University of Maryland, Baltimore County

About: University of Maryland, Baltimore County is a education organization based out in Baltimore, Maryland, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.

Inflammation enhances myeloid-derived suppressor cell cross-talk by signaling through Toll-like receptor 4.

Abstract: Myeloid-derived suppressor cells (MDSC) are potent inhibitors of anti-tumor immunity that facilitate tumor progression by blocking the activation of CD4+ and CD8+ T cells and by promoting a type 2 immune response through their production of IL-10 and down-regulation of macrophage production of IL-12. MDSC accumulate in many cancer patients and are a significant impediment to active cancer immunotherapies. Chronic inflammation has been shown recently to enhance the accumulation of MDSC and to increase their suppression of T cells. These findings led us to hypothesize that inflammation contributes to tumor progression through the induction of MDSC, which create a favorable environment for tumor growth. As chronic inflammation also drives type 2 immune responses, which favor tumor growth, we asked if inflammation mediates this effect through MDSC. We find that IL-1β-induced inflammation increased IL-10 production by MDSC and induces MDSC, which are more effective at down-regulating macrophage production of IL-12 as compared with MDSC isolated from less-inflammatory tumor microenvironments, thereby skewing tumor immunity toward a type 2 response. Inflammation heightens MDSC phenotype by signaling through the TLR4 pathway and involves up-regulation of CD14. Although this pathway is well-recognized in other myeloid cells, it has not been implicated previously in MDSC function. These studies demonstrate that MDSC are an intermediary through which inflammation promotes type 2 immune responses, and they identify the TLR4 pathway in MDSC as a potential target for down-regulating immune suppression and promoting anti-tumor immunity.

A High-Resolution X-Ray Image of the Jet in M87

Abstract: We present the first high-resolution X-ray image of the jet in M87 using the Chandra X-Ray Observatory. There is clear structure in the jet and almost all of the optically bright knots are detected individually. The unresolved core is the brightest X-ray feature but is only 2-3 times brighter than knot A (123 from the core) and the inner knot HST-1 (10 from the core). The X-ray and optical positions of the knots are consistent at the 01 level, but the X-ray emission from the brightest knot (A) is marginally upstream of the optical emission peak. Detailed Gaussian fits to the X-ray jet one-dimensional profile show distinct X-ray emission that is not associated with specific optical features. The X-ray/optical flux ratio decreases systematically from the core, and X-ray emission is not clearly detected beyond 20'' from the core. The X-ray spectra of the core and the two brightest knots, HST-1 and A, are consistent with a simple power law (Sν ∝ ν-α) with α = 1.46 ± 0.05, practically ruling out inverse Compton models as the dominant X-ray emission mechanism. The core flux is significantly larger than expected from an advective accretion flow, and the spectrum is much steeper, indicating that the core emission may be due to synchrotron emission from a small-scale jet. The spectral energy distributions of the knots are well fitted by synchrotron models. The spectral indices in the X-ray band, however, are comparable to that expected in the Kardashev-Pacholczyk synchrotron model but are much flatter than expected in the pitch-angle isotropization model of Jaffe and Perola. The break frequencies derived from both models drop by factors of 10-100 with distance from the core.

Distributed Data Mining in Peer-to-Peer Networks

Abstract: Peer-to-peer (P2P) networks are gaining popularity in many applications such as file sharing, e-commerce, and social networking, many of which deal with rich, distributed data sources that can benefit from data mining. P2P networks are, in fact, well-suited to distributed data mining (DDM), which deals with the problem of data analysis in environments with distributed data, computing nodes, and users. This article offers an overview of DDM applications and algorithms for P2P environments, focusing particularly on local algorithms that perform data analysis by using computing primitives with limited communication overhead. The authors describe both exact and approximate local P2P data mining algorithms that work in a decentralized and communication-efficient manner

A semantics approach for KQML—a general purpose communication language for software agents

Abstract: We investigate the semantics for Knowledge Query Manipulation Language (KQML) and we propose a semantic framework for the language. KQML is a language and a protocol to support communication between software agents. Based on ideas from speech act theory, we propose a semantic description for KQML that associates descriptions of the cognitive states of agents with the use of the language's primitives (performatives). We use this approach to describe the semantics for the basic set of KQML performatives. We also investigate implementation issues related to our semantic approach. We suggest that KQML can offer an all purpose communication language for software agents that requires no limiting pre-commitments on the agents' structure and implementation. KQML can provide the Distributed AI, Cooperative Distributed Problem Solving and Software Agents communities with an all purpose language and environment for intelligent inter-agent communication.