The Economics of Strategic Opportunity

As emphasized by Barney (1986), any explanation of superior profitability must account for why the resources supporting such profitability could have been acquired for a price below their rent generating capacity. Building upon the literature in economics on coordination failures and incomplete markets, we suggest a framework for analyzing such strategic factor market inefficiencies. Our point of departure is that a strategic opportunity exists whenever prices fail to reflect the value of a resource's best use. This paper examines the challenges of imputing a resource's value in the absence of explicit price guidance and suggests the likely characteristics of strategic opportunities. Our framework also suggests that the discovery of strategic opportunity is often a matter of serendipity and access to relevant idiosyncratic resources. This latter observation provides prescriptive advice, although the analysis also explains why more detailed guidance has to be firm specific.

Strategizing with biases : engineering choice contexts for better decisions using the Mindspace approach

We introduce strategists to the Mindspace framework and explore its applications in strategic contexts. This framework consists of nine effective behavioral interventions which are grounded in the public policy applications, and focuses on how changing the context can be more effective than attempts to de-bias decision-makers. Behavioral changes are likely when we follow rather than fight human nature. Better decisions can be achieved by engineering choice contexts to “engage a bias” to overcome a more damaging bias. We illustrate how to engineer strategic contexts through two case studies and outline directions and challenges when applying Mindspace to strategic decisions

On Adaptive Emergence of Trust Behavior in the Game of Stag Hunt

We study the emergence of trust behavior at both the individual and the population levels. At the individual level, in contrast to prior research that views trust as fixed traits, we model the emergence of trust or cooperation as a result of trial and error learning by a computer algorithm borrowed from the field of artificial intelligence (Watkins 1989). We show that trust can indeed arise as a result of trial and error learning. Emergence of trust at the population level is modeled by a grid-world consisting of cells of individual agents, a technique known as spatialization in evolutionary game theory. We show that, under a wide range of assumptions, trusting individuals tend to take over the population and trust becomes a systematic property. At both individual and population levels, therefore, we argue that trust behaviors will often emerge as a result of learning

The Well-Being of the German Adult Population Measured with the WHO-5 over Different Phases of the COVID-19 Pandemic: An Analysis within the COVID-19 Snapshot Monitoring Study (COSMO)

The aim of this study is to evaluate factors associated with the subjective well-being (SWB) and suspected depression measured with WHO-5 among German adults during different phases of the COVID-19 pandemic. Survey data were analyzed from the COVID-19 Snapshot Monitoring (COSMO) study, which collected data from 972, 1013, and 973 participants in time point 1 (19–20 May 2020), time point 2 (15–16 September 2020), and time point 3 (21–22 December 2020), respectively. Descriptive analyses and logistic regression analyses to identify the factors associated with suspected depression (WHO-5 ≤ 50) were conducted. Data showed that the mean WHO-5 scores in three time points were 56.17, 57.27, and 53.93, respectively. The risk of suspected depression was increased by about 1.5 times for females, 2.5–3 times among 18–24 year-olds compared to ages above 65 years, 1.5 times for singles, 2 times for those with chronic illnesses, and 2–3 times for people living in poverty. The main study findings show that German adult SWB is lower than pre-pandemic reference values. Special focus should be placed on vulnerable groups, such as females, younger persons, and people living in poverty who are most prone to a reduction in SWB and therefore suspected depression

Loss of β-catenin promotes chondrogenic differentiation of aortic valve interstitial cells

OBJECTIVE: The Wnt/β-catenin signaling pathway has been implicated in human heart valve disease and is required for early heart valve formation in mouse and zebrafish. However, the specific functions of Wnt/β-catenin signaling activity in heart valve maturation and maintenance in adults have not been determined previously. APPROACH AND RESULTS: Here, we show that Wnt/β-catenin signaling inhibits Sox9 nuclear localization and proteoglycan expression in cultured chicken embryo aortic valves. Loss of β-catenin in vivo in mice, using Periostin(Postn)Cre-mediated tissue-restricted loss of β-catenin (Ctnnb1) in valvular interstitial cells, leads to the formation of aberrant chondrogenic nodules and induction of chondrogenic gene expression in adult aortic valves. These nodular cells strongly express nuclear Sox9 and Sox9 downstream chondrogenic extracellular matrix genes, including Aggrecan, Col2a1, and Col10a1. Excessive chondrogenic proteoglycan accumulation and disruption of stratified extracellular matrix maintenance in the aortic valve leaflets are characteristics of myxomatous valve disease. Both in vitro and in vivo data demonstrate that the loss of Wnt/β-catenin signaling leads to increased nuclear expression of Sox9 concomitant with induced expression of chondrogenic extracellular matrix proteins. CONCLUSIONS: β-Catenin limits Sox9 nuclear localization and inhibits chondrogenic differentiation during valve development and in adult aortic valve homeostasis

