Screening of Variables Influencing the Clavulanic Acid Production by Streptomyces DAUFPE 3060 Strain

Clavulanic acid (CA) is a beta-lactam antibiotic, which has a potent beta-lactamase inhibiting activity. The influence of five variables, namely pH (6.0, 6.4, and 6.8), temperature (28A degrees C, 30A degrees C, and 32A degrees C), agitation intensity (150, 200, and 250 rpm), glycerol concentration (5.0, 7.5, and 10 g/L) and soybean flour concentration (5.0, 12.5, and 20 g/L), on CA production by a new isolate of Streptomyces (DAUFPE 3060) was investigated in 250-mL Erlenmeyer flasks using a fractional factorial design. Temperature and soybean flour concentration were shown to be the two variables that exerted the most important effects on the production of CA at 95% confidence level. The highest CA concentration (494 mg/L) was obtained after 48 h at 150 rpm, 32A degrees C, pH 6.0, 5.0 g/L glycerol, and 20 g/L soybean flour concentrations. Under these conditions, the yields of biomass and product on consumed substrate were 0.26 g(X)/g(S) and 64.3 mg(P)/g(S), respectively. Fermentations performed in 3.0-L bench-scale fermenter allowed increasing the CA production by about 60%.

Effect of brain-derived neurotrophic factor Val66Met polymorphism and serum levels on the progression of mild cognitive impairment

Objectives. Abnormalities in neurotrophic systems have been reported in Alzheimer`s disease (AD), as shown by decreased serum brain-derived neurotrophic factor (BDNF) levels and association with BDNF genetic polymorphisms. In this study, we investigate whether these findings can be detected in patients with mild cognitive impairment (MCI), which is recognized as a high risk condition for AD. We also address the impact of these variables on the progression of cognitive deficits within the MCI-AD continuum. Methods. One hundred and sixty older adults with varying degrees of cognitive impairment (30 patients with AD, 71 with MCI, and 59 healthy controls) were longitudinally assessed for up to 60 months. Baseline serum BDNF levels were determined by sandwich ELISA, and the presence of polymorphisms of BDNF and apolipoprotein E (Val66Met and APOE*E4, respectively) was determined by allelic discrimination analysis on real time PCR. Modifications of cognitive state were ascertained for non-demented subjects. Results. Mean serum BDNF levels were reduced in patients with MCI and AD, as compared to controls (509.2 +/- 210.5; 581.9 +/- 379.4; and 777.5 +/- 467.8 pg/l respectively; P < 0.001). Baseline serum BDNF levels were not associated with the progression of cognitive impairment upon follow-up in patients with MCI (progressive MCI, 750.8 +/- 463.0; stable MCI, 724.0 +/- 343.4; P = 0.8), nor with the conversion to AD. Although Val66Met polymorphisms were not associated with the cross-sectional diagnoses of MCI or AD, the presence of Met-BDNF allele was associated with a higher risk of disease-progression in patients with MCI (OR = 3.0 CI(95%) [1.2-7.8], P = 0.02). We also found a significant interaction between the APOE*E4 and Met-BDNF allele increasing the risk of progression of cognitive impairment in MCI patients (OR = 4.4 CI(95%) [1.6-12.1], P = 0.004). Conclusion. Decreased neurotrophic support, as indicated by a reduced systemic availability of BDNF, may play role in the neurodegenerative processes that underlie the continuum from MCI to AD. The presence of Met-BDNF allele, particularly in association with APOE*E4, may predict a worse cognitive outcome in patients with MCI.

Semiclassical evolution of dissipative Markovian systems

A semiclassical approximation for an evolving density operator, driven by a `closed` Hamiltonian operator and `open` Markovian Lindblad operators, is obtained. The theory is based on the chord function, i.e. the Fourier transform of the Wigner function. It reduces to an exact solution of the Lindblad master equation if the Hamiltonian operator is a quadratic function and the Lindblad operators are linear functions of positions and momenta. Initially, the semiclassical formulae for the case of Hermitian Lindblad operators are reinterpreted in terms of a (real) double phase space, generated by an appropriate classical double Hamiltonian. An extra `open` term is added to the double Hamiltonian by the non-Hermitian part of the Lindblad operators in the general case of dissipative Markovian evolution. The particular case of generic Hamiltonian operators, but linear dissipative Lindblad operators, is studied in more detail. A Liouville-type equivariance still holds for the corresponding classical evolution in double phase space, but the centre subspace, which supports the Wigner function, is compressed, along with expansion of its conjugate subspace, which supports the chord function. Decoherence narrows the relevant region of double phase space to the neighbourhood of a caustic for both the Wigner function and the chord function. This difficulty is avoided by a propagator in a mixed representation, so that a further `small-chord` approximation leads to a simple generalization of the quadratic theory for evolving Wigner functions.

A new family of generalized distributions

Kumaraswamy [Generalized probability density-function for double-bounded random-processes, J. Hydrol. 462 (1980), pp. 79-88] introduced a distribution for double-bounded random processes with hydrological applications. For the first time, based on this distribution, we describe a new family of generalized distributions (denoted with the prefix `Kw`) to extend the normal, Weibull, gamma, Gumbel, inverse Gaussian distributions, among several well-known distributions. Some special distributions in the new family such as the Kw-normal, Kw-Weibull, Kw-gamma, Kw-Gumbel and Kw-inverse Gaussian distribution are discussed. We express the ordinary moments of any Kw generalized distribution as linear functions of probability weighted moments (PWMs) of the parent distribution. We also obtain the ordinary moments of order statistics as functions of PWMs of the baseline distribution. We use the method of maximum likelihood to fit the distributions in the new class and illustrate the potentiality of the new model with an application to real data.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.