Transglycosylation Activity of Engineered Bifidobacterium Lacto-N-Biosidase Mutants at Donor Subsites for Lacto-N-Tetraose Synthesis

The health benefits of human milk oligosaccharides (HMOs) make them attractive targets as supplements for infant formula milks. However, HMO synthesis is still challenging and only two HMOs have been marketed. Engineering glycoside hydrolases into transglycosylases may provide biocatalytic routes to the synthesis of complex oligosaccharides. Lacto-N-biosidase from Bifidobacterium bifidum (LnbB) is a GH20 enzyme present in the gut microbiota of breast-fed infants that hydrolyzes lacto-N-tetraose (LNT), the core structure of the most abundant type I HMOs. Here we report a mutational study in the donor subsites of the substrate binding cleft with the aim of reducing hydrolytic activity and conferring transglycosylation activity for the synthesis of LNT from p-nitrophenyl β-lacto-N-bioside and lactose. As compared with the wt enzyme with negligible transglycosylation activity, mutants with residual hydrolase activity within 0.05% to 1.6% of the wild-type enzyme result in transglycosylating enzymes with LNT yields in the range of 10–30%. Mutations of Trp394, located in subsite -1 next to the catalytic residues, have a large impact on the transglycosylation/hydrolysis ratio, with W394F being the best mutant as a biocatalyst producing LNT at 32% yield. It is the first reported transglycosylating LnbB enzyme variant, amenable to further engineering for practical enzymatic synthesis of LNT.     

A Bluetooth Based Sensor Network for Civil Infrastructure Health Monitoring

Communicating with sensors has long been limited either to wired connections or to proprietary wireless communication protocols. Using a ubiquitous and inexpensive wireless communication technology to create Sensor Area Networks (SANs) will accelerate the extensive deployment of sensor technology. Bluetooth, an emerging, worldwide standard for inexpensive, local wireless communication is a viable choice for SANs because of its inherent support for some of the important requirements – low power, small form factor, low cost and sufficient communication range. In this paper we outline an approach, centered on the Bluetooth technology, to support a sensor network composed of fixed wireless sensors for health monitoring of highways, bridges and other civil infrastructures. We present a topology formation scheme that not only takes into account the traffic generated by different sensors but also the associated link strengths, buffer capacities and energy availability. The algorithm makes no particular assumptions as to the placement of nodes, and not all nodes need to be in radio proximity of each other. The output is a tree shaped scatternet rooted at the sensor hub (data logger) that is balanced in terms of traffic carried on each of the links. We also analyze the scheduling, routing and healing aspects of the resulting sensor-net topology.     

Influence of n-alkanes on wettability and zeta potential of quartz

Contact angles were measured in the following systems: quartz/water droplet/saturated vapor of water + n-alkane and quartz/water droplet/saturated vapor of n-alkane. The alkanes tested were from hexane to pentadecane. In both systems non-smooth changes of contact angle as a function of the chain length were observed. These changes are similar to the zeta-potential changes measured previously for two different samples of quartz in the quartz/n-alkana/water system. On the basis of the results and calculations it is suggested that the observed non-smooth changes of contact angle are due to similar changes in film pressures of the water and n-alkanes.     

Predicting Acute Renal Failure after Cardiac Surgery: Validation and Re‐definition of a Risk‐Stratification Algorithm

Background:  Acute renal failure (ARF) after cardiac surgery is associated with significant morbidity and mortality, irrespective of the need for dialysis. Previous studies have attempted to identify predictors of ARF and develop risk stratification algorithms. This study aims to validate the algorithm in an independent cohort of patients that includes a significant proportion of female and black patients and compares two different definitions of renal outcome.
Methods:  A large single center cardiac surgery database was examined (n, 24,660; 1993–2000) which included 29.9% females and 3.7% black patients. Post‐operative ARF was defined as: a) ARF requiring dialysis, b) > 50% reduction in creatinine clearance relative to baseline or requiring dialysis. Clinical variables related to baseline renal function and cardiovascular disease were used in recursive partitioning analysis for both outcome definitions. Chi‐square goodness of fit analysis was performed to validate the algorithm.
Results:  The frequency of post‐operative ARF requiring dialysis ranged between 0.5 and 15.5% based on the risk categories with the area under the receiver operating characteristic (ROC) curve of 0.78. Using the more inclusive definition of ARF, the frequency was significantly higher ranging from 2.6 to 25%(P < 0.001) with an area under ROC curve of 0.65.
Conclusions:  The renal risk stratification algorithm is valid in predicting post‐operative ARF in an independent cohort of patients, well represented by differences in gender and race. Since the need for dialysis remains subjective, a more objective and inclusive definition of ARF may help in identifying a larger number of patients 'at‐risk'.     

DSS research and practice in perspective

The aim of this paper is to assess the state-of-the-art in the Decision Support Systems (DSS) field from both a research and a practice perspective. Three main dimensions of DSS research and practice are addressed: 1) supporting human decision-making processes, 2) integrating DSS into the organizational context, and 3) identifying new application domains. The related analysis and discussion provides a better understanding of past developments in the DSS field and insights into future evolution patterns.     

OLAP and bibliographic databases

The application of online analytical processing (OLAP) technology to bibliographic databases is addressed. We show that OLAP tools can be used by librarians for periodic and ad hoc reporting, quality assurance, and data integrity checking, as well as by research policy makers for monitoring the development of science and evaluating or comparing disciplines, fields or research groups. It is argued that traditional relational database management systems, used mainly for day-to-day data storage and transactional processing, are not appropriate for performing such tasks on a regular basis. For the purpose, a fully functional OLAP solution has been implemented on Biomedicina Slovenica, a Slovenian national bibliographic database. We demonstrate the system's usefulness by extracting data for studying a selection of scientometric issues: changes in the number of published papers, citations and pure citations over time, their dependence on the number of co-operating authors and on the number of organisations the authors are affiliated to, and time-patterns of citations. Hardware, software and feasibility considerations are discussed and the phases of the process of developing bibliographic OLAP applications are outlined. This revised version was published online in June 2006 with corrections to the Cover Date.     

Traffic classification and scheduling in ATM networks

Virtual paths (VPs) are an integral part of the resource management and control hierarchy of ATM (asynchronous transfer mode) networks. To improve the utilization of network resources and facilitate management and control, source types are organized into traffic classes. Each traffic class is transported by its own virtual path subnetwork. In this paper, we consider issues related to the design of traffic classes. We consider an ATM switch node to which cells arrive from a diverse set of source types. Traffic classes are assumed to be served according to a weighted round robin policy, while cells belonging to a given traffic class are served in first-come-first-served order. We consider the problem of determining the optimal set of traffic classes. Under suitable simplifying assumptions, it is shown that the above problem can be modeled as a set-partitioning problem. The structure of the problem at hand is then exploited to develop an efficient heuristic. Several examples are given to illustrate the developed methodology.Supported partially through NSF Grant NCR-891447 and AT&T Grant 5-23690.     

Convergence of the inductive and deductive models in the measurement of reasoning abilities.

Reviews evidence concerning the congruence of the inductive and deductive models in logic and presents support for this congruence in the context of new test items designed to exemplify general-to-particular induction. Data from the Professional and Administrative Career Examination corroborate the logical foundations of deduction and induction as convergent models. Factor analysis of the items demonstrated factorial convergence, which lends additional support to the postulate of convergence. Implications for the understanding of cognitive processes and for psychometric practice are discussed in relation to such issues as the use of verbal and nonverbal test media, redundancy of measurement, and problem-solving strategies. (50 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)