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Background: The COVID-19 pandemic constitutes a social crisis that will have long-term health consequences for much of the global population, especially for adolescents. Adolescents are triply affected as they: 1) are experiencing its immediate, direct effects, 2) will carry forward health habits they develop now into adulthood, and 3) as future parents, will shape the early life health of the next generation. It is therefore imperative to assess how the pandemic is influencing adolescent wellbeing, identify sources of resilience, and outline strategies for attenuating its negative impacts. Methods: We report the results of longitudinal analyses of qualitative data from 28 focus group discussions (FGDs) with 39 Canadian adolescents and of cross-sectional analyses of survey data from 482 Canadian adolescents gathered between September 2020 and August 2021. FGD participants and survey respondents reported on their: socio-demographic characteristics; mental health and wellbeing before and during the pandemic; pre- and during-pandemic health behaviours; experiences living through a crisis; current perceptions of their school, work, social, media, and governmental environments; and ideas about pandemic coping and mutual aid. We plotted themes emerging from FGDs along a pandemic timeline, noting socio-demographic variations. Following assessment for internal reliability and dimension reduction, quantitative health/wellbeing indicators were analyzed as functions of composite socio-demographic, health-behavioural, and health-environmental indicators. Results: Our mixed methods analyses indicate that adolescents faced considerable mental and physical health challenges due to the pandemic, and were generally in poorer health than expected in non-crisis times. Nevertheless, some participants showed significantly better outcomes than others, specifically those who: got more exercise; slept better; were food secure; had clearer routines; spent more time in nature, deep in-person social relationships, and leisure; and spent less time on social media. Conclusions: Support for youth during times of crisis is essential to future population health because adolescence is a period in the life course which shapes the health behaviours, socio-economic capacities, and neurophysiology of these future parents/carers and leaders. Efforts to promote resilience in adolescents should leverage the factors identified above: helping them find structure and senses of purpose through strong social connections, well-supported work and leisure environments, and opportunities to engage with nature.

A business organization's objective is to make better decisions at all levels of the firm to improve performance. Typically organizations are multi-faceted and complex systems that use uncertain information. Therefore, making quality decisions to improve organizational performance is a daunting task. Organizations use decision support systems that apply different business intelligence techniques such as statistical models, scoring models, neural networks, expert systems, neuro-fuzzy systems, case-based systems, or simply rules that have been developed through experience. Managers need a decision-making approach that is robust, competent, effective, efficient, and integrative to handle the multi-dimensional organizational entities. The decision maker deals with multiple players in an organization such as products, customers, competitors, location, geographic structure, scope, internal organization, and cultural dimension [46]. Sound decisions include two important concepts: efficiency (return on invested resources) and effectiveness (reaching predetermined goals). However, quite frequently, the decision maker cannot simultaneously handle data from different sources. Hence, we recommend that managers analyze different aspects of data from multiple sources separately and integrate the results of the analysis. This study proposes the design of a multi-attribute-decision-support-system that combines the analytical power of two different tools: data envelopment analysis (DEA) and fuzzy logic. DEA evaluates and measures the relative efficiency of decision making units that use multiple inputs and outputs to provide non-objective measures without making any specific assumptions about data. On the other hand fuzzy logic's main strength lies in handling imprecise data. This study proposes a modeling technique that jointly uses the two techniques to benefit from the two methodologies. A major advantage of the DEA approach is that it clearly identifies the important factors contributing to the success of a decision. In addition, I also propose the use of a neuro-fuzzy model to create a rule-based system that can aid the decision-maker in making decisions regarding the implications of a decision. One of the important characteristics of neuro-fuzzy systems is their ability to deal with imprecise and uncertain information. The neuro-fuzzy model integrates the performance values of a set of production units derived by ranking using DEA to create IF-THEN rules to handle fluctuating and uncertain scenarios. Thus, a decision maker can easily analyze and understand any decision made by the neuro-fuzzy model in the form of the easily interpretable IF-THEN rules. [46] M. PorterCompetitive Strategy: techniques for Analyzing Industries and Competitors, The Free Press, New York, 1980.

We examined whether we could develop models based on data provided to the United States Renal Data System (USRDS) to accurately predict survival. Records were obtained from patients beginning dialysis in 1990 through 2007. We developed linear and neural network models and optimized the fit of these models to the actual time to death. Next, we examined whether we could accurately predict survival in a dataset containing censored and uncensored patients. The results with these models were contrasted with those obtained with a Cox proportional hazards model fit to the entire dataset. The average C statistic over a 6-month to 10-year time range achieved with these models was approximately 0.7891 (linear model), 0.7804 (transformed dataset linear model), 0.7769 (neural network model), 0.7774 (transformed dataset neural network model), 0.8019 (Cox model), and 0.7970 (transformed dataset Cox model). When we used the Cox proportional hazards model, superior C statistic results were found at time points between 2 and 10 years but at earlier time points, the Cox model was slightly inferior. These results suggest that data provided to the USRDS can allow for predictive models which have a high degree of accuracy years following the initiation of dialysis.

