Genome-wide association study of primary tooth eruption identifies pleiotropic loci associated with height and craniofacial distances

Twin and family studies indicate that the timing of primary tooth eruption is highly heritable, with estimates typically exceeding 80%. To identify variants involved in primary tooth eruption we performed a population based genome-wide association study of ‘age at first tooth’ and ‘number of teeth’ using 5998 and 6609 individuals respectively from the Avon Longitudinal Study of Parents and Children (ALSPAC) and 5403 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966). We tested 2,446,724 SNPs imputed in both studies. Analyses were controlled for the effect of gestational age, sex and age of measurement. Results from the two studies were combined using fixed effects inverse variance meta-analysis. We identified a total of fifteen independent loci, with ten loci reaching genome-wide significance (p<5x10−8) for ‘age at first tooth’ and eleven loci for ‘number of teeth’. Together these associations explain 6.06% of the variation in ‘age of first tooth’ and 4.76% of the variation in ‘number of teeth’. The identified loci included eight previously unidentified loci, some containing genes known to play a role in tooth and other developmental pathways, including a SNP in the protein-coding region of BMP4 (rs17563, P= 9.080x10−17). Three of these loci, containing the genes HMGA2, AJUBA and ADK, also showed evidence of association with craniofacial distances, particularly those indexing facial width. Our results suggest that the genome-wide association approach is a powerful strategy for detecting variants involved in tooth eruption, and potentially craniofacial growth and more generally organ development

Oxidation products of biogenic emissions contribute to nucleation of atmospheric particles

Atmospheric new-particle formation affects climate and is one of the least understood atmospheric aerosol processes. The complexity and variability of the atmosphere has hindered elucidation of the fundamental mechanism of new-particle formation from gaseous precursors. We show, in experiments performed with the CLOUD (Cosmics Leaving Outdoor Droplets) chamber at CERN, that sulfuric acid and oxidized organic vapors at atmospheric concentrations reproduce particle nucleation rates observed in the lower atmosphere. The experiments reveal a nucleation mechanism involving the formation of clusters containing sulfuric acid and oxidized organic molecules from the very first step. Inclusion of this mechanism in a global aerosol model yields a photochemically and biologically driven seasonal cycle of particle concentrations in the continental boundary layer, in good agreement with observations

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Efficacy of progressive aquatic resistance training for tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis : a randomised controlled trial

Objective: To study the efficacy of aquatic resistance training on biochemical composition of tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis (OA). Design: Eighty seven volunteer postmenopausal women, aged 60-68 years, with mild knee OA (Kellgren-Lawrence grades I/II and knee pain) were recruited and randomly assigned to an intervention (n = 43) and control (n = 44) group. The intervention group participated in 48 supervised aquatic resistance training sessions over 16 weeks while the control group maintained usual level of physical activity. The biochemical composition of the medial and lateral tibiofemoral cartilage was estimated using single-slice transverse relaxation time (T2) mapping and delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC index). Secondary outcomes were cardiorespiratory fitness, isometric knee extension and flexion force and knee injury and OA outcome (KOOS) questionnaire. Results: After 4-months aquatic training, there was a significant decrease in both T2 -1.2 ms (95% confidence interval (CI): -2.3 to -0.1, P = 0.021) and dGEMRIC index -23 ms (-43 to -3, P = 0.016) in the training group compared to controls in the full thickness posterior region of interest (ROI) of the medial femoral cartilage. Cardiorespiratory fitness significantly improved in the intervention group by 9.8% (P = 0.010). Conclusions: Our results suggest that, in postmenopausal women with mild knee OA, the integrity of the collagen-interstitial water environment (T2) of the tibiofemoral cartilage may be responsive to low shear and compressive forces during aquatic resistance training. More research is required to understand the exact nature of acute responses in dGEMRIC index to this type of loading. Further, aquatic resistance training improves cardiorespiratory fitness. (C) 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.Peer reviewe

Influence of tooth loss on mandibular morphology: A cone-beam computed tomography study

