Mitre Corporation

About: Mitre Corporation is a company organization based out in Bedford, Massachusetts, United States. It is known for research contribution in the topics: Air traffic control & National Airspace System. The organization has 4884 authors who have published 6053 publications receiving 124808 citations. The organization is also known as: Mitre & MITRE.

Transforming growth factor-β receptors type I, II and III in phenobarbital-promoted rat liver tumors

Abstract: Rat liver tumors initiated with N-nitrosodiethylamine (DEN) followed by promotion with phenobarbital (PB) were examined for expression of transforming growth factor-beta (TGF beta) type I, II and III receptors. RNase protection and TGF beta 1 affinity labeling assays were used to determine TGF beta receptor steady-state mRNA and protein levels, respectively. We have demonstrated that all three TGF beta receptors are expressed in both normal and malignant hepatic tissues. Long-term PB administration did not alter TGF beta receptor mRNA or protein levels in normal liver. However, type I, II and III TGF beta receptor mRNA and protein levels were decreased by approximately 50% in the DEN-initiated/PB-promoted liver tumors as compared to the receptor levels in normal liver tissue surrounding the tumors. In contrast, TGF beta receptor mRNA and protein levels were unchanged in liver tumors initiated with DEN but not PB-promoted. These data demonstrate that PB promotes the formation of a tumor phenotype that is characterized by a significantly reduced number of TGF beta type I, II and III receptors. This suggests that the down-regulation of TGF beta receptors in PB-promoted hepatic tumors may provide a selective growth advantage to the tumor cells by reducing the ability of TGF beta to inhibit their growth.

Bacterial communities in commercial aircraft high-efficiency particulate air (HEPA) filters assessed by PhyloChip analysis.

Abstract: Air travel can rapidly transport infectious diseases globally. To facilitate the design of biosensors for infectious organisms in commercial aircraft, we characterized bacterial diversity in aircraft air. Samples from 61 aircraft high-efficiency particulate air (HEPA) filters were analyzed with a custom microarray of 16S rRNA gene sequences (PhyloChip), representing bacterial lineages. A total of 606 subfamilies from 41 phyla were detected. The most abundant bacterial subfamilies included bacteria associated with humans, especially skin, gastrointestinal and respiratory tracts, and with water and soil habitats. Operational taxonomic units that contain important human pathogens as well as their close, more benign relatives were detected. When compared to 43 samples of urban outdoor air, aircraft samples differed in composition, with higher relative abundance of Firmicutes and Gammaproteobacteria lineages in aircraft samples, and higher relative abundance of Actinobacteria and Betaproteobacteria lineages in outdoor air samples. In addition, aircraft and outdoor air samples differed in the incidence of taxa containing human pathogens. Overall, these results demonstrate that HEPA filter samples can be used to deeply characterize bacterial diversity in aircraft air and suggest that the presence of close relatives of certain pathogens must be taken into account in probe design for aircraft biosensors. Practical Implications A biosensor that could be deployed in commercial aircraft would be required to function at an extremely low false alarm rate, making an understanding of microbial background important. This study reveals a diverse bacterial background present on aircraft, including bacteria closely related to pathogens of public health concern. Furthermore, this aircraft background is different from outdoor air, suggesting different probes may be needed to detect airborne contaminants to achieve minimal false alarm rates. This study also indicates that aircraft HEPA filters could be used with other molecular techniques to further characterize background bacteria and in investigations in the wake of a disease outbreak.

Approximation algorithms for data distribution with load balancing of web servers

Abstract: Given the increasing traffic on the World Wide Web (Web), it is difficult for a single popular Web server to handle the demand from its many clients. By clustering a group of Web servers, it is possible to reduce the origin Web server's load significantly and reduce user's response time when accessing a Web document. A fundamental question is how to allocate Web documents among these servers in order to achieve load balancing? In this paper, we are given a collection of documents to be stored on a cluster of Web servers. Each of the servers is associated with resource limits in its memory and its number of HTTP connections. Each document has an associated size and access cost. The problem is to allocate the documents among the servers so that no server's memory size is exceeded, and the load is balanced as equally as possible. In this paper, we show that most simple formulations of this problem are NP-hard, we establish lower bounds on the value of the optimal load, and we show that if there are no memory constraints for all the servers, then there is an allocation algorithm, that is within a factor 2 of the optimal solution. We show that if all servers have the same number of HTTP connections and the same memory size, then a feasible allocation is achieved within a factor 4 of the optimal solution using at most 4 times the optimal memory size. We also provide improved approximation results for the case where documents are relatively small.