Mutation spectrum of MLL2 in a cohort of Kabuki syndrome patients.

ABSTRACT: BACKGROUND: Kabuki syndrome (Niikawa-Kuroki syndrome) is a rare, multiple congenital anomalies/mental retardation syndrome characterized by a peculiar face, short stature, skeletal, visceral and dermatoglyphic abnormalities, cardiac anomalies, and immunological defects. Recently mutations in the histone methyl transferase MLL2 gene have been identified as its underlying cause. METHODS: Genomic DNAs were extracted from 62 index patients clinically diagnosed as affected by Kabuki syndrome. Sanger sequencing was performed to analyze the whole coding region of the MLL2 gene including intron-exon junctions. The putative causal and possible functional effect of each nucleotide variant identified was estimated by in silico prediction tools. RESULTS: We identified 45 patients with MLL2 nucleotide variants. 38 out of the 42 variants were never described before. Consistently with previous reports, the majority are nonsense or frameshift mutations predicted to generate a truncated polypeptide. We also identified 3 indel, 7 missense and 3 splice site. CONCLUSIONS: This study emphasizes the relevance of mutational screening of the MLL2 gene among patients diagnosed with Kabuki syndrome. The identification of a large spectrum of MLL2 mutations possibly offers the opportunity to improve the actual knowledge on the clinical basis of this multiple congenital anomalies/mental retardation syndrome, design functional studies to understand the molecular mechanisms underlying this disease, establish genotype-phenotype correlations and improve clinical management.

Imaging spectrum of the operated bladder : P41

Multiple complex procedures involving the bladder have been developed by surgeons in both children and adults, with their own advantages and drawbacks. A greater knowledge of the anatomic changes induced by each category of procedure is mandatory in the follow-up of patients and detection of early and late postoperative complications. A retrospective review of 50 pediatric and adult patients referred or treated in our institution is presented. The combined use of plain films, IVP, MCUG, US, Doppler US, CT, 3DCT and MRI is described. The imaging features are compared with surgical and anatomopathological findings. The purpose of this pictorial essay is to present a wide spectrum of diagnostic imaging findings in children and adult patients with operated bladder. The imaging features of surgical procedures with preserved, partially replaced and totally replaced bladder are described, with emphasis on a systematic multimodality approach. Learning objectives: 1) To provide an in-depth review of bladder surgical procedures with their indications, anatomopathological and imaging features. 2) To describe optimal multimodality imaging techniques for evaluating the operated bladder.

Microvascular burden and Alzheimer-type lesions across the age spectrum.

The occurrence of microvascular and small macrovascular lesions and Alzheimer's disease (AD)-related pathology in the aging human brain is a well-described phenomenon. Although there is a wide consensus about the relationship between macroscopic vascular lesions and incident dementia, the cognitive consequences of the progressive accumulation of these small vascular lesions in the human brain are still a matter of debate. Among the vast group of small vessel-related forms of ischemic brain injuries, the present review discusses the cognitive impact of cortical microinfarcts, subcortical gray matter and deep white matter lacunes, periventricular and diffuse white matter demyelinations, and focal or diffuse gliosis in old age. A special focus will be on the sub-types of microvascular lesions not detected by currently available neuroimaging studies in routine clinical settings. After providing a critical overview of in vivo data on white matter demyelinations and lacunes, we summarize the clinicopathological studies performed by our center in large cohorts of individuals with microvascular lesions and concomitant AD-related pathology across two age ranges (the younger old, 65-85 years old, versus the oldest old, nonagenarians and centenarians). In conjunction with other autopsy datasets, these observations fully support the idea that cortical microinfarcts are the only consistent determinant of cognitive decline across the entire spectrum from pure vascular cases to cases with combined vascular and AD lesion burden.

The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

A fully adaptive numerical approximation for a two-dimensional epidemic model with nonlinear cross-diffusion

An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

When genetic load does not correlate with phenotypic spectrum: lessons from the GnRH receptor (GNRHR).

