Deciphering High-Pressure metamorphism in collisional context using microprobe-mapping methods : application to the Stak eclogitic massif (NW Himalaya)

The Stak massif, northern Pakistan, is a newly recognized occurrence of eclogite formed by the subduction of the northern margin of the Indian continent in the northwest Himalaya. Although this unit was extensively retrogressed during the Himalayan collision, records of the high-pressure (HP) event as well as a continuous pressure-temperature (P-T) path were assessed from a single thin section using a new multiequilibrium method. This method uses microprobe X-ray compositional maps of garnet and omphacitic pyroxene followed by calculations of ∼200,000 P-T estimates using appropriate thermobarometers. The Stak eclogite underwent prograde metamorphism, increasing from 650 °C and 2.4 GPa to the peak conditions of 750 °C and 2.5 GPa, then retrogressed to 700–650 °C and 1.6–0.9 GPa under amphibolite-facies conditions. The estimated peak metamorphic conditions and P-T path are similar to those of the Kaghan and Tso Morari high- to ultrahigh-pressure (HP-UHP) massifs. We propose that these three massifs define a large HP to UHP province in the northwest Himalaya, comparable to the Dabie-Sulu province in China and the Western Gneiss Region in Norway.

The sensitivity of mapping methods to reference data quality:training supervised image classifications with imperfect reference data

The accuracy of a map is dependent on the reference dataset used in its construction. Classification analyses used in thematic mapping can, for example, be sensitive to a range of sampling and data quality concerns. With particular focus on the latter, the effects of reference data quality on land cover classifications from airborne thematic mapper data are explored. Variations in sampling intensity and effort are highlighted in a dataset that is widely used in mapping and modelling studies; these may need accounting for in analyses. The quality of the labelling in the reference dataset was also a key variable influencing mapping accuracy. Accuracy varied with the amount and nature of mislabelled training cases with the nature of the effects varying between classifiers. The largest impacts on accuracy occurred when mislabelling involved confusion between similar classes. Accuracy was also typically negatively related to the magnitude of mislabelled cases and the support vector machine (SVM), which has been claimed to be relatively insensitive to training data error, was the most sensitive of the set of classifiers investigated, with overall classification accuracy declining by 8% (significant at 95% level of confidence) with the use of a training set containing 20% mislabelled cases.

Local Distributional Effects of Government Cash Transfers in Chile

Despite rapid economic growth and poverty reduction, inequality in Chile has remained high and remarkably constant over the last 20 years, prompting academic and public interest in the subject. Due to data limitations, however, research on inequality in Chile has concentrated on the national and regional levels. The impact of cash subsidies to poor households on local inequality is thus not well understood. Using poverty-mapping methods to asses this impact, we find heterogeneity in the effectiveness of regional and municipal governments in reducing inequality via poverty-reduction transfers, suggesting that alternative targeting regimes may complement current practice in aiding the poor.

Three-dimensional mapping of hippocampal anatomy in unmedicated and lithium-treated patients with bipolar disorder

Declarative memory impairments are common in patients with bipolar illness, suggesting underlying hippocampal pathology. However, hippocampal volume deficits are rarely observed in bipolar disorder. Here we used surface-based anatomic mapping to examine hippocampal anatomy in bipolar patients treated with lithium relative to matched control subjects and unmedicated patients with bipolar disorder. High-resolution brain magnetic resonance images were acquired from 33 patients with bipolar disorder ( 21 treated with lithium and 12 unmedicated), and 62 demographically matched healthy control subjects. Three-dimensional parametric mesh models were created from manual tracings of the hippocampal formation. Total hippocampal volume was significantly larger in lithium-treated bipolar patients compared with healthy controls (by 10.3%; p=0.001) and unmedicated bipolar patients ( by 13.9%; p=0.003). Statistical mapping results, confirmed by permutation testing, revealed localized deficits in the right hippocampus, in regions corresponding primarily to cornu ammonis vertical bar subfields, in unmedicated bipolar patients, as compared to both normal controls (p=0.01), and in lithium-treated bipolar patients (p=0.03). These findings demonstrate the sensitivity of these anatomic mapping methods for detecting subtle alterations in hippocampal structure in bipolar disorder. The observed reduction in subregions of the hippocampus in unmedicated bipolar patients suggests a possible neural correlate for memory deficits frequently reported in this illness. Moreover, increased hippocampal volume in lithium-treated bipolar patients may reflect postulated neurotrophic effects of this agent, a possibility warranting further study in longitudinal investigations.

Disparate activation of the coronary sinus and inferior left atrium during atrial tachycardia after persistent atrial fibrillation ablation: prevalence, pitfalls, and impact on mapping.

