Use of the KlADH4 promoter for ethanol-dependent production of recombinant human serum albumine in Kluyveromyces lactis

KlADH4 is a gene of Kluyveromyces lactis encoding a mitochondrial alcohol dehydrogenase activity which is specifically induced by ethanol. The promoter of this gene was used for the expression of heterologous proteins in K. lactis, a very promising organism which can be used as an alternative host to Saccharomyces cerevisiae due to its good secretory properties. In this paper we report the ethanol-driven expression in K. lactis of the bacterial beta-glucuronidase and of the human serum albumin (HSA) genes under the control of the KlADH4 promoter. In particular, we studied the extracellular production of recombinant HSA (rHSA) with integrative and replicative vectors and obtained a significant increase in the amount of the protein with multicopy vectors, showing that no limitation of KlADH4 trans-acting factors occurred in the cells. By deletion analysis of the promoter, we identified an element (UASE) which is sufficient for the induction of KlADH4 by ethanol and, when inserted in the respective promoters, allows ethanol-dependent activation of other yeast genes, such as PGK and LAC4. We also analyzed the effect of medium composition on cell growth and protein secretion. A clear improvement in the production of the recombinant protein was achieved by shifting from batch cultures (0.3 g/liter) to fed-batch cultures (1 g/liter) with ethanol as the preferred carbon source

Quantum Pattern Retrieval by Qubit Networks with Hebb Interactions

Qubit networks with long-range interactions inspired by the Hebb rule can be used as quantum associative memories. Starting from a uniform superposition, the unitary evolution generated by these interactions drives the network through a quantum phase transition at a critical computation time, after which ferromagnetic order guarantees that a measurement retrieves the stored memory. The maximum memory capacity p of these qubit networks is reached at a memory density p/n=1.Comment: To appear in Physical Review Letter

Minimal Models for a Superconductor-Insulator Conformal Quantum Phase Transition

Conformal field theories do not only classify 2D classical critical behavior but they also govern a certain class of 2D quantum critical behavior. In this latter case it is the ground state wave functional of the quantum theory that is conformally invariant, rather than the classical action. We show that the superconducting-insulating (SI) quantum phase transition in 2D Josephson junction arrays (JJAs) is a (doubled) $c=1$ Gaussian conformal quantum critical point. The quantum action describing this system is a doubled Maxwell-Chern-Simons model in the strong coupling limit. We also argue that the SI quantum transitions in frustrated JJAs realize the other possible universality classes of conformal quantum critical behavior, corresponding to the unitary minimal models at central charge $c=1-6/m(m+1)$.Comment: 4 pages, no figure

Scaling properties of growing noninfinitesimal perturbations in space-time chaos

We study the spatiotemporal dynamics of random spatially distributed noninfinitesimal perturbations in one-dimensional chaotic extended systems. We find that an initial perturbation of finite size $\epsilon_0$ grows in time obeying the tangent space dynamic equations (Lyapunov vectors) up to a characteristic time $t_{\times}(\epsilon_0) \sim b - (1/\lambda_{max}) \ln (\epsilon_0)$, where $\lambda_{max}$ is the largest Lyapunov exponent and $b$ is a constant. For times $t < t_{\times}$ perturbations exhibit spatial correlations up to a typical distance $\xi \sim t^z$. For times larger than $t_{\times}$ finite perturbations are no longer described by tangent space equations, memory of spatial correlations is progressively destroyed and perturbations become spatiotemporal white noise. We are able to explain these results by mapping the problem to the Kardar-Parisi-Zhang universality class of surface growth.Comment: 4.5 pages LaTeX (RevTeX4) format, 3 eps figs included. Submitted to Phys Rev

Improved feed protein fractionation schemes for formulating rations with the Cornell Net Carbohydrate and Protein System

Adequate predictions of rumen-degradable protein (RDP) and rumen-undegradable protein (RUP) supplies are necessary to optimize performance while minimizing losses of excess nitrogen (N). The objectives of this study were to evaluate the original Cornell Net Carbohydrate Protein System (CNCPS) protein fractionation scheme and to develop and evaluate alternatives designed to improve its adequacy in predicting RDP and RUP. The CNCPS version 5 fractionates CP into 5 fractions based on solubility in protein precipitant agents, buffers, and detergent solutions: A represents the soluble nonprotein N, B1 is the soluble true protein, B2 represents protein with intermediate rates of degradation, B3 is the CP insoluble in neutral detergent solution but soluble in acid detergent solution, and C is the unavailable N. Model predictions were evaluated with studies that measured N flow data at the omasum. The N fractionation scheme in version 5 of the CNCPS explained 78% of the variation in RDP with a root mean square prediction error (RMSPE) of 275 g/d, and 51% of the RUP variation with RMSPE of 248 g/d. Neutral detergent insoluble CP flows were overpredicted with a mean bias of 128 g/d (40% of the observed mean). The greatest improvements in the accuracy of RDP and RUP predictions were obtained with the following 2 alternative schemes. Alternative 1 used the inhibitory in vitro system to measure the fractional rate of degradation for the insoluble protein fraction in which A = nonprotein N, B1 = true soluble protein, B2 = insoluble protein, C = unavailable protein (RDP: R(2) = 0.84 and RMSPE = 167 g/d; RUP: R(2) = 0.61 and RMSPE = 209 g/d), whereas alternative 2 redefined A and B1 fractions as the non-amino-N and amino-N in the soluble fraction respectively (RDP: R(2) = 0.79 with RMSPE = 195 g/d and RUP: R(2) = 0.54 with RMSPE = 225 g/d). We concluded that implementing alternative 1 or 2 will improve the accuracy of predicting RDP and RUP within the CNCPS framework

State estimation in quantum homodyne tomography with noisy data

In the framework of noisy quantum homodyne tomography with efficiency parameter $0 < \eta \leq 1$, we propose two estimators of a quantum state whose density matrix elements $\rho_{m,n}$ decrease like $e^{-B(m+n)^{r/ 2}}$, for fixed known $B>0$ and $0<r\leq 2$. The first procedure estimates the matrix coefficients by a projection method on the pattern functions (that we introduce here for $0<\eta \leq 1/2$), the second procedure is a kernel estimator of the associated Wigner function. We compute the convergence rates of these estimators, in $\mathbb{L}_2$ risk

Comparison of precipitated calcium carbonate/polylactic acid and halloysite/polylactic acid nanocomposites

PLA nanocomposites with stearate coated precipitated calcium carbonate (PCC) and halloysite natural nanotubes (HNT) were prepared by melt extrusion. The crystallization behavior, mechanical properties, thermal dynamical mechanical analysis (DMTA), and the morphology of the PCC/PLA, HNT/PLA, and HNT/PCC/PLA composites were discussed. Compared to halloysite nanotubes, PCC nanoparticles showed a better nucleating effect, which decreased both the glass transition and cold crystallization temperatures. The tensile performance of PLA composites showed that the addition of inorganic nanofillers increased Young’s modulus but decreased tensile strength. More interestingly, PLA composites with PCC particles exhibited an effectively increased elongation at break with respect to pure PLA, while HNT/PLA showed a decreased ultimate deformation of composites. DMTA results indicated that PLA composites had a similar storage modulus at temperatures below the glass transition and the addition of nanofillers into PLA caused to shift to lower temperatures by about 3°C. The morphological analysis of fractures surface of PLA nanocomposites showed good dispersion of nanofillers, formation of microvoids, and larger plastic deformation of the PLA matrix when the PCC particles were added, while a strong aggregation was noticed in composites with HNT nanofillers, which has been attributed to a nonoptimal surface coating