The differentiation of hematopoietic stem cells into cells of the immune system has been studied extensively in mammals, but the transcriptional circuitry that controls it is still only partially understood. Here, the Immunological Genome Project gene-expression profiles across mouse immune lineages allowed us to systematically analyze these circuits. To analyze this data set we developed Ontogenet, an algorithm for reconstructing lineage-specific regulation from gene-expression profiles across lineages. Using Ontogenet, we found differentiation stage-specific regulators of mouse hematopoiesis and identified many known hematopoietic regulators and 175 previously unknown candidate regulators, as well as their target genes and the cell types in which they act. Among the previously unknown regulators, we emphasize the role of ETV5 in the differentiation of γδ T cells. As the transcriptional programs of human and mouse cells are highly conserved, it is likely that many lessons learned from the mouse model apply to humans.

In this tribute to the 2015 recipient of the International Association for Conflict Management Lifetime Achievement Award Winner, we celebrate the work of J. Keith Murnighan. Each of us highlights a unique contribution of his research to a different area in the field of organizational behavior. The four areas we discuss are behavioral economics, experimental design, diversity, and ethics. We conclude our discussion of the four research areas by highlighting common themes suggested by this work. The article closes by giving Keith Murnighan “the final say” to reflect on our article and to impart his words of wisdom to doctoral students and scholars at different stages of their career.

Leprosy is an infectious disease caused by the obligate intracellular pathogen Mycobacterium leprae and remains endemic in many parts of the world. Despite several major studies on susceptibility to leprosy, few genomic loci have been replicated independently. We have conducted an association analysis of more than 1,500 individuals from different case-control and family studies, and observed consistent associations between genetic variants in both TLR1 and the HLA-DRB1/DQA1 regions with susceptibility to leprosy (TLR1 I602S, case-control P = 5.7 x 10(-8), OR = 0.31, 95% CI = 0.20-0.48, and HLA-DQA1 rs1071630, case-control P = 4.9 x 10(-14), OR = 0.43, 95% CI = 0.35-0.54). The effect sizes of these associations suggest that TLR1 and HLA-DRB1/DQA1 are major susceptibility genes in susceptibility to leprosy. Further population differentiation analysis shows that the TLR1 locus is extremely differentiated. The protective dysfunctional 602S allele is rare in Africa but expands to become the dominant allele among individuals of European descent. This supports the hypothesis that this locus may be under selection from mycobacteria or other pathogens that are recognized by TLR1 and its co-receptors. These observations provide insight into the long standing host-pathogen relationship between human and mycobacteria and highlight the key role of the TLR pathway in infectious diseases.

Copyright © 2014 by The American Association of Immunologists, Inc. All rights reserved. To determine the breadth and underpinning of changes in immunocyte gene expression due to genetic variation in mice, we performed, as part of the Immunological Genome Project, gene expression profiling for CD4+T cells and neutrophils purified from 39 inbred strains of the Mouse Phenome Database. Considering both cell types, a large number of transcripts showed significant variation across the inbred strains, with 22% of the transcriptome varying by 2-fold or more. These included 119 loci with apparent complete loss of function, where the corresponding transcript was not expressed in some of the strains, representing a useful resource of "natural knockouts." We identified 1222 cis-expression quantitative trait loci (cis-eQTL) that control some of this variation. Most (60%) cis-eQTLs were shared between T cells and neutrophils, but a significant portion uniquely impacted one of the cell types, suggesting cell type-specific regulatory mechanisms. Using a conditional regression algorithm, we predicted regulatory interactions between transcription factors and potential targets, and we demonstrated that these predictions overlap with regulatory interactions inferred from transcriptional changes during immunocyte differentiation. Finally, comparison of these and parallel data from CD4+T cells of healthy humans demonstrated intriguing similarities in variability of a gene's expression: the most variable genes tended to be the same in both species, and there was an overlap in genes subject to strong cis-acting genetic variants. We speculate that this "conservation of variation" reflects a differential constraint on intraspecies variation in expression levels of different genes, either through lower pressure for some genes, or by favoring variability for others.

The differentiation of αβT cells from thymic precursors is a complex process essential for adaptive immunity. Here we exploited the breadth of expression data sets from the Immunological Genome Project to analyze how the differentiation of thymic precursors gives rise to mature T cell transcriptomes. We found that early T cell commitment was driven by unexpectedly gradual changes. In contrast, transit through the CD4+CD8+stage involved a global shutdown of housekeeping genes that is rare among cells of the immune system and correlated tightly with expression of the transcription factor c-Myc. Selection driven by major histocompatibility complex (MHC) molecules promoted a large-scale transcriptional reactivation. We identified distinct signatures that marked cells destined for positive selection versus apoptotic deletion. Differences in the expression of unexpectedly few genes accompanied commitment to the CD4+or CD8+lineage, a similarity that carried through to peripheral T cells and their activation, demonstrated by mass cytometry phosphoproteomics. The transcripts newly identified as encoding candidate mediators of key transitions help define the 'known unknowns' of thymocyte differentiation. © 2013 Nature America, Inc. All rights reserved.

