprises several interconnected components, including preprocessing, feature extraction using Principal Component Analysis (PCA) and VGGNet, and classification using Support Vector Machines (SVM) and Multilayer Perceptron (MLP). The FER2013 dataset tests multiple models’ performances, and the best model is employed in the mental health state classification. The best model, which combines Visual Geometry Group Network (VGGNet) feature extraction with SVM classification, achieved an accuracy of 66%, demonstrating the effectiveness of the proposed methodology. By leveraging facial emotion recognition and machine learning techniques, the study aims to develop an effective method

Investigation of Magneto-/Radio-Metric Behavior in Order to Identify an Estimator Model Using K-Means Clustering and Artificial Neural Network (ANN) (Iron Ore Deposit, Yazd, IRAN)

The study area is located near Toot village in the Yazd province of Iran, which is considered in terms of its iron mineralization potential. In this area, due to radioactivity, radiometric surveys were performed in a part of the area where magnetometric studies have also been performed. According to geological studies, the presence of magnetic anomalies can have a complex relationship with the intensity of radioactivity of radioactive elements. Using the K-means clustering method, the centers of the clusters were calculated with and without considering the coordinates of radiometric points. Finally, the behavior of the two variables of magnetic field strength and radioactivity of radioactive elements relative to each other was studied, and a mathematical relationship was presented to analyze the behavior of these two variables relative to each other. On the other hand, the increasing and then decreasing behavior of the intensity of the Earth’s magnetic field relative to the intensity of radioactivity of radioactive elements shows that it is possible to generalize the results of magnetometric surveys to radiometry without radiometric re-sampling in this region and neighboring areas. For this purpose, using the general regression neural network and backpropagation neural network (BPNN) methods, radiometric data were estimated with very good accuracy. The general regression neural network (GRNN) method, with more precision in estimation, was used as a model for estimating the radiation intensity of radioactive elements in other neighboring areas

Evaluation and Simulation of SAR Among Patients Using MRI Machines

The expanding use of electric devices in everyday life has led to an augmented interest in investigating the interaction between electromagnetic fields and biological tissues. In order to ensure the secure advancement of electromagnetic devices and avoid potential health hazards, comprehending the distribution of electromagnetic fields in the human body is imperative. Magnetic resonance imaging (MRI) is a widely accepted technique for medical diagnosis. The use of high-field MRI has become increasingly popular in recent years as it can enhance signal-to-noise ratio (SNR) and image resolution, thereby decreasing acquisition time. This paper aims to investigate the impact of electromagnetic waves on the human body, particularly the specific absorption rate (SAR). Accurately calculating SAR in humans poses significant challenges and requires advanced mathematical models and computer simulations. To this end, the study utilized the Microwave Studio Transient Solver available in CST Studio Suite 2020 to solve the electromagnetic problem in different human models

Geochemical relations among elements in stream sediment samples from Siojan Prospecting Area, Iran using geostatistical methods

Stream sediment samples play an important role in identifying potential areas of metallic and non-metallic mineralization in mineral exploration studies. The relationship of geochemical elements with each other shows how the elements are distributed in the area. Also, by identifying related elements, sampling and targeted chemical analysis can be used in the next stages of exploration. The purpose of this study is to investigate the elements related to the copper element in the Siojan prospecting area, which is located in South-Khorasan province and 30 km northwest of Birjand city of Iran. In Siojan area, 120 stream sediment samples of a 60 square kilometer area were collected to detect geochemical anomalies and were consequently analyzed by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for 45 elements. Preliminary geological studies showed that the studied area has copper mineralization potential, and therefore, copper was selected as the target element in this study. Copper trace elements were identified in the area and the results were used to identify copper mineralized anomalies. For the elemental analysis data, methods of Principal Component Analysis (PCA), Factor Analysis (FA), Hierarchical Cluster Analysis (HCA) and K-Means Clustering were performed to identify the relevant elements and relationships among them. Statistical analysis of the concentration of geochemical elements in the region revealed that copper and cobalt elements were identified as two elements of the same family in terms of geochemical genetics. The average value for copper and cobalt elements in the analyzed samples was 27.2 ppm and 15.5 ppm, respectively. Finally, the relationship between copper and cobalt elements was modeled as an equation using the K-Means Clustering algorithm

