Quantifying rock fabrics: a test of autocorrelation of the spatial distribution of cristals

A novel test of spatial independence of the distribution of crystals or phases in rocksbased on compositional statistics is introduced. It improves and generalizes the commonjoins-count statistics known from map analysis in geographic information systems.Assigning phases independently to objects in RD is modelled by a single-trial multinomialrandom function Z(x), where the probabilities of phases add to one and areexplicitly modelled as compositions in the K-part simplex SK. Thus, apparent inconsistenciesof the tests based on the conventional joins{count statistics and their possiblycontradictory interpretations are avoided. In practical applications we assume that theprobabilities of phases do not depend on the location but are identical everywhere inthe domain of de nition. Thus, the model involves the sum of r independent identicalmultinomial distributed 1-trial random variables which is an r-trial multinomialdistributed random variable. The probabilities of the distribution of the r counts canbe considered as a composition in the Q-part simplex SQ. They span the so calledHardy-Weinberg manifold H that is proved to be a K-1-affine subspace of SQ. This isa generalisation of the well-known Hardy-Weinberg law of genetics. If the assignmentof phases accounts for some kind of spatial dependence, then the r-trial probabilitiesdo not remain on H. This suggests the use of the Aitchison distance between observedprobabilities to H to test dependence. Moreover, when there is a spatial uctuation ofthe multinomial probabilities, the observed r-trial probabilities move on H. This shiftcan be used as to check for these uctuations. A practical procedure and an algorithmto perform the test have been developed. Some cases applied to simulated and realdata are presented.Key words: Spatial distribution of crystals in rocks, spatial distribution of phases,joins-count statistics, multinomial distribution, Hardy-Weinberg law, Hardy-Weinbergmanifold, Aitchison geometry

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.

Distribution of free and conjugated cannabinoids in human bile samples.

The metabolism of Δ(9)-tetrahydrocannabinol (THC) is relatively complex, and over 80 metabolites have been identified. However, much less is known about the formation and fate of cannabinoid conjugates. Bile excretion is known to be an important route for the elimination of phase II metabolites. A liquid chromatography-tandem mass spectrometry LC-MS/MS procedure for measuring cannabinoids in oral fluid was adapted, validated and applied to 10 bile samples. THC, 11-hydroxy-Δ(9)-tetrahydrocannabinol (11-OH-THC), 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THCCOOH), cannabinol (CBN), cannabidiol (CBD), Δ(9)-tetrahydrocannabinolic acid A (THC-A), 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol glucuronide (THCCOOH-gluc) and Δ(9)-tetrahydrocannabinol glucuronide (THC-gluc) were determined following solid-phase extraction and LC-MS/MS. High concentrations of THCCOOH-gluc were found in bile samples (range: 139-21,275 ng/mL). Relatively high levels of THCCOOH (7.7-1548 ng/mL) and THC-gluc (38-1366 ng/mL) were also measured. THC-A, the plant precursor of THC, was the only cannabinoid that was not detected. These results show that biliary excretion is an important route of elimination for cannabinoids conjugates and that their enterohepatic recirculation is a significant factor to consider when analyzing blood elimination profiles of cannabinoids. Furthermore, we suggest that the bile is the matrix of choice for the screening of phase II cannabinoid metabolites.

Assessment of distribution and evolution of mechanical dyssynchrony in a porcine model of myocardial infarction by cardiovascular magnetic resonance.

