Telomerase activity, estrogen receptors (α, β), Bcl-2 expression in human breast cancer and treatment response

BACKGROUND: The mechanism for maintaining telomere integrity is controlled by telomerase, a ribonucleoprotein enzyme that specifically restores telomere sequences, lost during replication by means of an intrinsic RNA component as a template for polymerization. Among the telomerase subunits, hTERT (human telomerase reverse transcriptase) is expressed concomitantly with the activation of telomerase. The role of estrogens and their receptors in the transcriptional regulation of hTERT has been demonstrated. The current study determines the possible association between telomerase activity, the expression of both molecular forms of estrogen receptor (ERα and ERβ) and the protein bcl-2, and their relative associations with clinical parameters. METHODS: Tissue samples from 44 patients with breast cancer were used to assess telomerase activity using the TRAP method and the expression of ERα, ERβ and bcl-2 by means of immunocytochemical techniques. RESULTS: Telomerase activity was detected in 59% of the 44 breast tumors examined. Telomerase activity ranged from 0 to 49.93 units of total product generated (TPG). A correlation was found between telomerase activity and differentiation grade (p = 0.03). The only significant independent marker of response to treatment was clinical stage. We found differences between the frequency of expression of ERα (88%) and ERβ (36%) (p = 0.007); bcl-2 was expressed in 79.5% of invasive breast carcinomas. We also found a significant correlation between low levels of telomerase activity and a lack of ERβ expression (p = 0.03). CONCLUSION: Lower telomerase activity was found among tumors that did not express estrogen receptor beta. This is the first published study demonstrating that the absence of expression of ERβ is associated with low levels of telomerase activity

A Toxin–Antitoxin System Promotes the Maintenance of an Integrative Conjugative Element

SXT is an integrative and conjugative element (ICE) that confers resistance to multiple antibiotics upon many clinical isolates of Vibrio cholerae. In most cells, this ∼100 Kb element is integrated into the host genome in a site-specific fashion; however, SXT can excise to form an extrachromosomal circle that is thought to be the substrate for conjugative transfer. Daughter cells lacking SXT can theoretically arise if cell division occurs prior to the element's reintegration. Even though ∼2% of SXT-bearing cells contain the excised form of the ICE, cells that have lost the element have not been detected. Here, using a positive selection-based system, SXT loss was detected rarely at a frequency of ∼1×10−7. As expected, excision appears necessary for loss, and factors influencing the frequency of excision altered the frequency of SXT loss. We screened the entire 100 kb SXT genome and identified two genes within SXT, now designated mosA and mosT (for maintenance of SXT Antitoxin and Toxin), that promote SXT stability. These two genes, which lack similarity to any previously characterized genes, encode a novel toxin-antitoxin pair; expression of mosT greatly impaired cell growth and mosA expression ameliorated MosT toxicity. Factors that promote SXT excision upregulate mosAT expression. Thus, when the element is extrachromosomal and vulnerable to loss, SXT activates a TA module to minimize the formation of SXT-free cells

The Gac-Rsm and SadB Signal Transduction Pathways Converge on AlgU to Downregulate Motility in Pseudomonas fluorescens

Flagella mediated motility in Pseudomonas fluorescens F113 is tightly regulated. We have previously shown that motility is repressed by the GacA/GacS system and by SadB through downregulation of the fleQ gene, encoding the master regulator of the synthesis of flagellar components, including the flagellin FliC. Here we show that both regulatory pathways converge in the regulation of transcription and possibly translation of the algU gene, which encodes a sigma factor. AlgU is required for multiple functions, including the expression of the amrZ gene which encodes a transcriptional repressor of fleQ. Gac regulation of algU occurs during exponential growth and is exerted through the RNA binding proteins RsmA and RsmE but not RsmI. RNA immunoprecipitation assays have shown that the RsmA protein binds to a polycistronic mRNA encoding algU, mucA, mucB and mucD, resulting in lower levels of algU. We propose a model for repression of the synthesis of the flagellar apparatus linking extracellular and intracellular signalling with the levels of AlgU and a new physiological role for the Gac system in the downregulation of flagella biosynthesis during exponential growth

Data acquisition in sensor networks with large memories

Wireless Sensor Networks will soon become ubiquitous, making them essential tools for monitoring the activity and evolution of our surrounding environment. However such environments are expected to generate vast amounts of temporal data that needs to be processed in a power-effective manner. To this date sensor nodes feature small amounts of memory which mostly limits their capabilities to queries that only refer to the current point in time. In this paper we initiate a study on the deployment of large memories at sensor nodes. Such an approach gives birth to an array of new temporal and top-k queries which have been extensively studied by the database community. Our discussion is in the context of the RISE (RIverside SEnsor) hardware platform, in which sensor nodes feature external flash card memories that provide them several Megabytes of storage. 1

Supporting historic queries in sensor networks with flash storage

Many recent sensor devices are being equipped with flash memories due to their unique advantages: non-volatile storage, small size, shock-resistance, fast read access and power efficiency. The ability of storing large amounts of data in sensor devices necessitates the need for efficient indexing structures to locate required information. The challenge with flash memories is that they are unsuitable for maintaining dynamic data structures because of their specific read, write and wear constraints; this combined with very limited data memory on sensor devices prohibits the direct application of most existing indexing methods. In this paper we propose a suite of index structures and algorithms which permit us to efficiently support several types of historical online queries on flash-equipped sensor devices: temporally constrained aggregate queries, historical online sampling queries and pattern matching queries. We have implemented our methods using nesC and have run extensive experiments in TOSSIM, the simulation environment of TinyOS. Our experimental evaluation using trace-driven real world data sets demonstrates the efficiency of our indexing algorithms. © 2012 Elsevier Ltd. All rights reserved

Low-Rank Methods in Event Detection with Subsampled Point-to-Subspace Proximity Tests

Monitoring of streamed data to detect abnormal behaviour (variously known as event detection, anomaly detection, change detection, or outlier detection) underlies many applications, especially within the Internet of Things. There, one often collects data from a variety of sources, with asynchronous sampling, and missing data. In this setting, one can detect abnormal behavior using low-rank techniques. In particular, we assume that normal observations come from a low-rank subspace, prior to being corrupted by a uniformly distributed noise. Correspondingly, we aim to recover a representation of the subspace, and perform event detection by running point-to-subspace distance query for incoming data. We use a variant of low-rank factorisation, which considers interval uncertainty sets around “known entries”, on a suitable flattening of the input data to obtain a low-rank model. On-line, we compute the distance of incoming data to the low-rank normal subspace and update the subspace to keep it consistent with the seasonal changes present. For the distance computation, we consider subsampling. We bound the one-sided error as a function of the number of coordinates employed. In our experimental evaluation, we test the proposed algorithm on induction-loop data from Dublin, Ireland. Autho