Genome reorganization of the GmSHMT gene family in soybean showed a lack of functional redundancy in resistance to soybean cyst nematode

In soybeans, eighteen members constitute the serine hydroxymethyltransferase (GmSHMT) gene family, of which the cytosolic-targeted GmSHMT08c member has been reported to mediate resistance to soybean cyst nematode (SCN). This work presents a comprehensive study of the SHMT gene family members, including synteny, phylogeny, subcellular localizations, haplotypes, protein homology modeling, mutational, and expression analyses. Phylogenetic analysis showed that SHMT genes are divided into four classes refecting their subcellular distribution (cytosol, nucleus, mitochondrion, and chloroplast). Subcellular localization of selected GmSHMT members supports their in-silico predictions and phylogenetic distribution. Expression and functional analyses showed that GmSHMT genes display many overlapping, but some divergent responses during SCN infection. Furthermore, mutational analysis reveals that all isolated EMS mutants that lose their resistance to SCN carry missense and nonsense mutations at the GmSHMT08c, but none of the Gmshmt08c mutants carried mutations in the other GmSHMT genes. Haplotype clustering analysis using the whole genome resequencing data from a collection of 106 diverse soybean germplams (15X) was performed to identify allelic variants and haplotypes within the GmSHMT gene family. Interestingly, only the cytosolic-localized GmSHMT08c presented SNP clusters that were associated with SCN resistance, supporting our mutational analysis. Although eight GmSHMT members respond to the nematode infestation, functional and mutational analysis has shown the absence of functional redundancy in resistance to SCN. Structural analysis and protein homology modeling showed the presence of spontaneous mutations at important residues within the GmSHMT proteins, suggesting the presence of altered enzyme activities based on substrate afnities. Due to the accumulation of mutations during the evolution of the soybean genome, the other GmSHMT members have undergone neofunctionalization and subfunctionalization events

Inactivation of hypoxia inducible factor (HIF) 1 alpha induces obesity-associated metabolic disorders through brown adipose tissue dysfunction

published_or_final_versionThe 14th Medical Research Conference, Hong Kong, 10 January 2009. In Hong Kong Medical Journal, 2009, v. 15, suppl. 1, p. 40, article no. 6

Development of human single-chain antibodies against SARS-associated coronavirus.

The outbreak of severe acute respiratory syndrome (SARS), caused by a distinct coronavirus, in 2003 greatly threatened public health in China, Southeast Asia as well as North America. Over 1,000 patients died of the SARS virus, representing 10% of infected people. Like other coronaviruses, the SARS virus also utilizes a surface glycoprotein, namely the spike protein, to infect host cells. The spike protein of SARS virus consists of 1,255 amino acid residues and can be divided into two sub-domains, S1 and S2. The S1 domain mediates the binding of the virus to its receptor angiotensin-converting enzyme 2, which is abundantly distributed on the surface of human lung cells. The S2 domain mediates membrane fusion between the virus and the host cell. Hence two strategies can be used to block the infection of the SARS virus, either by interfering with the binding of the S1 domain to the receptor or by blocking the fusion of the virus with the cell membrane mediated by the S2 domain. Several antibodies against the S1 domain have been generated and all of them are able to neutralize the virus in vitro and in vivo using animal models. Unfortunately, point mutations have been identified in the S1 domain, so that the virus isolated in the future may not be recognized by these antibodies. As no mutation has been found in the S2 domain indicating that this region is more conserved than the S1 domain, it may be a better target for antibody binding. After predicting the immunogenicity of the epitopes of the S2 domain, we chemically synthesized two peptides and also expressed one of them using a recombinant DNA method. We screened a phage displaying library of human single-chain antibodies (ScFv) against the predicted epitopes and obtained a human ScFv which can recognize the SARS virus in vitro

Inhibition of Fungal Aflatoxin B1 Biosynthesis by Diverse Botanically-Derived Polyphenols

Purpose: To identify and characterize the capacity of diverse botanically-derived polyphenols to inhibit aflatoxin B1 (AFB1) production by Aspergillus flavus.Methods: A tea-derived polyphenol mixture and numerous individual polyphenols were tested for their effects on A. flavus growth and AFB1 production. Fungal spores were cultured for 60 h with polyphenols (range 0 ‒ 1,000 μg/mL). The fungi were enumerated by hemocytometry, and AFB1 in culture supernatants was quantified by high-performance liquid chromatography (HPLC).Results: Neither the tea-derived polyphenol mixture nor individual polyphenol compound, except quercetin, inhibited A. flavus growth. Quercetin detectably inhibited growth at 800 μg/mL; none of the remaining polyphenols inhibited fungal proliferation, even at 1,000 μg/mL. However, catechin mixture and all individual polyphenols differentially inhibited fungal AFB1 biosynthesis. Non-ester catechin derivatives revealed stronger inhibitory activity than ester derivatives.Conclusion: Quercetin exhibits the strongest inhibitory effect on AFB1 production and is the only test compound that also inhibits fungal proliferation. Botanically-derived polyphenols are, therefore, promising reagents for controlling fungal contamination and associated toxic aflatoxin deposition in harvested crops and in food processing operations.Keywords: Polyphenols, Quercetin, Aflatoxin B1, Inhibition, Antioxidatio

