Carboxylases Involved in Microbial Acetone and Acetophenone Metabolism

A number of bacteria are capable of growth with acetone and acetophenone as their sole sources of carbon and/or energy. The pathways and enzymes involved in the transformation of these molecules into useable carbon and energy are unique. Among these are two novel enzymes, acetone carboxylase and acetophenone carboxylase, which represent a fundamentally novel classes of carboxylases. The initial step in acetone metabolism, in X. autotrophicus st Py2, R. capsulatus st B10 and R. rhodochrous, is the thermodynamically unfavorable reaction to yield acetoacetate. This step is catalyzed by the enzyme acetone carboxylase and is coupled with the unprecedented, concomitant hydrolysis of two phosphoanhydride bonds of ATP. This enzyme also requires two tightly bound Mn2+ ions, among other co-factors, for catalytic activity. In a similar, albeit distinct manner, acetophenone carboxylase catalyzes the carboxylation of acetophenone to benzoylacetate. Reminiscent of acetone carboxylase, carboxylation activity in this enzyme is dependent on the hydrolysis of ATP to ADP and inorganic phosphate. Catalytic activity is also dependent on Zn2+ and either of Mn2+ or Mg2+ as co-factors. Additionally, similar to acetone carboxylase, acetophenone carboxylase shows uncoupled ATPase activity with either bicarbonate or acetophenone in the absence of a second substrate. This indicates that both substrates may be phosphorylated. The studies on acetone and acetophenone carboxylase have expanded our knowledge on the novel mechanisms and cofactors involved in the metabolism of toxic, reactive, xenobiotic molecules such as acetone and acetophenone. Further, as in the case of acetone carboxylase, homologs of these enzymes are found in higher organisms such as mammals. The biochemical and mechanistic properties of these enzymes may be relevant to the modes of action of these homologs. In this report, using the work currently accomplished on these enzymes, and by discussing their salient features, an effort has been made to provide a detailed insight into these enzymes

Integrating database and data stream systems

Traditionally, Database systems are viewed as passive data storage. Finite data sets are stored in traditional Database Systems and retrieved when needed. But applications such as sensor networks, network monitoring, retail transactions, and others, produce infinite data sets. A new system is under research and development, known as Data Stream Management System (DSMS), to deal with the infinite data sets. In DSMS, Data stream is a continuous source of sequential data. In Object-Oriented languages, like C/C++ and Java, the concept of stream does exist. The stream is viewed as a channel to which data is being inserted at one end and retrieved from the other end. To the database world, stream is a relatively new concept. In DSMS, data is processed on-line. Due to its very nature, the data fed to application through Data Stream can get lost, as it is never stored. This makes Data Stream non-persistent. Unlike this, Database Systems are persistent, which is the basis of my hypothesis. My hypothesis is Data Stream Management System and Database System can be combined under the same concepts and Data Stream can be made persistent. In this project, I have used an embedded database as a middleware to cache the data that is fed to an application through Data Stream. The embedded database is directly linked to the application that requires access to the stored data and is faster compared to a conventional database management system. Storing the streaming data in an embedded database makes Data Stream persistent. In the system developed, embedded database also stores the history of data from Database System. Now, any query that is run against the embedded database will generate combined result from Data Streams and Database Systems. An application is developed, using Active Collection Framework as a test bed, to prove the concept

Eficiencia relativa como indicador del rendimiento futuro.

