Pharmaceuticals: The Battle for Control in the 21st Century

To explore these concepts, this paper focuses on the Japanese motivation for taking control in the pharmaceutical industry and efforts that the US can take to ensure its role as a leader in the pharmaceutical industry. First, the paper discusses how Japan is poised to invade the US pharmaceutical market, reasons for Japanese entry into the market, the Japanese focus on research, recent examples of Japanese expansion and how US policy may affect Japanese expansion into the pharmaceutical market. The next section describes the need for the FDA to protect consumer interests in the US since market forces and / or the legal system cannot protect consumers against unsafe or ineffective drugs. The third section discusses both the fallacy of a proposal to deregulate the FDA and the effects of the proposed deregulation on the Japanese penetration of the pharmaceutical industry. Additionally, the need for FDA protection in a global market is stressed. The fourth section deals with the critical role of research to maintain US leadership in the pharmaceutical market. Finally, the fifth section discusses Japanese approaches that the US may adopt to help maintain its leadership position in the world pharmaceutical market

A Monte Carlo Study on the Dynamical Fluctuations Inside Quark and Antiquark Jets

The dynamical fluctuations inside the quark and antiquark jets are studied using Monte Carlo method. Quark and antiquark jets are identified from the 2-jet events in e+e- collisions at 91.2 GeV by checking them at parton level. It is found that transition point exists inside both of these two kinds of jets. At this point the jets are circular in the transverse plane with respect to the property of dynamical fluctuations. The results are consistent with the fact that the third jet (gluon jet) was historically first discovered in e+e- collisions in the energy region 17-30 GeV.Comment: 9 pages, 4 figure

LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates

BACKGROUND: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to identify patterns that together explain the data as a linear combination of expression signatures. Microarray data generally includes individual estimates of uncertainty for each gene in each condition, however NMF does not exploit this information. Previous work has shown that such uncertainties can be extremely valuable for pattern recognition. RESULTS: We have created a new algorithm, least squares non-negative matrix factorization, LS-NMF, which integrates uncertainty measurements of gene expression data into NMF updating rules. While the LS-NMF algorithm maintains the advantages of original NMF algorithm, such as easy implementation and a guaranteed locally optimal solution, the performance in terms of linking functionally related genes has been improved. LS-NMF exceeds NMF significantly in terms of identifying functionally related genes as determined from annotations in the MIPS database. CONCLUSION: Uncertainty measurements on gene expression data provide valuable information for data analysis, and use of this information in the LS-NMF algorithm significantly improves the power of the NMF technique

Novel Scaling Behavior for the Multiplicity Distribution under Second-Order Quark-Hadron Phase Transition

Deviation of the multiplicity distribution $P_q$ in small bin from its Poisson counterpart $p_q$ is studied within the Ginzburg-Landau description for second-order quark-hadron phase transition. Dynamical factor $d_q\equiv P_q/p_q$ for the distribution and ratio $D_q\equiv d_q/d_1$ are defined, and novel scaling behaviors between $D_q$ are found which can be used to detect the formation of quark-gluon plasma. The study of $d_q$ and $D_q$ is also very interesting for other multiparticle production processes without phase transition.Comment: 4 pages in revtex, 5 figures in eps format, will be appeared in Phys. Rev.

Relationship between adiposity and admixture in African-American and Hispanic-American women.

ObjectiveThe objective of this study was to investigate whether differences in admixture in African-American (AFA) and Hispanic-American (HA) adult women are associated with adiposity and adipose distribution.DesignThe proportion of European, sub-Saharan African and Amerindian admixture was estimated for AFA and HA women in the Women's Heath Initiative using 92 ancestry informative markers. Analyses assessed the relationship between admixture and adiposity indices.SubjectsThe subjects included 11 712 AFA and 5088 HA self-identified post-menopausal women.ResultsThere was a significant positive association between body mass index (BMI) and African admixture when BMI was considered as a continuous variable, and age, education, physical activity, parity, family income and smoking were included covariates (P<10(-4)). A dichotomous model (upper and lower BMI quartiles) showed that African admixture was associated with a high odds ratio (OR=3.27 (for 100% admixture compared with 0% admixture), 95% confidence interval 2.08-5.15). For HA, there was no association between BMI and admixture. In contrast, when waist-to-hip ratio (WHR) was used as a measure of adipose distribution, there was no significant association between WHR and admixture in AFA but there was a strong association in HA (P<10(-4); OR Amerindian admixture=5.93, confidence interval=3.52-9.97).ConclusionThese studies show that: (1) African admixture is associated with BMI in AFA women; (2) Amerindian admixture is associated with WHR but not BMI in HA women; and (3) it may be important to consider different measurements of adiposity and adipose distribution in different ethnic population groups

