Pfeiffer syndrome

Pfeiffer syndrome is a rare autosomal dominantly inherited disorder that associates craniosynostosis, broad and deviated thumbs and big toes, and partial syndactyly on hands and feet. Hydrocephaly may be found occasionally, along with severe ocular proptosis, ankylosed elbows, abnormal viscera, and slow development. Based on the severity of the phenotype, Pfeiffer syndrome is divided into three clinical subtypes. Type 1 "classic" Pfeiffer syndrome involves individuals with mild manifestations including brachycephaly, midface hypoplasia and finger and toe abnormalities; it is associated with normal intelligence and generally good outcome. Type 2 consists of cloverleaf skull, extreme proptosis, finger and toe abnormalities, elbow ankylosis or synostosis, developmental delay and neurological complications. Type 3 is similar to type 2 but without a cloverleaf skull. Clinical overlap between the three types may occur. Pfeiffer syndrome affects about 1 in 100,000 individuals. The disorder can be caused by mutations in the fibroblast growth factor receptor genes FGFR-1 or FGFR-2. Pfeiffer syndrome can be diagnosed prenatally by sonography showing craniosynostosis, hypertelorism with proptosis, and broad thumb, or molecularly if it concerns a recurrence and the causative mutation was found. Molecular genetic testing is important to confirm the diagnosis. Management includes multiple-staged surgery of craniosynostosis. Midfacial surgery is performed to reduce the exophthalmos and the midfacial hypoplasia

Quantifying the improvement of surrogate indices of hepatic insulin resistance using complex measurement techniques

We evaluated the ability of simple and complex surrogate-indices to identify individuals from an overweight/obese cohort with hepatic insulin-resistance (HEP-IR). Five indices, one previously defined and four newly generated through step-wise linear regression, were created against a single-cohort sample of 77 extensively characterised participants with the metabolic syndrome (age 55.6±1.0 years, BMI 31.5±0.4 kg/m2; 30 males). HEP-IR was defined by measuring endogenous-glucose-production (EGP) with [6–62H2] glucose during fasting and euglycemic-hyperinsulinemic clamps and expressed as EGP*fasting plasma insulin. Complex measures were incorporated into the model, including various non-standard biomarkers and the measurement of body-fat distribution and liver-fat, to further improve the predictive capability of the index. Validation was performed against a data set of the same subjects after an isoenergetic dietary intervention (4 arms, diets varying in protein and fiber content versus control). All five indices produced comparable prediction of HEP-IR, explaining 39–56% of the variance, depending on regression variable combination. The validation of the regression equations showed little variation between the different proposed indices (r2 = 27–32%) on a matched dataset. New complex indices encompassing advanced measurement techniques offered an improved correlation (r = 0.75, P<0.001). However, when validated against the alternative dataset all indices performed comparably with the standard homeostasis model assessment for insulin resistance (HOMA-IR) (r = 0.54, P<0.001). Thus, simple estimates of HEP-IR performed comparable to more complex indices and could be an efficient and cost effective approach in large epidemiological investigations

Cross-sectional associations between sleep duration, sedentary time, physical activity, and adiposity indicators among Canadian preschool-aged children using compositional analyses

Abstract Background Sleep duration, sedentary behaviour, and physical activity are three co-dependent behaviours that fall on the movement/non-movement intensity continuum. Compositional data analyses provide an appropriate method for analyzing the association between co-dependent movement behaviour data and health indicators. The objectives of this study were to examine: (1) the combined associations of the composition of time spent in sleep, sedentary behaviour, light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) with adiposity indicators; and (2) the association of the time spent in sleep, sedentary behaviour, LPA, or MVPA with adiposity indicators relative to the time spent in the other behaviours in a representative sample of Canadian preschool-aged children. Methods Participants were 552 children aged 3 to 4 years from cycles 2 and 3 of the Canadian Health Measures Survey. Sedentary time, LPA, and MVPA were measured with Actical accelerometers (Philips Respironics, Bend, OR USA), and sleep duration was parental reported. Adiposity indicators included waist circumference (WC) and body mass index (BMI) z-scores based on World Health Organization growth standards. Compositional data analyses were used to examine the cross-sectional associations. Results The composition of movement behaviours was significantly associated with BMI z-scores (p = 0.006) but not with WC (p = 0.718). Further, the time spent in sleep (BMI z-score: γ sleep  = −0.72; p = 0.138; WC: γ sleep  = −1.95; p = 0.285), sedentary behaviour (BMI z-score: γ SB  = 0.19; p = 0.624; WC: γ SB  = 0.87; p = 0.614), LPA (BMI z-score: γ LPA  = 0.62; p = 0.213, WC: γ LPA  = 0.23; p = 0.902), or MVPA (BMI z-score: γ MVPA  = −0.09; p = 0.733, WC: γ MVPA  = 0.08; p = 0.288) relative to the other behaviours was not significantly associated with the adiposity indicators. Conclusions This study is the first to use compositional analyses when examining associations of co-dependent sleep duration, sedentary time, and physical activity behaviours with adiposity indicators in preschool-aged children. The overall composition of movement behaviours appears important for healthy BMI z-scores in preschool-aged children. Future research is needed to determine the optimal movement behaviour composition that should be promoted in this age group