BACKGROUND: We sought to investigate the relationship between infarct and dyssynchrony post- myocardial infarct (MI), in a porcine model. Mechanical dyssynchrony post-MI is associated with left ventricular (LV) remodeling and increased mortality. METHODS: Cine, gadolinium-contrast, and tagged cardiovascular magnetic resonance (CMR) were performed pre-MI, 9 ± 2 days (early post-MI), and 33 ± 10 days (late post-MI) post-MI in 6 pigs to characterize cardiac morphology, location and extent of MI, and regional mechanics. LV mechanics were assessed by circumferential strain (eC). Electro-anatomic mapping (EAM) was performed within 24 hrs of CMR and prior to sacrifice. RESULTS: Mean infarct size was 21 ± 4% of LV volume with evidence of post-MI remodeling. Global eC significantly decreased post MI (-27 ± 1.6% vs. -18 ± 2.5% (early) and -17 ± 2.7% (late), p < 0.0001) with no significant change in peri-MI and MI segments between early and late time-points. Time to peak strain (TTP) was significantly longer in MI, compared to normal and peri-MI segments, both early (440 ± 40 ms vs. 329 ± 40 ms and 332 ± 36 ms, respectively; p = 0.0002) and late post-MI (442 ± 63 ms vs. 321 ± 40 ms and 355 ± 61 ms, respectively; p = 0.012). The standard deviation of TTP in 16 segments (SD16) significantly increased post-MI: 28 ± 7 ms to 50 ± 10 ms (early, p = 0.012) to 54 ± 19 ms (late, p = 0.004), with no change between early and late post-MI time-points (p = 0.56). TTP was not related to reduction of segmental contractility. EAM revealed late electrical activation and greatly diminished conduction velocity in the infarct (5.7 ± 2.4 cm/s), when compared to peri-infarct (18.7 ± 10.3 cm/s) and remote myocardium (39 ± 20.5 cm/s). CONCLUSIONS: Mechanical dyssynchrony occurs early after MI and is the result of delayed electrical and mechanical activation in the infarct.

NCoR1 is a conserved physiological modulator of muscle mass and oxidative function.

Transcriptional coregulators control the activity of many transcription factors and are thought to have wide-ranging effects on gene expression patterns. We show here that muscle-specific loss of nuclear receptor corepressor 1 (NCoR1) in mice leads to enhanced exercise endurance due to an increase of both muscle mass and of mitochondrial number and activity. The activation of selected transcription factors that control muscle function, such as MEF2, PPARβ/δ, and ERRs, underpins these phenotypic alterations. NCoR1 levels are decreased in conditions that require fat oxidation, resetting transcriptional programs to boost oxidative metabolism. Knockdown of gei-8, the sole C. elegans NCoR homolog, also robustly increased muscle mitochondria and respiration, suggesting conservation of NCoR1 function. Collectively, our data suggest that NCoR1 plays an adaptive role in muscle physiology and that interference with NCoR1 action could be used to improve muscle function.

K(+) channel expression distinguishes subpopulations of parvalbumin- and somatostatin-containing neocortical interneurons

Kv3.1 and Kv3.2 K+ channel proteins form similar voltage-gated K+ channels with unusual properties, including fast activation at voltages positive to −10 mV and very fast deactivation rates. These properties are thought to facilitate sustained high-frequency firing. Kv3.1 subunits are specifically found in fast-spiking, parvalbumin (PV)-containing cortical interneurons, and recent studies have provided support for a crucial role in the generation of the fast-spiking phenotype. Kv3.2 mRNAs are also found in a small subset of neocortical neurons, although the distribution of these neurons is different. We raised antibodies directed against Kv3.2 proteins and used dual-labeling methods to identify the neocortical neurons expressing Kv3.2 proteins and to determine their subcellular localization. Kv3.2 proteins are prominently expressed in patches in somatic and proximal dendritic membrane as well as in axons and presynaptic terminals of GABAergic interneurons. Kv3.2 subunits are found in all PV-containing neurons in deep cortical layers where they probably form heteromultimeric channels with Kv3.1 subunits. In contrast, in superficial layer PV-positive neurons Kv3.2 immunoreactivity is low, but Kv3.1 is still prominently expressed. Because Kv3.1 and Kv3.2 channels are differentially modulated by protein kinases, these results raise the possibility that the fast-spiking properties of superficial- and deep-layer PV neurons are differentially regulated by neuromodulators. Interestingly, Kv3.2 but not Kv3.1 proteins are also prominent in a subset of seemingly non-fast-spiking, somatostatin- and calbindin-containing interneurons, suggesting that the Kv3.1–Kv3.2 current type can have functions other than facilitating high-frequency firing.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Quantitative distribution of parvalbumin, calretinin, and calbindin D-28k immunoreactive neurons in the visual cortex of normal and Alzheimer cases.

