Bem1p contributes to secretory pathway polarization through a direct interaction with Exo70p.

The exocyst serves to tether secretory vesicles to cortical sites specified by polarity determinants, in preparation for fusion with the plasma membrane. Although most exocyst components are brought to these sites by riding on secretory vesicles as they are actively transported along actin cables, Exo70p displays actin-independent localization to these sites, implying an interaction with a polarity determinant. Here we show that Exo70p directly and specifically binds to the polarity determinant scaffold protein Bem1p. The interaction involves multiple domains of both Exo70p and Bem1p. Mutations in Exo70p that disrupt its interaction with Bem1, without impairing its interactions with other known binding partners, lead to the loss of actin-independent localization. Synthetic genetic interactions confirm the importance of the Exo70p-Bem1p interaction, although there is some possible redundancy with Sec3p and Sec15p, other exocyst components that also interact with polarity determinants. Similar to Sec3p, the actin-independent localization of Exo70p requires a synergistic interaction with the phosphoinositide PI(4,5)P2

Speciation of arsenic and selenium in rabbit using x-ray absorption spectroscopy

Chronic arsenic poisoning due to arsenic contamination of groundwater is a serious public health problem in Bangladesh and neighboring countries. Severe health effects associated with chronic exposure to arsenic include melanosis and several kinds of cancer. It is now generally agreed that the arsenic contamination of groundwater in Bangladesh is of geological origin. Arsenic naturally present in aquifers may be mobilized into drinking water by microbial action. The formation of a novel arsenic-selenium compound: seleno-bis (S-glutathionyl) arsinium ion, [(GS)2AsSe]-, and its subsequent excretion in rabbit bile has been demonstrated previously. This molecular basis for the in vivo antagonism between arsenic and selenium was discovered using X-ray absorption spectroscopy. There is growing evidence that, in Bangladeshi people who are suffering long term chronic lowlevel arsenic poisoning, this antagonism is causing a selenium deficiency. Administering selenium supplements might provide a simple but highly effective treatment of the Bangladeshi arsenic poisoning. In order to examine the disposition of [(GS)2AsSe]-, a set of rabbits were intravenously injected with selenite, arsenite or both. Whole blood, red blood cell and plasma samples were collected at different time intervals within 2hrs after injection and cecotrope samples 24hr after injection. Samples were examined using X-ray absorption spectroscopy and both arsenic and selenium K-near edge spectra were recorded. iii Speciation of arsenic and selenium will be discussed in this thesis. Results indicate that [(GS)2AsSe]- is formed in blood very rapidly after injection of both arsenite and selenite, and then is removed from blood stream within 2hrs post injection. Results also show that [(GS)2AsSe]- is assembled in red blood cells, with no [(GS)2AsSe]- detected in plasma samples. [(GS)2AsSe]- is also found in cecotrope samples after injection of both arsenite and selenite. The results of this study in rabbits will contribute to the understanding of chronic arsenic poisoning in humans

Construction of a Model Based Digital Twin Factory

In the digital factory system, physical factories, virtual factories, and digital twin service systems are three essential components. This article elaborates on the roles of the three in factory construction. The article utilizes m odel-based system engineering as the main idea to construct a digital twin service system, providing a basis for subsequent research

Selective Disassembly Research

This article transforms the disassembly graph model into a disassembly matrix model, and plans the path of selective disassembly by solving the matrix model.By conducting selective disassembly research on key components, a disassembly path is planned. When disassembling key parts, the goal is clear and unnecessary disassembly steps are omitted, greatly shortening the disassembly time and improving disassembly effi ciency.This article presents the results of this study through a case study, proving that the results can transform complex component connection diagrams into matrices, and then plan the disassembly path of key components

Screening for Differentially Expressed Genes: Are Multilevel Models Helpful?

Screening for changes in gene expression across biological conditions using microarrays is now a common tool in biology. Efficient use of these data for identifying important biological hypotheses is inherently a statistical problem. In this paper we present a broad Bayesian multilevel framework for developing computationally fast shrinkage-based screening tools for this purpose. Our scheme makes it easy to adapt the choice of statistics to the goals of the analysis and to the genomic distributions of signal and noise. We empirically investigate the extent to which these shrinkage-based statistics improve performance, and the conditions under which such improvements takes place. Our evaluation uses both extensive simulations and controlled biological experiments. The experimental data include a so-called spike-in experiment, in which the target biological signal is known, and a two-sample experiment, which illustrates the typical conditions in which the methods studied are applied. Our results emphasize two important practical concerns that are not receiving sufficient attention in applied work in this area. First, while shrinkage strategies based on multilevel models are able to improve selection performance, they require careful verification of the assumptions on the relationship between signal and noise. Incorrect specification of this relationship can negatively affect a selection procedure. Because this inter-gene relationship is generally identifiable in genomic experiments, we suggest a simple diagnostic plot to assist model checking. Secondly, no statistic performs optimally across two common categories of experimental goals: selecting genes with large changes, and selecting genes with reliably measured changes. Therefore, careful consideration of analysis goals is critical in the choice of the approach taken