Integration and Inclusion from Self-Contained Classrooms to Improve Academic and Social Outcomes

The inclusion of students with special needs is considered a hallmark of human rights policies and practices in many education systems throughout Canada and the world. However, the question of how to successfully enact such policies and practices in the face of human resource challenges, limited budgets, and other competing interests presents many challenges for policymakers and educators. This organizational improvement plan (OIP) aims to address this challenge as lived in District School Board X (DSBX). Many organizational challenges have created a dynamic where most students with significant special needs are segregated in self-contained classrooms focused on life-skills, even though numerous students can be successful in regular classrooms with adequate support. Many of these students do not develop the social and academic skills required to earn a secondary school diploma, while their disability may not be considered severe enough to secure a disability pension. This OIP will apply both a critical disability theory (CDT) and transformative leadership lens to this problem of practice (PoP) in showing stakeholders how the current paradigm marginalizes students with special needs. It will explore how shifting from a medical model of disability to a social model of disability will create an organizational dynamic focused on making regular classrooms more accommodating for students with special needs to reduce the reliance on self-contained classrooms. Through a pilot school approach, this OIP also outlines a change implementation plan focused on reducing the need for self-contained classrooms through an accountable process to increase integration and inclusion

Gene expression studies for the analysis of domoic acid production in the marine diatom Pseudo-nitzschia multiseries

Background: Pseudo-nitzschia multiseries Hasle (Hasle) (Ps-n) is distinctive among the ecologically important marine diatoms because it produces the neurotoxin domoic acid. Although the biology of Ps-n has been investigated intensely, the characterization of the genes and biochemical pathways leading to domoic acid biosynthesis has been limited. To identify transcripts whose levels correlate with domoic acid production, we analyzed Ps-n under conditions of high and low domoic acid production by cDNA microarray technology and reverse-transcription quantitative PCR (RT-qPCR) methods. Our goals included identifying and validating robust reference genes for Ps-n RNA expression analysis under these conditions. Results: Through microarray analysis of exponential- and stationary-phase cultures with low and high domoic acid production, respectively, we identified candidate reference genes whose transcripts did not vary across conditions. We tested eleven potential reference genes for stability using RT-qPCR and GeNorm analyses. Our results indicated that transcripts encoding JmjC, dynein, and histone H3 proteins were the most suitable for normalization of expression data under conditions of silicon-limitation, in late-exponential through stationary phase. The microarray studies identified a number of genes that were up- and down-regulated under toxin-producing conditions. RT-qPCR analysis, using the validated controls, confirmed the up-regulation of transcripts predicted to encode a cycloisomerase, an SLC6 transporter, phosphoenolpyruvate carboxykinase, glutamate dehydrogenase, a small heat shock protein, and an aldo-keto reductase, as well as the down-regulation of a transcript encoding a fucoxanthin-chlorophyll a-c binding protein, under these conditions. Conclusion: Our results provide a strong basis for further studies of RNA expression levels in Ps-n, which will contribute to our understanding of genes involved in the production and release of domoic acid, an important neurotoxin that affects human health as well as ecosystem function.Plymouth State University Graduate Programs OfficeWoods Hole Oceanographic Institution Academic Programs OfficeNew Hampshire IDeA Network of Biological Research Excellence (NH-INBRE)National Center for Research Resources (U.S.) (Grant 5P20RR030360-03)National Institute of General Medical Sciences (U.S.) (Grant 8P20GM103506-03

The uniqueome: a mappability resource for short-tag sequencing

Summary: Quantification applications of short-tag sequencing data (such as CNVseq and RNAseq) depend on knowing the uniqueness of specific genomic regions at a given threshold of error. Here, we present the ‘uniqueome’, a genomic resource for understanding the uniquely mappable proportion of genomic sequences. Pre-computed data are available for human, mouse, fly and worm genomes in both color-space and nucletotide-space, and we demonstrate the utility of this resource as applied to the quantification of RNAseq data

Resource-Area-Dependence Analysis: inferring animal resource needs from home-range and mapping data

An animal’s home-range can be expected to encompass the resources it requires for surviving or reproducing. Thus, animals inhabiting a heterogeneous landscape, where resource patches vary in size, shape and distribution, will naturally have home-ranges of varied sizes, so that each home-range encompasses a minimum required amount of a resource. Home-range size can be estimated from telemetry data, and often key resources, or proxies for them such as the areas of important habitat types, can be mapped. We propose a new method, Resource-Area-Dependence Analysis (RADA), which uses a sample of tracked animals and a categorical map to i) infer in which map categories important resources are accessible, ii) within which home range cores they are found, and iii) estimate the mean minimum areas of these map categories required for such resource provision. We provide three examples of applying RADA to datasets of radio-tracked animals from southern England: 15 red squirrels Sciurus vulgaris, 17 gray squirrels S. carolinensis and 114 common buzzards Buteo buteo. The analyses showed that each red squirrel required a mean (95% CL) of 0.48 ha (0.24–-0.97) of pine wood within the outermost home-range, each gray squirrel needed 0.34 ha (0.11–1.12) ha of mature deciduous woodland and 0.035–0.046 ha of wheat, also within the outermost home-range, while each buzzard required 0.54 ha (0.35–0.82) of rough ground close to the home-range center and 14 ha (11–17) of meadow within an intermediate core, with 52% of them also relying on 0.41 ha (0.29–0.59) of suburban land near the home-range center. RADA thus provides a useful tool to infer key animal resource requirements during studies of animal movement and habitat use

