The simulation studies of the interplay of peptides with lipids

Dit proefschrift richt zich op de wisselwerking tussen twee klassen van membraan actieve peptiden en membranen, namelijk de antimicrobiële peptiden Magainin 2, BP100, MSI-78 en MSI-103 en de amfipathische peptide Pex11-Amph, met behulp van moleculaire dynamica (MD) simulaties. Begrip van het samenspel tussen peptiden en membraan lipiden is belangrijk om fundamenteel inzicht te verkrijgen in vele biologische processen

Localization Preference of Antimicrobial Peptides on Liquid-Disordered Membrane Domains

We performed coarse-grained simulations of the antimicrobial peptides Magainin-2, BP100, MSI-103, and MSI-78 on a phase-separated membrane to study their preference for the different domains. All the peptides displayed a clear preference for the liquid-disordered (Ld) phase over the liquid-ordered (Lo) one. For BP100, MSI-103, and MSI-78 there was a further preference of the peptides for the domain interface. The peptides' preference toward the disordered phase was shown to reflect a penalization of lipid-lipid interaction enthalpy in the Lo phase, when in the vicinity of peptides. Similar results were observed at the two studied concentrations, although Ld phase saturation at the higher concentration drove some of the peptide excess to the Lo phase. Magainin-2 and MSI-103 were found to dimerize, in agreement with available experimental data. Interestingly, at high concentrations of Magainin-2 toroidal pores spontaneously formed in the Ld phase. We performed additional simulations to characterize this phenomenon, which is likely related to Magainin-2's membranolytic action

Sparse Estimation of Cox Proportional Hazards Models via Approximated Information Criteria

We propose a new sparse estimation method for Cox (1972) proportional hazards models by optimizing an approximated information criterion. The main idea involves approximation of the inline image norm with a continuous or smooth unit dent function. The proposed method bridges the best subset selection and regularization by borrowing strength from both. It mimics the best subset selection using a penalized likelihood approach yet with no need of a tuning parameter. We further reformulate the problem with a reparameterization step so that it reduces to one unconstrained nonconvex yet smooth programming problem, which can be solved efficiently as in computing the maximum partial likelihood estimator (MPLE). Furthermore, the reparameterization tactic yields an additional advantage in terms of circumventing postselection inference. The oracle property of the proposed method is established. Both simulated experiments and empirical examples are provided for assessment and illustration

Solvent-Free Plasticity and Programmable Mechanical Behaviors of Engineered Proteins

Biopolymeric networks with plasticity show great competences in diverse fields owing to the combined biocompatible and mechanical characteristics. However, to realize such plasticity external complicated treatments, e.g., UV or organic solvent have to be applied, which in turn impair the biological nature and even mechanical properties of those systems. To address this challenge, one new type of anhydrous protein liquid crystalline (LC) gels, which exhibit flexible morphological plasticity and mechanical programmability is demonstrated. Supramolecular interactions in the smectic biogels play an important role for their high plasticity. Remarkably, the samples exhibit outstanding mechanical behaviors. The tensile strength and Young's modulus at MPa levels are comparable or even higher than chemically cross-linked hydrogels and LC elastomers. More importantly, mechanical programmability of the LC gels is achieved by genetically tuning the charge density of protein backbones. Consequently, the mechanical performance is manipulated in the range of one order of magnitude. Thus, this type of anhydrous protein LC gels offers great opportunities for load-bearing high-tech applications

A fast responsive chromogenic and near-infrared fluorescence lighting-up probe for visual detection of toxic thiophenol in environmental water and living cells

Thiophenols as high toxic environmental pollutants are poisonous for animals and aquatic organisms. Therefore, it is indispensable to monitor thiophenols in the environment. Herein, a novel near-infrared fluorescent probe was developed for the detection of thiophenols, which was easily prepared by one-step coupling of 2,4-dini trobenzenesulfonyl chloride with Nile blue. The probe showed a significant near infrared (∼675 nm) fluores cence “turn-on” response to thiophenols with some good features including chromogenic reaction, high sensi tivity and selectivity, fast response, near-infrared emission along with low detection limit (1.8 nM). The probe was employed to rapidly and visually determine thiophenols in several industrial wastewaters with good re coveries (90–110%). Moreover, this probe has been demonstrated good capability for imaging thiophenol in HeLa cellsinfo:eu-repo/semantics/publishedVersio

Constructing Multivariate Survival Trees: The MST Package for R

Multivariate survival trees require few statistical assumptions, are easy to interpret, and provide meaningful diagnosis and prediction rules. Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection. These are useful features in many application fields and are often required in the current era of big data. The aim of this article is to introduce the R package MST. This package constructs multivariate survival trees using marginal model and frailty model based approaches. It allows the user to control and see how the trees are constructed. The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models

Rheological properties and structural features of coconut milk emulsions stabilized with maize kernels and starch

peer-reviewedIn this study, maize kernels and starch with different amylose contents at the same concentration were added to coconut milk. The nonionic composite surfactants were used to prepare various types of coconut milk beverages with optimal stability, and their fluid properties were studied. The steady and dynamic rheological property tests show that the loss modulus (G″) of coconut milk is larger than the storage modulus (G′), which is suitable for the pseudoplastic fluid model and has a shear thinning effect. As the droplet size of the coconut milk fluid changed by the addition of maize kernels and starch, the color intensity, ζ-potential, interfacial tension and stability of the sample significantly improved. The addition of the maize kernels significantly reduced the size of the droplets (p < 0.05). The potential values of zeta (ζ) and the surface tension of the coconut milk increased. Based on the differential scanning calorimetry (DSC) measurement, the addition of maize kernels leads to an increase in the transition temperature, especially in samples with a high amylose content. The higher transition temperature can be attributed to the formation of some starches and lipids and the partial denaturation of proteins in coconut milk, but phase separation occurs. These results may be helpful for determining the properties of maize kernels in food-containing emulsions (such as sauces, condiments, and beverages) that achieve the goal of physical stability