Reversible luminescence thermochromism in dipotassiumsodium tris[dicyanoargentate(I)] and the role of structural phase transitions

As a function of temperature, the layered compound K2Na[Ag(CN)213 displays dramatic variations in luminescence thermochromism with major trend changes occurring around 80 K. In order to understand these interesting optical properties, high-resolution neutron diffraction investigations were performed on a polycrystalline sample of this material in the temperature range from 1.5 to 300 K, and previous synchrotron X-ray data of Larochelle et al. (Solid State Commun. 114, 155 (2000)) were reinterpreted. The corresponding significant structural changes were found to be continuous with an anomalous increase of the monoclinic c-lattice parameter with decreasing temperature, associated with slight reorientations of two inequivalent, approximately linear N-C-Ag-C-N units. In the whole temperature range, the crystal structure is monoclinic with the space group C2/m. Based on the structural results, the major luminescence thermochromism changes around 80 K are attributed to the dominance of a back energy transfer process from low- to high-energy excitons at high temperatures. (E) 2002 Elsevier Science (USA).

Portugal making a difference with children and families: the GADIF model

Portugal is a culture grounded in strong traditions and family. Yet, social changes like women returning to the workforce and a decreas ed national birth rate are impacting the traditional family structure and care giving environments of children. Female employment has been increasing steadily in P ortugal over the last three decades (Galego & Pereira, 2006) and the total fert ility rate decreasing from 4.1 to 2.8 (INE, 2006). Furthermore, extended family me mbers, like grandparents, no longer reside close by to their children and grandc hildren as in the past, because of a changing labor market. Many of the younger gen eration are leaving their rural communities to flock to urban areas because o f job opportunities, leaving behind older relatives who would have otherwise par ticipated in the daily care of children. Given these social and economic changes, children are spending more time in out-of-home care with non-familial caregive rs. Yet, government regulations and guidelines in early care and educat ion (ECCE) and early intervention (EI) are only just emerging; it contin ues to be a work in progress.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Optical properties of zirconium oxynitride films: the effect of composition, electronic and crystalline structures

tThis work is devoted to the investigation of zirconium oxynitride (ZrOxNy) films with varied opticalresponses prompted by the variations in their compositional and structural properties. The films wereprepared by dc reactive magnetron sputtering of Zr, using Ar and a reactive gas mixture of N2+ O2(17:3).The colour of the films changed from metallic-like, very bright yellow-pale and golden yellow, for low gasflows to red-brownish for intermediate gas flows. Associated to this colour change there was a significantdecrease of brightness. With further increase of the reactive gas flow, the colour of the samples changedfrom red-brownish to dark blue or even to interference colourations. The variations in composition dis-closed the existence of four different zones, which were found to be closely related with the variationsin the crystalline structure. XRD analysis revealed the change from a B1 NaCl face-centred cubic zirco-nium nitride-type phase for films prepared with low reactive gas flows, towards a poorly crystallizedover-stoichiometric nitride phase, which may be similar to that of Zr3N4with some probable oxygeninclusions within nitrogen positions, for films prepared with intermediate reactive gas flows. For highreactive gas flows, the films developed an oxynitride-type phase, similar to that of -Zr2ON2with someoxygen atoms occupying some of the nitrogen positions, evolving to a ZrO2monoclinic type structurewithin the zone where films were prepared with relatively high reactive gas flows. The analysis carriedout by reflected electron energy loss spectroscopy (REELS) revealed a continuous depopulation of thed-band and an opening of an energy gap between the valence band (2p) and the Fermi level close to 5 eV.The ZrN-based coatings (zone I and II) presented intrinsic colourations, with a decrease in brightness anda colour change from bright yellow to golden yellow, red brownish and dark blue. Associated to thesechanges, there was also a shift of the reflectivity minimum to lower energies, with the increase of thenon-metallic content. The samples lying in the two last zones (zone III, oxynitride and zone IV, oxide films)revealed a typical semi-transparent-optical behaviour showing interference-like colourations only dueto the complete depopulation of the d band at the Fermi level. The samples lying in these zones presentedalso an increase of the optical bandgap from 2 to 3.6 eV.

