Synthesis and Biological Evaluation of Bromo‐ and Fluorodanicalipin A

We disclose the syntheses of (+)‐bromodanicalipin A as well as (±)‐fluorodanicalipin A. The relative configuration and ground‐state conformation in solution of both molecules was secured by J‐based configuration analysis which revealed that these are identical to natural danicalipin A. Furthermore, preliminary toxicological investigations suggest that the adverse effect of danicalipin A may be due to the lipophilicity of the halogens.     

Multivariate subexponential distributions and their applications

We propose a new definition of a multivariate subexponential distribution. We compare this definition with the two existing notions of multivariate subexponentiality, and compute the asymptotic behaviour of the ruin probability in the context of an insurance portfolio, when multivariate subexponentiality holds. Previously such results were available only in the case of multivariate regularly varying claims.     

A Trait‐based framework for mutation bias as a driver of long‐term evolutionary trends

Previous work has shown that mutation bias can direct evolutionary trends in genotypic space under strong selection and rare mutation. We present an extension of this work to general traits of the organism. We do this by allowing many different genotypes, with different fitnesses, to have the same trait value. This approach makes novel predictions and shows that the outcome of evolution for a trait is influenced by mutation bias as well as the fitness distribution of the genotypes that have the same trait value. This distribution can alter evolution in interesting ways, depending on the likelihood of generating high fitness mutants. We also show that mutation bias can direct evolution when many mutants are present at any one time. We demonstrate that mutation bias can drive long‐term evolutionary trends when the environment is constantly changing. Under biologically realistic conditions, we show that mutation bias can counter strong gradients of environmental selection over time. We conclude that evolutionary trends can be quite independent of the environment, even when they depress population fitness. Finally, we show that entropy can be a powerful source of mutation bias and can drive evolutionary trends. © 2015 Wiley Periodicals, Inc. Complexity 21: 331–345, 2016     

UPLC-MS/MS detection of disaccharides derived from glycosaminoglycans as biomarkers of mucopolysaccharidoses

Mucopolysaccharidoses (MPSs) are a group of disorders resulting from primary defects in lysosomal enzymes involved in the degradation of glycosaminoglycans (GAGs). Depending on the specific enzyme defect, the catabolism of one or more GAGs is blocked leading to accumulation in tissues and biological fluids. GAG measurements are important for high-risk screening, diagnosis, monitoring treatment efficacy, and patient follow up. The dimethylmethylene blue (DMB) spectrophotometric method commonly used in most biochemical genetics laboratories relies on a non-specific total GAG analysis which has led to false positive results, and even false negative results (mainly for MPS III and IV patients). The main objective of our project was to devise and validate a reliable tandem mass spectrometry multiplex analysis for the urine quantitation of four GAGs (dermatan sulfate (DS), heparan sulfate (HS), keratan sulfate (KS), and chondroitin sulfate (CS)) for an eventual technological transfer to the clinic. The developed methodology is rapid (7 min) and our results showed good intraday and interday precision (RSDs ≤ 8.7%) and accuracy (Biases range: −12.0%–18.4%). Linearity was good (r² > 0.995) for DS, HS, CS, and KS calibration curves. In comparison with the DMB spectrophotometric method, this multiplex tandem mass spectrometry method allows GAG fractionation, thus a differentiation of MPS types, except for MPS I and II which are characterized by the same GAG profile. The devised method is a useful and reliable tool for diagnosis of MPS patients, as well as their monitoring and follow up, as shown by longitudinal studies.     

A higher-order large-scale regularity theory for random elliptic operators

We develop a large-scale regularity theory of higher order for divergence-form elliptic equations with heterogeneous coefficient fields a in the context of stochastic homogenization. The large-scale regularity of a-harmonic functions is encoded by Liouville principles: The space of a-harmonic functions that grow at most like a polynomial of degree k has the same dimension as in the constant-coefficient case. This result can be seen as the qualitative side of a large-scale C^k,α-regularity theory, which in the present work is developed in the form of a corresponding C^k,α-“excess decay” estimate: For a given a-harmonic function u on a ball B_R, its energy distance on some ball B_r to the above space of a-harmonic functions that grow at most like a polynomial of degree k has the natural decay in the radius r above some minimal radius r₀.

