Bacillus anthracis: Molecular taxonomy, population genetics, phylogeny and patho-evolution

Bacillus anthracis, the etiological agent of anthrax, manifests a particular bimodal lifestyle. This bacterial species alternates between short replication phases of 20-40 generations that strictly require infection of the host, normally causing death, interrupted by relatively long, mostly dormant phases as spores in the environment. Hence, the B. anthracis genome is highly homogeneous. This feature and the fact that strains from nearly all parts of the world have been analysed for canonical single nucleotide polymorphisms (canSNPs) and variable number tandem repeats (VNTRs) has allowed the development of molecular epidemiological and molecular clock models to estimate the age of major diversifications in the evolution of B. anthracis and to trace the global spread of this pathogen, which was mostly promoted by movement of domestic cattle with settlers and by international trade of contaminated animal products. From a taxonomic and phylogenetic point of view, B. anthracis is a member of the Bacillus cereus group. The differentiation of B. anthracis from B. cereus sensu strict, solely based on chromosomal markers, is difficult. However, differences in pathogenicity clearly differentiate B. anthracis from B. cereus and are marked by the strict presence of virulence genes located on the two virulence plasmids pXO1 and pXO2, which both are required by the bacterium to cause anthrax. Conversely, anthrax-like symptoms can also be caused by organisms with chromosomal features that are more closely related to B. cereus, but which carry these virulence genes on two plasmids that largely resemble the B. anthracis virulence plasmids. (C) 2011 Elsevier B.V. All rights reserved.

Lichtheimia Infection in a Lymphoma Patient: Case Report and a Brief Review of the Available Diagnostic Tools

We describe the case of a patient with a T-lymphoblastic lymphoma whose disseminated mucormycosis was diagnosed with delay, and we address the diagnostic and therapeutic decision-making process and review the diagnostic workup of patients with potential IFD. The diagnosis was delayed despite a suggestive radiological presentation of the patient's pulmonary lesion. The uncommon risk profile (T-lymphoblastic lymphoma, short neutropenic phases) wrongly led to a low level of suspicion. The diagnosis was also hampered by the lack of indirect markers for infections caused by Mucorales, the low sensitivity of both fungal culture and panfungal PCR, and the limited availability of species-specific PCR. A high level of suspicion of IFD is needed, and aggressive diagnostic procedures should be promptly initiated even in apparently low-risk patients with uncommon presentations. The extent of the analytical workup should be decided on a case-by-case base. Diagnostic tests such as the galactomannan and β-D-glucan test and/or PCR on biological material followed by sequencing should be chosen according to their availability and after evaluation of their specificity and sensitivity. In high-risk patients, preemptive therapy with a broad-spectrum mould-active antifungal agent should be started before definitive diagnostic findings become available.

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.