Low energy ion scattering

Low energy ion scattering (LEIS) is the study of the composition and structure of a surface by the detection of low energy ions with energies ranging from 100 eV to 10 keV elastically scattered off the surface. The extreme sensitivity to the outermost atomic layer makes it as a unique tool for surface analysis. In this paper, concepts of shadowing, blocking, and also polar and azimuthal scans have been described. Surface order and surface atom spacings are revealed by using these concepts and measuring the intensity of backscattered projectiles as a function of the incident and azimuthal angles

Incidence of acute myocardial infarction in Islamic Republic of Iran: a study using national registry data in 2012

Population-based data on Myocardial infarction rates in the Islamic Republic of Iran have not been reported on a national or provincial scale. In a cross-sectional study, data were collected on 20 760 new cases Of myocardial infarction (ICD10 codes 121-22) admitted to hospitals and registered by the Iranian Myocardial Infarction Registry in 2012 The crude and age adjusted incidence for the 31 provinces and the whole country were directly calculated per 100 000 people using the WHO standard population. Overall males comprised 72.4% of cases and had a significantly lower Mean age at incidence than women 59.6 (SD 13.3) years versus 65.4 (SD 12.6) years]. The male:female incidence ratio was 2.63. The age-standardized Myocardial infarction incidence rate was 73.3 per 100 000 in country (95% Cl: 72.3%-74.3%) and varied Signifitantly from 24.5 to 152.5 per 100 000 across the I.ji provirites. The Study provides baseline data for monitoring and managing cardiovascular diseases in the country

Al, Pd Elements Deposited on the Surface of Al-Pd-Mn Quasicrystal

Pd element has been deposited on the clean surface of an Al-Pd-Mn quasicrystal by evaporation and using low energy ion scattering (LEIS) technique. The sample was prepared through a combination of sputtering and annealing. Then a Pd monolayer was deposited on the surface and measured the ratio of Al/Pd for clean annealed surface at the room temperature. Drawing the Al/Pd ratio versus time deposition showed a linear behavior, indicating Pd growth is Layer Growth (Frank-Van der-Merwe Growth). Similar experiment for Al has also been done. Results show that growth of Al on the sample is also conform Layer Growth (LG

Low vitamin B12 and lipid metabolism: evidence from pre-clinical and clinical studies

Obesity is a worldwide epidemic responsible for 5% of global mortality. The risks of developing other key metabolic disorders like diabetes, hypertension and cardiovascular diseases (CVDs) are increased by obesity, causing a great public health concern. A series of epidemiological studies and animal models have demonstrated a relationship between the importance of vitamin B12 (B12) and various components of metabolic syndrome. High prevalence of low B12 levels has been shown in European (27%) and South Indian (32%) patients with type 2 diabetes (T2D). A longitudinal prospective study in pregnant women has shown that low B12 status could independently predict the development of T2D five years after delivery. Likewise, children born to mothers with low B12 levels may have excess fat accumulation which in turn can result in higher insulin resistance and risk of T2D and/or CVD in adulthood. However, the independent role of B12 on lipid metabolism, a key risk factor for cardiometabolic disorders, has not been explored to a larger extent. In this review, we provide evidence from pre-clinical and clinical studies on the role of low B12 status on lipid metabolism and insights on the possible epigenetic mechanisms including DNA methylation, micro-RNA and histone modifications. Although, there are only a few association studies of B12 on epigenetic mechanisms, novel approaches to understand the functional changes caused by these epigenetic markers are warranted

Evaluation of Predictor Factors of Non-Diabetic Nephropathy in Diabetic Patient’s Biopsy Specimen in Labbafinejad Hospital

Background and Aim: Nephropathy is one of the major complications in diabetic patients that causes high mortality worldwide. In diabetic patients, differentiating non-diabetic nephropathy from diabetic nephropathy is clinically essential in treating patients. The present study aimed to examine clinical, laboratory, demographic variables and their relationship with the type of non-diabetic nephropathy in diabetic patients. Methods: Clinical, demographic and laboratory data of 104 diabetic patients who underwent renal biopsy in Labbafinejad Hospital in Tehran in 2009-2010 were assessed. Patients were categorized into two groups based on the type of nephropathy (whether diabetic or non-diabetic). The recorded data were statistically compared between the two groups at the time of kidney biopsy and six months later. Results: In this study, 104 patients were studied. The mean age of patients was 57.2 ± 13.4 years, and 50% of patients were male. Shorter duration of diabetes, no insulin use, renal failure, higher mean arterial pressure, smaller kidneys, lack of diabetic retinopathy, lower GFR and higher serum creatinine in patients with diabetic nephropathy were identical with non-diabetic nephropathy group (in all cases) (P < 0.05). Conclusion: The need for kidney biopsy in diabetic patients can be determined with acceptable accuracy using the mentioned demographic, clinical, imaging and laboratory data. This study showed that the six-month GFR index could be used as a prognostic marker in patients

Addressing key issues in the consanguinity-related risk of autosomal recessive disorders in consanguineous communities: lessons from a qualitative study of British Pakistanis