Determination of strongly overlapping signaling activity from microarray data

BACKGROUND: As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of signaling pathways during disease development or therapeutic intervention would assist in drug development, design of therapy, and target identification. Microarrays provide a global measure of cellular response, however linking these responses to signaling pathways requires an analytic approach tuned to the underlying biology. An ongoing issue in pattern recognition in microarrays has been how to determine the number of patterns (or clusters) to use for data interpretation, and this is a critical issue as measures of statistical significance in gene ontology or pathways rely on proper separation of genes into groups. RESULTS: Here we introduce a method relying on gene annotation coupled to decompositional analysis of global gene expression data that allows us to estimate specific activity on strongly coupled signaling pathways and, in some cases, activity of specific signaling proteins. We demonstrate the technique using the Rosetta yeast deletion mutant data set, decompositional analysis by Bayesian Decomposition, and annotation analysis using ClutrFree. We determined from measurements of gene persistence in patterns across multiple potential dimensionalities that 15 basis vectors provides the correct dimensionality for interpreting the data. Using gene ontology and data on gene regulation in the Saccharomyces Genome Database, we identified the transcriptional signatures of several cellular processes in yeast, including cell wall creation, ribosomal disruption, chemical blocking of protein synthesis, and, criticially, individual signatures of the strongly coupled mating and filamentation pathways. CONCLUSION: This works demonstrates that microarray data can provide downstream indicators of pathway activity either through use of gene ontology or transcription factor databases. This can be used to investigate the specificity and success of targeted therapeutics as well as to elucidate signaling activity in normal and disease processes

Energy Conservation Constraints on Multiplicity Correlations in QCD Jets

We compute analytically the effects of energy conservation on the self-similar structure of parton correlations in QCD jets. The calculations are performed both in the constant and running coupling cases. It is shown that the corrections are phenomenologically sizeable. On a theoretical ground, energy conservation constraints preserve the scaling properties of correlations in QCD jets beyond the leading log approximation.Comment: 11 pages, latex, 5 figures, .tar.gz version avaliable on ftp://www.inln.unice.fr

Criticality, Fractality and Intermittency in Strong Interactions

Assuming a second-order phase transition for the hadronization process, we attempt to associate intermittency patterns in high-energy hadronic collisions to fractal structures in configuration space and corresponding intermittency indices to the isothermal critical exponent at the transition temperature. In this approach, the most general multidimensional intermittency pattern, associated to a second-order phase transition of the strongly interacting system, is determined, and its relevance to present and future experiments is discussed.Comment: 15 pages + 2 figures (available on request), CERN-TH.6990/93, UA/NPPS-5-9

Hybrid Modeling of Cell Signaling and Transcriptional Reprogramming and Its Application in C. elegans Development

Modeling of signal driven transcriptional reprogramming is critical for understanding of organism development, human disease, and cell biology. Many current modeling techniques discount key features of the biological sub-systems when modeling multiscale, organism-level processes. We present a mechanistic hybrid model, GESSA, which integrates a novel pooled probabilistic Boolean network model of cell signaling and a stochastic simulation of transcription and translation responding to a diffusion model of extracellular signals. We apply the model to simulate the well studied cell fate decision process of the vulval precursor cells (VPCs) in C. elegans, using experimentally derived rate constants wherever possible and shared parameters to avoid overfitting. We demonstrate that GESSA recovers (1) the effects of varying scaffold protein concentration on signal strength, (2) amplification of signals in expression, (3) the relative external ligand concentration in a known geometry, and (4) feedback in biochemical networks. We demonstrate that setting model parameters based on wild-type and LIN-12 loss-of-function mutants in C. elegans leads to correct prediction of a wide variety of mutants including partial penetrance of phenotypes. Moreover, the model is relatively insensitive to parameters, retaining the wild-type phenotype for a wide range of cell signaling rate parameters

Quantitative reconstruction of late Holocene surface evolution on an alpine debris-flow fan

Debris-flow fans form a ubiquitous record of past debris-flow activity in mountainous areas, and may be useful for inferring past flow characteristics and consequent future hazard. Extracting information on past debris flows from fan records, however, requires an understanding of debris-flow deposition and fan surface evolution; field-scale studies of these processes have been very limited. In this paper, we document the patterns and timing of debris-flow deposition on the surface of the large and exceptionally active Illgraben fan in southwestern Switzerland. We use terrain analysis, radiocarbon dating of sediment fill in the Illgraben catchment, and cosmogenic 10Be and 36Cl exposure dating of debris-flow deposits on the fan to constrain the temporal evolution of the sediment routing system in the catchment and on the fan during the past 3200 years. We show that the fan surface preserves a set of debris-flow lobes that were predominantly deposited after the occurrence of a large rock avalanche near the fan apex at about 3200 years ago. This rock avalanche shifted the apex of the fan and impounded sediment within the Illgraben catchment. Subsequent evolution of the fan surface has been governed by both lateral and radial shifts in the active depositional lobe, revealed by the cosmogenic radionuclide dates and by cross-cutting geometrical relationships on the fan surface. This pattern of frequent avulsion and fan surface occupation provides field-scale evidence of the type of large-scale compensatory behavior observed in experimental sediment routing systems