Examining the Effectiveness of Explicit, Systematic Mathematics Vocabulary Instruction for Students with Learning Difficulties and Disabilities in a Specialized Setting

Many students in the United States are not proficient in mathematics. Mathematics vocabulary is one area that may impact students’ understanding of and engagement with mathematics. This dissertation investigated the implementation, effectiveness, and teacher’s perceptions of a program for teaching mathematics vocabulary necessary for fourth grade and beyond. This study randomly assigned 30 students (11-14 years old) to receive mathematics vocabulary instruction or not. Three teachers at a school for students with learning difficulties and disabilities administered mathematics vocabulary and mathematics achievement tests to all of their students before teaching the program to 17 of the students. A research assistant and I observed the teachers, and all of the teachers shared their perceptions of the lessons via a survey. Results show that the teachers taught the lessons as intended and that the students who received the lessons did better on the post-test than students who did not receive the lessons. Results from the survey suggest the teachers found the intervention acceptable, easy to use, and plan to use it or something similar to teach mathematics vocabulary in the future

Use Explicit Instruction

Highly effective instruction for struggling learners requires both excellent instructional materials and excellent interactive teaching that delivers instruction clearly and responds to students’ unique needs and strengths. Explicit Instruction is an evidence-based approach to both designing materials and delivering instruction that is effective for a wide range of learners. It has been shown to be effective for teaching many types of academic content (e.g., reading, writing, mathematics, science) and with students ranging from kindergarten to high school. It is comprised of 16 inter-related elements (see Table 1) that contribute to the effectiveness of the overall system (Archer et al., 2011). Explicit Instruction is designed to systematically prepare students to learn complex skills, present information clearly and unambiguously, support students to engage in new skills while receiving feedback, reduce support as students gain skills, and provide sufficient practice so that students are able to independently apply their new skills in a wide variety of situations

Mutation mapping and identification by whole-genome sequencing

Genetic mapping of mutations in model systems has facilitated the identification of genes contributing to fundamental biological processes including human diseases. However, this approach has historically required the prior characterization of informative markers. Here we report a fast and cost-effective method for genetic mapping using next-generation sequencing that combines single nucleotide polymorphism discovery, mutation localization, and potential identification of causal sequence variants. In contrast to prior approaches, we have developed a hidden Markov model to narrowly define the mutation area by inferring recombination breakpoints of chromosomes in the mutant pool. In addition, we created an interactive online software resource to facilitate automated analysis of sequencing data and demonstrate its utility in the zebrafish and mouse models. Our novel methodology and online tools will make next-generation sequencing an easily applicable resource for mutation mapping in all model systems.Harvard Stem Cell Institute (Junior Faculty Grant)National Institutes of Health (U.S.) (Grant 1R01DK090311)National Institutes of Health (U.S.) (Grant 5R01MH084676

Over-Expression of DSCAM and COL6A2 Cooperatively Generates Congenital Heart Defects

A significant current challenge in human genetics is the identification of interacting genetic loci mediating complex polygenic disorders. One of the best characterized polygenic diseases is Down syndrome (DS), which results from an extra copy of part or all of chromosome 21. A short interval near the distal tip of chromosome 21 contributes to congenital heart defects (CHD), and a variety of indirect genetic evidence suggests that multiple candidate genes in this region may contribute to this phenotype. We devised a tiered genetic approach to identify interacting CHD candidate genes. We first used the well vetted Drosophila heart as an assay to identify interacting CHD candidate genes by expressing them alone and in all possible pairwise combinations and testing for effects on rhythmicity or heart failure following stress. This comprehensive analysis identified DSCAM and COL6A2 as the most strongly interacting pair of genes. We then over-expressed these two genes alone or in combination in the mouse heart. While over-expression of either gene alone did not affect viability and had little or no effect on heart physiology or morphology, co-expression of the two genes resulted in ≈50% mortality and severe physiological and morphological defects, including atrial septal defects and cardiac hypertrophy. Cooperative interactions between DSCAM and COL6A2 were also observed in the H9C2 cardiac cell line and transcriptional analysis of this interaction points to genes involved in adhesion and cardiac hypertrophy. Our success in defining a cooperative interaction between DSCAM and COL6A2 suggests that the multi-tiered genetic approach we have taken involving human mapping data, comprehensive combinatorial screening in Drosophila, and validation in vivo in mice and in mammalian cells lines should be applicable to identifying specific loci mediating a broad variety of other polygenic disorders