Though motivated by stochastic homogenization, the contribution of this paper is of purely deterministic nature: We work under the assumption that for the given realization a of the coefficient field, the couple (φ, σ) of scalar and vector potentials of the harmonic coordinates, where φ is the usual corrector, grows sublinearly in a mildly quantified way. We then construct “kth-order correctors” and thereby the space of a-harmonic functions that grow at most like a polynomial of degree k, establish the above excess decay, and then the corresponding Liouville principle.     

Mechanochemically Induced Conversion of Crystalline Benzamide Polymorphs by Seeding

Benzamide has been known for its polymorphism for almost 200 years. Three polymorphic forms are described. To date, it was only possible to crystallize a metastable form in a mixture together with the thermodynamically most stable form I. A complete transformation of form I into the metastable form III by mechanochemical treatment has been achieved. Catalytic amounts of nicotinamide seeds were used to activate the conversion by mechanochemical seeding. NMR experiments indicated that the nicotinamide molecules were incorporated statistically in the crystal lattice of benzamide form III during the conversion. The transformation pathway was evaluated using in situ powder X‐ray diffraction.     

Diminishing blocking interval in particle-conveying channel bundles

We consider a channel bundle consisting of N_c parallel channels conveying a particulate flux. Particles enter these channels according to a homogeneous Poisson process and exit after a fixed transit time, τ. An individual channel blocks if N particles are simultaneously present. When a channel is blocked the flux previously entering it is redistributed evenly over the remaining open channels. We perform event driven simulations to examine the behaviour of an initially empty channel bundle with a total entering flux of intensity Λ. The mean blockage time of the kth channel is denoted by ? t_k ? ,k = 1,...,N_c. For N = 1, as shown previously, the interval between successive blockages is constant, while for N> 1 an accelerating cascade, i.e. one in which the interval between successive blockages decreases, is observed. After an initial transient regime we observe a well-defined universal regime that is characterized by\hbox{$\Delta_k^{(N)} = (-1)^{N-1}\frac{[(N-1)!]^2}{(\Lambda\tau)^N}$}Δk(N)=(?1)N?1[(N?1)!]2(Λτ)Nwhere \hbox{$\Delta_k^{(1)}=\langle t_k \rangle-\langle t_{k-1}\rangle$}Δk(1)=?tk???tk?1? and \hbox{$\Delta_k^{(j)}=\Delta_k^{(j-1)}-\Delta_{k-1}^{(j-1)}$}Δk(j)=Δk(j?1)?Δk?1(j?1) denotes the jth order difference.     

Accurate solubility prediction with error bars for electrolytes: a machine learning approach

Accurate in silico models for predicting aqueous solubility are needed in drug design and discovery and many other areas of chemical research. We present a statistical modeling of aqueous solubility based on measured data, using a Gaussian Process nonlinear regression model (GPsol). We compare our results with those of 14 scientific studies and 6 commercial tools. This shows that the developed model achieves much higher accuracy than available commercial tools for the prediction of solubility of electrolytes. On top of the high accuracy, the proposed machine learning model also provides error bars for each individual prediction.     

Aryl calcium compounds: syntheses, structures, physical properties, and chemical behavior

Organocalcium chemistry is still in its infancy. The direct synthesis of activated calcium and (substituted) iodobenzenes allows for the large-scale and high-yield synthesis of aryl calcium iodides. The influence of the substitution patterns of the phenyl group, halogen atom, and solvent is discussed. Aryl calcium iodides show a Schlenk equilibrium that enables the isolation of diaryl calcium derivatives. Owing to the high reactivity of aryl calcium halides, low temperatures have to be maintained throughout the preparative procedures in order to avoid side reactions. A decrease of reactivity and, hence, an enhanced stability at higher temperatures can be achieved by shielding of the calcium atom by increasing the coordination number of the metal center or by substitution of the iodide anion by bulky groups.