Searching for indole derivatives as potential mushroom tyrosinase inhibitors

Tyrosinase is a copper-containing enzyme widely distributed in nature, involved in the biosynthesis of melanin whose role is to protect the skin from ultraviolet damage. A great interest has been shown on the melanin involvement in malignant melanoma and other carcinogenetic processes. These phenomena have encouraged the research of tyrosinase inhibitors useful in therapeutic field as well as in foods and cosmetics to prevent browning. The idea was to screen our “in house” database to select suitable lead compounds for the discovery of potential drug-inhibiting enzyme. The obtained biological results demonstrated that compounds containing 4-fluorobenzyl moiety at N???1 position of indole system showed the best activity. In addition, the role of the portion linked to the carbonyl group at C???3 was discussed. A Lineweaver–Burk kinetic analysis of the most active indoles, CHI 1043 and derivative 4, showed a mixed-type inhibition in the presence of l-3,4-dihydroxyphenylalanine (l-DOPA) as substrate.     

A delay differential equation model of follicle waves in women

This article presents a mathematical model for hormonal regulation of the menstrual cycle which predicts the occurrence of follicle waves in normally cycling women. Several follicles of ovulatory size that develop sequentially during one menstrual cycle are referred to as follicle waves. The model consists of 13 nonlinear, delay differential equations with 51 parameters. Model simulations exhibit a unique stable periodic cycle and this menstrual cycle accurately approximates blood levels of ovarian and pituitary hormones found in the biological literature. Numerical experiments illustrate that the number of follicle waves corresponds to the number of rises in pituitary follicle stimulating hormone. Modifications of the model equations result in simulations which predict the possibility of two ovulations at different times during the same menstrual cycle and, hence, the occurrence of dizygotic twins via a phenomenon referred to as superfecundation. Sensitive parameters are identified and bifurcations in model behaviour with respect to parameter changes are discussed. Studying follicle waves may be helpful for improving female fertility and for understanding some aspects of female reproductive ageing.     

Mathematical and numerical comparisons of five single-population growth models

We investigate the properties of five mathematical models used to represent the growth of a single population. By imposing a common set of (normalizing) initial conditions, we are able to calculate and explicitly compare the time intervals required to reach specific values of population levels. Based on these results, we conclude that one must be careful when applying these models to interpret the dynamics of single-population growth. An additional implication is that they provide evidence that such caution should also be extended to the incorporation of these models into the formulation of interacting, multi-population models, which are used, for example, to study the spread of disease.     

Flux theory for Poisson distributed pores with Gaussian permeability

The mean of the solute flux through membrane pores depends on the random distribution and permeability of the pores. Mathematical models including such randomness factors make it possible to obtain statistical parameters for pore characterization. Here, assuming that pores follow a Poisson distribution in the lipid phase and that their permeabilities follow a Gaussian distribution, a mathematical model for solute dynamics is obtained by applying a general result from a previous work regarding any number of different kinds of randomly distributed pores.

The new proposed theory is studied using experimental parameters obtained elsewhere, and a method for finding the mean single pore flux rate from liposome flux assays is suggested. This method is useful for pores without requiring studies by patch-clamp in single cells or single-channel recordings. However, it does not apply in the case of ion-selective channels, in which a more complex flux law combining the concentration and electrical gradient is required.     

Image‐derived arterial input function for quantitative fluorescence imaging of receptor‐drug binding in vivo

Receptor concentration imaging (RCI) with targeted‐untargeted optical dye pairs has enabled in vivo immunohistochemistry analysis in preclinical subcutaneous tumors. Successful application of RCI to fluorescence guided resection (FGR), so that quantitative molecular imaging of tumor‐specific receptors could be performed in situ, would have a high impact. However, assumptions of pharmacokinetics, permeability and retention, as well as the lack of a suitable reference region limit the potential for RCI in human neurosurgery. In this study, an arterial input graphic analysis (AIGA) method is presented which is enabled by independent component analysis (ICA). The percent difference in arterial concentration between the image‐derived arterial input function (AIF_ICA) and that obtained by an invasive method (ICA_CAR) was 2.0 ± 2.7% during the first hour of circulation of a targeted‐untargeted dye pair in mice. Estimates of distribution volume and receptor concentration in tumor bearing mice (n = 5) recovered using the AIGA technique did not differ significantly from values obtained using invasive AIF measurements (p = 0.12). The AIGA method, enabled by the subject‐specific AIF_ICA, was also applied in a rat orthotopic model of U‐251 glioblastoma to obtain the first reported receptor concentration and distribution volume maps during open craniotomy.

     

Modern termites inherited the potential of collective construction from their common ancestor

Animal collective behaviors give rise to various spatial patterns, such as the nests of social insects. These structures are built by individuals following a simple set of rules, slightly varying within and among species, to produce a large diversity of shapes. However, little is known about the origin and evolution of the behavioral mechanisms regulating nest structures. In this study, we discuss the perspective of inferring the evolution of collective behaviors behind pattern formations using a phylogenetic framework. We review the collective behaviors that can be described by a single set of behavioral rules, and for which variations of the environmental and behavioral parameter values produce diverse patterns. We propose that this mechanism could be at the origin of the pattern diversity observed among related species, and that, when they are placed in the proper conditions, species have the behavioral potential to form patterns observed in related species. The comparative analysis of shelter tube construction by lower termites is consistent with this hypothesis. Although the use of shelter tubes in natural conditions is variable among species, most modern species have the potential to build them, suggesting that the behavioral rules for shelter tube construction evolved once in the common ancestor of modern termites. Our study emphasizes that comparative studies of behavioral rules have the potential to shed light on the evolution of collective behaviors.     

QUANTITATIVE GENETIC MODELING AND INFERENCE IN THE PRESENCE OF NONIGNORABLE MISSING DATA

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.     

The origin of life: what we know,what we can know and what we will never know

The origin of life (OOL) problem remains one of the more challenging scientific questions of all time. In this essay, we propose that following recent experimental and theoretical advances in systems chemistry, the underlying principle governing the emergence of life on the Earth can in its broadest sense be specified, and may be stated as follows: all stable (persistent) replicating systems will tend to evolve over time towards systems of greater stability. The stability kind referred to, however, is dynamic kinetic stability, and quite distinct from the traditional thermodynamic stability which conventionally dominates physical and chemical thinking. Significantly, that stability kind is generally found to be enhanced by increasing complexification, since added features in the replicating system that improve replication efficiency will be reproduced, thereby offering an explanation for the emergence of life''s extraordinary complexity. On the basis of that simple principle, a fundamental reassessment of the underlying chemistry–biology relationship is possible, one with broad ramifications. In the context of the OOL question, this novel perspective can assist in clarifying central ahistoric aspects of abiogenesis, as opposed to the many historic aspects that have probably been forever lost in the mists of time.