Associations between parental and child attachment representations.

In the present article on intergenerational transmission of attachment representations, we use mothers' and fathers' Adult Attachment Interview classifications to predict a 3-year-old's responses to the Attachment Story Completion Task (ASCT). We present a Q-sort coding procedure for the ASCT, which was developed for children as young as three. The Q-sort yields scores on four attachment dimensions (security, deactivation, hyperactivation, and disorganization). One-way ANOVAs revealed significant mother-child associations for each dimension, although results for the hyperactivation and disorganization dimensions were significant only according to contrast tests. Conversely, no father-child association was found, regardless of the dimension considered. Findings are discussed in terms of the respective part played by each parent in their children's emotional development.

Topographic ERP analyses: a step-by-step tutorial review.

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.

Update on oral Chagas disease outbreaks in Venezuela: epidemiological, clinical and diagnostic approaches

Orally transmitted Chagas disease has become a matter of concern due to outbreaks reported in four Latin American countries. Although several mechanisms for orally transmitted Chagas disease transmission have been proposed, food and beverages contaminated with whole infected triatomines or their faeces, which contain metacyclic trypomastigotes of Trypanosoma cruzi, seems to be the primary vehicle. In 2007, the first recognised outbreak of orally transmitted Chagas disease occurred in Venezuela and largest recorded outbreak at that time. Since then, 10 outbreaks (four in Caracas) with 249 cases (73.5% children) and 4% mortality have occurred. The absence of contact with the vector and of traditional cutaneous and Romana’s signs, together with a florid spectrum of clinical manifestations during the acute phase, confuse the diagnosis of orally transmitted Chagas disease with other infectious diseases. The simultaneous detection of IgG and IgM by ELISA and the search for parasites in all individuals at risk have been valuable diagnostic tools for detecting acute cases. Follow-up studies regarding the microepidemics primarily affecting children has resulted in 70% infection persistence six years after anti-parasitic treatment. Panstrongylus geniculatushas been the incriminating vector in most cases. As a food-borne disease, this entity requires epidemiological, clinical, diagnostic and therapeutic approaches that differ from those approaches used for traditional direct or cutaneous vector transmission.

An essential role for the Leishmania major metacaspase in cell cycle progression.

Metacaspases (MCAs) are distant orthologues of caspases and have been proposed to play a role in programmed cell death in yeast and plants, but little is known about their function in parasitic protozoa. The MCA gene of Leishmania major (LmjMCA) is expressed in actively replicating amastigotes and procyclic promastigotes, but at a lower level in metacyclic promastigotes. LmjMCA has a punctate distribution throughout the cell in interphase cells, but becomes concentrated in the kinetoplast (mitochondrial DNA) at the time of the organelle's segregation. LmjMCA also translocates to the nucleus during mitosis, where it associates with the mitotic spindle. Overexpression of LmjMCA in promastigotes leads to a severe growth retardation and changes in ploidy, due to defects in kinetoplast segregation and nuclear division and an impairment of cytokinesis. LmjMCA null mutants could not be generated and following genetic manipulation to express LmjMCA from an episome, the only mutants that were viable were those expressing LmjMCA at physiological levels. Together these data suggest that in L. major active LmjMCA is essential for the correct segregation of the nucleus and kinetoplast, functions that could be independent of programmed cell death, and that the amount of LmjMCA is crucial. The absence of MCAs from mammals makes the enzyme a potential drug target against protozoan parasites.

Sharing competences in strategic alliances: a case study of the Cosan and Shell biofuel venture

In a competitive world, the way a firm establishes its organizational arrangements may determine the enhancement of its core competences and the possibility of reaching new markets. Firms that find their skills to be applicable in just one type of market encounter constraints in expanding their markets, and through alliances may find a competitive form of value capture. Hybrid forms of organization appear primarily as an alternative to capturing value and managing joint assets when the market and hierarchy modes do not present any yields for the firm's competitiveness. As a result, this form may present other challenging issues, such as the allocation of rights and principal-agent problems. The biofuel market has presented a strong pattern of changes over the last 10 years. New intra-firm arrangements have appeared as a path to participate or survive among global competition. Given the need for capital to achieve better results, there has been a consistent movement of mergers and acquisitions in the Biofuel sector, especially since the 2008 financial crisis. In 2011 there were five major groups in Brazil with a grinding capacity of more than 15 million tons per year: Raízen (joint venture formed by Cosan and Shell), Louis Dreyfus, Tereos Petrobras, ETH, and Bunge. Major oil companies have implemented the strategy of diversification as a hedge against the rising cost of oil. Using the alliance of Cosan and Shell in the Brazilian biofuel market as a case study, this paper analyses the governance mode and challenging issues raised by strategic alliances when firms aim to reach new markets through the sharing of core competences with local firms. The article is based on documentary research and interviews with Cosan's Investor Relations staff, and examines the main questions involving hybrid forms through the lens of the Transaction Cost Economics (TCE), Agency Theory, Resource Based View (RBV), and dynamic capabilities theoretical approaches. One focal point is knowledge "appropriability" and the specific assets originated by the joint venture. Once the alliance is formed, it is expected that competences will be shared and new capabilities will expand the limits of the firm. In the case studied, Cosan and Shell shared a number of strategic assets related to their competences. Raízen was formed with economizing incentives, as well to continue marshalling internal resources to enhance the company's presence in the world energy sector. Therefore, some challenges might be related to the control and monitoring agents' behavior, considering the two-part organism formed by distinctive organizational culture, tacit knowledge, and long-term incentives. The case study analyzed illustrates the hybrid arrangement as a middle form for organizing the transaction: neither in the market nor in the hierarchy mode, but rather a more flexible commitment agreement with a strategic central authority. The corporate governance devices are also a challenge, since the alignment between the parent companies in the joint ventures is far more complex. These characteristics have led to an organism with bilateral dependence, offering favorable conditions for developing dynamic capabilities. However, these conditions might rely on the partners' long-term interest in the joint venture.

Adaptive search and information updating in sequential mate choice

Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.

Managing diabetes in Switzerland : a systemic approach

Executive summaryThe increasing prevalence of chronic diseases is one of the major causes of rising health expenditure, as stated by the WHO. Not only chronic diseases are very costly, but they are by far the leading cause of mortality in the world, representing 60% of all deaths. Diabetes in particular is becoming a major burden of disease. In Switzerland around 5% of the population suffer of type 2 diabetes and 5 to 10% of the annual health care budget is attributable to diabetes. If the predictions of WHO do realise, the prevalence of diabetes will double until 2030 and so is expected the attributable health expenditure.The objective of this thesis is to provide policy recommendations as to slow down the disease progression and its costly complication. We study the factors that influence diabetes dynamics and the interventions that improve health outcomes while decreasing costs according to different time horizon and use systems thinking and system dynamic.Our results show that managing diabetes requires using integrated care interventions that are effective on three fronts: (1) delaying the onset of complications, (2) slowing down the disease progression and (3) accelerating the time to diagnosis of diabetes and its complications. We recommend firstly the implementation of those interventions targeted at changing patients' behaviour which are also less expensive, but require a change in the delivery of care and medical practices. Then policies targeted at an earlier diagnosis of diabetes, its prevention and the diagnosis of complications are to be considered. This sequence of interventions allows saving money, as total costs decrease, even including the costs of interventions and result in longer life expectancy of diabetics in the long term.In diabetes management there is therefore a trade-off between medical costs and patients' benefits on the one hand and between the objectives of obtaining results in the short or long term on the other hand. Decision makers need to deliver acceptable outcomes in the short term. Considering this criterion, the preferred policy may be to focus only on diagnosed diabetics, thus attempting to slow down the progression of their disease, compared to an integrated care approach addressing all the aspects of the disease. Such a policy also yields desirable results in terms of costs and patients' benefits.

Time-delayed reaction-diffusion fronts

A time-delayed second-order approximation for the front speed in reaction-dispersion systems was obtained by Fort and Méndez [Phys. Rev. Lett. 82, 867 (1999)]. Here we show that taking proper care of the effect of the time delay on the reactive process yields a different evolution equation and, therefore, an alternate equation for the front speed. We apply the new equation to the Neolithic transition. For this application the new equation yields speeds about 10% slower than the previous one

A comparative analysis by means of quantum molecular similarity measures of density distributions derived from conventional ab initio and density functional methods

A procedure based on quantum molecular similarity measures (QMSM) has been used to compare electron densities obtained from conventional ab initio and density functional methodologies at their respective optimized geometries. This method has been applied to a series of small molecules which have experimentally known properties and molecular bonds of diverse degrees of ionicity and covalency. Results show that in most cases the electron densities obtained from density functional methodologies are of a similar quality than post-Hartree-Fock generalized densities. For molecules where Hartree-Fock methodology yields erroneous results, the density functional methodology is shown to yield usually more accurate densities than those provided by the second order Møller-Plesset perturbation theory

Ab initio benchmark study for the oxidative addition of CH4 to Pd: importance of basis-set flexibility and polarization

To obtain a state-of-the-art benchmark potential energy surface (PES) for the archetypal oxidative addition of the methane C-H bond to the palladium atom, we have explored this PES using a hierarchical series of ab initio methods (Hartree-Fock, second-order Møller-Plesset perturbation theory, fourth-order Møller-Plesset perturbation theory with single, double and quadruple excitations, coupled cluster theory with single and double excitations (CCSD), and with triple excitations treated perturbatively [CCSD(T)]) and hybrid density functional theory using the B3LYP functional, in combination with a hierarchical series of ten Gaussian-type basis sets, up to g polarization. Relativistic effects are taken into account either through a relativistic effective core potential for palladium or through a full four-component all-electron approach. Counterpoise corrected relative energies of stationary points are converged to within 0.1-0.2 kcal/mol as a function of the basis-set size. Our best estimate of kinetic and thermodynamic parameters is -8.1 (-8.3) kcal/mol for the formation of the reactant complex, 5.8 (3.1) kcal/mol for the activation energy relative to the separate reactants, and 0.8 (-1.2) kcal/mol for the reaction energy (zero-point vibrational energy-corrected values in parentheses). This agrees well with available experimental data. Our work highlights the importance of sufficient higher angular momentum polarization functions, f and g, for correctly describing metal-d-electron correlation and, thus, for obtaining reliable relative energies. We show that standard basis sets, such as LANL2DZ+ 1f for palladium, are not sufficiently polarized for this purpose and lead to erroneous CCSD(T) results. B3LYP is associated with smaller basis set superposition errors and shows faster convergence with basis-set size but yields relative energies (in particular, a reaction barrier) that are ca. 3.5 kcal/mol higher than the corresponding CCSD(T) values

Assessing dystrophies and other muscle diseases at the nanometer scale by atomic force microscopy.

AIM: Atomic force microscopy nanoindentation of myofibers was used to assess and quantitatively diagnose muscular dystrophies from human patients. MATERIALS & METHODS: Myofibers were probed from fresh or frozen muscle biopsies from human dystrophic patients and healthy volunteers, as well as mice models, and Young's modulus stiffness values were determined. RESULTS: Fibers displaying abnormally low mechanical stability were detected in biopsies from patients affected by 11 distinct muscle diseases, and Young's modulus values were commensurate to the severity of the disease. Abnormal myofiber resistance was also observed from consulting patients whose muscle condition could not be detected or unambiguously diagnosed otherwise. DISCUSSION & CONCLUSION: This study provides a proof-of-concept that atomic force microscopy yields a quantitative read-out of human muscle function from clinical biopsies, and that it may thereby complement current muscular dystrophy diagnosis.

