Peer Review Certifies Quality and Innovation in Clinical Pharmacology & Therapeutics.

Clinical Pharmacology & Therapeutics (CPT) is an established voice of the discipline, a trusted source of new knowledge showcasing discovery, translation, and application of novel therapeutic paradigms to advance the management of patients and populations. Identifying, evaluating, prioritizing, and disseminating the best science along the discovery-development-regulatory-utilization continuum are responsibilities shared through peer review. To enhance the uniformity of this essential component of quality assurance and innovation, and maximize the value of the journal and its contents to authors, reviewers, and the readership, we review key concepts concerning peer review as it specifically relates to CPT

Yeasts

Yeasts are a group of eukaryotic microfungi with a well-defined cell wall whose growth is either entirely unicellular or a combination of hyphal and unicellular reproduction. The approximately 1500 known yeast species belong to two distinct fungal phyla, the Ascomycota and the Basidiomycota. Within each these phyla, yeasts can be found in several subphyla or classes, reflecting the enormous diversity of their evolutionary origins and biochemical properties. In nature, yeasts are found mainly in association with plants or animals but are also present in soil and aquatic environments. Yeasts grow rapidly and have simple nutritional requirements, for which reason they have been used as model systems in biochemistry, genetics and molecular biology. They were the first microorganisms to be domesticated for the production of beer, bread or wine, and they continue to be used for the benefit of humanity in the production of many important health care and industrial commodities, including recombinant proteins, biopharmaceuticals, biocontrol agents and biofuels. The best-known yeast is the species Saccharomyces cerevisiae, which may be regarded as the world’s foremost industrial microbe

Generalizing the Planck distribution

Along the lines of nonextensive statistical mechanics, based on the entropy $S_q = k(1- \sum_i p_i^q)/(q-1) (S_1=-k \sum_i p_i \ln p_i)$, and Beck-Cohen superstatistics, we heuristically generalize Planck's statistical law for the black-body radiation. The procedure is based on the discussion of the differential equation $dy/dx=-a_{1}y-(a_{q}-a_{1}) y^{q}$ (with $y(0)=1$), whose $q=2$ particular case leads to the celebrated law, as originally shown by Planck himself in his October 1900 paper. Although the present generalization is mathematically simple and elegant, we have unfortunately no physical application of it at the present moment. It opens nevertheless the door to a type of approach that might be of some interest in more complex, possibly out-of-equilibrium, phenomena.Comment: 6 pages, including 2 figures. To appear in {\it Complexity, Metastability and Nonextensivity}, Proc. 31st Workshop of the International School of Solid State Physics (20-26 July 2004, Erice-Italy), eds. C. Beck, A. Rapisarda and C. Tsallis (World Scientific, Singapore, 2005

Stochastic Acceleration of 3^3He and 4^4He in Solar Flares by Parallel Propagating Plasma Waves: General Results

We study the acceleration in solar flares of $^3$He and $^4$He from a thermal background by parallel propagating plasma waves with a general broken power-law spectrum that takes into account the turbulence generation processes at large scales and the thermal damping effects at small scales. The exact dispersion relation for a cold plasma is used to describe the relevant wave modes. Because low-energy $\alpha$-particles only interact with small scale waves in the $^4$He-cyclotron branch, where the wave frequencies are below the $\alpha$-particle gyro-frequency, their pitch angle averaged acceleration time is at least one order of magnitude longer than that of $^3$He ions, which mostly resonate with relatively higher frequency waves in the proton-cyclotron (PC) branch. The $\alpha$-particle acceleration rate starts to approach that of $^3$He beyond a few tens of keV nucleon$^{-1}$, where $\alpha$-particles can also interact with long wavelength waves in the PC branch. However, the $^4$He acceleration rate is always smaller than that of $^3$He. Consequently, the acceleration of $^4$He is suppressed significantly at low energies, and the spectrum of the accelerated $\alpha$-particles is always softer than that of $^3$He. The model gives reasonable account of the observed low-energy $^3$He and $^4$He fluxes and spectra in the impulsive solar energetic particle events observed with the {\it Advanced Composition Explorer}. We explore the model parameter space to show how observations may be used to constrain the model.Comment: 29 pages, 11 Figures, Submitted to Ap

Faster Algorithms for the Maximum Common Subtree Isomorphism Problem

The maximum common subtree isomorphism problem asks for the largest possible isomorphism between subtrees of two given input trees. This problem is a natural restriction of the maximum common subgraph problem, which is ${\sf NP}$-hard in general graphs. Confining to trees renders polynomial time algorithms possible and is of fundamental importance for approaches on more general graph classes. Various variants of this problem in trees have been intensively studied. We consider the general case, where trees are neither rooted nor ordered and the isomorphism is maximum w.r.t. a weight function on the mapped vertices and edges. For trees of order $n$ and maximum degree $\Delta$ our algorithm achieves a running time of $\mathcal{O}(n^2\Delta)$ by exploiting the structure of the matching instances arising as subproblems. Thus our algorithm outperforms the best previously known approaches. No faster algorithm is possible for trees of bounded degree and for trees of unbounded degree we show that a further reduction of the running time would directly improve the best known approach to the assignment problem. Combining a polynomial-delay algorithm for the enumeration of all maximum common subtree isomorphisms with central ideas of our new algorithm leads to an improvement of its running time from $\mathcal{O}(n^6+Tn^2)$ to $\mathcal{O}(n^3+Tn\Delta)$, where $n$ is the order of the larger tree, $T$ is the number of different solutions, and $\Delta$ is the minimum of the maximum degrees of the input trees. Our theoretical results are supplemented by an experimental evaluation on synthetic and real-world instances