Ubiquitin-dependent proteolysis of trihydrophobin 1 (TH1) by the human papilloma virus E6-associated protein (E6-AP).

Human Papilloma virus E6-associated protein (E6-AP), which is known as an E3 ubiquitin ligase, mediates ubiquitination and subsequent degradation of a series of cellular proteins. In this paper, we identify here trihydrophobin 1 (TH1), an integral subunit of the human negative transcription elongation factor (NELF) complex, as a novel E6-AP interaction protein and a target of E6-AP-mediated degradation. Overexpression of E6-AP results in degradation of TH1 in a dose-dependent manner, whereas knock-down of endogenous E6-AP elevates the TH1 protein level. TH1 protein turnover is substantially faster, compared to controls, in cells that overexpressed E6-AP. Wild-type E6-AP promotes the ubiquitination of TH1, while a catalytically inactive point mutant of E6-AP abolishes its ubiquitination. Furthermore, in vitro ubiquitination assay also demonstrates that TH1 can be ubiquitinated by E6-AP. The degradation is blocked by treatment with proteasome inhibitor MG132. Herein, we provide strong evidence that TH1 is a specific substrate that is targeted for degradation through E6-AP-catalyzed polyubiquitination.

Gene selection by cooperative competition clustering

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.

Robust fuzzy Gustafson-Kessel clustering for nonlinear system identification

This paper deals with Takagi-Sugeno (TS) fuzzy model identification of nonlinear systems using fuzzy clustering. In particular, an extended fuzzy Gustafson-Kessel (EGK) clustering algorithm, using robust competitive agglomeration (RCA), is developed for automatically constructing a TS fuzzy model from system input-output data. The EGK algorithm can automatically determine the 'optimal' number of clusters from the training data set. It is shown that the EGK approach is relatively insensitive to initialization and is less susceptible to local minima, a benefit derived from its agglomerate property. This issue is often overlooked in the current literature on nonlinear identification using conventional fuzzy clustering. Furthermore, the robust statistical concepts underlying the EGK algorithm help to alleviate the difficulty of cluster identification in the construction of a TS fuzzy model from noisy training data. A new hybrid identification strategy is then formulated, which combines the EGK algorithm with a locally weighted, least-squares method for the estimation of local sub-model parameters. The efficacy of this new approach is demonstrated through function approximation examples and also by application to the identification of an automatic voltage regulation (AVR) loop for a simulated 3 kVA laboratory micro-machine system.

Support vector machine classification for large data sets via minimum enclosing ball clustering

Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is highly dependent on the size of data set. This paper presents a novel SVM classification approach for large data sets by using minimum enclosing ball clustering. After the training data are partitioned by the proposed clustering method, the centers of the clusters are used for the first time SVM classification. Then we use the clusters whose centers are support vectors or those clusters which have different classes to perform the second time SVM classification. In this stage most data are removed. Several experimental results show that the approach proposed in this paper has good classification accuracy compared with classic SVM while the training is significantly faster than several other SVM classifiers.

Development of an ELISA screening test for nitroimidazoles in egg and chicken muscle

An antibody was generated that can bind metronidazole (MNZ), a nitroimidazole drug used in veterinary medicine to treat poultry for coccidiosis and histomoniasis. A direct competitive enzyme-linked immunosorbent assay (cELISA) is described. It was used to characterise binding of this antibody to a number of nitroimidazole drugs. It displayed cross-reactivity with dimetridazole (DMZ), ronidazole (RNZ), hydroxydimetridazole (DMZOH), and ipronidazole (IPZ).

Size-assortative pairing in Gammarus pulex (Crustacea : Amphipoda): a test of the timing hypothesis

We present the first empirical test of the timing hypothesis regarding the generation of size-assortative pairing in amphipods. The timing hypothesis proposes that, since large males are better able to afford the costs of mate guarding than small males, the former can take larger females into precopula earlier in the female moult cycle than is feasible for the latter. This leaves small males to form pairs with smaller females closer to moult, thus generating size assortment. We presented male Gammarus pulex, collected both in precopula and as singletons, with females that were (1) previously guarded and therefore near to copulatory moult and (2) previously unguarded and therefore far from copulatory moult. This comparison tested the prediction of the timing hypothesis, that size assortment should break down when the opportunity for time-based male decisions is removed, but that size assortment should occur where timing is not disrupted. Counter to the hypothesis, we found that size assortment did not break down upon removal of the time factor. Large males tended to initiate mate guarding earlier than small males in both female moult groups. However, only in the previously unguarded group did large males guard for longer than small males. This result suggests that, although size assortment occurred in all groups, the causative mechanisms that generated this pattern may differ between these groups. We therefore consider the possible importance of mechanisms such as aggression, simultaneous manipulation of females and female resistance in producing size assortment where males encounter numerous females that are close to moult. We also observed that prior recent guarding experience by males had no effect on latency to guard or size-assortative pairing. (C) 2002 The Association for the Study of Animal Behaviour. Published by Elsevier Science Ltd. All rights reserved.

Rarity and decline in bumblebees - A test of causes and correlates in the Irish fauna

Bees are believed to be in decline across many of the world's ecosystems. Recent studies on British bumblebees proposed alternative theories to explain declines. One study suggested that greater dietary specialization among the rarer bumblebee species makes them more susceptible to decline. A second study disputed this theory and found that declines in British bumblebees were correlated with the size of species' European ranges, leading to the suggestion that climate and habitat specialization may be better indicators of the risk of decline. Here we use a new and independent dataset based on Irish bumblebees to test the generality of these theories. We found that most of the same bumblebee species are declining across the British Isles, but that, within Ireland, a simple food-plant specialization model is inadequate to explain these declines. Furthermore, we found no evidence of a relationship between declines in Irish bumblebees and the size of species' European ranges. However, we demonstrate that the late emerging species have declined in Ireland (and in Britain), and that these species show a statistically significant westward shift to the extremity of their range, probably as a result of changing land use. Irish data support the finding that rare and declining bumblebees are later nesting species, associated with open grassy habitats. We suggest that the widespread replacement of hay with silage in the agricultural landscape, which results in earlier and more frequent mowing and a reduction in late summer wildflowers, has played a major role in bumblebee declines. (C) 2006 Elsevier Ltd. All rights reserved.