Teaching for students\u27 confident transition from number to algebra

The adoption by all states and territories of the national curriculum by 2013 saw students in schools across the country taught introductory algebraic concepts from Year Five. In the twenty first century the need to be algebraically competent has become a necessity much as computation was in the previous centuries. The Researcher has found from experience that students who have struggled with number and number operations will then most probably make poor progress in their study of algebra. The transition from number to algebra requires a robust understanding of number and number operations This study investigated the balance of instructional strategies employed by teachers to support students transition from number to algebra. This research examined how teachers’ beliefs underpinned the way that they approached the teaching of algebra in Years Seven and Eight in Western Australian schools. This was a mixed methods study. The quantitative data from two questionnaires were used to analyse the teachers professed beliefs and also to contribute to the findings from the qualitative data to form the case study. The qualitative data was gathered from interviews, a focus group meeting, personal reflections by the teachers and video of four lessons taken of each teacher’s practice. The greatest variation in content planning and teaching evident in the teachers’ work was in the transitional material, namely moving students from working with number to algebraic variables. This research makes a contribution to our (and teachers’) knowledge about teaching algebra and it provides insights into understanding good practice in the teaching of beginning algebra

Curriculum enrichment for calculus: Mentoring and professional learning in senior secondary mathematics

To support the growth of science and mathematics in innovation and creative enterprises students need to be fully conversant with the power of calculus to solve problems, both existing and potential. This mathematical confidence is dependent on a deep understanding of the fundamental ideas of calculus, and our model examines best classroom practice for achieving this outcome. We interrogate the efficacy of a professional learning community comprising fourth year pre-service teachers, expert senior schooling teachers and mathematics educators

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Diversity and Complexity of the Large Surface Protein Family in the Compacted Genomes of Multiple Pneumocystis Species

Pneumocystis, a major opportunistic pathogen in patients with a broad range of immunodeficiencies, contains abundant surface proteins encoded by a multicopy gene family, termed the major surface glycoprotein (Msg) gene superfamily. This superfamily has been identified in all Pneumocystis species characterized to date, highlighting its important role in Pneumocystis biology. In this report, through a comprehensive and in-depth characterization of 459 msg genes from 7 Pneurnocystis species, we demonstrate, for the first time, the phylogeny and evolution of conserved domains in Msg proteins and provide a detailed description of the classification, unique characteristics, and phylogenetic relatedness of five Msg families. We further describe, for the first time, the relative expression levels of individual msg families in two rodent Pneumocystis species, the substantial variability of the msg repertoires in P. coda from laboratory and wild rats, and the distinct features of the expression site for the classic msg genes in Pneumocystis from 8 mammalian host species. Our analysis suggests multiple functions for this superfamily rather than just conferring antigenic variation to allow immune evasion as previously believed. This study provides a rich source of information that lays the foundation for the continued experimental exploration of the functions of the Msg superfamily in Pneumocystis biology. IMPORTANCE Pneumocystis continues to be a major cause of disease in humans with immunodeficiency, especially those with HIV/AIDS and organ transplants, and is being seen with increasing frequency worldwide in patients treated with immunode-pleting monoclonal antibodies. Annual health care associated with Pneumocystis pneumonia costs similar to$475 million dollars in the United States alone. In addition to causing overt disease in immunodeficient individuals, Pneumocystis can cause subclinical infection or colonization in healthy individuals, which may play an important role in species preservation and disease transmission. Our work sheds new light on the diversity and complexity of the msg superfamily and strongly suggests that the versatility of this superfamily reflects multiple functions, including antigenic variation to allow immune evasion and optimal adaptation to host environmental conditions to promote efficient infection and transmission. These findings are essential to consider in developing new diagnostic and therapeutic strategies.Peer reviewe

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment