Syndrome des ovaires polykystiques chez l’adolescente diabétique ou obèse [Polycystic ovary syndrome in obese or type 1 diabetic (T1D) adolescent girls]

Polycystic ovary syndrome (PCOS) is frequent during adolescence (prevalence ≈ 6 %), and the prevalence increases in obese or type 1 diabetic (T1D) adolescent girls. During puberty, PCOS diagnosis is difficult because of the overlap with some pubertal physiologic signs. The 2017 international consortium suggests two required diagnostic criteria: persistent menstrual disturbances and hyperandrogenism. PCOS physiopathology is complex, including interactions between genetic, epigenetic factors, primary ovarian abnormalities, neuroendocrine alterations, hormonal and metabolic factors. Insulin seems to have a central place in obese or T1D adolescent girls. The treatment is still debated and should be monitored according to the main symptoms

A novel CHD7 mutation in an adolescent presenting with growth and pubertal delay.

Mutations in the CHD7 gene, encoding for the chromodomain helicase DNA-binding protein 7, are found in approximately 60% of individuals with CHARGE syndrome (coloboma, heart defects, choanal atresia, retarded growth and development, genital hypoplasia, ear abnormalities and/or hearing loss). Herein, we present a clinical case of a 14-year-old male presenting for evaluation of poor growth and pubertal delay highlighting the diagnostic challenges of CHARGE syndrome. The patient was born full term and underwent surgery at 5 days of life for bilateral choanal atresia. Developmental milestones were normally achieved. At age 14 his height and weight were -2.04 and -1.74 standard deviation score respectively. He had anosmia as well as prepubertal testes and micropenis (4 cm×1 cm). The biological profile showed low basal serum testosterone and gonadotropins (testosterone, 0.2 nmol/L; luteinizing hormone, 0.5 U/L; follicle-stimulating hormone, 1.3 U/L), and otherwise normal pituitary function and normal imaging of the hypothalamic-pituitary area. The constellation of choanal atresia, anosmia, mild dysmorphic features, micropenis and delayed puberty were suggestive of CHARGE syndrome. Targeted genetic testing of CHD7 was performed revealing a de novo heterozygous CHD7 mutation (c.4234T>G [p.Tyr1412Asp]). Further paraclinical investigations confirmed CHARGE syndrome. Despite the presence of suggestive features, CHARGE syndrome remained undiagnosed in this patient until adolescence. Genetic testing helps clarify the phenotypic and genotypic spectrum to facilitate diagnosis, thus promoting optimal follow-up, treatment, and appropriate genetic counselling

Application of machine learning algorithms to the study of noise artifacts in gravitational-wave data

The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitational-wave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high enough rate such that accidental coincidence across multiple detectors is non-negligible. These “glitches” can easily be mistaken for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational waves. We apply machine-learning algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Noise sources may produce artifacts in these auxiliary channels as well as the gravitational-wave channel. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well suited. We demonstrate the feasibility and applicability of three different MLAs: artificial neural networks, support vector machines, and random forests. These classifiers identify and remove a substantial fraction of the glitches present in two different data sets: four weeks of LIGO’s fourth science run and one week of LIGO’s sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth-science-run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar performance to the benchmark algorithm, the ordered veto list, which is optimized to detect pairwise correlations between transients in LIGO auxiliary channels and glitches in the gravitational-wave data. This suggests that most of the useful information currently extracted from the auxiliary channels is already described by this model. Future performance gains are thus likely to involve additional sources of information, rather than improvements in the classification algorithms themselves. We discuss several plausible sources of such new information as well as the ways of propagating it through the classifiers into gravitational-wave searches

Evaluating the stable isotopic composition of phosphate oxygen as a tracer of phosphorus from waste water treatment works

