Hormonal parameters and sex hormone receptor gene polymorphisms in men with autoimmune diseases.

Autoimmune diseases (ADs) are more common in women than in men. Sex hormones may play a role. Sex hormone receptors (SHR) are expressed in cells of the immune system. We investigated the possible role of hormonal parameters and of common polymorphisms of the estrogen receptor alpha (ESR1), beta (ESR2), and androgen receptor (AR) genes in the appearance of AD in men. 277 men were studied; 125 with ≥1 AD: Hashimoto's autoimmune thyroiditis (n = 65), Graves' disease (n = 12), SLE (n = 10), and RA (n = 38). 152 were controls. Hormonal and biochemical parameters were measured after discontinuation for ≥1 month of any corticosteroid therapy. ESR1 PvuII, ESR2 AluI, and the AR (CAG)n repeats polymorphisms were analyzed. AD patients had higher estradiol levels (31.32 ± 12.10, controls 20.37 ± 7.91 pg/ml, p < 0.001). In multivariate analysis, significant predictors for AD were estrogen and BMI. The allele frequency of ESR1 PvuII and ESR2 AluI did not differ between patients and controls (AD: 47.8 %, 37.6 %; controls 49.8 %, 39.9 %). The distribution of (CAG)n did not differ between groups. In AD group, shorter (CAG)n alleles were associated with younger age of AD onset (short: 38.52 ± 14.8, long: 47.14 ± 17.34 years, p = 0.048). Carriers of ESR1 PvuII presented less frequently ≥2 AD (carriers 6.5 %, non-carriers 25.1 %, p = 0.019); carriers of AluI had lower SHBG levels and higher ΒΜΙ compared to non-carriers (p < 0.04). Higher estradiol may play a role in AD in men. Distribution of SHR gene polymorphisms is similar between patients and controls. Shorter AR (CAG)n repeats may predispose for younger AD onset. Coexistence of ≥2 AD is less frequent in carriers of ESR1 PvuII. ESR2 AluI may adversely affect obesity parameters.

A Multicenter, Cross-Sectional Study of the Incidence of Major Macular Diseases That Cause Visual Impairment and Require Therapeutic Intervention in Greece: The ADVICE Study.

PURPOSE: This multicenter, epidemiological, cross-sectional study aimed to estimate the annual cumulative incidence of major macular diseases that cause visual impairment and require therapeutic intervention in the routine care of Greece. METHODS: The study was carried out between December 2012 and May 2015 in 20 ophthalmology clinics. Over a one-year recruitment period per study site, all treatment naïve adult patients newly diagnosed with wet age-related macular degeneration, visual impairment due to diabetic macular edema or macular edema secondary to retinal vein occlusion requiring therapeutic management and who had not been diagnosed or treated for the same disease in the past were enrolled after providing informed consent. Study data were collected during the single study visit. RESULTS: A total of 1532 incident cases were enrolled. The estimated annual cumulative incidence of wet age-related macular degeneration, diabetic macular edema and macular edema secondary to retinal vein occlusion requiring therapeutic management was 0.82 [95% confidence interval (CI): 0.76, 0.88; n=723], 0.63 (95% CI: 0.58, 0.69; n=559), and 0.29 (95% CI: 0.25, 0.32; n=250) per 10,000 cases, respectively. CONCLUSION: The study provides estimates of the incidence of major macular diseases causing visual impairment and requiring treatment in outpatient hospital settings in Greece, indicating a considerable socioeconomic burden to the healthcare system.

A collaborative biomedical image mining framework: application on the image analysis of microscopic kidney biopsies.

The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, like data acquisition, preprocessing, segmentation, feature extraction and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image data set and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this work, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image mining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework.

Statistical data mining of streaming motion data for fall detection in assistive environments.

The analysis of human motion data is interesting for the purpose of activity recognition or emergency event detection, especially in the case of elderly or disabled people living independently in their homes. Several techniques have been proposed for identifying such distress situations using either motion, audio or video sensors on the monitored subject (wearable sensors) or the surrounding environment. The output of such sensors is data streams that require real time recognition, especially in emergency situations, thus traditional classification approaches may not be applicable for immediate alarm triggering or fall prevention. This paper presents a statistical mining methodology that may be used for the specific problem of real time fall detection. Visual data captured from the user's environment, using overhead cameras along with motion data are collected from accelerometers on the subject's body and are fed to the fall detection system. The paper includes the details of the stream data mining methodology incorporated in the system along with an initial evaluation of the achieved accuracy in detecting falls.

Classification of dermatological images using advanced clustering techniques.

