Advancing Employee Engagement With Internationalization Through Networked Leadership Approaches at a Canadian Community College

This organizational improvement plan, undergirded by social network theory, addresses the lack of engagement by many organizational members with an ambitious internationalization goal at Sky College (a pseudonym). The institutional climate is one in which day-to-day challenges prevail and motives for internationalization are questioned. Drawing on system and adaptive leadership, and within the functionalist paradigm, the case is made for advancing 4 factors to increase engagement with internationalization: a shared vision and understanding of internationalization, improving internal communication systems, fostering knowledge creation and sharing, and increasing connections in the network. The proposed solution is a 12-month series of focus on internationalization workshops, presentations, knowledge sharing, and dialogue (Series). To achieve these goals, deliver a successful Series, and advance internationalization as a greater strategic initiative, an integrated framework of change based on the change path model and the dual operating system is presented. Series implementation is situated in the awakening and mobilization phases of the change path model. The framework of change emphasizes creating and maintaining urgency around the big opportunity of internationalization, refining the change vision, and clarifying and adjusting Sky College’s internationalization change initiatives. Although the proposed Series may appear to be a simple solution, from a system leadership perspective, it can prove impactful. This approach can create opportunities for collaboration, mobilize stakeholders, and foster an environment in which the change becomes self-sustaining, becoming embedded within the institution. Similarly, from an adaptive leadership perspective, the Series promotes stakeholders as becoming change agents who collaboratively find their way to solutions. Change leaders work to deepen the debate, facilitate focus, and awaken and mobilize the system toward the desired future state. The Series aims to accomplish this outcome and prime Sky College and its organizational members for achieving the internationalization plan’s ambitious goals

Common variants at 10 Genomic loci influence hemoglobin A1C levels via glycemic and nonglycemic pathways

OBJECTIVE: Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels. RESEARCH DESIGN AND METHODS: We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS: Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10(−26)), HFE (rs1800562/P = 2.6 × 10(−20)), TMPRSS6 (rs855791/P = 2.7 × 10(−14)), ANK1 (rs4737009/P = 6.1 × 10(−12)), SPTA1 (rs2779116/P = 2.8 × 10(−9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10(−9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 × 10(−54)), MTNR1B (rs1387153/P = 4.0 × 10(−11)), GCK (rs1799884/P = 1.5 × 10(−20)) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10(−18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA(1c). CONCLUSIONS: GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c)

The kinematics and excitation of infrared water vapor emission from planet-forming disks: results from spectrally-resolved surveys and guidelines for JWST spectra

This work presents water emission spectra at wavelengths covered by JWST (2.9-12.8 $\mu$m) as spectrally-resolved with high resolving powers (R = 30,000-100,000) using ground-based spectrographs. Two new surveys with iSHELL and VISIR are combined with previous spectra from CRIRES and TEXES to cover parts of multiple ro-vibrational and rotational bands observable within telluric transmission bands, for a total of 85 disks and $\approx160$ spectra. The general expectation of a range of regions and excitation conditions traced by infrared water spectra is for the first time supported by the combined kinematics and excitation as spectrally resolved at multiple wavelengths. The main findings from this analysis are: 1) water lines are progressively narrower going from the ro-vibrational bands at 2-9 $\mu$m to the rotational lines at 12 $\mu$m, and partly match a broad (BC) and narrow (NC) emission components, respectively, as extracted from ro-vibrational CO spectra; 2) rotation diagrams of resolved water lines from upper level energies of 4000-9500 K show curvatures indicative of optically thick emission ($\approx 10^{18}$ cm$^{-2}$) from a range of excitation temperatures ($\approx$ 800-1100 K); 3) the new 5 $\mu$m spectra demonstrate that slab model fits to the rotational lines at $> 10 \mu$m strongly over-predict the ro-vibrational emission bands at $< 9 \mu$m, implying non-LTE excitation. We discuss these findings in the context of a emission from a disk surface and a molecular inner disk wind, and provide a list of detailed guidelines to support the analysis and interpretation of spectrally-unresolved JWST spectra.Comment: Posted on arXiv as submitted to AJ, for immediate access by teams working on the analysis of JWST spectr

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

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

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

p53 status and response to radiotherapy in rectal cancer: a prospective multilevel analysis