Eutrophication is a globally significant challenge facing freshwater ecosystems and is closely associated with anthropogenic enrichment of phosphorus (P) in the aquatic environment. Phosphorus inputs to rivers are usually dominated by diffuse sources related to farming activities and point sources such as waste water treatment works (WwTW). The limited availability of inherent labels for different P sources has constrained understanding of these triggers for eutrophication in natural systems. There have been substantial recent advances in the use of phosphate oxygen isotopes (δ18OPO4) as a way of understanding phosphate sources and processing. Results from all previous studies of the δ18OPO4 composition of WwTW effluent and septic tanks are combined together with significant new data from the UK to assess δ18OPO4 compositions in waste water sources. The overall average δ18OPO4 value is 13.9‰, ranging from 8.4 to 19.7‰. Values measured in the USA are much lower than those measured in Europe. A strong positive correlation exists between δ18OPO4 and δ18OH2O, suggesting biologically-mediated exchange between the water molecules and the phosphate ions. A comparison of δ18OPO4 and the offset from isotopic equilibrium showed a strong positive linear correlation (ρ = 0.94) for the data from Europe but no relationship for the historic USA data which may be due to recent advances in the extraction procedure or to a relative paucity of data. This offset is most strongly controlled by the δ18OH2O rather than temperature, with greater offsets occurring with lower δ18OH2O. Time series data collected over 8-24 hours for three sites showed that, although there were significant changes in the phosphate concentration, for a given WwTW the δ18OPO4 stayed relatively constant. Two new studies that considered instream processing of δ18OPO4 downstream of WwTWs showed mixing of the upstream source with effluent water but no evidence of biological cycling 3 km downstream. It is suggested that δ18OPO4 can be an effective tool to trace P from WwTWs provided the source of the effluent is known and samples are collected within a day

Experimental and Numerical Modeling of Segregation in Metallic Alloys

International audienceElectromagnetic levitation (EML) has been used as an experimental technique for investigating the effect of the nucleation and cooling rate on segregation and structure formation in metallic alloys. The technique has been applied to aluminum-copper alloys. For all samples, the primary phase nucleation has been triggered by the contact of the levitated droplet with an alumina plate at a given undercooling. Based on the recorded temperature curves, the heat extraction rate and the nucleation undercooling for the primary dendritic and the secondary eutectic structures have been determined. Metallurgical characterizations have consisted of composition measurements using a scanning electron microscope (SEM) equipped with energy dispersive X-ray spectrometry and the analysis of SEM images. The distribution maps drawn for the composition, the volume fraction of the eutectic structure, and the dendrite arm spacing (DAS) reveal strong correlations. Analysis of the measurements with the help of a cellular-automaton (CA)-finite-element (FE) model is also proposed. The model involves a new coupling scheme between the CA and FE methods and a segregation model accounting for diffusion in the solid and liquid phases. Extensive validation of the model has been carried out on a typical equiaxed grain configuration, i.e., considering the free growth of a mushy zone in an undercooled melt. It demonstrates its capability of dealing with mass exchange inside and outside the envelope of a growing primary dendritic structure. The model has been applied to predict the temperature curve, the segregation, and the eutectic volume fraction obtained upon single-grain nucleation and growth from the south pole of a spherical domain with and without triggering of the nucleation of the primary solid phase, thus simulating the solidification of a levitated droplet. Predictions permit a direct interpretation of the measurements

Numerical simulation of titanium alloy dry machining with a strain softening constitutive law

In this study, the commercial finite element software FORGE2005, able to solve complex thermo-mechanical problems is used to model titanium alloy dry machining. One of the main machining characteristics of titanium alloys is to produce a special chip morphology named “saw-tooth chip” or serrated chip for a wide range of cutting speeds and feeds. The mechanism of saw-tooth chip formation is still not completely understood. Among the two theories about its formation, this study assumes that chip segmentation is only induced by adiabatic shear band formation and thus no material failure occurs in the primary shear zone. Based on the assumption of material strain softening, a new material law was developed. The aim of this study is to analyze the newly developed model’s capacity to correctly simulate the machining process. The model validation is based on the comparison of experimental and simulated results, such as chip formation, global chip morphology, cutting forces and geometrical chip characteristics. A good correlation was found between the experimental and numerical results, especially for cutting speeds generating low tool wear