小鼠对不同拓扑性质图形的识别

视觉感知的一系列研究都支持大范围拓扑感知的理论．拓扑性质作为整体性质,是视觉感知的基础．视觉对图形拓扑特征差异的感知要优先于对局部特征差异的感知．采用Y迷宫研究了小鼠对不同拓扑性质图形的识别．训练小鼠学习识别圆环和实心矩形这一对拓扑性质不同的图形,之后用拓扑特征相同或不同的其他图形测试小鼠,这些图形包括空心矩形、实心圆、缺口的圆环、缺口的空心矩形．实验结果表明,学会识别圆环(奖励)和实心矩形(无奖励)的小鼠无法区分实心圆和实心矩形以及圆环和空心矩形,但是能够分别从缺口圆环、缺口的空心矩形、实心圆与空心矩形组成的图形对中识别出空心矩形．因此证实了小鼠的视觉系统能够感知拓扑特征的差异并且具有对拓扑性质的概括能力．结果为拓扑知觉对视觉系统来说是基本的这一假设提供了证据．     

Voting-Based Cancer Module Identification by Combining Topological and Data-Driven Properties

Recently, computational approaches integrating copy number aberrations (CNAs) and gene expression (GE) have been extensively studied to identify cancer-related genes and pathways. In this work, we integrate these two data sets with protein-protein interaction (PPI) information to find cancer-related functional modules. To integrate CNA and GE data, we first built a gene-gene relationship network from a set of seed genes by enumerating all types of pairwise correlations, e.g. GE-GE, CNA-GE, and CNA-CNA, over multiple patients. Next, we propose a voting-based cancer module identification algorithm by combining topological and data-driven properties (VToD algorithm) by using the gene-gene relationship network as a source of data-driven information, and the PPI data as topological information. We applied the VToD algorithm to 266 glioblastoma multiforme (GBM) and 96 ovarian carcinoma (OVC) samples that have both expression and copy number measurements, and identified 22 GBM modules and 23 OVC modules. Among 22 GBM modules, 15, 12, and 20 modules were significantly enriched with cancer-related KEGG, BioCarta pathways, and GO terms, respectively. Among 23 OVC modules, 19, 18, and 23 modules were significantly enriched with cancer-related KEGG, BioCarta pathways, and GO terms, respectively. Similarly, we also observed that 9 and 2 GBM modules and 15 and 18 OVC modules were enriched with cancer gene census (CGC) and specific cancer driver genes, respectively. Our proposed module-detection algorithm significantly outperformed other existing methods in terms of both functional and cancer gene set enrichments. Most of the cancer-related pathways from both cancer data sets found in our algorithm contained more than two types of gene-gene relationships, showing strong positive correlations between the number of different types of relationship and CGC enrichment -values (0.64 for GBM and 0.49 for OVC). This study suggests that identified modules containing both expression changes and CNAs can explain cancer-related activities with greater insights.     

New Inhibitor of Phosphodiesterase with Anti-bronchoconstrictor Properties

IN earlier work on the synthesis of isosteres of purine and in particular of theophylline (I), a series of triazolopyrimidines was found which could protect guinea-pigs against histamine bronchospasm. One compound (II) was also found to be active in certain cases of human asthma but it was found to be of no practical value because it had a tendency to cause nausea and vomiting. But because there is at present no adequate treatment for asthma, we undertook to prepare related substances which retain the activity but which are free of the defect: Thus we produced 3-acetamido-6-methyl-8-n-propyl-s-triazolo [4,3a] pyrazine (III; R=CO.Me;I.C.I.58,301 (ref. 3)). This substance is only in the early stages of clinical study in man, but we report here the chemical, biological and biochemical properties that led to its selection.     

Probing the Topological Properties of Complex Networks Modeling Short Written Texts

In recent years, graph theory has been widely employed to probe several language properties. More specifically, the so-called word adjacency model has been proven useful for tackling several practical problems, especially those relying on textual stylistic analysis. The most common approach to treat texts as networks has simply considered either large pieces of texts or entire books. This approach has certainly worked well—many informative discoveries have been made this way—but it raises an uncomfortable question: could there be important topological patterns in small pieces of texts? To address this problem, the topological properties of subtexts sampled from entire books was probed. Statistical analyses performed on a dataset comprising 50 novels revealed that most of the traditional topological measurements are stable for short subtexts. When the performance of the authorship recognition task was analyzed, it was found that a proper sampling yields a discriminability similar to the one found with full texts. Surprisingly, the support vector machine classification based on the characterization of short texts outperformed the one performed with entire books. These findings suggest that a local topological analysis of large documents might improve its global characterization. Most importantly, it was verified, as a proof of principle, that short texts can be analyzed with the methods and concepts of complex networks. As a consequence, the techniques described here can be extended in a straightforward fashion to analyze texts as time-varying complex networks.     

