Parameter set for computer-assisted texture analysis of fetal brain

Background

Magnetic resonance data were collected from a diverse population of gravid women to objectively compare the quality of 1.5-tesla (1.5 T) versus 3-T magnetic resonance imaging of the developing human brain. MaZda and B11 computational-visual cognition tools were used to process 2D images. We proposed a wavelet-based parameter and two novel histogram-based parameters for Fisher texture analysis in three-dimensional space.

Results

Wavenhl, focus index, and dispersion index revealed better quality for 3 T. Though both 1.5 and 3 T images were 16-bit DICOM encoded, nearly 16 and 12 usable bits were measured in 3 and 1.5 T images, respectively. The four-bit padding observed in 1.5 T K-space encoding mimics noise by adding illusionistic details, which are not really part of the image. In contrast, zero-bit padding in 3 T provides space for storing more details and increases the likelihood of noise but as well as edges, which in turn are very crucial for differentiation of closely related anatomical structures.

Conclusions

Both encoding modes are possible with both units, but higher 3 T resolution is the main difference. It contributes to higher perceived and available dynamic range. Apart from surprisingly larger Fisher coefficient, no significant difference was observed when testing was conducted with down-converted 8-bit BMP images.

     

Natural products from marine invertebrates against <Emphasis Type="Italic">Leishmania</Emphasis> parasites: a comprehensive review

Parasitic infections by Leishmania parasites remains a severe public health problem, especially in developing countries where it is highly endemic. Chemotherapy still remains a first option for the treatment of those diseases, despite the fact that available drugs exhibit a variety of shortcomings. Thus, innovative, less toxic more affordable and effective antileishmanial agents are urgently needed. The marine environment holds an immeasurable bio- and chemical diversity, being a valuable source of natural products with therapeutic potential. As invertebrates comprise about 60 % of all marine organisms, bioprospecting this class of organisms for antileishmanial properties may unravel unique and selective hit molecules. In this context, this review covers results on the literature of marine invertebrate extracts and pure compounds evaluated against Leishmania parasites mainly by in vitro methods. It comprises results obtained from the phyla Porifera, Cnidaria, Bryozoa (Ectoprota), Mollusca, Echinodermata, Annelida, Cetnophora, Platyhelminthes, sub phyla Crustacea (phylum Arthropoda) and Tunicata (phylum Chordata). Moreover, structure–activity relationships and possible mechanisms of action are mentioned, whenever available information is provided. About 70 species of marine invertebrates belonging to seven different phyla are included in this work. Besides a variety of crude extracts, a total of 140 pure compounds was tested against different Leishmania species. Although the research on the antileishmanial potential of marine invertebrates is in its early beginnings, promising results have been achieved that encourage further research. As more extracts and compounds are being screened, the possibility of finding active and selective antileishmanial molecules increases, rising new hope in the search for new treatments against leishmaniases.     

Non-monotonic Response to Monotonic Stimulus: Regulation of Glyoxylate Shunt Gene-Expression Dynamics in Mycobacterium tuberculosis

Understanding how dynamical responses of biological networks are constrained by underlying network topology is one of the fundamental goals of systems biology. Here we employ monotone systems theory to formulate a theorem stating necessary conditions for non-monotonic time-response of a biochemical network to a monotonic stimulus. We apply this theorem to analyze the non-monotonic dynamics of the σ^B-regulated glyoxylate shunt gene expression in Mycobacterium tuberculosis cells exposed to hypoxia. We first demonstrate that the known network structure is inconsistent with observed dynamics. To resolve this inconsistency we employ the formulated theorem, modeling simulations and optimization along with follow-up dynamic experimental measurements. We show a requirement for post-translational modulation of σ^B activity in order to reconcile the network dynamics with its topology. The results of this analysis make testable experimental predictions and demonstrate wider applicability of the developed methodology to a wide class of biological systems.     

Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI

Functional magnetic resonance imaging (fMRI) measures brain activity by detecting the blood-oxygen-level dependent (BOLD) response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new, independent validation data. These results open the door to a new type of fMRI analysis that more accurately reflects the true neuronal activity.