Biomedical subjects

Haijun Zhou

Publications and source records attributed to Haijun Zhou.

11 recordsLinked to original sources

PubMed2006

Investigation on glycosylation patterns of proteins from human liver cancer cell lines based on the multiplexed proteomics technology.

Glycosylation, a very important post-translational modification of proteins, is increasingly coming into notice. However, large-scale, throughput investigations on glycosylated proteins are few. We applied a sensitive and fast fluorescence-based multiplexed proteomics (MP) technology which included two-dimensional gel electrophoresis (2-DE) followed by the fluorescence staining of glycoprotein and mass spectrometry identification for the purpose of constructing glycoprotein databases of the typical human hepatocellular carcinoma cell lines including Hep3B cell line without metastasis and MHCC97H with highly metastatic potential as well as the control non-tumor Chang liver cell. 74+/-2 (n=3), 78+/-3 (n=3) and 72+/-5 (n=3) glycoprotein spots were detected on 2-DE gels from Chang liver, Hep3B and MHCC97H cell sample using this MP technique, respectively. In all, 80 glycoproteins from three cell lines were successfully identified via peptide mass profiling using MALDI-TOF-MS/MS and the identified glycoproteins were annotated to our databases. In addition, we also found the glycosylation pattern differences among these three cell lines. The protein glycosylation alteration would be have great significance for the diagnosis of HCC and prediction of its metastasis. This study described the construction of glycosylation patterns of proteins and glycoproteome databases of human liver cells by the novel technological platform. The glycoproteome databases also provide essential basis for following study.

Animals↗

PubMed2006

Message passing for vertex covers.

Constructing a minimal vertex cover of a graph can be seen as a prototype for a combinatorial optimization problem under hard constraints. In this paper, we develop and analyze message-passing techniques, namely, warning and survey propagation, which serve as efficient heuristic algorithms for solving these computational hard problems. We show also, how previously obtained results on the typical-case behavior of vertex covers of random graphs can be recovered starting from the message-passing equations, and how they can be extended.

Journal Article↗

PubMed2006

Collapse transition of two-dimensional flexible and semiflexible polymers.

The nature of the globule-coil transition of surface-confined polymers has been an issue of debate. Here this 2D collapse transition is studied through a partially directed lattice model. In the general case of polymers with positive bending stiffness (Delta>0), the collapse transition is first order; it becomes second order only in the limiting case of zero bending stiffness (Delta triple bond 0). These analytical results are confirmed by Monte Carlo simulations. We also suggest some possible future experiments.

DNA↗

PubMed2006

Identification and characterization of selenoprotein K: an antioxidant in cardiomyocytes.

Selenoprotein K (SelK) is a newly identified selenoprotein. We showed that selenium incorporation into SelK was dependent on the 3'UTR of SelK mRNA. Sec insertion sequence (SECIS) RNA binding assays demonstrated that human SBP2 bound to the SelK SECIS element through the conserved non-Watson-Crick base pair quartet but not the AAT motif. Examination of the expression pattern revealed that human SelK mRNA was highly expressed in heart. Immunofluorescence analysis showed that SelK localized to the endoplasmic reticulum. Using SelK recombinant adenovirus, we found that overexpression of SelK attenuated the intracellular reactive oxygen species level and protected cells from oxidative stress-induced toxicity in cardiomyocytes. Our findings indicated that SelK is a novel antioxidant in cardiomyocytes and is related to the regulation of cellular redox balance.

3' Untranslated Regions↗

PubMed2005

Dynamic pattern evolution on scale-free networks.

A general class of dynamic models on scale-free networks is studied by analytical methods and computer simulations. Each network consists of N vertices and is characterized by its degree distribution, P(k), which represents the probability that a randomly chosen vertex is connected to k nearest neighbors. Each vertex can attain two internal states described by binary variables or Ising-like spins that evolve in time according to local majority rules. Scale-free networks, for which the degree distribution has a power law tail P(k) approximately k(-gamma), are shown to exhibit qualitatively different dynamic behavior for gamma < 5/2 and gamma > 5/2, shedding light on the empirical observation that many real-world networks are scale-free with 2 < gamma < 5/2. For 2 < gamma < 5/2, strongly disordered patterns decay within a finite decay time even in the limit of infinite networks. For gamma > 5/2, on the other hand, this decay time diverges as ln(N) with the network size N. An analogous distinction is found for a variety of more complex models including Hopfield models for associative memory networks. In the latter case, the storage capacity is found, within mean field theory, to be independent of N in the limit of large N for gamma > 5/2 but to grow as N(alpha) with alpha = (5 - 2gamma)/(gamma - 1) for 2 < gamma < 5/2.

Journal Article↗

PubMed2005

Long-range frustration in a spin-glass model of the vertex-cover problem.