CHD1L protein is overexpressed in human ovarian carcinomas and is a novel predictive biomarker for patients survival

published_or_final_versio

p21/Cyclin E pathway modulates anticlastogenic function of Bmi-1 in cancer cells.

Apart from regulating stem cell self-renewal, embryonic development and proliferation, Bmi-1 has been recently reported to be critical in the maintenance of genome integrity. In searching for novel mechanisms underlying the anticlastogenic function of Bmi-1, we observed, for the first time, that Bmi-1 positively regulates p21 expression. We extended the finding that Bmi-1 deficiency induced chromosome breaks in multiple cancer cell models. Interestingly, we further demonstrated that knockdown of cyclin E or ectopic overexpression of p21 rescued Bmi-1 deficiency-induced chromosome breaks. We therefore conclude that p21/cyclin E pathway is crucial in modulating the anticlastogenic function of Bmi-1. As it is well established that the overexpression of cyclin E potently induces genome instability and p21 suppresses the function of cyclin E, the novel and important implication from our findings is that Bmi-1 plays an important role in limiting genomic instability in cylin E-overexpressing cancer cells by positive regulation of p21.published_or_final_versio

Single to Double Hump Transition in the Equilibrium Distribution Function of Relativistic Particles

We unveil a transition from single peaked to bimodal velocity distribution in a relativistic fluid under increasing temperature, in contrast with a non-relativistic gas, where only a monotonic broadening of the bell-shaped distribution is observed. Such transition results from the interplay between the raise in thermal energy and the constraint of maximum velocity imposed by the speed of light. We study the Bose-Einstein, the Fermi-Dirac, and the Maxwell-J\"uttner distributions, all exhibiting the same qualitative behavior. We characterize the nature of the transition in the framework of critical phenomena and show that it is either continuous or discontinuous, depending on the group velocity. We analyze the transition in one, two, and three dimensions, with special emphasis on two-dimensions, for which a possible experiment in graphene, based on the measurement of the Johnson-Nyquist noise, is proposed.Comment: 5 pages, 5 figure

Sheet metal plate design: a structured approach to product optimization in the presence of technological constraints

Geometrical optimization of structural components is a topic of high interest for engineers involved with design activities mainly related to mass reduction. The study described in these pages focuses on the optimization of plates subjected to bending for which stiffness is obtained by a pattern of ribs. Although stiffening by means of ribs is a well-known and old technique, the design of ribs for maximum stiffness is often based on practice and experience. Classical optimization methods such as topological, topographical and parametric optimization fail to give an efficient design with a reasonable programming effort, especially when dealing with many and complex constraints. These constraints are both technical and technological. A most promising technique to obtain optimal rib patterns was to define a set of feasible rib trajectories and then to select the subset with the most efficient combinations. The result is not unique and a method to select the optimal patterns is required. In fact, the stiffening effect increases with increasing rib length, but at a greater cost. A trade-off must be found between structural performance and cost: The tools to guide this selection process is the main objective of the paper, with particular attention in evaluating the stiffening due to the presence of beads on the plate with a close link with the production system and possible technological constraints which can occur during manufacturing processes, such as minimum rib distance or the presence of discontinuities or the presence of holes or other elements on the plate. A special tool with enforced rib cross section is considered, and optimal rib deployment has to be found. Numerical examples attached show the methodology and obtainable results. \ua9 2011 Springer-Verlag London Limited

Using Neural Networks for Relation Extraction from Biomedical Literature

Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedical literature. Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely, using neural networks algorithms. The use of multichannel architectures composed of multiple data representations, as in deep neural networks, is leading to state-of-the-art results. The right combination of data representations can eventually lead us to even higher evaluation scores in relation extraction tasks. Thus, biomedical ontologies play a fundamental role by providing semantic and ancestry information about an entity. The incorporation of biomedical ontologies has already been proved to enhance previous state-of-the-art results.Comment: Artificial Neural Networks book (Springer) - Chapter 1