PET Molecular Imaging of Hypoxia in Ischemic Stroke: An Update.

Hypoxia, a condition of insufficient oxygen availability to support metabolism, occurs when the vascular supply is interrupted, as in stroke. The identification of the hypoxic and viable tissue in stroke as compared with irreversible lesions (necrosis) has relevant implications for the treatment of ischemic stroke. Traditionally, imaging by positron emission tomography (PET), using 15O-based radiotracers, allowed the measurement of perfusion and oxygen extraction in stroke, providing important insights in its pathophysiology. However, these multitracer evaluations are of limited applicability in clinical settings. More recently, specific tracers have been developed, which accumulate with an inverse relationship to oxygen concentration and thus allow visualizing the hypoxic tissue non invasively. These belong to two main groups: nitroimidazoles, and among these the 18F-Fluoroimidazole (18F-FMISO) is the most widely used, and the copper-based tracers, represented mainly by Cu-ATSM. While these tracers have been at first developed and tested in order to image hypoxia in tumors, they have also shown promising results in stroke models and preliminary clinical studies in patients with cardiovascular disorders, allowing the detection of hypoxic tissue and the prediction of the extent of subsequent ischemia and clinical outcome. These tracers have therefore the potential to select an appropriate subgroup of patients who could benefit from a hypoxia-directed treatment and provide prognosis relevant imaging. The molecular imaging of hypoxia made important progress over the last decade and has a potential for integration into the diagnostic and therapeutic workup of patients with ischemic stroke.

Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.

Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

Peroxisome proliferator-activated receptor structures: ligand specificity, molecular switch and interactions with regulators.

Peroxisome proliferator-activated receptors (PPARs) compose a family of nuclear receptors that mediate the effects of lipidic ligands at the transcriptional level. In this review, we highlight advances in the understanding of the PPAR ligand binding domain (LBD) structure at the atomic level. The overall structure of PPARs LBD is described, and important protein ligand interactions are presented. Structure-activity relationships between isotypes structures and ligand specificity are addressed. It is shown that the numerous experimental three-dimensional structures available, together with in silico simulations, help understanding the role played by the activating function-2 (AF-2) in PPARs activation and its underlying molecular mechanism. The relation between the PPARs constitutive activity and the intrinsic stability of the active conformation is discussed. Finally, the interactions of PPARs LBD with co-activators or co-repressors, as well as with the retinoid X receptor (RXR) are described and considered in relation to PPARs activation.

Stem cell transplantation in brain tumors: a new field for molecular imaging?

Neural stem cells have been proposed as a new and promising treatment modality in various pathologies of the central nervous system, including malignant brain tumors. However, the underlying mechanism by which neural stem cells target tumor areas remains elusive. Monitoring of these cells is currently done by use of various modes of molecular imaging, such as optical imaging, magnetic resonance imaging and positron emission tomography, which is a novel technology for visualizing metabolism and signal transduction to gene expression. In this new context, the microenvironment of (malignant) brain tumors and the blood-brain barrier gains increased interest. The authors of this review give a unique overview of the current molecular-imaging techniques used in different therapeutic experimental brain tumor models in relation to neural stem cells. Such methods for molecular imaging of gene-engineered neural stem/progenitor cells are currently used to trace the location and temporal level of expression of therapeutic and endogenous genes in malignant brain tumors, closing the gap between in vitro and in vivo integrative biology of disease in neural stem cell transplantation.