Defining the Critical Hurdles in Cancer Immunotherapy

ABSTRACT: Scientific discoveries that provide strong evidence of antitumor effects in preclinical models often encounter significant delays before being tested in patients with cancer. While some of these delays have a scientific basis, others do not. We need to do better. Innovative strategies need to move into early stage clinical trials as quickly as it is safe, and if successful, these therapies should efficiently obtain regulatory approval and widespread clinical application. In late 2009 and 2010 the Society for Immunotherapy of Cancer (SITC), convened an "Immunotherapy Summit" with representatives from immunotherapy organizations representing Europe, Japan, China and North America to discuss collaborations to improve development and delivery of cancer immunotherapy. One of the concepts raised by SITC and defined as critical by all parties was the need to identify hurdles that impede effective translation of cancer immunotherapy. With consensus on these hurdles, international working groups could be developed to make recommendations vetted by the participating organizations. These recommendations could then be considered by regulatory bodies, governmental and private funding agencies, pharmaceutical companies and academic institutions to facilitate changes necessary to accelerate clinical translation of novel immune-based cancer therapies. The critical hurdles identified by representatives of the collaborating organizations, now organized as the World Immunotherapy Council, are presented and discussed in this report. Some of the identified hurdles impede all investigators, others hinder investigators only in certain regions or institutions or are more relevant to specific types of immunotherapy or first-in-humans studies. Each of these hurdles can significantly delay clinical translation of promising advances in immunotherapy yet be overcome to improve outcomes of patients with cancer

Defining the critical hurdles in cancer immunotherapy

Scientific discoveries that provide strong evidence of antitumor effects in preclinical models often encounter significant delays before being tested in patients with cancer. While some of these delays have a scientific basis, others do not. We need to do better. Innovative strategies need to move into early stage clinical trials as quickly as it is safe, and if successful, these therapies should efficiently obtain regulatory approval and widespread clinical application. In late 2009 and 2010 the Society for Immunotherapy of Cancer (SITC), convened an "Immunotherapy Summit" with representatives from immunotherapy organizations representing Europe, Japan, China and North America to discuss collaborations to improve development and delivery of cancer immunotherapy. One of the concepts raised by SITC and defined as critical by all parties was the need to identify hurdles that impede effective translation of cancer immunotherapy. With consensus on these hurdles, international working groups could be developed to make recommendations vetted by the participating organizations. These recommendations could then be considered by regulatory bodies, governmental and private funding agencies, pharmaceutical companies and academic institutions to facilitate changes necessary to accelerate clinical translation of novel immune-based cancer therapies. The critical hurdles identified by representatives of the collaborating organizations, now organized as the World Immunotherapy Council, are presented and discussed in this report. Some of the identified hurdles impede all investigators; others hinder investigators only in certain regions or institutions or are more relevant to specific types of immunotherapy or first-in-humans studies. Each of these hurdles can significantly delay clinical translation of promising advances in immunotherapy yet if overcome, have the potential to improve outcomes of patients with cancer

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

J Med Genet

was previously implicated in periventricular nodular heterotopia (PVNH) in only five individuals and systematic clinical characterisation was not available. The aim of this study is to provide a comprehensive description of the phenotypic and genotypic spectrum of -related neurodevelopmental disorder. We collected detailed phenotypes of an international cohort of individuals (n=17) with variants assembled through the GeneMatcher platform. Missense variants were structurally modelled, and the impact of several were functionally validated. De novo variants (10 missense, 1 frameshift, 1 splice altering resulting in 9 residues insertion) in were identified among 17 unrelated individuals. Detailed phenotypes included intellectual disability (ID), microcephaly, seizures and PVNH. No specific facial characteristics were consistent across all cases, however microretrognathia was common. Various hearing and visual defects were recurrent, and interestingly, some inflammatory features were reported. MRI of the brain frequently showed abnormalities consistent with a neuronal migration disorder. We confirm the role of in an autosomal dominant syndrome with a phenotypic spectrum including severe ID, microcephaly, seizures and PVNH due to impaired neuronal migration

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk

Features of Direct Instruction: Content Analysis

The goal of Direct Instruction (DI) is to teach content as effectively and efficiently as possible. To do this, instructional designers must identify generative relations or strategies that allow the learner to respond correctly to untaught situations. The purpose of content analysis is to identify generative relations in the domain to be taught and arrange the content in such a way that it supports maximally generative instruction. This article explains the role of content analysis in developing DI programs and provides examples and nonexamples of content analysis in five content domains: spelling, basic arithmetic facts, earth science, basic language, and narrative language. It includes a brief sketch of a general methods of conducting a content analysis. It concludes that content analysis is the foundation upon which generative instruction is built and that instructional designers could produce more effective, efficient, and powerful programs by attending explicitly and carefully to content analysis