Erythema nodosum as a result of estrogen patch therapy for prostate cancer: a case report.

© 2015 Coyle et al.Introduction: Erythema nodosum is often associated with a distressing symptomatology, including painful subcutaneous nodules, polyarthropathy, and significant fatigue. Whilst it is a well-documented side-effect of estrogen therapy in females, we describe what we believe to be the first report in the literature of erythema nodosum as a result of estrogen therapy in a male. Case presentation: A 64-year-old Afro-Caribbean man with locally advanced carcinoma of the prostate agreed to participate in a randomized controlled trial comparing estrogen patches with luteinizing hormone-releasing hormone analogs to achieve androgen deprivation, and was allocated to the group receiving estrogen patches. One month later he presented with tender lesions on his shins and painful swelling of his ankles, wrists, and left shoulder. This was followed by progressive severe fatigue that required hospital admission, where he was diagnosed with erythema nodosum by a rheumatologist. Two months after discontinuing the estrogen patches the erythema nodosum, and associated symptoms, had fully resolved, and to date he remains well with no further recurrence. Conclusion: Trial results may establish transdermal estrogen as an alternative to luteinizing hormone-releasing hormone analogs in the management of prostate cancer, and has already been established as a therapy for male to female transsexuals. It is essential to record the toxicity profile of transdermal estrogen in men to ensure accurate safety information. This case report highlights a previously undocumented toxicity of estrogen therapy in men, of which oncologists, urologists, and endocrinologists need to be aware. Rheumatologists and dermatologists should add estrogen therapy to their differential diagnosis of men presenting with erythema nodosum

A management architecture for active networks

In this paper we present an architecture for network and applications management, which is based on the Active Networks paradigm and shows the advantages of network programmability. The stimulus to develop this architecture arises from an actual need to manage a cluster of active nodes, where it is often required to redeploy network assets and modify nodes connectivity. In our architecture, a remote front-end of the managing entity allows the operator to design new network topologies, to check the status of the nodes and to configure them. Moreover, the proposed framework allows to explore an active network, to monitor the active applications, to query each node and to install programmable traps. In order to take advantage of the Active Networks technology, we introduce active SNMP-like MIBs and agents, which are dynamic and programmable. The programmable management agents make tracing distributed applications a feasible task. We propose a general framework that can inter-operate with any active execution environment. In this framework, both the manager and the monitor front-ends communicate with an active node (the Active Network Access Point) through the XML language. A gateway service performs the translation of the queries from XML to an active packet language and injects the code in the network. We demonstrate the implementation of an active network gateway for PLAN (Packet Language for Active Networks) in a forty active nodes testbed. Finally, we discuss an application of the active management architecture to detect the causes of network failures by tracing network events in time

A novel synthetic chemistry approach to linkage-specific ubiquitin conjugation.

Ubiquitination is of great importance as the post-translational modification of proteins with ubiquitin, or ubiquitin chains, facilitates a number of vital cellular processes. Herein we present a facile method of preparing various ubiquitin conjugates under mild conditions using michael acceptors based on dibromo-maleimides and dibromo-pyridazinediones

Distributed XQuery

XQuery is increasingly being used for ad-hoc integration of heterogeneous data sources that are logically mapped to XML. For example, scientists need to query multiple scientific databases, which are distributed over a large geographic area, and it is possible to use XQuery for that. However, the language currently supports only the data shipping query evaluation model (through the document() function): it fetches all data sources to a single server, then runs the query there. This is a major limitation for many applications, especially when some data sources are very large, or when a data source is only a virtual XML view over some other logical data model. We propose here a simple extension to XQuery that allows query shipping to be expressed in the language, in addition to data shipping

Binary Decision Diagrams: from Tree Compaction to Sampling

Any Boolean function corresponds with a complete full binary decision tree. This tree can in turn be represented in a maximally compact form as a direct acyclic graph where common subtrees are factored and shared, keeping only one copy of each unique subtree. This yields the celebrated and widely used structure called reduced ordered binary decision diagram (ROBDD). We propose to revisit the classical compaction process to give a new way of enumerating ROBDDs of a given size without considering fully expanded trees and the compaction step. Our method also provides an unranking procedure for the set of ROBDDs. As a by-product we get a random uniform and exhaustive sampler for ROBDDs for a given number of variables and size