Currently there is no consensus regarding services required to help families with consanguineous marriages manage their increased genetic reproductive risk. Genetic services for communities with a preference for consanguineous marriage in the UK remain patchy, often poor. Receiving two disparate explanations of the cause of recessive disorders (cousin marriage and recessive inheritance) leads to confusion among families. Further, the realisation that couples in non-consanguineous relationships have affected children leads to mistrust of professional advice. British Pakistani families at-risk for recessive disorders lack an understanding of recessive disorders and their inheritance. Such an understanding is empowering and can be shared within the extended family to enable informed choice. In a three-site qualitative study of British Pakistanis, we explored family and health professional perspectives on recessively inherited conditions. Our findings suggest, first, that family networks hold strong potential for cascading genetic information, making the adoption of a family centred approach an efficient strategy for this community. However, this is dependent on provision of high quality and timely information from health care providers. Secondly, families’ experience was of ill-coordinated and time-starved services, with few having access to specialist provision from Regional Genetics Services; these perspectives were consistent with health professionals’ views of services. Thirdly, we confirm previous findings that genetic information is difficult to communicate and comprehend, further complicated by the need to communicate the relationship between cousin marriage and recessive disorders. A communication tool we developed and piloted is described and offered as a useful resource for communicating complex genetic information

Deep Learning Model With Adaptive Regularization for EEG-Based Emotion Recognition Using Temporal and Frequency Features

Since EEG signal acquisition is non-invasive and portable, it is convenient to be used for different applications. Recognizing emotions based on Brain-Computer Interface (BCI) is an important active BCI paradigm for recognizing the inner state of persons. There are extensive studies about emotion recognition, most of which heavily rely on staged complex handcrafted EEG feature extraction and classifier design. In this paper, we propose a hybrid multi-input deep model with convolution neural networks (CNNs) and bidirectional Long Short-term Memory (Bi-LSTM). CNNs extract time-invariant features from raw EEG data, and Bi-LSTM allows long-range lateral interactions between features. First, we propose a novel hybrid multi-input deep learning approach for emotion recognition from raw EEG signals. Second, in the first layers, we use two CNNs with small and large filter sizes to extract temporal and frequency features from each raw EEG epoch of 62-channel 2-s and merge with differential entropy of EEG band. Third, we apply the adaptive regularization method over each parallel CNN’s layer to consider the spatial information of EEG acquisition electrodes. The proposed method is evaluated on two public datasets, SEED and DEAP. Our results show that our technique can significantly improve the accuracy in comparison with the baseline where no adaptive regularization techniques are used

Rare single gene disorders:estimating baseline prevalence and outcomes worldwide

As child mortality rates overall are decreasing, non-communicable conditions, such as genetic disorders, constitute an increasing proportion of child mortality, morbidity and disability. To date, policy and public health programmes have focused on common genetic disorders. Rare single gene disorders are an important source of morbidity and premature mortality for affected families. When considered collectively, they account for an important public health burden, which is frequently under-recognised. To document the collective frequency and health burden of rare single gene disorders, it is necessary to aggregate them into large manageable groupings and take account of their family implications, effective interventions and service needs. Here, we present an approach to estimate the burden of these conditions up to 5 years of age in settings without empirical data. This approaches uses population-level demographic data, combined with assumptions based on empirical data from settings with data available, to provide population-level estimates which programmes and policy-makers when planning services can use

Exploring Dietary Patterns with the Rapid Eating and Activity Assessment for Patients (REAP) Tool in a Dental School Clinic

Background: Dietary pattern assessment by healthcare providers leads to a better understanding of usual intake and evaluation of nutritional status, systemic health, and disease. Interprofessional team members can use such information to provide interventions leading to improved health outcomes. Objective: The aim was to explore the dietary patterns of adults seen in a dental clinic using the Rapid Eating and Activity Assessment for Patients (REAP) tool. Methods: This was a cross-sectional study of data from 220 adult patients (aged 18-89 years) who had a diet evaluation completed in a dental school clinic. Demographic information and REAP responses were obtained from the electronic health record and reported using frequency distributions. Results: The study sample (N=220) was 50.0% male (n= 110). The median (IQR) age and BMI were 56.0 years (IQR=48.2, 66.0) and 28.0 kg/m2 (IQR= 24.3, 32.8 kg/m2), respectively; 73.5% had a BMI considered overweight or obese. Approximately one-third reported usually/sometimes eating sweets more than twice/day (n=74, 35.9%) and drinking more than 16 ounces of SSBs (n=74, 34.1%). Most reported usually/sometimes eating less than 3 servings of whole grains (n=165, 75.0%), 2-3 servings of fruit (n=155, 71.1%), or 3-4 servings of vegetables (n=121, 70.8%) daily. Seventy-two percent (n=156) indicated they were willing to make dietary changes. Conclusion: This study revealed that the dietary patterns of adults seen in a dental school clinic did not align with the Dietary Guidelines for Americans recommendations. Diet assessment is feasible in this setting and may be an important part of interprofessional education