Analysis of finite-buffer state-dependent bulk queues

<p>In this paper, we consider a general state-dependent finite-buffer bulk queue in which the rates and batch sizes of arrivals and services are allowed to depend on the number of customers in queue and service batch sizes. Such queueing systems have rich applications in manufacturing, service operations, computer and telecommunication systems. Interesting examples include batch oven processes in the aircraft and semiconductor industry; serving of passengers by elevators, shuttle buses, and ferries; and congestion control mechanisms to regulate transmission rates in packet-switched communication networks. We develop a unifying method to study the performance of this general class of finite-buffer state-dependent bulk queueing systems. For this purpose, we use semi-regenerative analysis to develop a numerically stable method for calculating the limiting probability distribution of the queue length process. Based on the limiting probabilities, we present various performance measures for evaluating admission control and batch service policies, such as the loss probability for an arriving group of customers and for individual customers within a group. We demonstrate our method by means of numerical examples.</p>

Runtime analysis of evolutionary multi-objective algorithms optimising the degree and diameter of spanning trees

Motivated by the telecommunication network design, we study the problem of finding diverse set of minimum spanning trees of a certain complete graph based on the two features which are maximum degree and diameter. In this study, we examine a simple multi-objective EA, GSEMO, in solving the two problems where we maximise or minimise the two features at the same time.With a rigorous runtime analysis, we provide understanding of how GSEMO optimize the set of minimum spanning trees in these two different feature spaces.Wanru Gao, Mojgan Pourhassan, Vahid Roostapour, and Frank Neuman

Hendra Virus Infection Dynamics in Australian Fruit Bats

Hendra virus is a recently emerged zoonotic agent in Australia. Since first described in 1994, the virus has spilled from its wildlife reservoir (pteropid fruit bats, or ‘flying foxes’) on multiple occasions causing equine and human fatalities. We undertook a three-year longitudinal study to detect virus in the urine of free-living flying foxes (a putative route of excretion) to investigate Hendra virus infection dynamics. Pooled urine samples collected off plastic sheets placed beneath roosting flying foxes were screened for Hendra virus genome by quantitative RT-PCR, using a set of primers and probe derived from the matrix protein gene. A total of 1672 pooled urine samples from 67 sampling events was collected and tested between 1 July 2008 and 30 June 2011, with 25% of sampling events and 2.5% of urine samples yielding detections. The proportion of positive samples was statistically associated with year and location. The findings indicate that Hendra virus excretion occurs periodically rather than continuously, and in geographically disparate flying fox populations in the state of Queensland. The lack of any detection in the Northern Territory suggests prevalence may vary across the range of flying foxes in Australia. Finally, our findings suggest that flying foxes can excrete virus at any time of year, and that the apparent seasonal clustering of Hendra virus incidents in horses and associated humans (70% have occurred June to October) reflects factors other than the presence of virus. Identification of these factors will strengthen risk minimization strategies for horses and ultimately humans

Adaptation of a malaria surveillance system for use in a visceral leishmaniasis elimination programme.

Background: Successful public practice relies on generation and use of high-quality data. A data surveillance system (the Disease Data Management System [DDMS]) in use for malaria was adapted for use in the Indian visceral leishmaniasis elimination programme. Methods: A situational analysis identified the data flows in current use. Taxonomic trees for the vector of visceral leishmaniasis in India, Phlebotomus argentipes, were incorporated into the DDMS to allow entry of quality assurance and insecticide susceptibility data. A new quality assurance module was created to collate the concentration of DDT that was applied to walls during the indoor residual spraying (IRS) vector control programme. Results: The DDMS was implemented in Bihar State and used to collate and manage data from sentinel sites in eight districts. Quality assurance data showed that DDT was under-applied to walls during IRS; this, combined with insecticide susceptibility data showing widespread vector resistance to DDT prompted a national policy change to using compression pumps and alpha-cypermethrin insecticide for IRS. Conclusions: The adapted DDMS centralises programmatic data and enhances evidence-based decision making and active policy change. Moving forward, further modules of the system will be implemented, allowing extended data capture and streamlined transmission of key information to decision makers

Methylation of Wnt7a Is Modulated by DNMT1 and Cigarette Smoke Condensate in Non-Small Cell Lung Cancer

Wnt7a is known to be a tumor suppressor that is lost in NSCLC, but no mechanism of loss has been established. Methylation of promoter regions has been established as a common mechanism of loss of tumor suppressor expression in NSCLC. We previously demonstrated that loss of Wnt7a in non-transformed lung epithelial cell lines led to increased cell growth, altered 3-D culture growth, and increased migration. The Wnt7a promoter has a higher percentage of methylation in NSCLC tumor tissue compared to matched normal lung tissue and methylation of the promoter region leads to decreased activity. We treated H157 and H1299 NSCLC cell lines with 5-Aza-2′-deoxycytidine and detected loss of Wnt7a promoter methylation, increased Wnt7a expression, and increased activity of the Wnt7a lung signaling pathway. When DNMT1 expression was knocked down by shRNA, expression of Wnt7a increased and methylation decreased. Together these data suggest that in NSCLC, Wnt7a is lost by methylation in a subset of tumors and that this methylation is maintained by DNMT1. Restoration of Wnt7a expression through demethylation could be an important therapeutic approach in the treatment of NSCLC