INTRODUCTION: Persistent atrial fibrillation (AF) ablation may lead to partial disconnection of the coronary sinus (CS). As a result, disparate activation sequences of the local CS versus contiguous left atrium (LA) may be observed during atrial tachycardia (AT). We aimed to evaluate the prevalence of this phenomenon and its impact on activation mapping. METHODS: AT occurring after persistent AF ablation were investigated in 74 consecutive patients. Partial CS disconnection during AT was suspected when double potentials with disparate activation sequences were observed on the CS catheter. Endocardial mapping facing CS bipoles was performed to differentiate LA far-field from local CS potentials. RESULTS: A total of 149 ATs were observed. Disparate LA-CS activations were apparent in 20 ATs after magnifying the recording scale (13%). The most common pattern (90%) was distal to proximal endocardial LA activation against proximal to distal CS activation, the latter involving the whole CS or its distal part. Perimitral macroreentry was more common when disparate LA-CS activations were observed (67% vs 29%; P = 0.002). Partial CS disconnection also resulted in "pseudo" mitral isthmus (MI) block during LA appendage pacing in 20% of patients as local CS activation was proximal to distal despite distal to proximal activation of the contiguous LA. CONCLUSION: Careful analysis of CS recordings during AT following persistent AF ablation often reveals disparate patterns of activation. Recognizing when endocardial LA activation occurs in the opposite direction to the more obvious local CS signals is critical to avoid misleading interpretations during mapping of AT and evaluation of MI block.

ADC mapping of chronic cerebral hypoperfusion induced by carotid artery stenosis.

BACKGROUND: Carotid artery stenosis is associated with the occurrence of acute and chronic ischemic lesions that increase with age in the elderly population. Diffusion Imaging and ADC mapping may be an appropriate method to investigate patients with chronic hypoperfusion consecutive to carotid stenosis. This non-invasive technique allows to investigate brain integrity and structure, in particular hypoperfusion induced by carotid stenosis diseases. The aim of this study was to evaluate the impact of a carotid stenosis on the parenchyma using ADC mapping. METHODS: Fifty-nine patients with symptomatic (33) and asymptomatic (26) carotid stenosis were recruited from our multidisciplinary consultation. Both groups demonstrated a similar degree of stenosis. All patients underwent MRI of the brain including diffusion-weighted MR imaging with ADC mapping. Regions of interest were defined in the anterior and posterior paraventricular regions both ipsilateral and contralateral to the stenosis (anterior circulation). The same analysis was performed for the thalamic and occipital regions (posterior circulation). RESULTS: ADC values of the affected vascular territory were significantly higher on the side of the stenosis in the periventricular anterior (P<0.001) and posterior (P<0.01) area. There was no difference between ipsilateral and contralateral ADC values in the thalamic and occipital regions. CONCLUSIONS: We have shown that carotid stenosis is associated with significantly higher ADC values in the anterior circulation, probably reflecting an impact of chronic hypoperfusion on the brain parenchyma in symptomatic and asymptomatic patients. This is consistent with previous data in the literature.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Sequential Quantitative Trait Locus Mapping in Experimental Crosses

The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

Association between food assistance program participation and overweight

OBJECTIVE The objective of this study was to investigate the association between food assistance program participation and overweight/obesity according to poverty level. METHODS A cross-sectional analysis of data from 46,217 non-pregnant and non-lactating women in Lima, Peru was conducted; these data were obtained from nationally representative surveys from the years 2003, 2004, 2006, and 2008-2010. The dependent variable was overweight/obesity, and the independent variable was food assistance program participation. Poisson regression was used to stratify the data by family socioeconomic level, area of residence (Lima versus the rest of the country; urban versus rural), and survey year (2003-2006 versus 2008-2010). The models were adjusted for age, education level, urbanization, and survey year. RESULTS Food assistance program participation was associated with an increased risk of overweight/obesity in women living in homes without poverty indicators [prevalence ratio (PR) = 1.29; 95% confidence interval (CI) 1.06;1.57]. When stratified by area of residence, similar associations were observed for women living in Lima and urban areas; no associations were found between food assistance program participation and overweight/obesity among women living outside of Lima or in rural areas, regardless of the poverty status. CONCLUSIONS Food assistance program participation was associated with overweight/obesity in non-poor women. Additional studies are required in countries facing both aspects of malnutrition.

The BOLD Effect of Interictal Spike Activity in Childhood Occipital Lobe Epilepsy

Occipital lobe epilepsy (OLE) presents in childhood with different manifestations, age of onset and EEG features that form distinct syndromes. The ictal clinical symptoms are difficult to correlate with onset in particular areas in the occipital lobes, and the EEG recordings have not been able to overcome this limitation. The mapping of epileptogenic cortical regions in OLE remains therefore an important goal in our understanding of these syndromes.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Protein-protein interaction investigated by steered molecular dynamics: the TCR-pMHC complex.

We present a novel steered molecular dynamics scheme to induce the dissociation of large protein-protein complexes. We apply this scheme to study the interaction of a T cell receptor (TCR) with a major histocompatibility complex (MHC) presenting a peptide (p). Two TCR-pMHC complexes are considered, which only differ by the mutation of a single amino acid on the peptide; one is a strong agonist that produces T cell activation in vivo, while the other is an antagonist. We investigate the interaction mechanism from a large number of unbinding trajectories by analyzing van der Waals and electrostatic interactions and by computing energy changes in proteins and solvent. In addition, dissociation potentials of mean force are calculated with the Jarzynski identity, using an averaging method developed for our steering scheme. We analyze the convergence of the Jarzynski exponential average, which is hampered by the large amount of dissipative work involved and the complexity of the system. The resulting dissociation free energies largely underestimate experimental values, but the simulations are able to clearly differentiate between wild-type and mutated TCR-pMHC and give insights into the dissociation mechanism.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.