The impact of teaching assistants on pupils

The International Guide to Student Achievement brings together and critically examines the major influences shaping student achievement today

Highlights of the SLD Physics Program at the SLAC Linear Collider

Starting in 1989, and continuing through the 1990s, high-energy physics witnessed a flowering of precision measurements in general and tests of the standard model in particular, led by e+e- collider experiments operating at the Z0 resonance. Key contributions to this work came from the SLD collaboration at the SLAC Linear Collider. By exploiting the unique capabilities of this pioneering accelerator and the SLD detector, including a polarized electron beam, exceptionally small beam dimensions, and a CCD pixel vertex detector, SLD produced a broad array of electroweak, heavy-flavor, and QCD measurements. Many of these results are one of a kind or represent the world's standard in precision. This article reviews the highlights of the SLD physics program, with an eye toward associated advances in experimental technique, and the contribution of these measurements to our dramatically improved present understanding of the standard model and its possible extensions.Comment: To appear in 2001 Annual Review of Nuclear and Particle Science; 78 pages, 31 figures; A version with higher resolution figures can be seen at http://www.slac.stanford.edu/pubs/slacpubs/8000/slac-pub-8985.html; Second version incorporates minor changes to the tex

The radial metallicity gradients in the Milky Way thick disk as fossil signatures of a primordial chemical distribution

In this letter we examine the evolution of the radial metallicity gradient induced by secular processes, in the disk of an $N$-body Milky Way-like galaxy. We assign a [Fe/H] value to each particle of the simulation according to an initial, cosmologically motivated, radial chemical distribution and let the disk dynamically evolve for 6 Gyr. This direct approach allows us to take into account only the effects of dynamical evolution and to gauge how and to what extent they affect the initial chemical conditions. The initial [Fe/H] distribution increases with R in the inner disk up to R ~ 10 kpc and decreases for larger R. We find that the initial chemical profile does not undergo major transformations after 6 Gyr of dynamical evolution. The final radial chemical gradients predicted by the model in the solar neighborhood are positive and of the same order of those recently observed in the Milky Way thick disk. We conclude that: 1) the spatial chemical imprint at the time of disk formation is not washed out by secular dynamical processes, and 2) the observed radial gradient may be the dynamical relic of a thick disk originated from a stellar population showing a positive chemical radial gradient in the inner regions.Comment: 10 pages, 5 figures, Accepted for publication on Astrophysical Journal Letter

Detecting modules in biological networks by edge weights clustering and entropy significance

Detection of the modular structure of biological networks is of interest to researchers adopting a systems perspective for the analysis of omics data. Computational systems biology has provided a rich array of methods for network clustering. To date, the majority of approaches address this task through a network node classification based on topological or external quantifiable properties of network nodes. Conversely, numerical properties of network edges are underused, even though the information content which can be associated with network edges has augmented due to steady advances in molecular biology technology over the last decade. Properly accounting for network edges in the development of clustering approaches can become crucial to improve quantitative interpretation of omics data, finally resulting in more biologically plausible models. In this study, we present a novel technique for network module detection, named WG-Cluster (Weighted Graph CLUSTERing). WG-Cluster's notable features, compared to current approaches, lie in: (1) the simultaneous exploitation of network node and edge weights to improve the biological interpretability of the connected components detected, (2) the assessment of their statistical significance, and (3) the identification of emerging topological properties in the detected connected components. WG-Cluster utilizes three major steps: (i) an unsupervised version of k-means edge-based algorithm detects sub-graphs with similar edge weights, (ii) a fast-greedy algorithm detects connected components which are then scored and selected according to the statistical significance of their scores, and (iii) an analysis of the convolution between sub-graph mean edge weight and connected component score provides a summarizing view of the connected components. WG-Cluster can be applied to directed and undirected networks of different types of interacting entities and scales up to large omics data sets. Here, we show that WG-Cluster can be successfully used in the differential analysis of physical protein-protein interaction (PPI) networks. Specifically, applying WG-Cluster to a PPI network weighted by measurements of differential gene expression permits to explore the changes in network topology under two distinct (normal vs. tumor) conditions. WG-Cluster code is available at https://sites.google.com/site/paolaleccapersonalpage/