Multi-objective optimization of genome-scale metabolic models: the case of ethanol production

Ethanol is among the largest fermentation product used worldwide, accounting for more than 90% of all biofuel produced in the last decade. However current production methods of ethanol are unable to meet the requirements of increasing global demand, because of low yields on glucose sources. In this work, we present an in silico multi-objective optimization and analyses of eight genome-scale metabolic networks for the overproduction of ethanol within the engineered cell. We introduce MOME (multi-objective metabolic engineering) algorithm, that models both gene knockouts and enzymes up and down regulation using the Redirector framework. In a multi-step approach, MOME tackles the multi-objective optimization of biomass and ethanol production in the engineered strain; and performs genetic design and clustering analyses on the optimization results. We find in silico E. coli Pareto optimal strains with a knockout cost of 14 characterized by an ethanol production up to 19.74mmolgDW−1h−1 (+832.88% with respect to wild-type) and biomass production of 0.02h−1 (−98.06% ). The analyses on E. coli highlighted a single knockout strategy producing 16.49mmolgDW−1h−1 (+679.29% ) ethanol, with biomass equals to 0.23h−1 (−77.45% ). We also discuss results obtained by applying MOME to metabolic models of: (i) S. aureus; (ii) S. enterica; (iii) Y. pestis; (iv) S. cerevisiae; (v) C. reinhardtii; (vi) Y. lipolytica. We finally present a set of simulations in which constrains over essential genes and minimum allowable biomass were included. A bound over the maximum allowable biomass was also added, along with other settings representing rich media compositions. In the same conditions the maximum improvement in ethanol production is +195.24%

The PE-PPE Domain in Mycobacterium Reveals a Serine α/β Hydrolase Fold and Function: An In-Silico Analysis

The PE and PPE proteins first reported in the genome sequence of Mycobacterium tuberculosis strain H37Rv are now identified in all mycobacterial species. The PE-PPE domain (Pfam ID: PF08237) is a 225 amino acid residue conserved region located towards the C-terminus of some PE and PPE proteins and hypothetical proteins. Our in-silico sequence analysis revealed that this domain is present in all Mycobacteria, some Rhodococcus and Nocardia farcinica genomes. This domain comprises a pentapeptide sequence motif GxSxG/S at the N-terminus and conserved amino acid residues Ser, Asp and His that constitute a catalytic triad characteristic of lipase, esterase and cutinase activity. The fold prediction and comparative modeling of the 3-D structure of the PE-PPE domain revealed a “serine α/β hydrolase” structure with a central β-sheet flanked by α-helices on either side. The structure comprises a lid insertion with a closed structure conformation and has a solvent inaccessible active site. The oxyanion hole that stabilizes the negative charge on the tetrahedral intermediate has been identified. Our findings add to the growing list of serine hydrolases in mycobacterium, which are essential for the maintenance of their impermeable cell wall and virulence. These results provide the directions for the design of experiments to establish the function of PE and PPE proteins

Mycobacterium tuberculosis Lipolytic Enzymes as Potential Biomarkers for the Diagnosis of Active Tuberculosis

BACKGROUND: New diagnosis tests are urgently needed to address the global tuberculosis (TB) burden and to improve control programs especially in resource-limited settings. An effective in vitro diagnostic of TB based on serological methods would be regarded as an attractive progress because immunoassays are simple, rapid, inexpensive, and may offer the possibility to detect cases missed by standard sputum smear microscopy. However, currently available serology tests for TB are highly variable in sensitivity and specificity. Lipolytic enzymes have recently emerged as key factors in lipid metabolization during dormancy and/or exit of the non-replicating growth phase, a prerequisite step of TB reactivation. The focus of this study was to analyze and compare the potential of four Mycobacterium tuberculosis lipolytic enzymes (LipY, Rv0183, Rv1984c and Rv3452) as new markers in the serodiagnosis of active TB. METHODS: Recombinant proteins were produced and used in optimized ELISA aimed to detect IgG and IgM serum antibodies against the four lipolytic enzymes. The capacity of the assays to identify infection was evaluated in patients with either active TB or latent TB and compared with two distinct control groups consisting of BCG-vaccinated blood donors and hospitalized non-TB individuals. RESULTS: A robust humoral response was detected in patients with active TB whereas antibodies against lipolytic enzymes were infrequently detected in either uninfected groups or in subjects with latent infection. High specifity levels, ranging from 93.9% to 97.5%, were obtained for all four antigens with sensitivity values ranging from 73.4% to 90.5%, with Rv3452 displaying the highest performances. Patients with active TB usually exhibited strong IgG responses but poor IgM responses. CONCLUSION: These results clearly indicate that the lipolytic enzymes tested are strongly immunogenic allowing to distinguish active from latent TB infections. They appear as potent biomarkers providing high sensitivity and specificity levels for the immunodiagnosis of active TB