Blame and Credit in Organizations: Theory and Evidence Explaining the Responses of Leaders after Failure and Success

The blame and credit literature has operated largely on the assumption that actors want to reduce the blame assigned to them and increase assigned credit (Gioia & Sims, 1985; Greenwald, 1980; Shaver, 1985). As a result, much of the literature has focused on the shifting of blame away from the self and of credit towards the self (e.g., Crant & Bateman, 1993), rather than other behaviors that are less self-serving (e.g., blame-taking, Gunia, 2011). This dissertation explores a variety of blame and credit behaviors and explains why leaders may enact different types of blame and credit behaviors. In Chapter 2, I conducted a Pilot Study of semi-structured interviews with coaches to examine their thought processes leading up to communications of blame and credit. Study 1 painted a more comprehensive picture of the expressions and patterns of blame and credit which arise during post-game press conferences of NFL coaches. In Chapter 3, I drew from and integrated four separate literatures to develop a theoretical model proposing that there are four motives that drive leader blame and credit behaviors, and that contextual factors may influence the relationship between motive and behavior. In Chapter 4, I conducted three studies to test key elements of the theoretical model, combining an online field survey and experimental designs in the laboratory. These studies revealed that leaders with disparate motives may enact different blame behaviors in light of unsuccessful outcomes in particular. Overall, this dissertation (1) evolves our understanding of the communication and variety of blame and credit in organizations, (2) establishes a theoretical model delineating the motives driving leader blame and credit behaviors, and (3) provides empirical evidence that supports the validity of the theoretical model. This is the first paper of its kind to provide theory and scientific evidence regarding the motives behind blame and credit behaviors of leaders. In doing so, this dissertation brings to the forefront the importance of leaders’ blame and credit behaviors in organizations, and both generates and advances the conversation about these behaviors in the workplace

Shaping frontline practices: a scoping review of human factors implicated in electrical safety incidents

Injuries sustained while performing electrical work are a significant threat to the health and safety of workers and occur frequently. In some jurisdictions, non-fatal serious incidents have increased in recent years. Although significant work has been carried out on electrical safety from a human factor perspective, reviews of this literature are sparse. Thus, the purpose of this review is to collate and summarize human factors implicated in electrical safety events. Articles were collected from three databases (Scopus, Web of Science, and Google Scholar), using the search terms: safety, electri*, human factors, and arc flash. Titles and abstracts were screened, full-text reviews were conducted, and 18 articles were included in the final review. Quality checks were undertaken using the Mixed Methods Appraisal Tool and the Critical Appraisal Skills Program. Environmental, individual, team, organizational, and macro factors were identified in the literature as factors which shape frontline electrical worker behavior, highlighting the complexity of injury prevention. The key contributions of this paper include: (1) a holistic and integrated summary of human factors implicated in electrical safety events, (2) the application of an established theoretical model to explain dynamic forces implicated in electrical safety incidents, and (3) several practical implications and recommendations to improve electrical safety. It is recommended that this framework is used to develop and test future interventions at the individual, team, organizational, and regulator level to mitigate risk and create meaningful and sustainable change in the electrical safety spac

A Genome-Wide Study of Cytogenetic Changes in Colorectal Cancer Using SNP Microarrays: Opportunities for Future Personalized Treatment

In colorectal cancer (CRC), chromosomal instability (CIN) is typically studied using comparative-genomic hybridization (CGH) arrays. We studied paired (tumor and surrounding healthy) fresh frozen tissue from 86 CRC patients using Illumina's Infinium-based SNP array. This method allowed us to study CIN in CRC, with simultaneous analysis of copy number (CN) and B-allele frequency (BAF) - a representation of allelic composition. These data helped us to detect mono-allelic and bi-allelic amplifications/deletion, copy neutral loss of heterozygosity, and levels of mosaicism for mixed cell populations, some of which can not be assessed with other methods that do not measure BAF. We identified associations between CN abnormalities and different CRC phenotypes (histological diagnosis, location, tumor grade, stage, MSI and presence of lymph node metastasis). We showed commonalities between regions of CN change observed in CRC and the regions reported in previous studies of other solid cancers (e.g. amplifications of 20q, 13q, 8q, 5p and deletions of 18q, 17p and 8p). From Therapeutic Target Database, we identified relevant drugs, targeted to the genes located in these regions with CN changes, approved or in trials for other cancers and common diseases. These drugs may be considered for future therapeutic trials in CRC, based on personalized cytogenetic diagnosis. We also found many regions, harboring genes, which are not currently targeted by any relevant drugs that may be considered for future drug discovery studies. Our study shows the application of high density SNP arrays for cytogenetic study in CRC and its potential utility for personalized treatment

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks

In vivo partial cellular reprogramming enhances liver plasticity and regeneration.