After infection, many factors coordinate the population expansion and differentiation of CD8+effector and memory T cells. Using data of unparalleled breadth from the Immunological Genome Project, we analyzed the CD8+T cell transcriptome throughout infection to establish gene-expression signatures and identify putative transcriptional regulators. Notably, we found that the expression of key gene signatures can be used to predict the memory-precursor potential of CD8+effector cells. Long-lived memory CD8+cells ultimately expressed a small subset of genes shared by natural killer T and γδ T cells. Although distinct inflammatory milieu and T cell precursor frequencies influenced the differentiation of CD8+effector and memory populations, core transcriptional signatures were regulated similarly, whether polyclonal or transgenic, and whether responding to bacterial or viral model pathogens. Our results provide insights into the transcriptional regulation that influence memory formation and CD8+T cell immunity. © 2013 Nature America, Inc. All rights reserved.

Invariant natural killer T cells (iNKT cells) are innate-like T lymphocytes that act as critical regulators of the immune response. To better characterize this population, we profiled gene expression in iNKT cells during ontogeny and in peripheral subsets as part of the Immunological Genome Project. High-resolution comparative transcriptional analyses defined developmental and subset-specific programs of gene expression by iNKT cells. In addition, we found that iNKT cells shared an extensive transcriptional program with NK cells, similar in magnitude to that shared with major histocompatibility complex (MHC)-restricted T cells. Notably, the program shared by NK cells and iNKT cells also operated constitutively in γδ T cells and in adaptive T cells after activation. Together our findings highlight a core effector program regulated distinctly in innate and adaptive lymphocytes. © 2013 Nature America, Inc. All rights reserved.

We assessed gene expression in tissue macrophages from various mouse organs. The diversity in gene expression among different populations of macrophages was considerable. Only a few hundred mRNA transcripts were selectively expressed by macrophages rather than dendritic cells, and many of these were not present in all macrophages. Nonetheless, well-characterized surface markers, including MerTK and FcγR1 (CD64), along with a cluster of previously unidentified transcripts, were distinctly and universally associated with mature tissue macrophages. TCEF3, C/EBP-α, Bach1 and CREG-1 were among the transcriptional regulators predicted to regulate these core macrophage-associated genes. The mRNA encoding other transcription factors, such as Gata6, was associated with single macrophage populations. We further identified how these transcripts and the proteins they encode facilitated distinguishing macrophages from dendritic cells. © 2012 Nature America, Inc. All rights reserved.

Although the field has a long collaborative tradition, immunology has made less use than genetics of 'consortium biology', wherein groups of investigators together tackle large integrated questions or problems. However, immunology is naturally suited to large-scale integrative and systems-level approaches, owing to the multicellular and adaptive nature of the cells it encompasses. Here, we discuss the value and drawbacks of this organization of research, in the context of the long-running 'big science' debate, and consider the opportunities that may exist for the immunology community. We position this analysis in light of our own experience, both positive and negative, as participants of the Immunological Genome Project. © 2012 Macmillan Publishers Limited. All rights reserved.

Using whole-genome microarray data sets of the Immunological Genome Project, we demonstrate a closer transcriptional relationship between NK cells and T cells than between any other leukocytes, distinguished by their shared expression of genes encoding molecules with similar signaling functions. Whereas resting NK cells are known to share expression of a few genes with cytotoxic CD8 + T cells, our transcriptome-wide analysis demonstrates that the commonalities extend to hundreds of genes, many encoding molecules with unknown functions. Resting NK cells demonstrate a 'preprimed' state compared with naive T cells, which allows NK cells to respond more rapidly to viral infection. Collectively, our data provide a global context for known and previously unknown molecular aspects of NK cell identity and function by delineating the genome-wide repertoire of gene expression of NK cells in various states. © 2012 Nature America, Inc. All rights reserved.

Although much progress has been made in the understanding of the ontogeny and function of dendritic cells (DCs), the transcriptional regulation of the lineage commitment and functional specialization of DCs in vivo remains poorly understood. We made a comprehensive comparative analysis of CD8 +, CD103 +, CD11b + and plasmacytoid DC subsets, as well as macrophage DC precursors and common DC precursors, across the entire immune system. Here we characterized candidate transcriptional activators involved in the commitment of myeloid progenitor cells to the DC lineage and predicted regulators of DC functional diversity in tissues. We identified a molecular signature that distinguished tissue DCs from macrophages. We also identified a transcriptional program expressed specifically during the steady-state migration of tissue DCs to the draining lymph nodes that may control tolerance to self tissue antigens. © 2012 Nature America, Inc. All rights reserved.