Diagnosis of dihydropyrimidinase deficiency in a Chinese boy with dihydropyrimidinuria

published_or_final_versio

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

"Meaning" as a sociological concept: A review of the modeling, mapping, and simulation of the communication of knowledge and meaning

The development of discursive knowledge presumes the communication of meaning as analytically different from the communication of information. Knowledge can then be considered as a meaning which makes a difference. Whereas the communication of information is studied in the information sciences and scientometrics, the communication of meaning has been central to Luhmann's attempts to make the theory of autopoiesis relevant for sociology. Analytical techniques such as semantic maps and the simulation of anticipatory systems enable us to operationalize the distinctions which Luhmann proposed as relevant to the elaboration of Husserl's "horizons of meaning" in empirical research: interactions among communications, the organization of meaning in instantiations, and the self-organization of interhuman communication in terms of symbolically generalized media such as truth, love, and power. Horizons of meaning, however, remain uncertain orders of expectations, and one should caution against reification from the meta-biological perspective of systems theory

The Function and Organization of Lateral Prefrontal Cortex: A Test of Competing Hypotheses

The present experiment tested three hypotheses regarding the function and organization of lateral prefrontal cortex (PFC). The first account (the information cascade hypothesis) suggests that the anterior-posterior organization of lateral PFC is based on the timing with which cue stimuli reduce uncertainty in the action selection process. The second account (the levels-of-abstraction hypothesis) suggests that the anterior-posterior organization of lateral PFC is based on the degree of abstraction of the task goals. The current study began by investigating these two hypotheses, and identified several areas of lateral PFC that were predicted to be active by both the information cascade and levels-of-abstraction accounts. However, the pattern of activation across experimental conditions was inconsistent with both theoretical accounts. Specifically, an anterior area of mid-dorsolateral PFC exhibited sensitivity to experimental conditions that, according to both accounts, should have selectively engaged only posterior areas of PFC. We therefore investigated a third possible account (the adaptive context maintenance hypothesis) that postulates that both posterior and anterior regions of PFC are reliably engaged in task conditions requiring active maintenance of contextual information, with the temporal dynamics of activity in these regions flexibly tracking the duration of maintenance demands. Activity patterns in lateral PFC were consistent with this third hypothesis: regions across lateral PFC exhibited transient activation when contextual information had to be updated and maintained in a trial-by-trial manner, but sustained activation when contextual information had to be maintained over a series of trials. These findings prompt a reconceptualization of current views regarding the anterior-posterior organization of lateral PFC, but do support other findings regarding the active maintenance role of lateral PFC in sequential working memory paradigms

Particles and fields in fluid turbulence

The understanding of fluid turbulence has considerably progressed in recent years. The application of the methods of statistical mechanics to the description of the motion of fluid particles, i.e. to the Lagrangian dynamics, has led to a new quantitative theory of intermittency in turbulent transport. The first analytical description of anomalous scaling laws in turbulence has been obtained. The underlying physical mechanism reveals the role of statistical integrals of motion in non-equilibrium systems. For turbulent transport, the statistical conservation laws are hidden in the evolution of groups of fluid particles and arise from the competition between the expansion of a group and the change of its geometry. By breaking the scale-invariance symmetry, the statistically conserved quantities lead to the observed anomalous scaling of transported fields. Lagrangian methods also shed new light on some practical issues, such as mixing and turbulent magnetic dynamo.Comment: 165 pages, review article for Rev. Mod. Phy

Sociological and Communication-Theoretical Perspectives on the Commercialization of the Sciences

Both self-organization and organization are important for the further development of the sciences: the two dynamics condition and enable each other. Commercial and public considerations can interact and "interpenetrate" in historical organization; different codes of communication are then "recombined." However, self-organization in the symbolically generalized codes of communication can be expected to operate at the global level. The Triple Helix model allows for both a neo-institutional appreciation in terms of historical networks of university-industry-government relations and a neo-evolutionary interpretation in terms of three functions: (i) novelty production, (i) wealth generation, and (iii) political control. Using this model, one can appreciate both subdynamics. The mutual information in three dimensions enables us to measure the trade-off between organization and self-organization as a possible synergy. The question of optimization between commercial and public interests in the different sciences can thus be made empirical.Comment: Science & Education (forthcoming

What is new in surgical treatment of vesicoureteric reflux?

In addition to conventional open surgery and endoscopic techniques, laparoscopic correction of vesicoureteric reflux, sometimes even robot-assisted, is becoming an alternative surgical treatment modality for this condition in a number of centres around the world. At least for a subgroup of patients laparoscopists are trying to develop new techniques in an effort to combine the best of both worlds: the minimal invasiveness of the STING and the same lasting effectiveness as in open surgery. The efficacy and potential advantages or disadvantages of these techniques are still under investigation. The different laparoscopic techniques and available data are presented