How Self-Regulated Strategy Development In Writing Eases The Transition From Special Education To Regular Education For Students With Learning Disabilities

The author’s own and her students’ struggles with writing encouraged her to research best practices in teaching written language in order to ease the transition of students with learning disabilities to the regular education classroom. She found that Self-Regulated Strategy Development (SRSD) along with teaching the writing as a recursive process had the highest effect size. She narrowed her research by focusing on the stages of SRSD and best practices for teaching writing. She also reviewed the Minnesota writing standards for third through fifth grade. The author created an eight-lesson curriculum that incorporated the stages of SRSD for teaching narrative text structure, the writing process, as well as some of the the writing standards for third through fifth grade

Strategi Guru dalam Meningkatkan Kemampuan Berbicara Pada Anak

Penelitian ini bertujuan untuk mengetahui strategi guru dalam meningkatkankan kemampuan berbicara pada anak. Penelitian ini menggunakan metode  deskriptif kualitatif. Pengumpulan data dilakukan dengan observasi, dokumentasi dan wawancara. Hasil penelitian bahwa deskripsi kemampuan berbicara anak di TK ini yaitu dapat berkembang dengan optimal, terlihat dari indikator pertama gambaran kemampuan berbicara terdapat 6 dari 15 anak yang kemampuan berbicaranya masih minim, dikarenakan kurangnya stimulasi dari orangtua dalam meningkatkan kemampuan berbicara anak. Sebaliknya banyak anak yang kemampuan berbicaranya sudah baik. Hal ini juga dipengaruhi oleh pernguasaan kosa kata yang dimiliki anak. Guru harus memiliki kemampuan dalam mengembangkan strategi pembelajaran karena guru merupakan kunci utama keberhasilan siswa. Terdapat 4 strategi yang digunakan guru dalam meningkatkan kemampuan berbicara yaitu, bermain peran, bercakap-cakap, bernyanyi, bercerita dan bermain show and tell. Adapun faktor yang mempengaruhi kemampuan anak dalam bercerita adalah kecerdasan dan lingunganKata kunci:  Strategi, Kemampuan Berbicara, Ana

1-D Transient Thermal Modeling of an Ablative Material (MCC-1) Exposed to a Simulated Convective Titan 4 Launch Environment

The purpose of the work is to demonstrate that the flat test panel substrate temperatures are consistent with analysis predictions for MCC-1 applied to a aluminum substrate. The testing was performed in an aerothermal facility on samples of three different thicknesses of MCC-1 on an aluminum substrate. The results of the test were compared with a Transient Thermal model. The key assumptions of the Transient Thermal model were: (1) a one-dimensional heat transfer; (2) a constant ablation recession rate (determined from pre and post-test measurements); (3) ablation temperature of 540 degrees F; (4) Char left behind the ablation front; and (5) temperature jump correction for incident heat transfer coefficient. Two methods were used to model the heating of bare MCC-1: (1) Directly input surface temperature as a function of time; and (2) Aerothermal heating using calibration plate data and subtracting the radiation losses to tunnel walls. The results are presented as graphs. This article is presented in Viewgraph format

Epigenetics of Lipid Phenotypes

Dyslipidemia is a well-established risk factor for cardiovascular disease, the main cause of death worldwide. Blood lipid profiles are patterned by both genetic and environmental factors. In recent years, epigenetics has emerged as a paradigm that unifies these influences. In this review, we have summarized the latest evidence implicating epigenetic mechanisms—DNA methylation, histone modification, and regulation by RNAs—in lipid homeostasis. Key findings have emerged in a number of novel epigenetic loci located in biologically plausible genes (eg, CPT1A, ABCG1, SREBF1, and others), as well as microRNA-33a/b. Evidence from animal and cell culture models suggests a complex interplay between different classes of epigenetic processes in the lipid-related genomic regions. Although epigenetic findings hold the potential to explain the interindividual variability in lipid profiles as well as the underlying mechanisms, they have yet to be translated into effective therapies for dyslipidemia

Development of Eosinophilic Airway Inflammation and Airway Hyperresponsiveness in Mast Cell–deficient Mice

Mast cells are the main effector cells of immediate hypersensitivity and anaphylaxis. Their role in the development of allergen-induced airway hyperresponsiveness (AHR) is controversial and based on indirect evidence. To address these issues, mast cell–deficient mice (W/W  v) and their congenic littermates were sensitized to ovalbumin (OVA) by intraperitoneal injection and subsequently challenged with OVA via the airways. Comparison of OVA-specific immunoglobulin E (IgE) levels in the serum and numbers of eosinophils in bronchoalveolar lavage fluid or lung digests showed no differences between the two groups of mice. Further, measurements of airway resistance and dynamic compliance at baseline and after inhalation of methacholine were similar. These data indicate that mast cells or IgE–mast cell activation is not required for the development of eosinophilic inflammation and AHR in mice sensitized to allergen via the intraperitoneal route and challenged via the airways

Genetic-Based Hypertension Subtype Identification Using Informative SNPs

In this work, we proposed a process to select informative genetic variants for identifying clinically meaningful subtypes of hypertensive patients. We studied 575 African American (AA) and 612 Caucasian hypertensive participants enrolled in the Hypertension Genetic Epidemiology Network (HyperGEN) study and analyzed each race-based group separately. All study participants underwent GWAS (Genome-Wide Association Studies) and echocardiography. We applied a variety of statistical methods and filtering criteria, including generalized linear models, F statistics, burden tests, deleterious variant filtering, and others to select the most informative hypertension-related genetic variants. We performed an unsupervised learning algorithm non-negative matrix factorization (NMF) to identify hypertension subtypes with similar genetic characteristics. Kruskal–Wallis tests were used to demonstrate the clinical meaningfulness of genetic-based hypertension subtypes. Two subgroups were identified for both African American and Caucasian HyperGEN participants. In both AAs and Caucasians, indices of cardiac mechanics differed significantly by hypertension subtypes. African Americans tend to have more genetic variants compared to Caucasians; therefore, using genetic information to distinguish the disease subtypes for this group of people is relatively challenging, but we were able to identify two subtypes whose cardiac mechanics have statistically different distributions using the proposed process. The research gives a promising direction in using statistical methods to select genetic information and identify subgroups of diseases, which may inform the development and trial of novel targeted therapies

A 6-CpG Validated Methylation Risk Score Model for Metabolic Syndrome: The HyperGEN and GOLDN Studies

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups