Stability and convergence of a new finite volume method for a two-sided space-fractional diffusion equation

In this paper, we consider a two-sided space-fractional diffusion equation with variable coefficients on a finite domain. Firstly, based on the nodal basis functions, we present a new fractional finite volume method for the two-sided space-fractional diffusion equation and derive the implicit scheme and solve it in matrix form. Secondly, we prove the stability and convergence of the implicit fractional finite volume method and conclude that the method is unconditionally stable and convergent. Finally, some numerical examples are given to show the effectiveness of the new numerical method, and the results are in excellent agreement with theoretical analysis.

The effect of atypical antipsychotics on pituitary gland volume in patients with first-episode psychosis: A longitudinal MRI study

BACKGROUND: Pituitary volume is currently measured as a marker of hypothalamic-pituitary-adrenal hyperactivity in patients with psychosis despite suggestions of susceptibility to antipsychotics. Qualifying and quantifying the effect of atypical antipsychotics on the volume of the pituitary gland will determine whether this measure is valid as a future estimate of HPA-axis activation in psychotic populations. AIMS: To determine the qualitative and quantitative effect of atypical antipsychotic medications on pituitary gland volume in a first-episode psychosis population. METHOD: Pituitary volume was measured from T1-weighted magnetic resonance images in a group of 43 first-episode psychosis patients, the majority of whom were neuroleptic-naive, at baseline and after 3months of treatment, to determine whether change in pituitary volume was correlated with cumulative dose of atypical antipsychotic medication. RESULTS: There was no significant baseline difference in pituitary volume between subjects and controls, or between neuroleptic-naive and neuroleptic-treated subjects. Over the follow-up period there was a negative correlation between percentage change in pituitary volume and cumulative 3-month dose of atypical antipsychotic (r=-0.37), i.e. volume increases were associated with lower doses and volume decreases with higher doses. CONCLUSIONS: Atypical antipsychotic medications may reduce pituitary gland volume in a dose-dependent manner suggesting that atypical antipsychotic medication may support affected individuals to cope with stress associated with emerging psychotic disorders.

Pituitary volume and early treatment response in drug-naïve first-episode psychosis patients

BACKGROUND: An early response to antipsychotic treatment in patients with psychosis has been associated with a better course and outcome. However, factors that predict treatment response are not well understood. The onset of schizophrenia and related disorders has been associated with increased levels of stress and hyper-activation of the hypothalamic-pituitary-adrenal (HPA) axis. This study examined whether pituitary volume at the onset of psychosis may be a potential predictor of early treatment response in first-episode psychosis (FEP) patients. METHODS: We investigated the relationship between baseline pituitary volume and symptomatic treatment response over 12 weeks using mixed model analysis in a sample of 42 drug-naïve or early treated FEP patients who participated in a controlled dose-finding study of quetiapine fumarate. Logistic regression was used to examine predictors of treatment response. Pituitary volume was measured from magnetic resonance imaging scans that were obtained upon entry into the trial. RESULTS: Larger pituitary volume was associated with less improvement in overall psychotic symptoms (Brief Psychiatric Rating Scale (BPRS) P=0.031) and positive symptoms (BPRS positive symptom subscale P=0.010). Regardless of gender, patients with a pituitary volume at the 25th percentile (413 mm(3)) were approximately three times more likely to respond to treatment by week 12 than those at the 75th percentile (635 mm(3)) (odds ratio=3.07, CI: 0.90-10.48). CONCLUSION: The association of baseline pituitary volumes with early treatment response highlights the importance of the HPA axis in emerging psychosis. Potential implications for treatment strategies in early psychosis are discussed.

An MRI study of pituitary volume and parasuicidal behavior in teenagers with first-presentation borderline personality disorder

This structural magnetic resonance imaging study examined the relationship between pituitary gland volume (PGV) and lifetime number of parasuicidal behaviors in a first-presentation, teenage borderline personality disorder (BPD) sample with minimal exposure to treatment. Hierarchical regression analysis revealed that age and number of parasuicidal behaviors were significant predictors of PGV. These findings indicate that parasuicidal behavior in BPD might be associated with greater activation of the hypothalamic-pituitary-adrenal (HPA) axis. Further studies are required using direct neuroendocrine measures and exploring other parameters of self-injurious behavior, such as recency of self-injurious behavior, intent to die and medical threat.