In a spin-glass system on a random graph, some vertices have their spins changing among different configurations of a ground-state domain. Long-range frustrations may exist among these unfrozen vertices in the sense that certain combinations of spin values for these vertices may never appear in any configuration of this domain. We present a mean field theory to tackle such long-range frustrations and apply it to the NP-hard minimum vertex-cover (hard-core gas condensation) problem. Our analytical results on the ground-state energy density and on the fraction of frozen vertices are in good agreement with known numerical and mathematical results.

Journal Article↗

PubMed2005

Hierarchical chain model of spider capture silk elasticity.

Spider capture silk is a biomaterial with both high strength and high elasticity, but the structural design principle underlying these remarkable properties is still unknown. It was revealed recently by atomic force microscopy that an exponential force-extension relationship holds both for capture silk mesostructures and for intact capture silk fibers [N. Becker et al., Nat. Mater. 2, 278 (2003)]]. In this Letter a simple hierarchical chain model was proposed to understand and reproduce this striking observation. In the hierarchical chain model, a polymer is composed of many structural motifs which organize into structural modules and supramodules in a hierarchical manner. Each module in this hierarchy has its own characteristic force. The repetitive patterns in the amino-acid sequence of the major flagelliform protein of spider capture silk is in support of this model.

Animals↗

PubMed2005

[Quantitative characteristics of soil aggregates under different vegetations in upper reach of Minjiang River].

Quantitative analysis on the soil aggregates under dark coniferous forest, coniferous and broad-leaved mixed forest, fargesia under the gap of dark coniferous forest, and sclerophyllous oaks (Quercus semicarpifolia) at Wolong Natural Reserve in the upper reach of Minjiang River showed that wet-sieving soil aggregates were of logarithmic- normal distribution, and the geometric mean diameters were negatively correlated to geometric standard deviation. The aggregates under coniferous and broad-leaved mixed forest and sclerophyllous oaks had larger sizes than those under other vegetations. The range of fractal dimension of soil aggregates was 2.40 - 2.78, along with more aggregates less than 0.25 mm in size. The fractal dimension of soil aggregates under dark coniferous forest and fargesia were larger than that under other vegetations. The soil aggregates with 3 - 1 mm and 1 - 0.5 mm in size had a higher stability, while those with > 10 mm and 0.5 - 0.25 mm in size were in adverse. The aggregate stability index of soil under coniferous and broad-leaved mixed forest was the highest, followed by that under sclerophyllous oaks, fargesia under the gap of dark coniferous forest, and dark coniferous forest, which meant that coniferous and broadleaf mixed forest and sclerophyllous oaks were favorable for soil aggregate stability. Significant correlations were found among the three quantitative characteristics, which could be used to indicate the stability of soil aggregates.

China↗

PubMed2003

Distance, dissimilarity index, and network community structure.

We address the question of finding the community structure of a complex network. In an earlier effort [H. Zhou, Phys. Rev. E 67, 041908 (2003)], the concept of network random walking is introduced and a distance measure defined. Here we calculate, based on this distance measure, the dissimilarity index between nearest-neighboring vertices of a network and design an algorithm to partition these vertices into communities that are hierarchically organized. Each community is characterized by an upper and a lower dissimilarity threshold. The algorithm is applied to several artificial and real-world networks, and excellent results are obtained. In the case of artificially generated random modular networks, this method outperforms the algorithm based on the concept of edge betweenness centrality. For yeast's protein-protein interaction network, we are able to identify many clusters that have well defined biological functions.

Algorithms↗

PubMed2003

Network landscape from a Brownian particle's perspective.

Given a complex biological or social network, how many clusters should it be decomposed into? We define the distance d(i,j) from node i to node j as the average number of steps a Brownian particle takes to reach j from i. Node j is a global attractor of i if d(i,j)< or =d(i,k) for any k of the graph; it is a local attractor of i if j in E(i) (the set of nearest neighbors of i) and d(i,j)< or =d(i,l) for any l in E(i). Based on the intuition that each node should have a high probability to be in the same community as its global (local) attractor on the global (local) scale, we present a simple method to uncover a network's community structure. This method is applied to several real networks and some discussion on its possible extensions is made.

Algorithms↗

PubMed2002

Scaling exponents and clustering coefficients of a growing random network.

The statistical property of a growing scale-free network is studied based on an earlier model proposed by Krapivsky, Rodgers, and Redner [Phys. Rev. Lett. 86, 5401 (2001)], with the additional constraints of forbidding self-connection and multiple links of the same direction between any two nodes. Scaling exponents in the range of 1-2 are obtained through Monte Carlo simulations and various clustering coefficients are calculated, one of which, C(out), is of the order of 10(-1), indicating that the network resembles a small world. The out-degree distribution has an exponential cutoff for large out degree.

Journal Article↗