Factors that Influence Technology Integration in the Classroom

Education is one area where the use of technology has had great impact on student learning. The integration of technology in teaching and learning can significantly influence the outcome of education in the classroom. However, there are a myriad of factors that influence technology integration in the classroom. The purpose of this study was to investigate the variation of teacher integration of technology into classroom instruction. Factors that teachers perceive as being the most influential will be analyzed. The investigation also serves to inform school leaders about specific ways to ensure maximum use of instructional technology by all staff members. The study involved a comprehensive high school centrally located in a suburban county in Maryland with an on-time graduation of above 95%. This study surveyed 49 teachers who are employed at this high school and represent various years’ experience. Their teaching assignments range from standard level to advanced placement courses in one of the following content areas: English, science, social studies, or math. The research design in this study is quantitative in nature and was conducted through an on-line anonymous, eleven question survey using the Qualtrics platform. A total of 44/49 participants, or 90%, provided responses to all of the questions asked on the anonymous survey. Results indicated that content, grade, skill level of student, and years’ experience had no effect on the integration of technology in the classroom as 84% reported daily integration. Smart Boards and Laptops were the most frequently used while responders/clickers and the document camera were the least frequently used. Teachers reported using the Internet to develop lessons, Moodle, and video clips from the Internet were the most common uses of technology. Furthermore, results indicated that personal interest, availability, and professional development had the greatest influence over a teacher’s decision to integrate technology

Unique molecular identifier-based high-resolution HLA typing and transcript quantitation using long-read sequencing

HLA typing provides essential results for stem cell and solid organ transplants, as well as providing diagnostic benefits for various rheumatology, gastroenterology, neurology, and infectious diseases. It is becoming increasingly clear that understanding the expression of patient HLA transcripts can provide additional benefits for many of these same patient groups. Our study cohort was evaluated using a long-read RNA sequencing methodology to provide rapid HLA genotyping results and normalized HLA transcript expression. Our assay used NGSEngine to determine the HLA genotyping result and normalized mRNA transcript expression using Athlon2. The assay demonstrated an excellent concordance rate of 99.7%. Similar to previous studies, for the class I loci, patients demonstrated significantly lower expression o

Performance Characteristics and Validation of Next-Generation Sequencing for Human Leucocyte Antigen Typing

High-resolution human leukocyte antigen (HLA) matching reduces graft-versus-host disease and improves overall patient survival after hematopoietic stem cell transplant. Sanger sequencing has been the gold standard for HLA typing since 1996. However, given the increasing number of new HLA alleles identified and the complexity of the HLA genes, clinical HLA typing by Sanger sequencing requires several rounds of additional testing to provide allele-level resolution. Although next-generation sequencing (NGS) is routinely used in molecular genetics, few clinical HLA laboratories use the technology. The performance characteristics of NGS HLA typing using TruSight HLA were determined using Sanger sequencing as the reference method. In total, 211 samples were analyzed with an overall accuracy of 99.8% (2954/2961) and 46 samples were analyzed for precision with 100% (368/368) reproducibility. Most discordant alleles were because of technical error rather than assay performance. More important, the ambiguity rate was 3.5% (103/2961). Seventy-four percentage of the ambiguities were within the DRB1 and DRB4 loci. HLA typing by NGS saves approximately $6000 per run when compared to Sanger sequencing. Thus, TruSight HLA assay enables high-throughput HLA typing with an accuracy, precision, ambiguity rate, and cost savings that should facilitate adoption of NGS technology in clinical HLA laboratories

Unique Molecular Identifier based High-resolution HLA Typing and Transcript Quantitation using Long-Read Sequencing

HLA typing provides essential results for stem cell and solid organ transplants, as well as providing diagnostic benefits for various rheumatology, gastroenterology, neurology, and infectious diseases. It is becoming increasingly clear that understanding the expression of patient HLA transcripts can provide additional benefits for many of these same patient groups. Our study cohort was evaluated using a long-read RNA sequencing methodology to provide rapid HLA genotyping results and normalized HLA transcript expression. Our assay used NGSEngine to determine the HLA genotyping result and normalized mRNA transcript expression using Athlon2. The assay demonstrated an excellent concordance rate of 99.7%. Similar to previous studies, for the class I loci, patients demonstrated significantly lower expression of HLA-C than HLA-A and -B (Mann–Whitney U, P value = 0.0065 & P value = 0.0154, respectively). In general, the expression of class II transcripts was lower than that of class I transcripts. This study demonstrates a rapid high-resolution HLA typing assay using RNA-Seq that can provide accurate HLA genotyping and HLA allele-specific transcript expression in 7 to 8 hours, a timeline short enough to perform the assay for deceased donors

Allele-specific quantification of human leukocyte antigen transcript isoforms by nanopore sequencing