Pituitary volume in teenagers with first-presentation borderline personality disorder

This study used magnetic resonance imaging to examine pituitary gland volume (PGV) in teenage patients with a first presentation of borderline personality disorder (BPD). No difference in PGV was observed between healthy controls (n=20) and the total BPD cohort (n=20). However, within the BPD cohort, those exposed to childhood trauma (n=9) tended to have smaller pituitaries (-18%) than those with no history of childhood trauma (n=10). These preliminary findings suggest that exposure to childhood trauma, rather than BPD, per se, might be associated with reduced PGV, possibly reflecting hypothalamic-pituitary-adrenal axis dysfunction.

Pituitary volume predicts future transition to psychosis in individuals at ultra-high risk of developing psychosis

Background We examined pituitary volume before the onset of psychosis in subjects who were at ultra-high risk (UHR) for developing psychosis. Methods Pituitary volume was measured on 1.5-mm, coronal, 1.5-T magnetic resonance images in 94 UHR subjects recruited from admissions to the Personal Assessment and Crisis Evaluation Clinic in Melbourne, Australia and in 49 healthy control subjects. The UHR subjects were scanned at baseline and were followed clinically for a minimum of 1 year to detect transition to psychosis. Results Within the UHR group, a larger baseline pituitary volume was a significant predictor of future transition to psychosis. The UHR subjects who later went on to develop psychosis (UHR-P, n = 31) had a significantly larger (+12%; p = .001) baseline pituitary volume compared with UHR subjects who did not go on to develop psychosis (UHR-NP, n = 63). The survival analysis conducted by Cox regression showed that the risk of developing psychosis during the follow-up increased by 20% for every 10% increase in baseline pituitary volume (p = .002). Baseline pituitary volume of the UHR-NP subjects was smaller not only compared with UHR-P (as described above) but also compared with control subjects (−6%; p = .032). Conclusions The phase before the onset of psychosis is associated with a larger pituitary volume, suggesting activation of the HPA axis.

Left ventricular volume and valve gradient analysis using an Apple Macintosh computer

A description of a computer program to analyse cine angiograms of the heart and pressure waveforms to calculate valve gradients.

The Cougar Point tuff: Implications for thermochemical zonation and longevity of high-temperature, large-volume silicic magmas of the Miocene Yellowstone hotspot

The 12.7-10.5 Ma Cougar Point Tuff in southern Idaho, USA, consists of 10 large-volume (>10²-10³ km³ each), high-temperature (800-1000 °C), rhyolitic ash-flow tuffs erupted from the Bruneau-Jarbidge volcanic center of the Yellowstone hotspot. These tuffs provide evidence for compositional and thermal zonation in pre-eruptive rhyolite magma, and suggest the presence of a long-lived reservoir that was tapped by numerous large explosive eruptions. Pyroxene compositions exhibit discrete compositional modes with respect to Fe and Mg that define a linear spectrum punctuated by conspicuous gaps. Airfall glass compositions also cluster into modes, and the presence of multiple modes indicates tapping of different magma volumes during early phases of eruption. Equilibrium assemblages of pigeonite and augite are used to reconstruct compositional and thermal gradients in the pre-eruptive reservoir. The recurrence of identical compositional modes and of mineral pairs equilibrated at high temperatures in successive eruptive units is consistent with the persistence of their respective liquids in the magma reservoir. Recurrence intervals of identical modes range from 0.3 to 0.9 Myr and suggest possible magma residence times of similar duration. Eruption ages, magma temperatures, Nd isotopes, and pyroxene and glass compositions are consistent with a long-lived, dynamically evolving magma reservoir that was chemically and thermally zoned and composed of multiple discrete magma volumes.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Alzheimer's disease risk gene, GAB2, is associated with regional brain volume differences in 755 young healthy twins

The development of late-onset Alzheimer's disease (LOAD) is under strong genetic control and there is great interest in the genetic variants that confer increased risk. The Alzheimer's disease risk gene, growth factor receptor bound protein 2-associated protein (GAB2), has been shown to provide a 1.27- 1.51 increased odds of developing LOAD for rs7101429 major allele carriers, in case-control analysis. GAB2 is expressed across the brain throughout life, and its role in LOAD pathology is well understood. Recent studies have begun to examine the effect of genetic variation in the GAB2 gene on differences in the brain. However, the effect of GAB2 on the young adult brain has yet to be considered. Here we found a significant association between the GAB2 gene and morphological brain differences in 755 young adult twins (469 females) (M = 23.1, SD = 3.1 years), using a gene-based test with principal components regression (PCReg). Detectable differences in brain morphology are therefore associated with variation in the GAB2 gene, even in young adults, long before the typical age of onset of Alzheimer's disease.