Background: Tooth loss adversely affects patients’ health and psychosocial wellbeing. In addition, it changes mandibular morphology. Objective: To evaluate the effect of tooth loss, age, and gender on mandibular morphology. Materials and Methods: Cone-beam computed tomographic (CBCT) scans of 101 patients were examined to measure the gonial angle (GA), ramus height (RH) and condylar height (CH). Patients’ age, gender, and dental status were recorded. Repeated measures analysis of variance (ANOVA) was used to assess the impact of gender, age, and tooth loss on the GA, RH and CH. The mean measurements of the GA, RH and CH were compared between dentate/edentulous patients after splitting by gender. Results: The GA was larger in edentulous patients compared to dentate ones, in females than in males, and in older than in younger. RH on the right side was significantly longer than on the left side (P< 0.0001), and also longer in males and younger patients. CH was shorter in younger than in older patients and in dentate than in edentulous patients. Conclusions: Tooth loss is associated with changes in mandibular morphology and its prevention would avoid these irreversible changes.</p

Joint inflammation related citrullination of functional arginines in extracellular proteins

We report the extent, specific sites and structural requirements of joint inflammation related citrullination in extracellular proteins. A total of 40 synovial fluid samples derived from chronically inflamed human joints were analysed by heparin-agarose fractionation and LC-MS/MS. Citrullination of 55 arginines in extracellular proteins was detected. Importantly, 20% of the sites have a characterized function related to the hallmarks of destructive joint inflammation. E.g. four arginine residues, shown here to be citrullinated, are also affected by mutations in inherited diseases causing haemolysis or blood clotting dysfunction. Citrullination of integrin ligands was selected for further studies since fibronectin R234 in isoDGR was among the most frequently citrullinated arginines in synovial fluid. Assays with synovial fibroblasts and integrin alpha V beta 3 indicated decreased affinity to the enzymatically citrullinated integrin binding sites. To conclude, our data indicate that in inflamed joints extensive citrullination affects the functional arginine residues in extracellular proteins

Aging and serum exomiR content in women-effects of estrogenic hormone replacement therapy

Exosomes participate in intercellular messaging by transporting bioactive lipid-, protein-and RNA-molecules and -complexes. The contents of the exosomes reflect the physiological status of an individual making exosomes promising targets for biomarker analyses. In the present study we extracted exosome microRNAs (exomiRs) from serum samples of premenopausal women (n = 8) and monozygotic postmenopausal twins (n = 10 female pairs), discordant for the use of estrogenic hormone replacement therapy (HRT), in order to see whether the age or/and the use of HRT associates with exomiR content. A total of 241 exomiRs were detected by next generation sequencing, 10 showing age, 14 HRT and 10 age + HRT-related differences. When comparing the groups, differentially expressed miRs were predicted to affect cell proliferation processes showing inactivation with younger age and HRT usage. MiR-106-5p, -148a-3p, -27-3p, -126-5p, -28-3p and -30a-5p were significantly associated with serum 17 beta-estradiol. MiRs formed two hierarchical clusters being indicative of positive or negative health outcomes involving associations with body composition, serum 17 beta-estradiol, fat-, glucose-and inflammatory markers. Circulating exomiR clusters, obtained by NGS, could be used as indicators of metabolic and inflammatory status affected by hormonal changes at menopause. Furthermore, the individual effects of HRT-usage could be evaluated based on the serum exomiR signature

A machine learning approach based on generative topographic mapping for disruption prevention and avoidance at JET

The need for predictive capabilities greater than 95% with very limited false alarms are demanding requirements for reliable disruption prediction systems in tokamaks such as JET or, in the near future, ITER. The prediction of an upcoming disruption must be provided sufficiently in advance in order to apply effective disruption avoidance or mitigation actions to prevent the machine from being damaged. In this paper, following the typical machine learning workflow, a generative topographic mapping (GTM) of the operational space of JET has been built using a set of disrupted and regularly terminated discharges. In order to build the predictive model, a suitable set of dimensionless, machine-independent, physics-based features have been synthesized, which make use of 1D plasma profile information, rather than simple zero-D time series. The use of such predicting features, together with the power of the GTM in fitting the model to the data, obtains, in an unsupervised way, a 2D map of the multi-dimensional parameter space of JET, where it is possible to identify a boundary separating the region free from disruption from the disruption region. In addition to helping in operational boundaries studies, the GTM map can also be used for disruption prediction exploiting the potential of the developed GTM toolbox to monitor the discharge dynamics. Following the trajectory of a discharge on the map throughout the different regions, an alarm is triggered depending on the disruption risk of these regions. The proposed approach to predict disruptions has been evaluated on a training and an independent test set and achieves very good performance with only one tardive detection and a limited number of false detections. The warning times are suitable for avoidance purposes and, more important, the detections are consistent with physical causes and mechanisms that destabilize the plasma leading to disruptions.Peer reviewe