CONTEXT: A broad spectrum of GnRH-deficient phenotypes has been identified in individuals with both mono- and biallelic GNRHR mutations. OBJECTIVE: The objective of the study was to determine the correlation between the severity of the reproductive phenotype(s) and the number and functional severity of rare sequence variants in GNRHR. SUBJECTS: Eight hundred sixty-three probands with different forms of GnRH deficiency, 46 family members and 422 controls were screened for GNRHR mutations. The 70 subjects (32 patients and 38 family members) harboring mutations were divided into four groups (G1-G4) based on the functional severity of the mutations (complete or partial loss of function) and the number of affected alleles (monoallelic or biallelic) with mutations, and these classes were mapped on their clinical phenotypes. RESULTS: The prevalence of heterozygous rare sequence variants in GNRHR was significantly higher in probands vs. controls (P < 0.01). Among the G1-G3 groups (homozygous subjects with successively decreasing severity and number of mutations), the hypogonadotropic phenotype related to their genetic load. In contrast, subjects in G4, with only monoallelic mutations, demonstrated a greater diversity of clinical phenotypes. CONCLUSIONS: In patients with GnRH deficiency and biallelic mutations in GNRHR, genetic burden defined by severity and dose is associated with clinical phenotype. In contrast, for patients with monoallelic GNRHR mutations this correlation does not hold. Taken together, these data indicate that as-yet-unidentified genetic and/or environmental factors may combine with singly mutated GNRHR alleles to produce reproductive phenotypes.

Brain volumetric correlates of autism spectrum disorder symptoms in attention deficit/hyperactivity disorder.

Autism spectrum disorder (ASD) symptoms frequently occur in subjects with attention deficit/hyperactivity disorder (ADHD). While there is evidence that both ADHD and ASD have differential structural correlates, no study to date has investigated these structural correlates within a framework that robustly accounts for the phenotypic overlap between the two disorders. The presence of ASD symptoms was measured by the parent-reported Children's Social and Behavioural Questionnaire (CSBQ) in ADHD subjects (n = 180), their unaffected siblings (n = 118) and healthy controls (n = 146). ADHD symptoms were assessed by a structured interview (K-SADS-PL) and the Conners' ADHD questionnaires. Whole brain T1-weighted MPRAGE images were acquired and the structural MRI correlates of ASD symptom scores were analysed by modelling ASD symptom scores against white matter (WM) and grey matter (GM) volumes using mixed effects models which controlled for ADHD symptom levels. ASD symptoms were significantly elevated in ADHD subjects relative to both controls and unaffected siblings. ASD scores were predicted by the interaction between WM and GM volumes. Increasing ASD score was associated with greater GM volume. Equivocal results from previous structural studies in ADHD and ASD may be due to the fact that comorbidity has not been taken into account in studies to date. The current findings stress the need to account for issues of ASD comorbidity in ADHD.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

Linear and nonlinear optical properties of Si nanocrystals in SiO2 deposited by plasma-enhanced chemical-vapor deposition

Linear and nonlinear optical properties of silicon suboxide SiOx films deposited by plasma-enhanced chemical-vapor deposition have been studied for different Si excesses up to 24¿at.¿%. The layers have been fully characterized with respect to their atomic composition and the structure of the Si precipitates. Linear refractive index and extinction coefficient have been determined in the whole visible range, enabling to estimate the optical bandgap as a function of the Si nanocrystal size. Nonlinear optical properties have been evaluated by the z-scan technique for two different excitations: at 0.80¿eV in the nanosecond regime and at 1.50¿eV in the femtosecond regime. Under nanosecond excitation conditions, the nonlinear process is ruled by thermal effects, showing large values of both nonlinear refractive index (n2 ~ ¿10¿8¿cm2/W) and nonlinear absorption coefficient (ß ~ 10¿6¿cm/W). Under femtosecond excitation conditions, a smaller nonlinear refractive index is found (n2 ~ 10¿12¿cm2/W), typical of nonlinearities arising from electronic response. The contribution per nanocrystal to the electronic third-order nonlinear susceptibility increases as the size of the Si nanoparticles is reduced, due to the appearance of electronic transitions between discrete levels induced by quantum confinement.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

The complete Raman spectrum of nanometric SnO2 particles

The complete Raman spectrum of SnO2 nanoparticles in presented and analyzed. In addition to the "classical" modes observed in the rutile structure, two other regions shown Raman activity for nanoparticles. The Raman bands in the low-frequency region are attributed to acoustic modes associated with the vibration of the individual nanoparticle as a whole. The high-frequency region is activated by surface disorder. A detailed analysis of these regions and the changes in the normal modes of SnO2 are presented as a function nanoparticle size.

