How Do Auditors Behave During Periods of Market Euphoria? The Case of Internet IPOs

The study of periods of market euphoria, such as Holland’s seventeenth-century tulip mania, England’s eighteenth-century South Sea Company, America’s nineteenth-century railroads, or, most recently, the U.S. housing market, is a topic of long-standing interest to economists. Theorists specify conditions under which market participants and institutions cause "bubbles" to arise and persist and empiricists test participant-centric or institution- centric explanations (Hong, Scheinkman, and Xiong 2008; Schultz 2008; Greenwood and Nagel 2009). In this paper, we study a different participant other than one that stands to gain from price fluctuations. We are interested in how auditors behave during periods of market euphoria. Given their gatekeeper responsibility to act in the public’s interest, along with the seeming inevitability of bubbles (Rampell 2009), it is important to study how auditors behave during euphoric market conditions. To address this question, we examine auditor going-concern (GC) opinions around the time of the wave of stressed Internet firms filing to go public on NASDAQ, the capital markets entry point for the companies that went on to constitute "dotcom mania"

Induction of the HIV-1 Tat co-factor cyclin T1 during monocyte differentiation is required for the regulated expression of a large portion of cellular mRNAs

BACKGROUND: P-TEFb, a general RNA polymerase II elongation factor, is composed of CDK9 (cyclin-dependent kinase 9) as a catalytic unit and either cyclin T1, T2 or K as a regulatory subunit. The cyclin T1/P-TEFb complex is targeted by HIV to mediate Tat transactivation. Cyclin T1 protein expression is induced during early macrophage differentiation, suggesting a role in regulation of mRNA expression during the differentiation process. To study the functional significance of cyclin T1 induction during differentiation, we utilized the human Mono Mac 6 (MM6) monocytic cell line. RESULTS: We found that cyclin T1 protein expression is induced by a post-transcriptional mechanism following PMA treatment of MM6 cells, similar to its induction in primary monocytes and macrophages. Also in agreement with findings in primary cells, cyclin T2a is present at relatively high levels in MM6 cells and is not induced by PMA. Although the knock-down of cyclin T1 in MM6 cells by shRNA inhibited HIV-1 Tat transactivation, MM6 cell growth was not affected by the depletion of cyclin T1. Using DNA microarray technology, we found that more than 20% of genes induced by PMA require cyclin T1 for their normal level of induction, and approximately 15% of genes repressed by PMA require cyclin T1 for their normal level of repression. Gene ontology analysis indicates that many of these cyclin T1-dependent genes are related to immune response and signal transduction. CONCLUSION: These results suggest that cyclin T1 serves a critical role in the program of macrophage differentiation, and this raises questions about the feasibility of cyclin T1 serving as an antiviral therapeutic target

Epstein-Barr Virus BART9 miRNA Modulates LMP1 Levels and Affects Growth Rate of Nasal NK T Cell Lymphomas

Nasal NK/T cell lymphomas (NKTCL) are a subset of aggressive Epstein-Barr virus (EBV)-associated non-Hodgkin's lymphomas. The role of EBV in pathogenesis of NKTCL is not clear. Intriguingly, EBV encodes more than 40 microRNAs (miRNA) that are differentially expressed and largely conserved in lymphocryptoviruses. While miRNAs play a critical role in the pathogenesis of cancer, especially lymphomas, the expression and function of EBV transcribed miRNAs in NKTCL are not known. To examine the role of EBV miRNAs in NKTCL, we used microarray profiling and qRT-PCR to identify and validate expression of viral miRNAs in SNK6 and SNT16 cells, which are two independently derived NKTCL cell lines that maintain the type II EBV latency program. All EBV BART miRNAs except BHRF-derived miRNAs were expressed and some of these miRNAs are expressed at higher levels than in nasopharyngeal carcinomas. Modulating the expression of BART9 with antisense RNAs consistently reduced SNK6 and SNT16 proliferation, while antisense RNAs to BARTs-7 and -17-5p affected proliferation only in SNK6 cells. Furthermore, the EBV LMP-1 oncoprotein and transcript levels were repressed when an inhibitor of BART9 miRNA was transfected into SNK6 cells, and overexpression of BART9 miRNA increased LMP-1 protein and mRNA expression. Our data indicate that BART9 is involved in NKTCL proliferation, and one of its mechanisms of action appears to be regulating LMP-1 levels. Our findings may have direct application for improving NKTCL diagnosis and for developing possible novel treatment approaches for this tumor, for which current chemotherapeutic drugs have limited effectiveness

Resolving Gas Dynamics in the Circumnuclear Region of a Disk Galaxy in a Cosmological Simulation