Mammals have limited regenerative capacity, whereas some vertebrates, like fish and salamanders, are able to regenerate their organs efficiently. The regeneration in these species depends on cell dedifferentiation followed by proliferation. We generate a mouse model that enables the inducible expression of the four Yamanaka factors (Oct-3/4, Sox2, Klf4, and c-Myc, or 4F) specifically in hepatocytes. Transient in vivo 4F expression induces partial reprogramming of adult hepatocytes to a progenitor state and concomitantly increases cell proliferation. This is indicated by reduced expression of differentiated hepatic-lineage markers, an increase in markers of proliferation and chromatin modifiers, global changes in DNA accessibility, and an acquisition of liver stem and progenitor cell markers. Functionally, short-term expression of 4F enhances liver regenerative capacity through topoisomerase2-mediated partial reprogramming. Our results reveal that liver-specific 4F expression in vivo induces cellular plasticity and counteracts liver failure, suggesting that partial reprogramming may represent an avenue for enhancing tissue regeneration

The Cost of Virulence: Retarded Growth of Salmonella Typhimurium Cells Expressing Type III Secretion System 1

Virulence factors generally enhance a pathogen's fitness and thereby foster transmission. However, most studies of pathogen fitness have been performed by averaging the phenotypes over large populations. Here, we have analyzed the fitness costs of virulence factor expression by Salmonella enterica subspecies I serovar Typhimurium in simple culture experiments. The type III secretion system ttss-1, a cardinal virulence factor for eliciting Salmonella diarrhea, is expressed by just a fraction of the S. Typhimurium population, yielding a mixture of cells that either express ttss-1 (TTSS-1+ phenotype) or not (TTSS-1− phenotype). Here, we studied in vitro the TTSS-1+ phenotype at the single cell level using fluorescent protein reporters. The regulator hilA controlled the fraction of TTSS-1+ individuals and their ttss-1 expression level. Strikingly, cells of the TTSS-1+ phenotype grew slower than cells of the TTSS-1− phenotype. The growth retardation was at least partially attributable to the expression of TTSS-1 effector and/or translocon proteins. In spite of this growth penalty, the TTSS-1+ subpopulation increased from <10% to approx. 60% during the late logarithmic growth phase of an LB batch culture. This was attributable to an increasing initiation rate of ttss-1 expression, in response to environmental cues accumulating during this growth phase, as shown by experimental data and mathematical modeling. Finally, hilA and hilD mutants, which form only fast-growing TTSS-1− cells, outcompeted wild type S. Typhimurium in mixed cultures. Our data demonstrated that virulence factor expression imposes a growth penalty in a non-host environment. This raises important questions about compensating mechanisms during host infection which ensure successful propagation of the genotype

TGF-ß Sma/Mab Signaling Mutations Uncouple Reproductive Aging from Somatic Aging

Female reproductive cessation is one of the earliest age-related declines humans experience, occurring in mid-adulthood. Similarly, Caenorhabditis elegans' reproductive span is short relative to its total life span, with reproduction ceasing about a third into its 15–20 day adulthood. All of the known mutations and treatments that extend C. elegans' reproductive period also regulate longevity, suggesting that reproductive span is normally linked to life span. C. elegans has two canonical TGF-ß signaling pathways. We recently found that the TGF-ß Dauer pathway regulates longevity through the Insulin/IGF-1 Signaling (IIS) pathway; here we show that this pathway has a moderate effect on reproductive span. By contrast, TGF-ß Sma/Mab signaling mutants exhibit a substantially extended reproductive period, more than doubling reproductive span in some cases. Sma/Mab mutations extend reproductive span disproportionately to life span and act independently of known regulators of somatic aging, such as Insulin/IGF-1 Signaling and Dietary Restriction. This is the first discovery of a pathway that regulates reproductive span independently of longevity and the first identification of the TGF-ß Sma/Mab pathway as a regulator of reproductive aging. Our results suggest that longevity and reproductive span regulation can be uncoupled, although they appear to normally be linked through regulatory pathways

Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR=0.42, 95% CI: 0.21-0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR=1.53, 95% CI: 1.21-1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features. Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care