The receptors and cells for mammalian taste

The emerging picture of taste coding at the periphery is one of elegant simplicity. Contrary to what was generally believed, it is now clear that distinct cell types expressing unique receptors are tuned to detect each of the five basic tastes: sweet, sour, bitter, salty and umami. Importantly, receptor cells for each taste quality function as dedicated sensors wired to elicit stereotypic responses.     

A bottom-up approach to gene regulation

The ability to construct synthetic gene networks enables experimental investigations of deliberately simplified systems that can be compared to qualitative and quantitative models. If simple, well-characterized modules can be coupled together into more complex networks with behaviour that can be predicted from that of the individual components, we may begin to build an understanding of cellular regulatory processes from the 'bottom up'. Here we have engineered a promoter to allow simultaneous repression and activation of gene expression in Escherichia coli. We studied its behaviour in synthetic gene networks under increasingly complex conditions: unregulated, repressed, activated, and simultaneously repressed and activated. We develop a stochastic model that quantitatively captures the means and distributions of the expression from the engineered promoter of this modular system, and show that the model can be extended and used to accurately predict the in vivo behaviour of the network when it is expanded to include positive feedback. The model also reveals the counterintuitive prediction that noise in protein expression levels can increase upon arrest of cell growth and division, which we confirm experimentally. This work shows that the properties of regulatory subsystems can be used to predict the behaviour of larger, more complex regulatory networks, and that this bottom-up approach can provide insights into gene regulation.     

多元Jensen不等式及其应用

简明扼要地给出了多元凸函数的最一般概念,简化了Jensen加权不等式及Jensen积分不等式的证明,定理的证明方法采取了由特殊到一般的归纳证法,导出了某些特殊不等式作为其应用.     

Clustering patents using non-exhaustive overlaps

Patent documents are unique external sources of information that reveal the core technology underlying new inventions.Patents also serve as a strategic data source that can be mined to discover state-of-the-art technical development and subsequently help guide R&D investments.This research incorporates an ontology schema to extract and represent patent concepts.A clustering algorithm with non-exhaustive overlaps is proposed to overcome deficiencies with exhaustive clustering methods used in patent mining and technology discovery.The non-exhaustive clustering approach allows for the clustering of patent documents with overlapping technical findings and claims,a feature that enables the grouping of patents that define related key innovations.Legal advisors can use this approach to study potential cases of patent infringement or devise strategies to avoid litigation.The case study demonstrates the use of non-exhaustive overlaps algorithm by clustering US and Japan radio frequency identification (RFID) patents and by analyzing the legal implications of automated discovery of patent infringement.     

Conjugated action of two species-specific invasion proteins for fetoplacental listeriosis

The ability to cross host barriers is an essential virulence determinant of invasive microbial pathogens. Listeria monocytogenes is a model microorganism that crosses human intestinal and placental barriers, and causes severe maternofetal infections by an unknown mechanism. Several studies have helped to characterize the bacterial invasion proteins InlA and InlB. However, their respective species specificity has complicated investigations on their in vivo role. Here we describe two novel and complementary animal models for human listeriosis: the gerbil, a natural host for L. monocytogenes, and a knock-in mouse line ubiquitously expressing humanized E-cadherin. Using these two models, we uncover the essential and interdependent roles of InlA and InlB in fetoplacental listeriosis, and thereby decipher the molecular mechanism underlying the ability of a microbe to target and cross the placental barrier.     

Preserving cell shape under environmental stress

Maintaining cell shape and tone is crucial for the function and survival of cells and tissues. Mechanotransduction relies on the transformation of minuscule mechanical forces into high-fidelity electrical responses. When mechanoreceptors are stimulated, mechanically sensitive cation channels open and produce an inward transduction current that depolarizes the cell. For this process to operate effectively, the transduction machinery has to retain integrity and remain unfailingly independent of environmental changes. This is particularly challenging for poikilothermic organisms, where changes in temperature in the environment may impact the function of mechanoreceptor neurons. Thus, we wondered how insects whose habitat might quickly vary over several tens of degrees of temperature manage to maintain highly effective mechanical senses. We screened for Drosophila mutants with defective mechanical responses at elevated ambient temperatures, and identified a gene, spam, whose role is to protect the mechanosensory organ from massive cellular deformation caused by heat-induced osmotic imbalance. Here we show that Spam protein forms an extracellular shield that guards mechanosensory neurons from environmental insult. Remarkably, heterologously expressed Spam protein also endowed other cells with superb defence against physically and chemically induced deformation. We studied the mechanical impact of Spam coating and show that spam-coated cells are up to ten times stiffer than uncoated controls. Together, these results help explain how poikilothermic organisms preserve the architecture of critical cells during environmental stress, and illustrate an elegant and simple solution to such challenge.     

Automatic patent document summarization for collaborative knowledge systems and services

Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R&D knowledge, reduces new product development time, increases market success, and reduces potential patent infringement. Thus, it is beneficial to automatically and systematically extract information from patent documents in order to improve knowledge sharing and collaboration among R&D team members. In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach. The ontology captures the general knowledge and core meaning of patents in a given domain. Then, the proposed methodology extracts, clusters, and integrates the content of a patent to derive a summary and a cluster tree diagram of key terms. Patents from the International Patent Classification (IPC) codes B25C, B25D, B25F (categories for power hand tools) and B24B, C09G and H011 (categories for chemical mechanical polishing) are used as case studies to evaluate the compression ratio, retention ratio, and classification accuracy of the summarization results. The evaluation uses statistics to represent the summary generation and its compression ratio, the ontology based keyword extraction retention ratio, and the summary classification accuracy. The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a 14% improvement for classification accuracy.