The effect of siesta in parameters of cardiac structure and in interpretation of ambulatory arterial blood pressure monitoring

OBJECTIVE: To evaluate the influence of the siesta in ambulatory blood pressure (BP) monitoring and in cardiac structure parameters. METHODS: 1940 ambulatory arterial blood pressure monitoring tests were analyzed (Spacelabs 90207, 15/15 minutes from 7:00 to 22:00 hours and 20/20 minutes from 22:01 to 6.59hours) and 21% of the records indicated that the person had taken a siesta (263 woman, 52±14 years). The average duration of the siesta was 118±58 minutes. RESULTS: (average ± standard deviation) The average of systolic/diastolic pressures during wakefulness, including the napping period, was less than the average for the period not including the siesta (138±16/85±11 vs 139±16/86±11 mmHg, p<0.05); 2) pressure loads during wakefulness including the siesta, were less than those observed without the siesta); 3) the averages of nocturnal sleep blood pressures were similar to those of the siesta, 4) nocturnal sleep pressure drops were similar to those in the siesta including wakefulness with and without the siesta; 5) the averages of BP in men were higher (p<0.05) during wakefulness with and without the siesta, during the siesta and nocturnal sleep in relation to the average obtained in women; 6) patients with a reduction of 0- 5% during the siesta had thickening of the interventricular septum and a larger posterior wall than those with a reduction during the siesta >5%. CONCLUSION: The siesta influenced the heart structure parameters and from a statistical point of view the average of systolic and diastolic pressures and the respective pressure loads of the wakeful period.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

Dinámica y cinética de los procesos físicos y químicos del radical OH con compuestos orgánicos volátiles (COVs) de relevancia atmosférica. Dynamics and kinetics of the physical and chemical processes of OH radicals with atmospheric relevant volatile organic compounds (VOCs)

El objetivo del presente proyecto es estudiar los procesos físicos y químicos del radical OH con compuestos orgánicos volátiles (COVs), con los cuales sea factible la formación de agregados de van der Waals (vdW) responsables de la curvatura en los gráficos de Arrhenius, empleando técnicas modernas, complementarias entre si y novedosas en el país. El problema será abordado desde tres perspectivas complementarias: 1) estudios cinéticos, 2) estudios mecanísticos y de distribución de productos y 3) estudios de la dinámica de los procesos físicos y químicos. La finalidad es alcanzar una mejor comprensión de los mecanismos que intervienen en el comportamiento químico de especies presentes en la atmósfera y obtener datos cinéticos de alta calidad que puedan alimentar modelos computacionales capaces de describir la composición de la atmósfera, presente y futura. Los objetivos son estudiar: 1) mediante fotólisis láser pulsada con detección por fluorescencia inducida por láser (PLP-LIF), en reactores de flujo, la cinética de reacción del radical OH(v”=0) con COVs que presentan gráficos de Arrhenius curvos con energías de activación negativas, tales como alcoholes insaturados, alquenos halogenados, éteres halogenados, ésteres alifáticos; 2) en una cámara de simulación de condiciones atmosféricas de gran volumen (4500 L), la identidad y el rendimiento de productos de las reacciones mencionadas, a fines de evaluar su impacto atmosférico y dilucidar los mecanismos de reacción; 3) mediante haces moleculares y espectroscopía láser, la estructura y reactividad de complejos de vdW entre alcoholes insaturados o aromáticos (cresoles) y el radical OH, como modelo de los aductos propuestos como responsables de la desviación al comportamiento de Arrhenius de las reacciones mencionadas; 4) mediante PLP-LIF y expansiones supersónicas, las constantes específicas estado a estado (ksts) de relajación/reacción del radical OH(v”=1-4) vibracionalmente excitado con los COVs mencionados. Los resultados experimentales obtenidos serán contrastados con cálculos ab-initio de estructura electrónica, los cuales apoyarán las interpretaciones, permitirán proponer estructuras de estados de transición y aductos colisionales, como así también calcular las frecuencias de vibración de los complejos de vdW para su posterior asignación en los espectros LIF y REMPI. Asimismo, los mecanismos de reacción propuestos y los parámetros cinéticos medidos experimentalmente serán comparados con aquellos obtenidos por cálculos teóricos. The aim of this project is to study the physical and chemical processes of OH radicals with volatile organic compounds (VOCs) with which the formation of van der Waals (vdW) clusters, responsible for the observed curvature in the Arrhenius plots, might be feasible. The problem will be addressed as follow : 1) kinetic studies; 2) products distribution and mechanistic studies and 3) dynamical studies of the physical and chemical processes. The purpose is to obtain a better understanding of the mechanisms that govern the chemical behavior of species present in the atmosphere and to obtain high quality kinetic data to be used as input to computational models. We will study: 1) the reaction kinetics of OH (v”=0) radicals with VOCs such as unsaturated alcohols, halogenated alkenes, halogenated ethers, aliphatic esters, which show curved Arrhenius plots and negative activation energies, by PLP-LIF, in flow systems; 2) in a large volume (4500 L) atmospheric simulation chamber, reaction products yields in order to evaluate their atmospheric impact and reaction mechanisms; 3) using molecular beams and laser spectroscopy, the structure and reactivity of the vdW complexes formed between the unsaturated or aromatic alcohols and the OH radicals as a model of the adducts proposed as responsible for the non-Arrhenius behavior; 4) the specific state-to-state relaxation/reaction rate constants (ksts) of the vibrationally excited OH (v”=1-4) radical with the VOCs by PLP-LIF and supersonic expansions. Ab-initio calculations will be carried out to support the interpretation of the experimental results, to obtain the transition state and collisional adducts structures, as well as to calculate the vibrational frequencies of the vdW complexes to assign to the LIF and REMPI spectra. Also, the proposed reaction mechanisms and the experimentally measured kinetic parameters will be compared with those obtained from theoretical calculations.

Muscle recovery after repair of short and long peripheral nerve gaps using fibrin conduits.

Peripheral nerve injuries with loss of nervous tissue are a significant clinical problem and are currently treated using autologous nerve transplants. To avoid the need for donor nerve, which results in additional morbidity such as loss of sensation and scarring, alternative bridging methods have been sought. Recently we showed that an artificial nerve conduit moulded from fibrin glue is biocompatible to nerve regeneration. In this present study, we have used the fibrin conduit or a nerve graft to bridge either a 10 mm or 20 mm sciatic nerve gap and analyzed the muscle recovery in adult rats after 16 weeks. The gastrocnemius muscle weights of the operated side were similar for both gap sizes when treated with nerve graft. In contrast, muscle weight was 48.32 ± 4.96% of the contra-lateral side for the 10 mm gap repaired with fibrin conduit but only 25.20 ± 2.50% for the 20 mm gap repaired with fibrin conduit. The morphology of the muscles in the nerve graft groups showed an intact, ordered structure, with the muscle fibers grouped in fascicles whereas the 20 mm nerve gap fibrin group had a more chaotic appearance. The mean area and diameter of fast type fibers in the 20 mm gap repaired with fibrin conduits were significantly (P<0.01) worse than those of the corresponding 10 mm gap group. In contrast, both gap sizes treated with nerve graft showed similar fiber size. Furthermore, the 10 mm gaps repaired with either nerve graft or fibrin conduit showed similar muscle fiber size. These results indicate that the fibrin conduit can effectively treat short nerve gaps but further modification such as the inclusion of regenerative cells may be required to attain the outcomes of nerve graft for long gaps.

Novel microsatellite loci for Sebaea aurea (Gentianaceae) and cross-amplification in related species.

Premise of the study: Microsatellite loci were developed in Sebaea aurea (Gentianaceae) to investigate the functional role of diplostigmaty (i.e., the presence of additional stigmas along the style). Methods and Results: One hundred seventy-four and 180 microsatellite loci were isolated through 454 shotgun sequencing of genomic and microsatellite-enriched DNA libraries, respectively. Sixteen polymorphic microsatellite loci were characterized, and 12 of them were selected to genotype individuals from two populations. Microsatellite amplification was conducted in two multiplex groups, each containing six microsatellite loci. Cross-species amplification was tested in seven other species of Sebaea. The 12 novel microsatellite loci amplified only in the two most closely related species to S. aurea (i.e., S. ambigua and S. minutiflora) and were also polymorphic in these two species. Conclusions: These results demonstrate the usefulness of this set of newly developed microsatellite loci to investigate the mating system and population genetic structure in S. aurea and related species.