The GALEX Arecibo SDSS survey: III. Evidence for the Inside-Out Formation of Galactic Disks

We analyze a sample of galaxies with stellar masses greater than $10^{10} M_{\odot}$ and with redshifts in the range $0.025<z<0.05$ for which HI mass measurements are available from the GALEX Arecibo SDSS Survey (GASS) or from the Arecibo Legacy Fast ALFA survey (ALFALFA). At a given value of $M_*$, our sample consists primarily of galaxies that are more HI-rich than average. We constructed a series of three control samples for comparison with these HI-rich galaxies. As expected, HI-rich galaxies differ strongly from galaxies of same stellar mass that are selected without regard to HI content. The majority of these differences are attributable to the fact that galaxies with more gas are bluer and more actively star-forming. In order to identify those galaxy properties that are causally connected with HI content, we compare results derived for the HI sample with those derived for galaxies matched in stellar mass, size and NUV-$r$ colour. The only photometric property that is clearly attributable to increasing HI content, is the colour gradient of the galaxy. Galaxies with larger HI fractions have bluer, more actively star-forming outer disks compared to the inner part of the galaxy. HI-rich galaxies also have larger $g$-band radii compared to $i$-band radii. Our results are consistent with the "inside-out" picture of disk galaxy formation, which has commonly served as a basis for semi-analytic models of the formation of disks in the context of Cold Dark Matter cosmologies. The lack of any intrinsic connection between HI fraction and galaxy asymmetry suggests that gas is accreted smoothly onto the outer disk.Comment: 18 pages, 20 figures. Accepted for publication in MNRAS. GASS publications and released data can be found at http://www.mpa-garching.mpg.de/GASS/index.ph

Multiple Sclerosis: LIFNano-CD4 for Trojan Horse Delivery of the Neuro-Protective Biologic “LIF” Into the Brain: Preclinical Proof of Concept

Multiple sclerosis (MS) is a demyelinating autoimmune disease that attacks the brain, with year-on-year loss of brain volume, starting late teens and becoming manifest late twenties. There is no cure, and current therapies are immunosuppressive only. LIF is a vital stem cell growth factor active throughout life—and essential for health of the central nervous system (CNS), being tolerogenic, myelinogenic, and neuroprotective. Nano-formulation of LIF (LIFNano) using FDA-approved PLGA captures LIF's compound therapeutic properties, increasing potency 1,000-fold when targeted to CD4 (LIFNano-CD4). Moreover, circulating CD4+ lymphocytes are themselves regulated by LIF to express the Treg phenotype, known to release T cell-derived LIF upon engagement with cognate antigen, perpetuating antigen-specific self-tolerance. With the longer-term aim of treating inflammatory lesions of MS, we asked, does LIFNano-CD4 cross the blood–brain barrier (BBB)? We measure pK and pD using novel methodologies, demonstrate crossing of the BBB, show LIF-cargo-specific anti-inflammatory efficacy in the frontal cortex of the brain, and show safety of intravenous delivery of LIFNano-CD4 at doses known to provide efficacious concentrations of LIF cargo behind the BBB

Mechanisms of Severe Acute Respiratory Syndrome Coronavirus-Induced Acute Lung Injury

ABSTRACT Systems biology offers considerable promise in uncovering novel pathways by which viruses and other microbial pathogens interact with host signaling and expression networks to mediate disease severity. In this study, we have developed an unbiased modeling approach to identify new pathways and network connections mediating acute lung injury, using severe acute respiratory syndrome coronavirus (SARS-CoV) as a model pathogen. We utilized a time course of matched virologic, pathological, and transcriptomic data within a novel methodological framework that can detect pathway enrichment among key highly connected network genes. This unbiased approach produced a high-priority list of 4 genes in one pathway out of over 3,500 genes that were differentially expressed following SARS-CoV infection. With these data, we predicted that the urokinase and other wound repair pathways would regulate lethal versus sublethal disease following SARS-CoV infection in mice. We validated the importance of the urokinase pathway for SARS-CoV disease severity using genetically defined knockout mice, proteomic correlates of pathway activation, and pathological disease severity. The results of these studies demonstrate that a fine balance exists between host coagulation and fibrinolysin pathways regulating pathological disease outcomes, including diffuse alveolar damage and acute lung injury, following infection with highly pathogenic respiratory viruses, such as SARS-CoV.IMPORTANCESevere acute respiratory syndrome coronavirus (SARS-CoV) emerged in 2002 and 2003, and infected patients developed an atypical pneumonia, acute lung injury (ALI), and acute respiratory distress syndrome (ARDS) leading to pulmonary fibrosis and death. We identified sets of differentially expressed genes that contribute to ALI and ARDS using lethal and sublethal SARS-CoV infection models. Mathematical prioritization of our gene sets identified the urokinase and extracellular matrix remodeling pathways as the most enriched pathways. By infecting Serpine1-knockout mice, we showed that the urokinase pathway had a significant effect on both lung pathology and overall SARS-CoV pathogenesis. These results demonstrate the effective use of unbiased modeling techniques for identification of high-priority host targets that regulate disease outcomes. Similar transcriptional signatures were noted in 1918 and 2009 H1N1 influenza virus-infected mice, suggesting a common, potentially treatable mechanism in development of virus-induced ALI