Exhaustive search of the SNP-sNP interactome identifies epistatic effects on brain volume in two cohorts

The SNP-SNP interactome has rarely been explored in the context of neuroimaging genetics mainly due to the complexity of conducting approximately 10(11) pairwise statistical tests. However, recent advances in machine learning, specifically the iterative sure independence screening (SIS) method, have enabled the analysis of datasets where the number of predictors is much larger than the number of observations. Using an implementation of the SIS algorithm (called EPISIS), we used exhaustive search of the genome-wide, SNP-SNP interactome to identify and prioritize SNPs for interaction analysis. We identified a significant SNP pair, rs1345203 and rs1213205, associated with temporal lobe volume. We further examined the full-brain, voxelwise effects of the interaction in the ADNI dataset and separately in an independent dataset of healthy twins (QTIM). We found that each additional loading in the epistatic effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both the ADNI and QTIM samples.

Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects

Deficits in lentiform nucleus volume and morphometry are implicated in a number of genetically influenced disorders, including Parkinson's disease, schizophrenia, and ADHD. Here we performed genome-wide searches to discover common genetic variants associated with differences in lentiform nucleus volume in human populations. We assessed structural MRI scans of the brain in two large genotyped samples: the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 706) and the Queensland Twin Imaging Study (QTIM; N = 639). Statistics of association from each cohort were combined meta-analytically using a fixed-effects model to boost power and to reduce the prevalence of false positive findings. We identified a number of associations in and around the flavin-containing monooxygenase (FMO) gene cluster. The most highly associated SNP, rs1795240, was located in the FMO3 gene; after meta-analysis, it showed genome-wide significant evidence of association with lentiform nucleus volume (PMA = 4. 79 × 10-8). This commonly-carried genetic variant accounted for 2. 68 % and 0. 84 % of the trait variability in the ADNI and QTIM samples, respectively, even though the QTIM sample was on average 50 years younger. Pathway enrichment analysis revealed significant contributions of this gene to the cytochrome P450 pathway, which is involved in metabolizing numerous therapeutic drugs for pain, seizures, mania, depression, anxiety, and psychosis. The genetic variants we identified provide replicated, genome-wide significant evidence for the FMO gene cluster's involvement in lentiform nucleus volume differences in human populations.

The contribution of genes to cortical thickness and volume

We analyzed brain MRI data from 372 young adult twins toidentify cortical regions in which gray matter thickness and volume are influenced by genetics. This was achieved using an A/C/E structural equation model that divides the variance of these traits, at each point on the cortex, into additive genetic (A), shared (C), and unique environmental (E) components. A strong genetic influencewas found in frontal and parietal regions. Inaddition, we correlated cortical thickness with full-scale intelligence quotient for comparison with the A/C/E maps, and several regions where cortical structure was correlated with intelligence quotient are under genetic control. These cortical measures may be useful phenotypes to narrow the searchfor quantitative trait lociinfluencing brain structure.

A new combined surface and volume registration

3D registration of brain MRI data is vital for many medical imaging applications. However, purely intensitybased approaches for inter-subject matching of brain structure are generally inaccurate in cortical regions, due to the highly complex network of sulci and gyri, which vary widely across subjects. Here we combine a surfacebased cortical registration with a 3D fluid one for the first time, enabling precise matching of cortical folds, but allowing large deformations in the enclosed brain volume, which guarantee diffeomorphisms. This greatly improves the matching of anatomy in cortical areas. The cortices are segmented and registered with the software Freesurfer. The deformation field is initially extended to the full 3D brain volume using a 3D harmonic mapping that preserves the matching between cortical surfaces. Finally, these deformation fields are used to initialize a 3D Riemannian fluid registration algorithm, that improves the alignment of subcortical brain regions. We validate this method on an MRI dataset from 92 healthy adult twins. Results are compared to those based on volumetric registration without surface constraints; the resulting mean templates resolve consistent anatomical features both subcortically and at the cortex, suggesting that the approach is well-suited for cross-subject integration of functional and anatomic data.