Waiting time for cancer treatment and mental health among patients with newly diagnosed esophageal or gastric cancer: a nationwide cohort study

Background Except for overall survival, whether or not waiting time for treatment could influences other domains of cancer patients’ overall well-being is to a large extent unknown. Therefore, we performed this study to determine the effect of waiting time for cancer treatment on the mental health of patients with esophageal or gastric cancer. Methods Based on the Swedish National Quality Register for Esophageal and Gastric Cancers (NREV), we followed 7,080 patients diagnosed 2006–2012 from the time of treatment decision. Waiting time for treatment was defined as the interval between diagnosis and treatment decision, and was classified into quartiles. Mental disorders were identified by either clinical diagnosis through hospital visit or prescription of psychiatric medications. For patients without any mental disorder before treatment, the association between waiting time and subsequent onset of mental disorders was assessed by hazard ratios (HRs) with 95% confidence interval (CI), derived from multivariable-adjusted Cox model. For patients with a preexisting mental disorder, we compared the rate of psychiatric care by different waiting times, allowing for repeated events. Results Among 4,120 patients without any preexisting mental disorder, lower risk of new onset mental disorders was noted for patients with longer waiting times, i.e. 18–29 days (HR 0.86; 95% CI 0.74-1.00) and 30–60 days (HR 0.79; 95% CI 0.67-0.93) as compared with 9–17 days. Among 2,312 patients with preexisting mental disorders, longer waiting time was associated with more frequent psychiatric hospital care during the first year after treatment (37.5% higher rate per quartile increase in waiting time; p for trend = 0.0002). However, no such association was observed beyond one year nor for the prescription of psychiatric medications. Conclusions These data suggest that waiting time to treatment for esophageal or gastric cancer may have different mental health consequences for patients depending on their past psychiatric vulnerabilities. Our study sheds further light on the complexity of waiting time management, and calls for a comprehensive strategy that takes into account different domains of patient well-being in addition to the overall survival.This study was partly supported by the Swedish Cancer Society (grant No: CAN 2014/417).Peer Reviewe

CompMoby: Comparative MobyDick for detection of cis-regulatory motifs

<p>Abstract</p> <p>Background</p> <p>The regulation of gene expression is complex and occurs at many levels, including transcriptional and post-transcriptional, in metazoans. Transcriptional regulation is mainly determined by sequence elements within the promoter regions of genes while sequence elements within the 3' untranslated regions of mRNAs play important roles in post-transcriptional regulation such as mRNA stability and translation efficiency. Identifying cis-regulatory elements, or motifs, in multicellular eukaryotes is more difficult compared to unicellular eukaryotes due to the larger intergenic sequence space and the increased complexity in regulation. Experimental techniques for discovering functional elements are often time consuming and not easily applied on a genome level. Consequently, computational methods are advantageous for genome-wide cis-regulatory motif detection. To decrease the search space in metazoans, many algorithms use cross-species alignment, although studies have demonstrated that a large portion of the binding sites for the same trans-acting factor do not reside in alignable regions. Therefore, a computational algorithm should account for both conserved and nonconserved cis-regulatory elements in metazoans.</p> <p>Results</p> <p>We present CompMoby (Comparative MobyDick), software developed to identify cis-regulatory binding sites at both the transcriptional and post-transcriptional levels in metazoans without prior knowledge of the trans-acting factors. The CompMoby algorithm was previously shown to identify cis-regulatory binding sites in upstream regions of genes co-regulated in embryonic stem cells. In this paper, we extend the software to identify putative cis-regulatory motifs in 3' UTR sequences and verify our results using experimentally validated data sets in mouse and human. We also detail the implementation of CompMoby into a user-friendly tool that includes a web interface to a streamlined analysis. Our software allows detection of motifs in the following three categories: one, those that are alignable and conserved; two, those that are conserved but not alignable; three, those that are species specific. One of the output files from CompMoby gives the user the option to decide what category of cis-regulatory element to experimentally pursue based on their biological problem. Using experimentally validated biological datasets, we demonstrate that CompMoby is successful in detecting cis-regulatory target sites of known and novel trans-acting factors at the transcriptional and post-transcriptional levels.</p> <p>Conclusion</p> <p>CompMoby is a powerful software tool for systematic <it>de novo </it>discovery of evolutionarily conserved and nonconserved cis-regulatory sequences involved in transcriptional or post-transcriptional regulation in metazoans. This software is freely available to users at <url>http://genome.ucsf.edu/compmoby/</url>.</p