Introduction While tens of thousands of HLA alleles have been identified by DNA sequencing, the contribution of alternative splicing to HLA diversity is not well characterized. In this study, we sought to determine if long-read sequencing could be used to accurately quantify allele-specific HLA transcripts in primary human lymphocytes. Methods cDNA libraries were prepared from peripheral blood lymphocytes from 12 donors and sequenced by nanopore long-read sequencing. HLA reads were aligned to donor-specific reference sequences based on the known type of each donor. Allele-specific exon utilization was calculated as the proportion of reads aligning to each allele containing known exons, and transcript isoforms were quantified based on patterns of exon utilization within individual reads. Results Splice variants were rare among class I HLA genes (median exon retention rate 99%–100%), except for several HLA-C alleles with exon 5 spliced out of up to 15% of reads. Splice variants were also rare among class II HLA genes (median exon retention rate 98%–100%), except for HLA-DQB1. Consistent with previous work, exon 5 of HLA-DQB1 was spliced out in alleles with a mutated splice acceptor site at rs28688207. Surprisingly, a 28% loss of exon 5 was also observed in HLA-DQB1 alleles with an intact splice acceptor site at rs28688207. Discussion We describe a simple bioinformatic workflow to quantify allele-specific expression of HLA transcript isoforms. Further studies are warranted to characterize the repertoire of HLA transcripts expressed in different cell types and tissues across diverse populations

Allele-specific quantification of human leukocyte antigen transcript isoforms by nanopore sequencing

IntroductionWhile tens of thousands of HLA alleles have been identified by DNA sequencing, the contribution of alternative splicing to HLA diversity is not well characterized. In this study, we sought to determine if long-read sequencing could be used to accurately quantify allele-specific HLA transcripts in primary human lymphocytes.MethodscDNA libraries were prepared from peripheral blood lymphocytes from 12 donors and sequenced by nanopore long-read sequencing. HLA reads were aligned to donor-specific reference sequences based on the known type of each donor. Allele-specific exon utilization was calculated as the proportion of reads aligning to each allele containing known exons, and transcript isoforms were quantified based on patterns of exon utilization within individual reads.ResultsSplice variants were rare among class I HLA genes (median exon retention rate 99%–100%), except for several HLA-C alleles with exon 5 spliced out of up to 15% of reads. Splice variants were also rare among class II HLA genes (median exon retention rate 98%–100%), except for HLA-DQB1. Consistent with previous work, exon 5 of HLA-DQB1 was spliced out in alleles with a mutated splice acceptor site at rs28688207. Surprisingly, a 28% loss of exon 5 was also observed in HLA-DQB1 alleles with an intact splice acceptor site at rs28688207.DiscussionWe describe a simple bioinformatic workflow to quantify allele-specific expression of HLA transcript isoforms. Further studies are warranted to characterize the repertoire of HLA transcripts expressed in different cell types and tissues across diverse populations

Cloning, purification and characterisation of a recombinant purine nucleoside phosphorylase from Bacillus halodurans Alk36

A purine nucleoside phosphorylase from the alkaliphile Bacillus halodurans Alk36 was cloned and overexpressed in Escherichia coli. The enzyme was purified fivefold by membrane filtration and ion exchange. The purified enzyme had a Vmax of 2.03 × 10−9 s −1 and a Km of 206 μM on guanosine. The optimal pH range was between 5.7 and 8.4 with a maximum at pH 7.0. The optimal temperature for activity was 70°C and the enzyme had a half life at 60°C of 20.8 h

Variants at multiple loci implicated in both innate and adaptive immune responses are associated with Sjögren’s syndrome

Sjögren’s syndrome is a common autoimmune disease (~0.7% of European Americans) typically presenting as keratoconjunctivitis sicca and xerostomia. In addition to strong association within the HLA region at 6p21 (Pmeta=7.65×10−114), we establish associations with IRF5-TNPO3 (Pmeta=2.73×10−19), STAT4 (Pmeta=6.80×10−15), IL12A (Pmeta =1.17×10−10), FAM167A-BLK (Pmeta=4.97×10−10), DDX6-CXCR5 (Pmeta=1.10×10−8), and TNIP1 (Pmeta=3.30×10−8). Suggestive associations with Pmeta<5×10−5 were observed with 29 regions including TNFAIP3, PTTG1, PRDM1, DGKQ, FCGR2A, IRAK1BP1, ITSN2, and PHIP amongst others. These results highlight the importance of genes involved in both innate and adaptive immunity in Sjögren’s syndrome

word~river literary review (2013)

wordriver is a literary journal dedicated to the poetry, short fiction, and creative nonfiction of adjunct, part-time and fulltime instructors teaching under a semester or yearly contract in our universities, colleges, and community colleges worldwide. Graduate student teachers who have used up their teaching assistant time and are teaching with adjunct contracts for the remainder of their graduate program are also eligible. We’re looking for work that demonstrates the creativity and craft of adjunct/part-time instructors in English and other disciplines. We reserve first publication rights and onetime anthology publication rights for all work published. We do not accept simultaneous submissions.https://digitalscholarship.unlv.edu/word_river/1004/thumbnail.jp

A large-scale genome-wide association study meta-analysis of cannabis use disorder

Summary Background Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50–70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07–1·15, p=1·84 × 10−9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86–0·93, p=6·46 × 10−9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10−21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder. Funding National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.Peer reviewe