Una parte importante de la investigación reciente se ha dirigido a explorar las posibilidades de incluir indicadores del rendimiento futuro en los sistemas de control de gestión. La literatura sobre predicción de resultados muestra que medidas tradicionales de rendimiento, tales como el resultado de explotación, pueden no ser un buen instrumento de predicción por incorporar componentes de carácter transitorio. Una medida que sea capaz de capturar el componente permanente de los resultados pudiera tener capacidad predictiva en adicción a la del resultado actual y pasado. El Análisis Envolvente de Datos (DEA) es una metodología que permite determinar la eficiencia relativa de las empresas en la utilización de los recursos disponibles. En este trabajo evaluamos la utilidad de una medida DEA de la eficiencia en la gestión, para la predicción del resultado de explotación futuro. En una primera etapa utilizamos el Análisis Envolvente de Datos (DEA) para determinar la eficiencia relativa de una muestra de empresas. En una segunda etapa, estimamos un modelo de regresión para valorar la utilidad de la medida DEA en la predicción del resultado de explotación futuro. Los resultados indican que esta medida de eficiencia tiene contenido informativo para la predicción del resultado de explotación futuro, en adición al resultado actual y pasado.A considerable amount of recent literature has been devoted to examining the potential for including forward-looking performance measures in the management control systems of firms. Prior research has shown that traditional performance measures such as current operating income may not be a perfect predictor of future operating income because of transitory economic conditions that are reflected in current earnings. A measure that is able to capture the persistent component of firm performance may have pred ictive ability over and above past earnings information. Data Envelopment Analysis (DEA) is an estimation methodology that measures the relative efficiency of business units in the use of available resources for generating revenue. In this paper, we evaluate the information content of a DEA-based efficiency measure for predicting future operating income. In the first stage of our analysis we use DEA to determine the relative performance of a sample of firms. In the second st age, we estimate regression models to assess the information content of this DEA measure of relative efficiency in forecasting the following year’s operating income. Our empirical results show that th e efficiency measure has significant ability to predict the following year’s operating income even after controlling for current and the prior years’ operating income

A universal cloning method based on yeast homologous recombination that is simple, efficient, and versatile

AbstractCloning by homologous recombination (HR) in Saccharomyces cerevisiae is an extremely efficient and cost-effective alternative to other methods of recombinant DNA technologies. Unfortunately, it is incompatible with all the various specialized plasmids currently used in microbiology and biomedical research laboratories, and is therefore, not widely adopted. In an effort to dramatically improve the versatility of yeast gap-repair cloning and make it compatible with any DNA plasmid, we demonstrate that by simply including a yeast-cloning cassette (YCC) that contains the 2-micron origin of replication (2μm ori) and the ura3 gene for selection, multiple DNA fragments can be assembled into any DNA vector. We show this has almost unlimited potential by building a variety of plasmid for different uses including: recombinant protein production, epitope tagging, site-directed mutagenesis, and expression of fluorescent fusion proteins. We demonstrate the use in a variety of plasmids for use in microbial systems and even demonstrate it can be used in a vertebrate model. This method is remarkably simple and extremely efficient, plus it provides a significant cost saving over commercially available kits

Asymmetric persistence and the market pricing of accruals and cash flows

We investigate whether stock prices reflect the asymmetric persistence of accruals and cash flows resulting from conditional conservatism. Using the Mishkin (1983) test (MT), we provide further evidence on the earnings fixation explanation for the accrual anomaly. We also apply panel estimation techniques that significantly affect market efficiency inferences. Our results suggest that over our sample period (1) investors seem to partially anticipate asymmetric persistence in accruals and cash flows; (2) the accrual anomaly originates in the dispricing of accruals in years of economic gains, even though the differential persistence between accruals and cash flows is greatest in years of economic losses; (3) investors respond differently to accrual and cash flow surprises and therefore they do not naively fixate on earnings surprises; and (4) after clustering standard errors in the MT by firm and year dimensions, there is no longer evidence of cash flow mispricing, while the statistical significance of accrual mispricing falls. All our findings contradict the earnings fixation explanation for the accrual anomaly. Our study has implications for understanding the accrual anomaly in relation to accrual dynamics, as well as for researchers interested in using the MT framework to test the rationality of investor expectations more generally

The role of financial analysts in stock market efficiency with respect to annual earnings and its cash and accrual components