Ore Genesis of the Abu Ghalaga Ferro-Ilmenite Ore Associated with Neoproterozoic Massive-Type Gabbros, South-Eastern Desert of Egypt: Evidence from Texture and Mineral Chemistry

Massif-type mafic intrusions (gabbro and anorthosite) are known for their considerable resources of vanadium-bearing iron–titanium oxide ores. Massive-type gabbroic and anorthosite rocks are frequently associated with magmatic rocks that have significant quantities of iron, titanium, and vanadium. The most promising intrusions that host Fe-Ti oxide ores are the gabbroic rocks in the south-eastern desert. The ilmenite ore deposits are hosted in arc gabbroic and anorthosite rocks. They are classified into three types, namely black ore, red ore, and disseminated ore. The black ilmenite ore is located at the deeper level, while the oxidized red ore is mainly located at or near the surface. Petrographically, the gabbro and ilmenite ores indicate a crystallization sequence of plagioclase, titaniferous pyroxene, and ilmenite. This reveals that the ilmenite is a magmatic deposit formed by the liquid gravity concentration of ilmenite following the crystallization of feldspar and pyroxene. Meanwhile, quartz, tremolite, zoisite, and opaque minerals are accessory minerals. The Fe-Ti ores are composed of ilmenite hosting exsolved hematite lamellae of variable sizes and shapes, gangue silicate minerals, and some sulfides. The X-ray diffraction (XRD) data reveal the presence of two mineral phases: ilmenite and hematite formed by the unmixing of the ferroilmenite homogeneous phase upon cooling. As a result, the ore is mostly made up of hemo-ilmenite. Using an electron microscope (SEM), as well as by observing the textures seen by the ore microscope, ilmenite is the dominant Fe-Ti oxide and contains voluminous hematite exsolved crystals. Under the scanning electron microscope, ilmenite contained intergrowths of hematite as a thin sandwich and lens shape. The formation of hematite lamellae indicates an oxidation process. Mineral chemistry-based investigations reveal late/post-magmatic activity at high temperatures. The examined ilmenite plots on the ferro-ilmenite line were created by continuous solid solution over 800 °C, whereas the analyzed magnetite and Ti-magnetite plot near the magnetite line and were formed by continuous solid solution exceeding 600 °C

Cohousing design guidelines for better social integration in the United Arab Emirates

Considering cohousing as a new typology in the United Arab Emirates’ (UAE) housing market is a challenge due to the cultural and societal dimensions. However, the variety of societies in the Emirates reflecting various habits, experiences, and traditions can allow testing such new types of housing which can be adapted to the local context, considering the needs of the society. This study aims at developing design guidelines for future cohousing in the UAE, considering the pillars of the Estidama program, i.e., social, cultural, economic, and environmental aspects, in addition to the role of architecture design. The present study is based on an empirical investigation from the viewpoint of future cohousing residents in the UAE. Semi-structured interviews considering 87 individuals were conducted. Moreover, a focus group discussion targeting eight professionals was performed. Furthermore, the Quality Function Deployment (QFD) method was applied to include the people’s voices directly when developing the design guidelines for cohousing in the UAE. The study showed that the aspects of culture and privacy are crucial in the future of cohousing in the UAE. In addition, providing local facilities such as majlis and praying rooms is vital to consider. Moreover, other aspects such as sustainable design, universal design, and safety are also valuable. For the outdoor environment, the study highlighted the importance of urban design quality, landscape solutions, shading, and natural ventilation strategies in outdoor spaces. Future cohousing in the UAE is expected to enhance social interaction and contribute to sustainability in the long-term perspective