Micro Soft Tissues Visualization Based on X-Ray Phase-Contrast Imaging

The current imaging methods have a limited ability to visualize microstructures of biological soft tissues. Small lesions cannot be detected at the early stage of the disease. Phase contrast imaging (PCI) is a novel non-invasive imaging technique that can provide high contrast images of soft tissues by the use of X-ray phase shift. It is a new choice in terms of non-invasively revealing soft tissue details. In this study, the lung and hepatic fibrosis models of mice and rats were used to investigate the ability of PCI in microstructures observation of soft tissues. Our results demonstrated that different liver fibrosis stages could be distinguished non-invasively by PCI. The three-dimensional morphology of a segment of blood vessel was constructed. Noteworthy, the blood clot inside the vessel was visualized in three dimensions which provided a precise description of vessel stenosis. Furthermore, the whole lung airways including the alveoli were obtained. We had specifically highlighted its use in the visualization and assessment of the alveoli. To our knowledge, this was the first time for non-invasive alveoli imaging using PCI. This finding may offer a new perspective on the diagnosis of respiratory disease. All the results confirmed that PCI will be a valuable tool in biological soft tissues imaging

Folate catabolites in spot urine as non-invasive biomarkers of folate status during habitual intake and folic acid supplementation.

Folate status, as reflected by red blood cell (RCF) and plasma folates (PF), is related to health and disease risk. Folate degradation products para-aminobenzoylglutamate (pABG) and para-acetamidobenzoylglutamate (apABG) in 24 hour urine have recently been shown to correlate with blood folate. Since blood sampling and collection of 24 hour urine are cumbersome, we investigated whether the determination of urinary folate catabolites in fasted spot urine is a suitable non-invasive biomarker for folate status in subjects before and during folic acid supplementation. Immediate effects of oral folic acid bolus intake on urinary folate catabolites were assessed in a short-term pre-study. In the main study we included 53 healthy men. Of these, 29 were selected for a 12 week folic acid supplementation (400 µg). Blood, 24 hour and spot urine were collected at baseline and after 6 and 12 weeks and PF, RCF, urinary apABG and pABG were determined. Intake of a 400 µg folic acid bolus resulted in immediate increase of urinary catabolites. In the main study pABG and apABG concentrations in spot urine correlated well with their excretion in 24 hour urine. In healthy men consuming habitual diet, pABG showed closer correlation with PF (rs = 0.676) and RCF (rs = 0.649) than apABG (rs = 0.264, ns and 0.543). Supplementation led to significantly increased folate in plasma and red cells as well as elevated urinary folate catabolites, while only pABG correlated significantly with PF (rs = 0.574) after 12 weeks. Quantification of folate catabolites in fasted spot urine seems suitable as a non-invasive alternative to blood or 24 hour urine analysis for evaluation of folate status in populations consuming habitual diet. In non-steady-state conditions (folic acid supplementation) correlations between folate marker (RCF, PF, urinary catabolites) decrease due to differing kinetics

Regulation of Ubx Expression by Epigenetic Enhancer Silencing in Response to Ubx Levels and Genetic Variation

For gene products that must be present in cells at defined concentrations, expression levels must be tightly controlled to ensure robustness against environmental, genetic, and developmental noise. By studying the regulation of the concentration-sensitive Drosophila melanogaster Hox gene Ultrabithorax (Ubx), we found that Ubx enhancer activities respond to both increases in Ubx levels and genetic background. Large, transient increases in Ubx levels are capable of silencing all enhancer input into Ubx transcription, resulting in the complete silencing of this gene. Small increases in Ubx levels, brought about by duplications of the Ubx locus, cause sporadic silencing of subsets of Ubx enhancers. Ubx enhancer silencing can also be induced by outcrossing laboratory stocks to D. melanogaster strains established from wild flies from around the world. These results suggest that enhancer activities are not rigidly determined, but instead are sensitive to genetic background. Together, these findings suggest that enhancer silencing may be used to maintain gene product levels within the correct range in response to natural genetic variation

Evolution under Fluctuating Environments Explains Observed Robustness in Metabolic Networks

A high level of robustness against gene deletion is observed in many organisms. However, it is still not clear which biochemical features underline this robustness and how these are acquired during evolution. One hypothesis, specific to metabolic networks, is that robustness emerges as a byproduct of selection for biomass production in different environments. To test this hypothesis we performed evolutionary simulations of metabolic networks under stable and fluctuating environments. We find that networks evolved under the latter scenario can better tolerate single gene deletion in specific environments. Such robustness is underlined by an increased number of independent fluxes and multifunctional enzymes in the evolved networks. Observed robustness in networks evolved under fluctuating environments was “apparent,” in the sense that it decreased significantly as we tested effects of gene deletions under all environments experienced during evolution. Furthermore, when we continued evolution of these networks under a stable environment, we found that any robustness they had acquired was completely lost. These findings provide evidence that evolution under fluctuating environments can account for the observed robustness in metabolic networks. Further, they suggest that organisms living under stable environments should display lower robustness in their metabolic networks, and that robustness should decrease upon switching to more stable environments

Single neuron transcriptomics identify SRSF/ SR protein B52 as a regulator of axon growth and Choline acetyltransferase splicing.

We removed single identified neurons from living Drosophila embryos to gain insight into the transcriptional control of developing neuronal networks. The microarray analysis of the transcriptome of two sibling neurons revealed seven differentially expressed transcripts between both neurons (threshold: log(2)1.4). One transcript encodes the RNA splicing factor B52. Loss of B52 increases growth of axon branches. B52 function is also required for Choline acetyltransferase (ChAT ) splicing. At the end of embryogenesis, loss of B52 function impedes splicing of ChAT, reduces acetylcholine synthesis, and extends the period of uncoordinated muscle twitches during larval hatching. ChAT regulation by SRSF proteins may be a conserved feature since changes in SRSF5 expression and increased acetylcholine levels in brains of bipolar disease patients have been reported recently

Understanding the Adaptive Growth Strategy of Lactobacillus plantarum by In Silico Optimisation

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy