Regioselective modification at the 2,3- and 6-positions of chitosan with phenylcarbamates for chromatographic enantioseparation.

Chitosan derivatives with two different phenylcarbamate pendants at the 6-position and 2,3-positions of the glucosamine unit were synthesized by triphenylmethyl as a protective group. The regioselective chitosan derivatives were prepared corresponding to coated-type chiral packed materials (CPMs), which were evaluated with thirteen chiral compounds by high-performance liquid chromatography (HPLC). The regioselective chitosan derivatives (4aⅠ/4aⅡ, 4bⅠ/4bⅡ) bearing electron-withdrawing 3,5­chloro or 4­chloro at the 6-position can recognize 7 or 8 of the 13 enantiomers and achieve baseline separation for enantiomers 5 and 7. They exhibited better chiral recognition abilities than the other derivatives with different substituents at the 6-position and the same 3,5-dimethylphenyl substituent at the 2,3-postion. In comparison to Chit-1 featuring a 3,5-dimethylphenyl substituent at the 2,3- and 6-positions, it was observed that the combination of both an electron-withdrawing and an electron-donating substituent of the regioselective chitosan derivatives (4aⅠ/4aⅡ, 4bⅠ/4bⅡ) showed better or similar enantioseparation abilities for racemic Compounds 7 and 6, respectively. The molecular weight-performance relationship of the regioselective chitosan derivatives was investigated in detail. It was found that with increasing molecular weight, the derivatives 4aⅡ and 4bⅡ all possessed greater enantioseparation power for 4 enantiomers, such as enantiomers 4, 7, 11, and 15, than the corresponding derivatives with low molecular weights. The molecular docking simulation results showed that excellent enantioseparation power significantly depended on the combination and interaction of multiple factors, such as steric hindrance, and polarity of the substituents on the CPMs and enantiomers.

Synthesis and application of chitosan thiourea derivatives as chiral stationary phases in HPLC.

Chitosan 2-thiourea derivatives with various substituents, including 3-(methylthio)propyl, phenyl, octyl and ethoxycarbonyl, at the 2-position of the glucosamine skeleton were prepared via isothiocyanates with the above substituents. The obtained chitosan 2-thiourea derivatives without ethoxycarbonyl were then esterified to develop a new series of chitosan 2-thiourea-3,6-diphenylcarbamate derivatives. The enantioseparation properties of the obtained chitosan derivatives were examined by high-performance liquid chromatography (HPLC). These results demonstrated that these chitosan 2-[3-(methylthio)propylthiourea]-3,6-diphenylcarbamate derivatives showed attractive chiral recognition abilities, especially for dihydropyridine calcium antagonist racemates. This result was probably attributed to the fact that the 2-thiourea substituents of this series of chitosan derivatives, as well as the 3,6-phenylcarbamate substituents, provided more favorable sites, which evidently enhanced the interactions between the enantiomers and the chitosan derivatives. The mechanism involved in the enantioseparation of the chitosan 2-[3-(methylthio)propylthiourea]-3,6-diphenylcarbamate derivatives was further discussed by molecular docking simulation.

Enantioseparation using chitosan 2-isopropylthiourea-3,6-dicarbamate derivatives as chiral stationary phases for high-performance liquid chromatography.

A new class of chitosan derivatives with an isopropylthiourea at the 2-position and various carbamates at the 3,6-positions of the glucosamine skeleton was synthesized by the selective thiocarbamoylation of the 2-amino group. The chiral stationary phases (CSPs) were then prepared by coating the obtained chitosan 2-isopropylthiourea-3,6-dicarbamate derivatives onto silica gel. The enantioseparation property of the chitosan-based CSPs was assessed with twelve racemates by high-performance liquid chromatography (HPLC). The CSPs displayed a characteristic enantioseparation power, which seemed to be significantly affected by the 3,6-substituents of the glucosamine unit. The chitosan derivatives with the 3,6-diphenylcarbamate, except for 2-methylphenylcarbamate, possessed higher enantioseparation abilities than those with the 3,6-dicyclohexylcarbamate. Compared to other chitosan derivatives with 2-various substituents and commercialized Chiralcel OD, the chitosan 2-isopropylthiourea derivatives revealed a relatively higher enantioselectivity for some racemic compounds.

Evaluating link significance in maintaining network connectivity based on link prediction.

Evaluating the significance of nodes or links has always been an important issue in complex networks, and the definition of significance varies with different perspectives. The significance of nodes or links in maintaining the network connectivity is widely discussed due to its application in targeted attacks and immunization. In this paper, inspired by the weak tie phenomenon, we define the links' significance by the dissimilarity of their endpoints. Some link prediction algorithms are introduced to define the dissimilarity of nodes based solely on the network topology. Experiments in synthetic and real networks demonstrate that the method is especially effective in the networks with higher clustering coefficients.

Minimum Memory-Based Sign Adjustment in Signed Social Networks.