Computer vision-based diagnosis systems have been widely used in dermatology, aiming at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumor. This paper proposes a novel clustering technique for the characterization and categorization of pigmented skin lesions in dermatological images. Appropriate image processing techniques (i.e. segmentation, border detection, color and texture processing) are utilized for feature extraction. The proposed method uses Principal Component Analysis and is considered appropriate, since it is suitable for problems with high dimensional data. Initial experimental results have proved the superiority of this method against traditional ones.

Classification of apoptosis using advanced clustering techniques on digital microscopic images.

Programmed cell death, also known as apoptosis is of fundamental importance in many biological processes and also highly associated with serious diseases like cancer and HIV. The current paper presents an innovative method for apoptosis phenomenon characterization based on apoptotic cell quantification and detection using active contours. Subsequently, we employ appropriate data mining techniques and perform characterization of apoptosis on digital microscopic images. A particular class of clustering algorithms, utilizing information driven by the Principal Component Analysis, has been very successful in dealing with such data. In this work, we employ a recently proposed clustering algorithm to solve this real world clustering task.

Estrogen receptor beta gene variants may be associated with more favorable metabolic profile in postmenopausal women undergoing coronary angiography.

AIM: Estrogen action is exerted on the vasculature through estrogen receptors ER alpha and ER beta. We have previously reported significant association of ER alpha gene (ESR1) variants with more severe coronary artery disease (CAD) in postmenopausal women. The influence of ER beta gene (ESR2) variants on the cardiovascular system is not well established. We investigated the association of common ESR2 variants with risk factors for cardiovascular disease and with the severity of CAD in postmenopausal women. METHODS: ESR2 polymorphisms Alu I (1730 G > A) and Rsa I (1082 G > A) were studied in 174 postmenopausal women undergoing coronary angiography (age 45 - 88 yrs). The severity of CAD (0 - 3 vessels with > 50 % stenosis), indices of obesity and other predisposing risk factors for cardiovascular disease, biochemical and hormonal parameters were recorded. RESULTS: 75 women had 0, 39 had one, 37 had two and 23 had three vessels with severe stenosis in the coronary angiography. There was no association between Alu I (allele frequency = 40.2 %) and Rsa I (allele frequency = 2.6 %) variants and CAD severity. Carriers of Alu I had lower BMI (p = 0.044), lower waist perimeter (p = 0.029) and lower total cholesterol (p = 0.033) and LDL levels (p = 0.029). There was no association between Rsa I polymorphism and any metabolic risk factors. CONCLUSIONS: ESR2 Alu I polymorphism may have a favorable influence on risk factors for cardiovascular disease such as obesity indices and cholesterol levels. It does not appear to be associated with the severity of CAD in women.

Medical Image Compression using Wavelet Transform on Mobile Devices with ROI coding support.

Medical applications have already been integrated into mobile devices (e.g. Tablet PC's and PDA's) and are being used by medical personnel in treatment centers, for retrieving and examining patient data and medical images. Network transmission and image data processing are key issues in such platforms, due to the significant image file sizes. Wavelet transform has been considered to be a highly efficient technique of image compression resulting in both lossless and lossy compressed images of great accuracy, enabling its use on medical images. This paper discusses a Picture Archiving and Communication Systems (PACS) application designed for viewing DICOM compliant medical images using Wavelet compression with ROI coding support, on mobile devices. In addition, it presents initial results from its pilot application and demonstrates its performance over heterogeneous radio network segments, like IEEE 802.11b, GPRS and DVB-H.

Molecular heterogeneity of the glucose-6-phosphate dehydrogenase deficiency in the Hellenic population.

We report results from a systematic study to identify the molecular basis of glucose-6-phosphate dehydrogenase (G6PD) deficiency on a sample of 299 male subjects from the Hellenic population. Our stepwise approach involved partial biochemical characterization and quantitation of the enzyme's activity, MboII restriction endonuclease digestion to identify the G6PD Mediterranean variant, which represents the most frequent G6PD variant in our population and a nonradioactive polymerase chain reaction-single-strand conformation polymorphism methodology for the detection of the underlying molecular defect(s) in the rest of the non-Mediterranean G6PD-deficient individuals. Through this approach, six different G6PD variants were identified (G6PD Mediterranean, G6PD Hermoupolis, G6PD Cassano, G6PD Seattle, G6PD Ierapetra and G6PD Acrokorinthos), two of which were new (G6PD Hermoupolis, G6PD Acrokorinthos). In essence, this study underlines the remarkable genetic heterogeneity of the G6PD deficiency in the Hellenic population, while the finding of the double mutant, G6PD Hermoupolis, may help to outline the relationship and evolution of mutations in the human G6PD locus.