Effect of PEG conjugation on entropy driven self-assembly of coiled coils

Coiled coil helix bundles are one of the most common protein motifs known, playing significant roles in various mechanobiological processes. The desirable functionalities of -helical coiled coils are dependent upon their thermal and structural stability, which can be lost under extreme environmental conditions such as elevated temperatures, pressures, or pH. Recently, conjugation of -helices with polymers, particularly poly(ethylene glycol) (PEG), has been utilized to produce environmentally responsive protein-based block copolymers with improved structural and thermal stability. A fundamental question regarding helix–PEG conjugates is how PEG conjugation affects the secondary structure of helices [1] as well as their tertiary structure, which is the mechanism of self-assembly. In particular, the influence of PEG conjugation site on the assembly of helix bundles remains to be fully characterized. In order to address these questions, we perform coarse-grained molecular dynamics simulations of a trimeric coiled coil conjugated with PEG [2]. The effect of conjugation location is studied by covalently attaching the PEG chain either to the end or to the side of each helix in the three-helix assembly. First, we utilize annealing simulations to investigate the melting behavior and thermal stability of the coiled coil with no PEG attached, with side-conjugated PEG, and with end-conjugated PEG. Our simulation predictions for the coiled coil melting temperature are in good agreement with experimental data and show an insignificant difference between the melting temperatures of peptide itself and peptide-PEG conjugates. Next, we study the entropy driven self-assembly patterns of coiled coils with and without PEG by considering various peptide concentrations in the simulation box. Our results show that as the concentration increases, the number of assembled clusters decreases while the aggregation number in each cluster increases. Coiled coils without PEG, with end-conjugated PEG, and with side-conjugated PEG have the smallest number of clusters and the largest aggregation number, in order. These observations confirm that the peptide assembly patterns are affected not only by the presence of PEG chain, but also by the location of PEG conjugation. These findings lay the groundwork for the study of mechanisms underpinning the thermomechanical stability and assembly of coiled coils as well as other helix bundles. REFERENCES [1] Hamed, E., Xu, T., Keten, S. Poly(ethylene glycol) conjugation stabilizes the secondary structure of α-helices by reducing peptide solvent accessible surface area. Biomacromolecules. 2013, 14, 4053–4060. [2] Hamed, E, Ma, D, Keten, S. Effect of PEG conjugation on thermomechanical stability and self-assembly of coiled coil helix bundles (In submission)

Compressive Strength of Bulk-Fill and Conventional Nano-hybrid Composite Resins: An in Vitro Study

Objectives Evaluation of the properties of recently introduced bulk-fill composite resins from different aspects is important. We aimed to evaluate the compressive strength of two bulk-fill composite resins with different viscosities compared with one conventional composite resin. Methods This in vitro study evaluated two different bulk-fill composite resins and one conventional composite resin. Twelve samples were prepared for each group in a mold, measuring 4 mm in diameter and 6 mm in height. In group 1, x-tra fil bulk-fill composite resin was light-cured with 4-mm thickness for 40 seconds. Then, a 2-mm thick increment of composite resin from the same brand was placed over it and light-cured. In group 2, x-tra base composite resin was light-cured with 4 mm thickness. Then, Grandio conventional composite resin was placed over it with 2-mm thickness and light-cured. In group 3, Grandio conventional composite resin was placed in 2-mm thickness using the incremental technique and light-cured. The samples were stored in distilled water at 37°C for 48 hours, followed by the compressive strength test in a universal testing machine at a crosshead speed of 1 mm/minute. The data were analyzed with SPSS 21 using one-way ANOVA and post hoc Tukey’s test. Statistical significance was set at P<0.05. Results There were no significant differences in compressive strength values of the three study groups (P>0.05). Conclusion The bulk-fill composite resins evaluated in the present study exhibited compressive strength values similar to that of the conventional composite resin, indicating favorable compressive strength, with decreased working time

Dietary pattern of adolescent girls in relation to socio-economic factors; A comparison between North and South Tehran

Comparing dietary pattern and related socio-economic factors among adolescent girls in the North and South of Tehran, the capital of Iran. This cross-sectional and analytical study 210 adolescent girls, aged 14-17 years, from high schools in the North district of Tehran (n=105; high socio-economic level) and the South district (n=105; low socio-economic level) were selected by the two-step, cluster random sampling method. Demographic data, including mothers´ and fathers´ educational levels and parents´ occupation were gathered, using a validated self-administered questionnaire. Three questionnaires of food frequency, one-day 24-hour food recall and one-day 24-hour food record were used for assessing dietary pattern. The results showed that the frequency consumption of certain fatty foods, including dairy products and meat group, and fats in district 1 are higher than in district 19 adolescent girls; based on many differences such as life style and food accessibility. This indicated that there is a significant difference in the quality pattern of fat intake between the two districts. It is suggested to design and implement nutritional intervention programs for adolescent girls, particularly in the low socio- economic districts

