Assessment of the knowledge and attitude of the pregnant women who referred to Iran University of Medical Sciences in 2005 toward Islams hygienic instructions during their pregnancy and breast feeding periods

Background and aim: Pregnancy and infancy are as diving profits, which are of the most enjoyable times of women. Islams living doctrine recommends some adwises for pregnant women to have healthy generation with good physical, mental and social dimensions. Therefore, the aim of this study was to evaluate the knowledge and attitude of the pregnant women who referred to Iran University of Medical Sciences in 2005 toward Islam’s hygienic instructions during their pregnancy and breast feeding period. Methods: In this descriptive-analytical study, a total of 300 pregnant women were selected from parental care unite using multistage sampling. The data was gathered through self-reporting questionnaire which contained some questions about the individuals characteristics, attitude and awareness. Subsequently, using χ2, Pearson correlation and Spearman tests, data were analyzed. Results: The percentage of the knowledge about the Islams healthy instructions during pregnancy was graded: good 20.6%, average 64.7% and poor 14.7%. During breast-feeding, the knowledge was 6.3% good, 77% average and 16.7% poor. There was a positive relationship between the women’s level of education and their knowledge about Islamic trainings. The attitude of the women about the instructions during their pregnancy was positive in 68.3% and negative in 31.7% of them. This attitude during breast feeding was positive in 64% and negative in 36% of the women studied. There was relationship between the knowledge toward the instructions and the level of education during pregnancy and also between this knowledge and the number of pregnancy and the level of education (p<0.01). Conclusion: In addition to moderate knowledge and positive attitude of most of samples and undeniable religious force, on promoting health, recommended that health managers programmed to pregnant women care based on Islamic recommendations and health care workers have more attention in their education training

Rare Primary Dyslipidaemias Associated with Low LDL and HDL Cholesterol Values in Portugal

Background: Dyslipidaemia represents a group of disorders of lipid metabolism, characterized by either an increase or decrease in lipid particles, usually associated with triglycerides, LDL cholesterol (LDL-C) and/or HDL cholesterol (HDL-C). Most hyperlipidaemias and HDL deficiencies confer an increased cardiovascular risk, while hypolipidaemia, such as abeta or hypobetalipoproteinemia, may present different manifestations ranging from poor weight progression to neurological manifestations. The aim of this study is to present 7 cases with rare dyslipidaemias associated with low LDL or low HDL cholesterol values, referred to our laboratory for the genetic identification of the cause of the dyslipidaemia. Methods: Lipid profile was determined for each individual in an automated equipment Integra Cobas (Roche). Molecular analysis was performed by NGS with a target panel of 57 genes involved in lipid metabolism (Sure select QXT, Agilent) and samples were run in a NextSEQ Sequencer (Illumina). Only genes associated to rare forms of low HDL-c or LDL-c were analysed for this work, namely: ABCA1, APOA1, LCAT, SCARB1, APOB, PCSK9, MTTP, SAR1B, and ANGPTL3. All rare variants (MAFA) and the other is a possible compound heterozygous for APOB variants c.2604+1G>A and c.4651C>T/p.(Gln1551*). In two patients only a variant in heterozygosity (c.3365delG/p.(Gly1122Vfs*62) and c.11095A>T/p.(Arg3699*)). In the remaining patient, no variants were identified. NGS proved to be a fundamental key for genetic testing of rare lipid disorders, allowing us to find the genetic cause of disease in 6/7 patients with low HDL-c and LDL-c. Patients with these rare conditions should be identified as early as possible in order to minimize or prevent clinical manifestations. The unsolved case is still under investigation.info:eu-repo/semantics/publishedVersio

Work functions, ionization potentials, and in-between: Scaling relations based on the image charge model

We revisit a model in which the ionization energy of a metal particle is associated with the work done by the image charge force in moving the electron from infinity to a small cut-off distance just outside the surface. We show that this model can be compactly, and productively, employed to study the size dependence of electron removal energies over the range encompassing bulk surfaces, finite clusters, and individual atoms. It accounts in a straightforward manner for the empirically known correlation between the atomic ionization potential (IP) and the metal work function (WF), IP/WF$\sim$2. We formulate simple expressions for the model parameters, requiring only a single property (the atomic polarizability or the nearest neighbor distance) as input. Without any additional adjustable parameters, the model yields both the IP and the WF within $\sim$10% for all metallic elements, as well as matches the size evolution of the ionization potentials of finite metal clusters for a large fraction of the experimental data. The parametrization takes advantage of a remarkably constant numerical correlation between the nearest-neighbor distance in a crystal, the cube root of the atomic polarizability, and the image force cutoff length. The paper also includes an analytical derivation of the relation of the outer radius of a cluster of close-packed spheres to its geometric structure.Comment: Original submission: 8 pages with 7 figures incorporated in the text. Revised submission (added one more paragraph about alloy work functions): 18 double spaced pages + 8 separate figures. Accepted for publication in PR

Assessing L2 Argumentation in the UAE Context

In this rapidly changing world, argumentation and critical thinking skills are undeniably crucial for new generations of Emirati students. These skills lay the groundwork for a competitive economy, which is a priority for the UAE in its Vision 2021. Specifically, today’s modern workplaces require workers to evaluate different propositions and develop their own after weighing up these various ideas, and thus the ability to defend arguments in English has become increasingly important for UAE university students in English-medium universities as well as their future professional contexts. Despite this importance, research regarding argumentation and the related critical thinking skills is sorely lacking in the UAE. This chapter delineates how written argumentation was assessed in a timed essay in a mandatory argumentative writing course taken by university freshmen in a government university in the UAE, and how the feedback gleaned from this common assessment was mapped to the teaching curriculum to shed light on the teaching effectiveness and to provide directions for future teaching

Agarose-Based biomaterials: Opportunities and challenges in cartilage tissue engineering

The lack of adequate blood/lymphatic vessels as well as low-potential articular cartilage regeneration underlines the necessity to search for alternative biomaterials. Owing to their unique features, such as reversible thermogelling behavior and tissue-like mechanical behavior, agarose-based biomaterials have played a key role in cartilage tissue repair. Accordingly, the need for fabricating novel highly efficient injectable agarose-based biomaterials as hydrogels for restoration of injured cartilage tissue has been recognized. In this review, the resources and conspicuous properties of the agarose-based biomaterials were reviewed. First, different types of signals together with their functionalities in the maintenance of cartilage homeostasis were explained. Then, various cellular signaling pathways and their significant role in cartilage tissue engineering were overviewed. Next, the molecular structure and its gelling behavior have been discussed. Eventually, the latest advancements, the lingering challenges, and future ahead of agarose derivatives from the cartilage regeneration perspective have been discussed. © 2020 by the authors

CovidCTNet: an open-source deep learning approach to diagnose covid-19 using small cohort of CT images

Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method; however, its accuracy in detection is only ~70�75. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80�98, but similar accuracy of 70. To enhance the accuracy of CT imaging detection, we developed an open-source framework, CovidCTNet, composed of a set of deep learning algorithms that accurately differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 95 compared to radiologists (70). CovidCTNet is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. To facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and model parameter details as open-source. Open-source sharing of CovidCTNet enables developers to rapidly improve and optimize services while preserving user privacy and data ownership. © 2021, The Author(s)