Respiratory variability in mechanically ventilated patients. Critical Care 2011

Introduction: Increased respiratory pattern variability is associated with improved oxygenation. Pressure support (PS) is a widely used partial-assist mechanical ventilation (MV) mode, in which each breathing cycle is initiated by flow or pressure variation at the airway due to patient inspiratory effort. Neurally adjusted ventilatory assist (NAVA) is relatively new and uses the electrical activity of the diaphragm (Eadi) to deliver ventilatory support proportional to the patient's inspiratory demand. We hypothesize that respiratory variability should be greater with NAVA compared with PS.Methods: Twenty-two patients underwent 20 minutes of PS followed by 20 minutes of NAVA. Flow and Eadi curves were used to obtain tidal volume (Vt) and ∫Eadi for 300 to 400 breaths in each patient. Patient-specific cumulative distribution functions (CDF) show the percentage Vt and ∫Eadi within a clinically defined (±10%) variability band for each patient. Values are normalized to patient-specific medians for direct comparison. Variability in Vt (outcome) is thus expressed in terms of variability in ∫Eadi (demand) on the same plot.Results: Variability in Vt relative to variability in ∫Eadi is significantly greater for NAVA than PS (P = 0.00012). Hence, greater variability in outcome Vt is obtained for a given demand in ∫Eadi, under NAVA, as illustrated in Figure 1 for a typical patient. A Fisher 2 × 2 contingency analysis showed that 45% of patients under NAVA had a Vt variability in equal proportion to ∫Eadi variability, versus 0% for PS (P < 0.05).Conclusions: NAVA yields greater variability in tidal volume, relative to ∫Eadi demand, and a better match between Vt and ∫Eadi. These results indicate that NAVA could achieve improved oxygenation compared with PS when sufficient underlying variability in ∫Eadi is present, due to its ability to achieve higher tidal volume variability from a given variability in ∫Eadi.

Redox dysregulation, neurodevelopment, and schizophrenia.

In schizophrenia, a developmental redox dysregulation constitutes one 'hub' on which converge genetic impairments of glutathione synthesis and environmental vulnerability factors generating oxidative stress. Their timing at critical periods of neurodevelopment could play a decisive role in inducing impairment of neural connectivity and synchronization as observed in schizophrenia. In experimental models, such redox dysregulation induces anomalies strikingly similar to those observed in patients. This is mediated by hypoactive NMDA receptors, impairment of fast-spiking parvalbumin GABA interneurons and deficit in myelination. A treatment restoring the redox balance without side effects yields improvements of negative symptoms in chronic patients. Novel interventions based on these mechanisms if applied in early phases of the disease hold great therapeutic promise.

Estimation of inelastic seismic material properties of a surgical sea-bed from multi-component marine seismic data

To date, state-of-the-art seismic material parameter estimates from multi-component sea-bed seismic data are based on the assumption that the sea-bed consists of a fully elastic half-space. In reality, however, the shallow sea-bed generally consists of soft, unconsolidated sediments that are characterized by strong to very strong seismic attenuation. To explore the potential implications, we apply a state-of-the-art elastic decomposition algorithm to synthetic data for a range of canonical sea-bed models consisting of a viscoelastic half-space of varying attenuation. We find that in the presence of strong seismic attenuation, as quantified by Q-values of 10 or less, significant errors arise in the conventional elastic estimation of seismic properties. Tests on synthetic data indicate that these errors can be largely avoided by accounting for the inherent attenuation of the seafloor when estimating the seismic parameters. This can be achieved by replacing the real-valued expressions for the elastic moduli in the governing equations in the parameter estimation by their complex-valued viscoelastic equivalents. The practical application of our parameter procedure yields realistic estimates of the elastic seismic material properties of the shallow sea-bed, while the corresponding Q-estimates seem to be biased towards too low values, particularly for S-waves. Given that the estimation of inelastic material parameters is notoriously difficult, particularly in the immediate vicinity of the sea-bed, this is expected to be of interest and importance for civil and ocean engineering purposes.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.