In social networks comprised of positive (P) and negative (N) symmetric relations, individuals (nodes) will, under the stress of structural balance, alter their relations (links or edges) with their neighbours, either from positive to negative or vice versa. In the real world, individuals can only observe the influence of their adjustments upon the local balance of the network and take this into account when adjusting their relationships. Sometime, their local adjustments may only respond to their immediate neighbourhoods, or centre upon the most important neighbour. To study whether limited memory affects the convergence of signed social networks, we introduce a signed social network model, propose random and minimum memory-based sign adjustment rules, and analyze and compare the impacts of an initial ratio of positive links, rewire probability, network size, neighbor number, and randomness upon structural balance under these rules. The results show that, with an increase of the rewiring probability of the generated network and neighbour number, it is more likely for the networks to globally balance under the minimum memory-based adjustment. While the Newmann-Watts small world model (NW) network becomes dense, the counter-intuitive phenomena emerges that the network will be driven to a global balance, even under the minimum memory-based local sign adjustment, no matter the network size and initial ratio of positive links. This can help to manage and control huge networks with imited resources.

Optimal disintegration strategy in multiplex networks.

Network disintegration comprises the problem of identifying the critical nodes or edges whose removal will lead to a network collapse. The solution of this problem is significant for strategies for dismantling terrorist organizations and for immunization in disease spreading. Network disintegration has received considerable attention in isolated networks. Here, we consider the generalization of optimal disintegration strategy problems to multiplex networks and propose a disintegration strategy based on tabu search. Experiments show that the disintegration effect of our strategy is clearly superior to those of typical disintegration strategies. Moreover, our approach sheds light on the properties of the nodes within the optimal disintegration strategies.

Genetic variation and association mapping for 12 agronomic traits in indica rice.

BACKGROUND: Increasing rice (Oryza sativa L.) yield is a crucial challenge for modern agriculture. The ideal plant architecture is considered to be critical to enhance rice yield. Elite plant morphological traits should include compact plant type, short stature, few unproductive tillers, thick and sturdy stems and erect leaves. To reveal the genetic variations of important morphological traits, 523 germplasm accessions were genotyped using the Illumina custom-designed array containing 5,291 single nucleotide polymorphisms (SNPs) and phenotyped in two independent environments. Genome-wide association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. RESULTS: In total, 126 and 172 significant loci were identified and these loci explained an average of 34.45% and 39.09% of the phenotypic variance in two environments, respectively, and 16 of 298 (~5.37%) loci were detected across the two environments. For the 16 loci, 423 candidate genes were predicted in a 200-kb region (±100 kb of the peak SNP). Expression-level analyses identified four candidate genes as the most promising regulators of tiller angle. Known (NAL1 and Rc) and new significant loci showed pleiotropy and gene linkage. In addition, a long genome region covering ~1.6 Mb on chromosome 11 was identified, which may be critical for rice leaf architecture because of a high association with flag leaf length and the ratio of flag leaf length and width. The pyramid effect of the elite alleles indicated that these significant loci could be beneficial for rice plant architecture improvements in the future. Finally, 37 elite varieties were chosen as breeding donors for further rice plant architectural modifications. CONCLUSIONS: This study detected multiple novel loci and candidate genes related to rice morphological traits, and the work demonstrated that genome-wide association studies are powerful strategies for uncovering the genetic variations of complex traits and identifying candidate genes in rice, even though the linkage disequilibrium decayed slowly in self-pollinating species. Future research will focus on the biological validation of the candidate genes, and elite varieties will also be of interest in genome selection and breeding by design.

Robustness of random graphs based on graph spectra.

It has been recently proposed that the robustness of complex networks can be efficiently characterized through the natural connectivity, a spectral property of the graph which corresponds to the average Estrada index. The natural connectivity corresponds to an average eigenvalue calculated from the graph spectrum and can also be interpreted as the Helmholtz free energy of the network. In this article, we explore the use of this index to characterize the robustness of Erdos-Rényi (ER) random graphs, random regular graphs, and regular ring lattices. We show both analytically and numerically that the natural connectivity of ER random graphs increases linearly with the average degree. It is also shown that ER random graphs are more robust than the corresponding random regular graphs with the same number of vertices and edges. However, the relative robustness of ER random graphs and regular ring lattices depends on the average degree and graph size: there is a critical graph size above which regular ring lattices are more robust than random graphs. We use our analytical results to derive this critical graph size as a function of the average degree.

Relationship between degree-rank function and degree distribution of protein-protein interaction networks.

It is argued that both the degree-rank function r=f(d), which describes the relationship between the degree d and the rank r of a degree sequence, and the degree distribution P(k), which describes the probability that a randomly chosen vertex has degree k, are important statistical properties to characterize protein-protein interaction (PPI) networks, both rank-degree plot and frequency-degree plot are reliable tools to analyze PPI networks. An exact mathematical relationship between degree-rank functions and degree distributions of PPI networks is derived. It is demonstrated that a power law degree distribution is equivalent to a power law degree-rank function only if scaling exponent is greater than 2. The puzzle that the degree distributions of some PPI networks follow a power law using frequency-degree plots, whereas the degree sequences do not follow a power law using rank-degree plots is explained using the mathematical relationship.