Critical analysis and extension of the Hirshfeld atoms in molecules

The computational approach to the Hirshfeld [Theor. Chim. Acta 44, 129 (1977)] atom in a molecule is critically investigated, and several difficulties are highlighted. It is shown that these difficulties are mitigated by an alternative, iterative version, of the Hirshfeld partitioning procedure. The iterative scheme ensures that the Hirshfeld definition represents a mathematically proper information entropy, allows the Hirshfeld approach to be used for charged molecules, eliminates arbitrariness in the choice of the promolecule, and increases the magnitudes of the charges. The resulting "Hirshfeld-I charges" correlate well with electrostatic potential derived atomic charges

Intramolecular basis set superposition error effects on the planarity of benzene and other aromatic molecules: A solution to the problem

Recently, the surprising result that ab initio calculations on benzene and other planar arenes at correlated MP2, MP3, configuration interaction with singles and doubles (CISD), and coupled cluster with singles and doubles levels of theory using standard Pople’s basis sets yield nonplanar minima has been reported. The planar optimized structures turn out to be transition states presenting one or more large imaginary frequencies, whereas single-determinant-based methods lead to the expected planar minima and no imaginary frequencies. It has been suggested that such anomalous behavior can be originated by two-electron basis set incompleteness error. In this work, we show that the reported pitfalls can be interpreted in terms of intramolecular basis set superposition error (BSSE) effects, mostly between the C–H moieties constituting the arenes. We have carried out counterpoise-corrected optimizations and frequency calculations at the Hartree–Fock, B3LYP, MP2, and CISD levels of theory with several basis sets for a number of arenes. In all cases, correcting for intramolecular BSSE fixes the anomalous behavior of the correlated methods, whereas no significant differences are observed in the single-determinant case. Consequently, all systems studied are planar at all levels of theory. The effect of different intramolecular fragment definitions and the particular case of charged species, namely, cyclopentadienyl and indenyl anions, respectively, are also discussed

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Comparative gene prediction in human and mouse

The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.

Mutational and computational analysis of the alpha(1b)-adrenergic receptor. Involvement of basic and hydrophobic residues in receptor activation and G protein coupling.

To investigate their role in receptor coupling to G(q), we mutated all basic amino acids and some conserved hydrophobic residues of the cytosolic surface of the alpha(1b)-adrenergic receptor (AR). The wild type and mutated receptors were expressed in COS-7 cells and characterized for their ligand binding properties and ability to increase inositol phosphate accumulation. The experimental results have been interpreted in the context of both an ab initio model of the alpha(1b)-AR and of a new homology model built on the recently solved crystal structure of rhodopsin. Among the twenty-three basic amino acids mutated only mutations of three, Arg(254) and Lys(258) in the third intracellular loop and Lys(291) at the cytosolic extension of helix 6, markedly impaired the receptor-mediated inositol phosphate production. Additionally, mutations of two conserved hydrophobic residues, Val(147) and Leu(151) in the second intracellular loop had significant effects on receptor function. The functional analysis of the receptor mutants in conjunction with the predictions of molecular modeling supports the hypothesis that Arg(254), Lys(258), as well as Leu(151) are directly involved in receptor-G protein interaction and/or receptor-mediated activation of the G protein. In contrast, the residues belonging to the cytosolic extensions of helices 3 and 6 play a predominant role in the activation process of the alpha(1b)-AR. These findings contribute to the delineation of the molecular determinants of the alpha(1b)-AR/G(q) interface.

Complex regional pain syndrome type I affects brain structure in prefrontal and motor cortex.

The complex regional pain syndrome (CRPS) is a rare but debilitating pain disorder that mostly occurs after injuries to the upper limb. A number of studies indicated altered brain function in CRPS, whereas possible influences on brain structure remain poorly investigated. We acquired structural magnetic resonance imaging data from CRPS type I patients and applied voxel-by-voxel statistics to compare white and gray matter brain segments of CRPS patients with matched controls. Patients and controls were statistically compared in two different ways: First, we applied a 2-sample ttest to compare whole brain white and gray matter structure between patients and controls. Second, we aimed to assess structural alterations specifically of the primary somatosensory (S1) and motor cortex (M1) contralateral to the CRPS affected side. To this end, MRI scans of patients with left-sided CRPS (and matched controls) were horizontally flipped before preprocessing and region-of-interest-based group comparison. The unpaired ttest of the "non-flipped" data revealed that CRPS patients presented increased gray matter density in the dorsomedial prefrontal cortex. The same test applied to the "flipped" data showed further increases in gray matter density, not in the S1, but in the M1 contralateral to the CRPS-affected limb which were inversely related to decreased white matter density of the internal capsule within the ipsilateral brain hemisphere. The gray-white matter interaction between motor cortex and internal capsule suggests compensatory mechanisms within the central motor system possibly due to motor dysfunction. Altered gray matter structure in dorsomedial prefrontal cortex may occur in response to emotional processes such as pain-related suffering or elevated analgesic top-down control.