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Mandelate racemase (MR) catalyzes the interconversion of the enantiomers of mandelate using a two-base mechanism with Lys 166 acting as the Bronsted base to abstract the α-proton from (S)-mandelate. The resulting intermediate is subsequently re-protonated by the conjugate acid of His 297 to yield (R)-mandelate. The roles of these amino acids are reversed when (R)-mandelate is the substrate. The side chains of Tyr 137, Lys 164, and Lys 166 form a H-bonding network and the proximity of the two e-NH3+ groups is believed to lower the pKa of Lys 166. We used site-directed mutagenesis, kinetics, and pH-rate studies to explore the roles of Lys 164 (K164 C/M) and Tyr 137 (Y137 L/F/S/T) in catalysis. The efficiency (kcat/Km) was reduced ∼3.5 × 105-fold for K164C MR, relative to wild-type MR, indicating a major role for this residue in catalysis. The efficiency of Y137F MR, however, was reduced only 25–30-fold. pH-Rate profiles (log kcat vs. pH) revealed that substitution of Tyr 137 by Phe increased the kinetic pKa of Lys 166 from 5.88 ± 0.02 to 7.3 ± 0.2. Hence, Tyr 137 plays an important role in facilitating the reduction of the pKa of the Bronsted base Lys 166 by ∼1.4 units. Interestingly, the Phe substitution also increased the kinetic pKa of His 297 from 5.97 ± 0.04 to 7.1 ± 0.1. Thus, the Tyr 137-Lys 164-Lys 166 H-bonding network plays a broader role in modulating the pKa of catalytic residues by influencing the electrostatic character of the entire active site, not only by decreasing the observed pKa value of Lys 166, but also by decreasing the pKa of His 297 by 1.1 units.

Background The selection of optimal donor is crucial for successful hematopoietic stem cell transplantation (HSCT). Thereby, it is appropriate to know, in addition to basic human leukocyte antigen (HLA) gene matches, other immunogenic or nonimmunogenic parameters predicting the outcome of transplant. Objective A unified approach is necessary to provide a comprehensive view of the patient-donor compatibility characterization outside of standard HLA genes. The approach should be applicable as a tool for optimizing procedures for extended donor typing and/or verification typing of a donor. Methods The study used the summary, unification, and innovation of existing practical knowledge and experience of the Czech National Marrow Donor Registry of various factors beyond HLA matching with impact on transplant outcome. Results An information technology system–implemented procedure (a verification algorithm) is presented as the decision support approach for prematurely discarding less suitable donors from the transplantation process. It is intended primarily for the transplant specialist to help establish optimal procedures for verifying and determining donor critical factors. Conclusions A process defining HLAs, killer cell immunoglobulin–like receptors, and cytokine typing strategies was proposed to provide support to a transplant specialist in refining the choice of a suitable donor.

Research notes supply chains where competitors selling the same types of products at the same level of the supply chain may work together to achieve superior profits, using the term “co-opetition” to describe the phenomenon. Using a co-opetitive supply chain design in the bearing and power transmission industry as a practical guide, we develop a multi-level simulation to compare the effects of serial versus a co-opetitive supply chain design on inventory management, order fulfillment, and cost performance. Specifically, we examine supply chain network membership, product demand volatility, and in-transit shipping consolidation effects in our model. This research aims to (1) quantify the performance benefits to be expected from co-opetition and (2) examine the structural conditions present that may enable these co-opetitive networks to achieve value-added inventory cost and delivery performance. We find that the co-opetitive distribution strategies can significantly improve inventory management performance when supply chains have a larger number of competing products, manufacturer׳s product freight-billing allows for in-transit shipping, and supply networks have a longer reach.

The Northridge earthquake of 1994 displaced almost 10,000 families and destroyed major transportation infrastructure within Southern California, and Hurricane Katrina created the largest national housing crisis since the Dust Bowl of 1930, destroying over 300,000 homes and leaving over one million people seeking shelter. Numerous smaller disasters each year such as tornados, costal or inland flooding, and less severe earthquakes also destroy homes and displace families, although on a much smaller scale. Arranging housing for disaster victims ranks as a top priority after the immediate needs for food and medical care are met. This task becomes more challenging as families are displaced for a longer period of time due to increases in costs, government involvement, and expectations of the victims. In early 2009, FEMA released the first-ever National Disaster Housing Strategy which calls for improved planning and outlines the key principles and policies guiding disaster sheltering, interim housing, and restoration of permanent housing. While all three housing problems are very difficult, the provision of adequate temporary or interim housing is perhaps the most challenging. A few researchers have addressed the issue of optimal allocation of temporary housing, but have focused primarily on the first part of the problem which focuses on the selection of adequate capacity from among available interim housing alternatives. The second part of the problem, which consists of recommending housing alternatives to individual families from the pool of temporary housing units selected in phase one such that educational, healthcare, and socio-economic needs are met, has not yet been addressed to the best of our knowledge. We propose a decision support system for assigning families to housing units which addresses these needs. We develop a benchmark integer programming model for developing a balanced housing plan, and then use the model to evaluate three heuristics which could be practically applied with our system. We use a prototypical example to illustrate the model and evaluate the heuristics, and to demonstrate their appropriateness for the development of realistic real-time housing recommendations. We model the recommendation of housing alternatives to disaster victims.Our goal is to minimize distance to socio-economic support structure.Heuristics are developed to allow for real-time support.The best heuristic uses a weighted preference between distance and housing size.We use this heuristic as the foundation of a decision support system.

Although large amounts of disaster-generated debris significantly strain landfill capacities, until recently existing policy provided no financial incentive to consider other disposal alternatives such as recycling. In 2007, the U.S. Federal Emergency Management Agency (FEMA) released a new pilot program that provides incentives for communities to recycle by allowing them to retain revenue from the sale of disaster debris. This first-ever policy offers significant financial benefits for communities seeking to cleanup in an environmentally responsible way but requires reexamining existing assumptions and decision processes that are based on prior reimbursement programs. This paper presents a decision model with recycling incentives for locating temporary disposal and storage reduction (TDSR) facilities in support of disaster debris cleanup operations. A facility location model is proposed to incorporate the unique assumptions, objectives, and constraints of disaster recovery in light of FEMA’s new policy.