This study examines biases in stock prices and financial analysts\u27 earnings forecasts. These biases take the form of systematic overweighting or underweighting of the persistence characteristics of cash versus accrual earnings components. Our evidence suggests that stock prices tend to overweight and financial analysts tend to underweight these persistence characteristics. Furthermore, we find that analysts\u27 underweighting attenuates stock price overweighting. However, we find little evidence that the overweighting in stock prices attenuates analyst underweighting. This study brings a new perspective to the literature regarding the disciplining role of financial analysts in capital markets

Investor Competition Over Information and the Pricing of Information Asymmetry

Whether the information environment affects the cost of capital is a fundamental question in accounting and finance research. Relying on theories about competition between informed investors as well as the pricing of information asymmetry, we hypothesize a cross-sectional variation in the pricing of information asymmetry that is conditional on competition. We develop and validate empirical proxies for competition using the number and concentration of institutional investor ownership. Using these proxies, we find a lower pricing of information asymmetry when there is more competition. Overall, our results suggest that competition between informed investors has an important effect on how the information environment affects the cost of capital.Deloitte Foundatio

Maximizing Wound Coverage in Full-Thickness Skin Defects: A Randomized-Controlled Trial of Autologous Skin Cell Suspension and Widely Meshed Autograft Versus Standard Autografting

BACKGROUND: Traumatic insults, infection, and surgical procedures can leave skin defects that are not amenable to primary closure. Split-thickness skin grafting (STSG) is frequently used to achieve closure of these wounds. Although effective, STSG can be associated with donor site morbidity, compounding the burden of illness in patients undergoing soft tissue reconstruction procedures. With an expansion ratio of 1:80, autologous skin cell suspension (ASCS) has been demonstrated to significantly decrease donor skin requirements compared with traditional STSG in burn injuries. We hypothesized that the clinical performance of ASCS would be similar for soft tissue reconstruction of nonburn wounds. METHODS: A multicenter, within-patient, evaluator-blinded, randomized-controlled trial was conducted of 65 patients with acute, nonthermal, full-thickness skin defects requiring autografting. For each patient, two treatment areas were randomly assigned to concurrently receive a predefined standard-of-care meshed STSG (control) or ASCS + more widely meshed STSG (ASCS+STSG). Coprimary endpoints were noninferiority of ASCS+STSG for complete treatment area closure by Week 8, and superiority for relative reduction in donor skin area. RESULTS: At 8 weeks, complete closure was observed for 58% of control areas compared with 65% of ASCS+STSG areas (p = 0.005), establishing noninferiority of ASCS+STSG. On average, 27.4% less donor skin was required with ASCS+ STSG, establishing superiority over control (p \u3c 0.001). Clinical healing (≥95% reepithelialization) was achieved in 87% and 85% of Control and ASCS+STSG areas, respectively, at 8 weeks. The treatment approaches had similar long-term scarring outcomes and safety profiles, with no unanticipated events and no serious ASCS device-related events. CONCLUSION: ASCS+STSG represents a clinically effective and safe solution to reduce the amount of skin required to achieve definitive closure of full-thickness defects without compromising healing, scarring, or safety outcomes. This can lead to reduced donor site morbidity and potentially decreased cost associated with patient care. Clincaltrials.gov identifier: NCT04091672. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level I

Long-Term Industry Reversals

YesThis study investigates whether, how and why industry performance can drive long-term return reversals. Using data from the UK, we find that firms in losing industries significantly outperform those in winning industries over the subsequent five years. These industry reversals remain strong and persistent after controlling for stock momentum, industry momentum, seasonal effects and traditional risk factors. We find a strong influence of past industry performance on stock return reversals. Our results also show that past industry performance is the driving force behind long-term reversals. Specifically, we find that industry components drive stock reversals, while past stock performance does not explain industry reversals. Further analysis suggests that industry reversals are present in both good and bad states of the economy and are stronger in industries with high valuation uncertainty. This implies that industry reversals are more likely to be a result of mispricing