Changes in the use of broad-spectrum antibiotics after withdrawal of cefepime from the market: an interrupted time series analysis

Background and objective: Cefepime was one of the most used broad-spectrum antibiotics in Swiss public acute care hospitals. The drug was withdrawn from market in January 2007, and then replaced by a generic since October 2007. The goal of the study was to evaluate changes in the use of broad-spectrum antibiotics after the withdrawal of the cefepime original product. Design: A generalized regression-based interrupted time series model incorporating autocorrelated errors assessed how much the withdrawal changed the monthly use of other broad-spectrum antibiotics (ceftazidime, imipenem/cilastin, meropenem, piperacillin/ tazobactam) in defined daily doses (DDD)/100 bed-days from January 2004 to December 2008 [1, 2]. Setting: 10 Swiss public acute care hospitals (7 with\200 beds, 3 with 200-500 beds). Nine hospitals (group A) had a shortage of cefepime and 1 hospital had no shortage thanks to importation of cefepime from abroad. Main outcome measures: Underlying trend of use before the withdrawal, and changes in the level and in the trend of use after the withdrawal. Results: Before the withdrawal, the average estimated underlying trend (coefficient b1) for cefepime was decreasing by -0.047 (95% CI -0.086, -0.009) DDD/100 bed-days per month and was significant in three hospitals (group A, P\0.01). Cefepime withdrawal was associated with a significant increase in level of use (b2) of piperacillin/tazobactam and imipenem/cilastin in, respectively, one and five hospitals from group A. After the withdrawal, the average estimated trend (b3) was greatest for piperacillin/tazobactam (+0.043 DDD/100 bed-days per month; 95% CI -0.001, 0.089) and was significant in four hospitals from group A (P\0.05). The hospital without drug shortage showed no significant change in the trend and the level of use. The hypothesis of seasonality was rejected in all hospitals. Conclusions: The decreased use of cefepime already observed before its withdrawal from the market could be explained by pre-existing difficulty in drug supply. The withdrawal of cefepime resulted in change in level for piperacillin/tazobactam and imipenem/cilastin. Moreover, an increase in trend was found for piperacillin/tazobactam thereafter. As these changes generally occur at the price of lower bacterial susceptibility, a manufacturers' commitment to avoid shortages in the supply of their products would be important. As perspectives, we will measure the impact of the changes in cost and sensitivity rates of these antibiotics.

On the consequences of misspecifing assumptions concerning residuals distribution in a repeated measures and nonlinear mixed modelling context

In this paper we describe the results of a simulation study performed to elucidate the robustness of the Lindstrom and Bates (1990) approximation method under non-normality of the residuals, under different situations. Concerning the fixed effects, the observed coverage probabilities and the true bias and mean square error values, show that some aspects of this inferential approach are not completely reliable. When the true distribution of the residuals is asymmetrical, the true coverage is markedly lower than the nominal one. The best results are obtained for the skew normal distribution, and not for the normal distribution. On the other hand, the results are partially reversed concerning the random effects. Soybean genotypes data are used to illustrate the methods and to motivate the simulation scenarios

Impact of incorrect assumptions on the covariance structure of random effects and/or residuals in nonlinear mixed models for repeated measures data

In this paper we analyse, using Monte Carlo simulation, the possible consequences of incorrect assumptions on the true structure of the random effects covariance matrix and the true correlation pattern of residuals, over the performance of an estimation method for nonlinear mixed models. The procedure under study is the well known linearization method due to Lindstrom and Bates (1990), implemented in the nlme library of S-Plus and R. Its performance is studied in terms of bias, mean square error (MSE), and true coverage of the associated asymptotic confidence intervals. Ignoring other criteria like the convenience of avoiding over parameterised models, it seems worst to erroneously assume some structure than do not assume any structure when this would be adequate.