The distribution of parvalbumin (PV), calretinin (CR), and calbindin (CB) immunoreactive neurons was studied with the help of an image analysis system (Vidas/Zeiss) in the primary visual area 17 and associative area 18 (Brodmann) of Alzheimer and control brains. In neither of these areas was there a significant difference between Alzheimer and control groups in the mean number of PV, CR, or CB immunoreactive neuronal profiles, counted in a cortical column going from pia to white matter. Significant differences in the mean densities (numbers per square millimeter of cortex) of PV, CR, and CB immunoreactive neuronal profiles were not observed either between groups or areas, but only between superficial, middle, and deep layers within areas 17 and 18. The optical density of the immunoreactive neuropil was also similar in Alzheimer and controls, correlating with the numerical density of immunoreactive profiles in superficial, middle, and deep layers. The frequency distribution of neuronal areas indicated significant differences between PV, CR, and CB immunoreactive neuronal profiles in both areas 17 and 18, with more large PV than CR and CB positive profiles. There were also significantly more small and less large PV and CR immunoreactive neuronal profiles in Alzheimer than in controls. Our data show that, although the brain pathology is moderate to severe, there is no prominent decrease of PV, CR and CB positive neurons in the visual cortex of Alzheimer brains, but only selective changes in neuronal perikarya.

Stratification by smoking status reveals an association of CHRNA5-A3-B4 genotype with body mass index in never smokers.

We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00 × 10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI +0.18 to +0.52, P = 6.38 × 10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95 × 10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.

Global mass wasting during the Middle Ordovician: Meteoritic trigger or plate-tectonic environment ?

Mass wasting at continental margins on a global scale during the Middle Ordovician has recently been related to high meteorite influx. Although a high meteorite influx during the Ordovician should not be neglected, we challenge the idea that mass wasting was mainly produced by meteorite impacts over a period of almost 10 Ma. Having strong arguments against the impact-related hypothesis, we propose an alternative explanation, which is based on a re-evaluation of the mass wasting sites, considering their plate-tectonic distribution and the global sea level curve. A striking and important feature is the distribution of most of the mass wasting sites along continental margins characterised by periods of magmatism, terrane accretion and continental or back-arc rifting, respectively, related to subduction of oceanic lithosphere. Such processes are commonly connected with seismic activity causing earthquakes, which can cause downslope movement of sediment and rock. Considering all that, it seems more likely that most of this mass wasting was triggered by earthquakes related to plate-tectonic processes, which caused destabilisation of continental margins resulting in megabreccias and debris flows. Moreover, the period of mass wasting coincides with sea level drops during global sea level lowstand. In some cases, sea level drops can release pore-water overpressure reducing sediment strength and hence promoting instability of sediment at continental margins. Reduced pore-water overpressure can also destabilise gas hydrate-bearing sediment, causing slope failure, and thus resulting in submarine mass wasting. Overall, the global mass wasting during the Middle Ordovician does not need meteoritic trigger. (C) 2010 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

Lower thigh subcutaneous and higher visceral abdominal adipose tissue content both contribute to insulin resistance.

It is well known that visceral adipose tissue (VAT) is associated with insulin resistance (IR). Considerable debate remains concerning the potential positive effect of thigh subcutaneous adipose tissue (TSAT). Our objective was to observe whether VAT and TSAT are opposite, synergistic or additive for both peripheral and hepatic IR. Fifty-two volunteers (21 male/31 female) between 30 and 75 years old were recruited from the general population. All subjects were sedentary overweight or obese (mean BMI 33.0 ± 3.4 kg/m(2)). Insulin sensitivity was determined by a 4-h hyperinsulinemic-euglycemic clamp with stable isotope tracer dilution. Total body fat and lean body mass were determined by dual X-ray absorptiometry. Abdominal and mid-thigh adiposity was determined by computed tomography. VAT was negatively associated with peripheral insulin sensitivity, while TSAT, in contrast, was positively associated with peripheral insulin sensitivity. Subjects with a combination of low VAT and high TSAT had the highest insulin sensitivity, subjects with a combination of high VAT and low TSAT were the most insulin resistant. These associations remained significant after adjusting for age and gender. These data confirm that visceral excess abdominal adiposity is associated with IR across a range of middle-age to older men and women, and further suggest that higher thigh subcutaneous fat is favorably associated with better insulin sensitivity. This strongly suggests that these two distinct fat distribution phenotypes should both be considered in IR as important determinants of cardiometabolic risk.