The aim of this study was to evaluate, in a prospective study, the predictive role of p53 status analysed at four different levels in identifying the response to preoperative radiotherapy in rectal adenocarcinoma. Before treatment, 70 patients were staged and endoscopic forceps biopsies from the tumour area were taken. p53 status was assessed by total cDNA sequencing, allelic loss analysis, immunohistochemistry, and p53 antibodies. Neoadjuvant treatment was based on preoperative radiotherapy or radiochemotherapy. Response to therapy was evaluated after surgery by both pathologic downstaging and histologic tumour regression grade. In all, 35 patients (50.0%) had p53 gene mutations; 44.4% of patients had an allelic loss; nuclear p53 overexpression was observed in 39 patients (55.7%); and p53 antibodies were detected in 11 patients (16.7%). In the multilevel analysis of p53 status, gene mutations correlated with both nuclear protein overexpression (P<0.0001) and loss of heterozygosity (P=0.013). In all, 29 patients (41.4%) were downstaged by pathologic analysis, and 19 patients (29.2%) were classified as tumour regression grade 1. Whatever the method of evaluation of treatment response, no correlation between p53 alterations and response to radiotherapy was observed. Our results do not support the use of p53 alterations alone as a predictive marker for response to radiotherapy in rectal carcinoma

Myelin Basic Protein as a Novel Genetic Risk Factor in Rheumatoid Arthritis—A Genome-Wide Study Combined with Immunological Analyses

Rheumatoid arthritis (RA) is a major cause of adult chronic inflammatory arthritis and a typical complex trait. Although several genetic determinants have been identified, they account for only a part of the genetic susceptibility. We conducted a genome-wide association study of RA in Japanese using 225,079 SNPs genotyped in 990 cases and 1,236 controls from two independent collections (658 cases and 934 controls in collection1; 332 cases and 302 controls in collection2), followed by replication studies in two additional collections (874 cases and 855 controls in collection3; 1,264 cases and 948 controls in collection4). SNPs showing p<0.005 in the first two collections and p<10−4 by meta-analysis were further genotyped in the latter two collections. A novel risk variant, rs2000811, in intron2 of the myelin basic protein (MBP) at chromosome 18q23 showed strong association with RA (p = 2.7×10−8, OR 1.23, 95% CI: 1.14–1.32). The transcription of MBP was significantly elevated with the risk allele compared to the alternative allele (p<0.001). We also established by immunohistochemistry that MBP was expressed in the synovial lining layer of RA patients, the main target of inflammation in the disease. Circulating autoantibody against MBP derived from human brain was quantified by ELISA between patients with RA, other connective tissue diseases and healthy controls. As a result, the titer of anti-MBP antibody was markedly higher in plasma of RA patients compared to healthy controls (p<0.001) and patients with other connective tissue disorders (p<0.001). ELISA experiment using citrullinated recombinant MBP revealed that a large fraction of anti-MBP antibody in RA patients recognized citrullinated MBP. This is the first report of a genetic study in RA implicating MBP as a potential autoantigen and its involvement in pathogenesis of the disease

Effects of Ploidy and Recombination on Evolution of Robustness in a Model of the Segment Polarity Network

Many genetic networks are astonishingly robust to quantitative variation, allowing these networks to continue functioning in the face of mutation and environmental perturbation. However, the evolution of such robustness remains poorly understood for real genetic networks. Here we explore whether and how ploidy and recombination affect the evolution of robustness in a detailed computational model of the segment polarity network. We introduce a novel computational method that predicts the quantitative values of biochemical parameters from bit sequences representing genotype, allowing our model to bridge genotype to phenotype. Using this, we simulate 2,000 generations of evolution in a population of individuals under stabilizing and truncation selection, selecting for individuals that could sharpen the initial pattern of engrailed and wingless expression. Robustness was measured by simulating a mutation in the network and measuring the effect on the engrailed and wingless patterns; higher robustness corresponded to insensitivity of this pattern to perturbation. We compared robustness in diploid and haploid populations, with either asexual or sexual reproduction. In all cases, robustness increased, and the greatest increase was in diploid sexual populations; diploidy and sex synergized to evolve greater robustness than either acting alone. Diploidy conferred increased robustness by allowing most deleterious mutations to be rescued by a working allele. Sex (recombination) conferred a robustness advantage through “survival of the compatible”: those alleles that can work with a wide variety of genetically diverse partners persist, and this selects for robust alleles