New Indices for Predicting Glycaemic Variability

Blood glucose variability is known to be associated with increased risk of long-term complications. Reliable indices for predicting hyperglycaemic and hypoglycaemic fluctuations are therefore needed. Glycaemic standard deviation (SD) obtained by continuous glucose monitoring correlates closely with nine previously described glycaemic variability formulas. Here, new indices predictive of glycaemic variability were developed, which can be calculated from laboratory measures based on a single blood draw. The indices included the glycated albumin (GA) to HbA1c ratio (GA/A1c ratio) and the fasting C-peptide immunoreactivity (FCPR) to fasting plasma glucose (FPG) ratio (FCPR index). Predictive values of these indices were assessed in 100 adults with diabetes. GA/A1c ratio and FCPR index showed close associations with glycaemic SD in addition to the nine existing glucose variability formulas. Subjects with a GA/A1c ratio ≥2.8 and FCPR index <3.0 showed the greatest SD and longest durations of hypoglycaemia, while those with a GA/A1c ratio <2.8 and FCPR index ≥3.0 had smaller SDs and little sign of hypoglycaemia. In adults with diabetes, a high GA/A1c ratio and low FCPR index value reflect higher glycaemic excursions, irrespective of diabetes type. Simultaneous measurements of GA, HbA1c, FPG and FCPR may help to identify a group of patients who warrant closer monitoring in relation to glycaemic variability and hypoglycaemia.     

胎儿体重预测的一种新方法

利用B型超声对520例胎儿的股骨长、腹围测量数据,经非线性回归分析得出预测胎儿体重的修正Logistic模型,并用所建模型对982例胎儿进行实例验证,其结果大大优于国内外已有文献报道．     

A New Bithiazole Derivative with Intercalative Properties

Abstract

In the course of studies related to new molecules with intercalative properties, we have been led to design and synthesize a bithiazole derivative, namely the 2-phenyl-6- [2′-(4′-(ethoxy-carbony1)thiazoly1)] thiazolo[3,2-b] [1,2,4]triazole (PETT). Its interaction with calf thymus DNA was studied using thermal denaturation and viscometry. Our results set in evidence that PETT acts as an intercalator, giving Δ Tm, elongation and unwinding of DNA comparable to the values obtained for daunorubicin. The discrepancy between the data presented herein and those precedently obtained for bleomycin and bleomycin models provide evidence that these bithiazole derivatives interact differently with DNA.     

Landscape Excitation Profiles and Excess Thermodynamic Properties of Disaccharide Aqueous Solutions

We will consider the use of the bond model in characterizing, by the direct calculation route, the full excitation profile. The present work sets the temperature behaviour of the excessive value of some thermodynamic quantities, such as configurational entropy and heat capacity of two homologous disaccharide aqueous solutions. The findings represent important data for understanding the better lyoprotectant effectiveness of trehalose in comparison with sucrose.     

Predicting Statistical Properties of Open Reading Frames in Bacterial Genomes

An analytical model based on the statistical properties of Open Reading Frames (ORFs) of eubacterial genomes such as codon composition and sequence length of all reading frames was developed. This new model predicts the average length, maximum length as well as the length distribution of the ORFs of 70 species with GC contents varying between 21% and 74%. Furthermore, the number of annotated genes is predicted with high accordance. However, the ORF length distribution in the five alternative reading frames shows interesting deviations from the predicted distribution. In particular, long ORFs appear more often than expected statistically. The unexpected depletion of stop codons in these alternative open reading frames cannot completely be explained by a biased codon usage in the +1 frame. While it is unknown if the stop codon depletion has a biological function, it could be due to a protein coding capacity of alternative ORFs exerting a selection pressure which prevents the fixation of stop codon mutations. The comparison of the analytical model with bacterial genomes, therefore, leads to a hypothesis suggesting novel gene candidates which can now be investigated in subsequent wet lab experiments.     

Predicting the Size of Silver Nanoparticles from Their Optical Properties

Plasmonics - In this study, localized surface plasmon resonance (LSPR) of the spherical silver nanoparticles (AgNPs) was evaluated based on experimental and theoretical viewpoints. In the...     

TREAP: A New Topological Approach to Drug Target Inference

Over 50% of drugs fail in stage 3 clinical trials, many because of a poor understanding of the drug’s mechanisms of action (MoA). A better comprehension of drug MoA will significantly improve research and development (R&D). Current proposed algorithms, such as ProTINA and DeMAND, can be overly complex. Additionally, they are unable to predict whether the drug-induced gene expression or the topology of the networks used to model gene regulation primarily impacts accurate drug target inference. In this work, we evaluate how network and gene expression data affect ProTINA’s accuracy. We find that network topology predominantly determines the accuracy of ProTINA’s predictions. We further show that the size of an interaction network and/or selecting cell-specific networks has a limited effect on accuracy. We then demonstrate that a specific network topology measure, betweenness, can be used to improve drug target prediction. Based on these results, we create a new algorithm, TREAP, that combines betweenness values and adjusted p-values for target inference. TREAP offers an alternative approach to drug target inference and is advantageous because it is not computationally demanding, provides easy-to-interpret results, and is often more accurate at predicting drug targets than current state-of-the-art approaches.     

Construction of Selection Indexes with Restrictions

In this paper the problem of unistage selection with inequality constraints is formulated. If the predictor and criterion variables are all normally distributed, this problem can be written as a convex programming problem, with a linear objective function and with linear constraints and a quadratic constraint. Using the duality theory, for convex nonlinear programming it is proved, that its dual problem can be transformed into a convex minimization problem with non-negativity conditions. Good computational methods are known for solving this problem. By the help of the dual problem sufficient conditions for a solution of the original primal problem are derived and illustrated by an example of practical interest.     

Topological Estimation Biases with Covarion Evolution

Covarion processes allow changes in evolutionary rates at sites along the branches of a phylogenetic tree. Covarion-like evolution is increasingly recognized as an important mode of protein evolution. Several recent reports suggest that maximum likelihood estimation employing covarion models may support different optimal topologies than estimation using standard rates-across-sites (RAS) models. However, it remains to be demonstrated that ignoring covarion evolution will generally result in topological misestimation. In this study we performed analytical and theoretical studies of limiting distances under the covarion model and four-taxon tree simulations to investigate the extent to which the covarion process impacts on phylogenetic estimation. In particular, we assessed the limits of an RAS model-based maximum likelihood method to recover the phylogenies when the sequence data were simulated under the covarion processes. We find that, when ignored, covarion processes can induce systematic errors in phylogeny reconstruction. Surprisingly, when sequences are evolved under a covarion process but an RAS model is used for estimation, we find that a long branch repel bias occurs.     

Bound Water and Cryptobiosis:Thermodynamic Properties of Water at Biopolymer Surfaces

The molecular mechanisms underlying the adaptations to water loss developed in several tardigrade species remain poorly understood. It seems, however, that the binding of the disaccharide trehalose to membranes and other cellular components at low water contents is important for the tolerance to extreme drought. Trehalose is thus thought to replace interfacial- or “bound” water and enhance the conformational stability of labile macromolecules. To gain further insight into this we investigate here thermodynamic properties of water bound to the protein lysozyme at low water content (<100 water molecules pr. protein). It appears that this surface water has a higher enthalpy and higher entropy than the bulk liquid. These observations call for re-evaluation of the term “bound water” since “bound” carries the connotation of a low-energy, ordered (i.e. low-entropy) state.

To rationalize these observations it is suggested that — in addition to the self-evident energetic contribution from biopolymer-water contacts — the properties of interfacial water are dominated by two effects. These are i) the ability of water to facilitate fast movements of individual parts of biopolymers and ii) the high molecular cohesion in the aqueous bulk. Thus, the hydration of a surface leads to enhanced flexibility in the biopolymer and breakage in the network of hydrogen bonding in the liquid bulk, and these effects collectively increase the enthalpy and entropy of the system. As a result, the thermodynamic parameters of hydration of lysozyme carry the thermodynamic hallmarks of an order → disorder process, even for the first hundred (i.e. most strongly associated) water molecules. We discuss these data for protein hydration together with some recent, very similar observations for the hydration of lipid bilayer membranes.     

Thermodynamic and Transport Properties of Beryllium Vapor in the Supercritical Fluid State

The thermal and caloric equations of state, composition, and conductivity of a supercritical beryllium vapor are calculated using the earlier proposed “3+” chemical model, which incorporates atoms, electrons, ions, and electron jellium with allowance for interatomic and intercharge interactions. The introduction of an electron jellium makes it possible to describe the pressure-induced ionization and explain the increase in the conductivity of beryllium vapor under compression. The cohesive bond of atoms caused by the electron jellium compensates for interactions when calculating the composition and reduces the effect of intercharge interactions on the equation of state. The parameters of the beryllium critical point and the applicability domain of the model are discussed.