Using a hydrodynamic adaptive mesh refinement code, we simulate the growth and evolution of a galaxy, which could potentially host a supermassive black hole, within a cosmological volume. Reaching a dynamical range in excess of 10 million, the simulation follows the evolution of the gas structure from super-galactic scales all the way down to the outer edge of the accretion disk. Here, we focus on global instabilities in the self-gravitating, cold, turbulence-supported, molecular gas disk at the center of the model galaxy, which provide a natural mechanism for angular momentum transport down to sub-pc scales. The gas density profile follows a power-law scaling as r^-8/3, consistent with an analytic description of turbulence in a quasi-stationary circumnuclear disk. We analyze the properties of the disk which contribute to the instabilities, and investigate the significance of instability for the galaxy's evolution and the growth of a supermassive black hole at the center.Comment: 16 pages (includes appendix), submitted to ApJ. Figures here are at low resolution; for higher resolution version, download http://casa.colorado.edu/~levinerd/ms.pd

Visualization of positive and negative sense viral RNA for probing the mechanism of direct-acting antivirals against hepatitis C virus

RNA viruses are highly successful pathogens and are the causative agents for many important diseases. To fully understand the replication of these viruses it is necessary to address the roles of both positive-strand RNA ((+)RNA) and negative-strand RNA ((-)RNA), and their interplay with viral and host proteins. Here we used branched DNA (bDNA) fluorescence in situ hybridization (FISH) to stain both the abundant (+)RNA and the far less abundant (-)RNA in both hepatitis C virus (HCV)- and Zika virus-infected cells, and combined these analyses with visualization of viral proteins through confocal imaging. We were able to phenotypically examine HCV-infected cells in the presence of uninfected cells and revealed the effect of direct-acting antivirals on HCV (+)RNA, (-)RNA, and protein, within hours of commencing treatment. Herein, we demonstrate that bDNA FISH is a powerful tool for the study of RNA viruses that can provide insights into drug efficacy and mechanism of action

NSCAT high-resolution surface wind measurements in Typhoon Violet

NASA scatterometer (NSCAT) measurements of the western Pacific Supertyphoon Violet are presented for revolutions 478 and 485 that occurred in September 1996. A tropical cyclone planetary boundary layer numerical, model, which uses conventional meteorological and geostationary cloud data, is used to estimate the winds at 10-m elevation in the cyclone. These model winds are then compared with the winds inferred from the NSCAT backscatter data by means of a novel approach that allows a wind speed to be recovered from each individual backscatter cell. This spatial adaptive (wind vector) retrieval algorithm employs several unique steps. The backscatter values are first regrouped in terms of closest neighbors in sets of four. The maximum likelihood estimates of speed and direction are then used to obtain speeds and directions for each group. Since the cyclonic flow around the tropical cyclone is known, NSCAT wind direction alias selection is easily accomplished. The selected wind directions are then used to convert each individual backscatter value to a wind speed. The results are compared to the winds obtained from the tropical cyclone boundary layer model. The NSCAT project baseline geophysical model function, NSCAT 1, was found to yield wind speeds that were systematically too low, even after editing for suspected rain areas of the cyclone. A new geophysical model function was developed using conventional NSCAT data and airborne Ku band scatterometer measurements in an Atlantic hurricane. This new model uses the neural network method and yields substantially better agreement with the winds obtained from the boundary layer model according to the statistical tests that were used

Application of machine learning constructs to predict post-operative complications and adverse events following shoulder hemiarthroplasty

Background: Artificial intelligence (AI) constructs and machine learning (ML) algorithms have demonstrated utility in predicting various clinical, surgical, and financial outcomes. In this study, we applied AI to shoulder hemiarthroplasty (HA) to predict various post-operative complications. Methods: The sample was queried from the American college of surgeons-national surgical quality improvement program (ACS-NSQIP) database for all shoulder HA cases from 2008-2018. Six ML algorithms-random forest classifier, gradient boosting classifier, decision tree classifier, SVM classifier-tuned model, Gaussian Naïve Bayes classifier, multi-layer perception-analyzed the sample dataset. Postoperative complications included extended length of stay, non-home discharge destination, transfusion, and any adverse event. Each ML model was compared to logistic regression (LR), and model strength was evaluated. Results: We identified a total of 1585 shoulder HA cases. Mean age, BMI, operative time, and length of stay were 66±12 years, 31±8 kg/m2, 114±61 minutes, and 2.93±6.61 days. Preop hematocrit, longer operative time, and older age were most predictive of extended length of stay. Preop hematocrit, operative time, and ASA class had the highest importance in any adverse events (AAE) prediction. ML models outperformed traditional comorbidity indices, LR, for predicting extended length of stay (79% vs. 66%), non-home discharge destination (79% vs. 65%), any adverse event (78% vs. 66%), and transfusion requirement (82% vs. 63%).  Conclusions: ML algorithms predicted post-surgical outcomes of interest following shoulder HA at a higher rate to conventional LR and can assist orthopedic surgeons in decision making.