Febrile Seizure: Demographic Features and Causative Factors

How to cite this article: Esmaili Gourabi H, Bidabadi E, Cheraghalipour  F, Aarabi  Y, Salamat F. Febrile Seizure: Demographic Features and Causative Factors. Iran J Child Neurol Autumn 2012; 6(4):33-37.Abstract Objective Because of geographical and periodical variation, we prompted to determine the demographic features and causative factors for febrile seizure in Rasht. Materials & Methods In this cross-sectional study, all 6–month- to 6-year-old children with the diagnosis of febrile seizure admitted to 17 Shahrivar hospital in Rasht, from August, 2009 to August, 2010 were studied. Age, sex, family history of the disease, seizure types, body temperature upon admission and infectious causes of the fever were recorded. All statistical analysis was performed with SPSS software, version 16. Results Of the 214 children (mean age, 25.24±15.40 months), 124 were boys and 109 had a positive family history. Complex seizures were seen in 39 cases. In patients with a complex febrile seizure, 59% had the repetitive type, 20.5% had the focal type and 20.5% had more than 15 minutes duration of seizures. Most of the repetitive seizures (78.3%) occurred in patients under 2 years old; the difference between under and over 2-year-old patients was statistically significant (P=0.02). Study results did not show significant differences between the two genders for simple or complex seizures. The mean body temperature upon admission was 38.2±1.32◦C (38.31±0.82 degrees in boys and 38.04±1.78 in girls). Upper respiratory infections were seen in most patients (74.29%). All cases of lower respiratory infections were boys. There was a statistically significant difference between boys and girls in causes of fever. Conclusion Most of the children had a positive family history and the most common causative factor was upper respiratory infection.  References: Huang MC, Huang CC, Thomas K. 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Studying Students' Knowledge of the Benefits, Challenges, and Applications of Big Data Analytics in Healthcare

The purpose of this study was to evaluate the students' familiarity from different universities of Mashhad with the benefits, applications and challenges of Big Data analysis. This is a cross-sectional study that was conducted on students of different fields, including Medical Engineering, Medical Informatics, Medical Records and Health Information Management in Mashhad-Iran. A questionnaire was designed. The designed questionnaire evaluated the opinion of students regarding benefits, challenges and applications of Big Data analytics. 200 students participated and participants' opinions were evaluated descriptively and analytically. Most students were between 20 and 30 years old. 43.5% had no work experience. Current and previous field of study of most of the students were HIT, HIM, and Medical Records. Most of the participants in this study were undergraduates. 61.5% were economically active, 54.5% were exposed to Big Data. The mean scores of participants in benefits, applications, and challenges section were 3.71, 3.68, and 3.71, respectively, and process management was significant in different age groups (p=0.046), information, modelling, research, and health informatics across different fields of studies were significant (p=0.015, 0.033, 0.001, 0.024) Information and research were significantly different between groups (p=0.043 and 0.019), research in groups with / without economic activity was significant (p= 0.017) and information in exposed / non-exposed to Big Data groups was significant (p=0.02). Despite the importance and benefits of Big Data analytics, students' lack of familiarity with the necessity and importance is significant. The field of study and level of study does not appear to have an effect on the degree of knowledge of individuals regarding Big Data analysis. The design of technical training courses in this field may increase the level of knowledge of individuals regarding Big Data analysis

Perfectionism and writing anxiety as predictors of Iranian EFL learners’ performance in IELTS writing module: a multi-dimensional perspective

This study aimed to investigate the relationship between Iranian EFL Learners’ perfectionism and writing anxiety and their performance in the IELTS Writing Module. To this end, sixty-eight Iranian EFL learners were selected via convenience sampling. Multidimensional Perfectionism Scale developed and validated by Hewitt and Flett (1991) and Second Language Writing Anxiety Inventory devised by Cheng (2004) were administered to the participants. The participants were then asked to write on an assigned topic from IELTS Writing Task 2. The findings of the study indicated that of the three dimensions of perfectionism (i.e., self-oriented, other-oriented and socially prescribed), none were associated with the learners’ writing performance, while a significant negative relationship was found between the learners’ writing anxiety consisting of somatic anxiety, cognitive anxiety, and avoidance behavior and their writing performance. The results of multiple regression analysis suggested that somatic anxiety, and avoidance behavior were significant predictors of writing performance. The implications highlight the strategies that should be deployed by educational policy-makers, practitioners, and examiners to alleviate anxiety in L2 classrooms, promoting a safe and stress-free educational environment

A Survey of Students’ Attitudes to Big Data Analysis in Iranian Universities

Today, with the emergence of new technologies and massive data, big data analysis has attracted the attention of researchers, industries and universities on a global scale. The present research aims to explore students’ attitude to big data analysis in different fields of study. The present cross-sectional study was conducted with students at different universities and fields of study in Iran. A questionnaire was developed. This questionnaire explored students’ attitude toward big data analysis. To this aim, 359 university students participated in the research. The data were analyzed using descriptive and inferential statistics. The age of the students ranged between 25 and 34 years. 55.2% were female and 54% were economically active. 40.9% had a work experience of less than a year. The academic degree of the majority of participants was master’s degree. 93.9% of the participants believed that big data analysis was essential for the country. 43.2% maintained that big data mostly belonged to the communication industry. 28.1% perceived MATLAB useful software for analysis. 40.9% were familiar with the benefits of analysis. Engage in economic activities, less than 1 year of experience and studies for a Master’s degree showed to be significantly correlated with familiarity with the benefits of big data (p≤0.01). Such issues as high costs, managers’ unfamiliarity and lack of expertise and complexity were raised by the respondents. Considering the undeniable benefits of big data analysis, it seems essential to familiarize university students with these analyses through particular training courses, conferences and so on