Pyramids to Players Clubs: The Battle for Competitive Advantage in Las Vegas

The evolution of the Las Vegas casinos from owner operator to the institutionally financed and corporately managed casino-resort has been the predominant feature of the evolution of the US Gaming market in the past 30 years. This paper examines the strategic frameworks used by Las Vegas casino resorts and identifies the drivers for competitive advantage moving forward

Elvis Who? Understanding, Attracting and Retaining the Next Generation of Las Vegas Customers

Las Vegas is in the middle of a period of generational transformation. The visitor profile has changed greatly since 2007, however the behavior and attitudes of this new visitor are very different that of previous generations of visitors. By undertaking a survey of this group we identify several key trends that make this group unique. Not only does this new visitor come to Las Vegas more frequently, follow Las Vegas when they are not in the city, they demonstrate planning and spending patterns that are unlike any other group. This paper analyses the next generation of visitor, and suggests methods to capture loyalty and market share

The Las Vegas Loyalty Battle Is Over. What’s Next?

The strategic mission by Las Vegas casino operators to capture customer loyalty over the past decade has been a success. In 2021, 57% of visitors were generally loyal to a particular resort, compared to 32% in 2011. Only 7% of visitors were not a member of any rewards program in 2021, compared to 16% in 2011. This has consequences for new market entrants who face a greater challenge to capture customers in a more mature, consolodated and strategic business environment. Moreover, the drivers of loyalty remain different within the various customer segments, with the new generation of visitors responding less to traditional “transactional” methods of loyalty seen in traditional rewards programs. For resorts that are new to market, or have an existing footprint, this research provides a guide to future relevance in a competitive environment, as the path to obsolescence is visible to even the most notable icons

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Fairness and feasibility in deep mitigation pathways with novel carbon dioxide removal considering institutional capacity to mitigate

Questions around the technical and political feasibility of deep mitigation scenarios assessed by the Intergovernmental Panel on Climate Change have increasingly been raised as have calls for more directly analyzing and incorporating aspects of justice and fairness. Simultaneously, models are increasing the technical representation of novel carbon-dioxide removal (CDR) approaches to provide policy-relevant analyses of mitigation portfolios in the context of the rising number of net-zero CO _2 and GHG targets made by parties to the Paris Agreement. Still, in most cost-effective mitigation scenarios developed by integrated assessment models, a significant portion of mitigation is assumed to take place in developing regions. We address these intersecting questions through analyzing scenarios that include direct air capture of CO _2 with storage (DACCS), a novel CDR technology that is not dependent on land potential and can be deployed widely, as well as regional variations in institutional capacity for mitigation based on country-level governance indicators. We find that including novel CDR and representations of institutional capacity can enhance both the feasibility and fairness of 2 °C and 1.5 °C high-overshoot scenarios, especially in the near term, with institutional capacity playing a stronger role than the presence of additional carbon removal methods. However, our results indicate that new CDR methods being studied by models are not likely to change regional mitigation outcomes of scenarios which achieve the 1.5 °C goal of the Paris Agreement. Thus, while engineered carbon removals like DACCS may play a significant role by midcentury, gross emissions reductions in mitigation pathways arriving at net-zero CO _2 emissions in line with 1.5 °C do not substantially change. Our results highlight that further investment and development of novel CDR is critical for post-net-zero CO _2 mitigation, but that equitable achievement of this milestone will need to arrive through technical and financial transfers, rather than by substantial carbon removals in developed countries before mid-century

Climate mitigation scenarios with persistent COVID-19-related energy demand changes

The COVID-19 pandemic caused radical temporary breaks with past energy use trends. How post-pandemic recovery will impact the longer-term energy transition is unclear. Here we present a set of global COVID-19 shock-and-recovery scenarios that systematically explore the effect of demand changes persisting. Our pathways project final energy demand reductions of 1–36 EJ yr−1 by 2025 and cumulative CO2 emission reductions of 14–45 GtCO2 by 2030. Uncertainty ranges depend on the depth and duration of the economic downturn and demand-side changes. Recovering from the pandemic with energy-efficient practices embedded in new patterns of travel, work, consumption and production reduces climate mitigation challenges. A low energy demand recovery reduces carbon prices for a 1.5 °C-consistent pathway by 19%, lowers energy supply investments until 2030 by US$1.8 trillion and softens the pressure to rapidly upscale renewable energy technologies

Persistent mTORC1 signaling in cell senescence results from defects in amino acid and growth factor sensing

Mammalian target of rapamycin complex 1 (mTORC1) and cell senescence are intimately linked to each other and to organismal aging. Inhibition of mTORC1 is the best-known intervention to extend lifespan, and recent evidence suggests that clearance of senescent cells can also improve health and lifespan. Enhanced mTORC1 activity drives characteristic phenotypes of senescence, although the underlying mechanisms responsible for increased activity are not well understood. We have identified that in human fibroblasts rendered senescent by stress, replicative exhaustion, or oncogene activation, mTORC1 is constitutively active and resistant to serum and amino acid starvation. This is driven in part by depolarization of senescent cell plasma membrane, which leads to primary cilia defects and a resultant failure to inhibit growth factor signaling. Further, increased autophagy and high levels of intracellular amino acids may act to support mTORC1 activity in starvation conditions. Interventions to correct these phenotypes restore sensitivity to the mTORC1 signaling pathway and cause death, indicating that persistent signaling supports senescent cell survival