Pédiatrie [Current progress in pediatrics: obesity and diagnosis approach to the febrile child]

The literature shows that obesity is a public health problem concerning especially the general paediatrician. While prevention has probably more chances of success than treatment, drugs or, in case of failure, the surgical approach are reserved for extreme cases. In the domain of infectiology the different laboratory tests allow only partially to diagnose severe infections. But in the context of a potential influenza pandemic rapid virologic tests become more and more important. They allow a more precise diagnosis and a reduction of hospitalisations and of antibiotic prescriptions. A review of the north American experience with the pneumococal vaccine shows that the heptavalent vaccine will change our approach in infants with fever in whom we suspect a severe infection.

Les sinusites d'origine dentaire: diagnostic et prise en charge [Diagnosis and management of sinusitis of odontogenic origin]

Les sinusites maxillaires sont des infections fréquentes de la sphère ORL. On retrouve une étiologie dentaire dans environ 10% des cas. L'extension des infections dentaires dans le sinus maxillaire est possible en raison de la proximité des racines des dents postérieures avec le bas fond sinusien. Une source odontogène doit être suspectée chez les patients ayant une anamnèse de douleur ou d'infection dentaires, de soins dentaires récents et qui présentent une sinusite unilatérale prolongée ou résistant à un traitement conservateur habituel. Les infections d'origine dentaire possèdent une flore bactérienne mixte. Le diagnostic et la prise en charge nécessitent un bilan radiologique précis. Le traitement doit prendre en charge conjointement la cause dentaire et la sinusite. Un geste chirurgical peut être indiqué dans un deuxième temps afin de restaurer la fonction sinusienne. Maxillary sinusitis are common infections. A dental origin is found in about 10% of the cases. The roots of the posterior maxillary teeth are adjacent to the sinus floor. Extensions of dental infections are therefore possible to the sinus. An odontogenic source should be considered in patients with a history of dental pain or recent oral surgery and those with extended unilateral sinusitis or unilateral sinusitis resistant to conventional treatment. Maxillary sinusitis of dental origin are polymicrobial infections. Conventional radiographs and CT-scans are required for the diagnosis and proper management. Dental treatments to remove the underlying cause combined with oral antibiotics to treat the infection are required. Endoscopic or open surgery may be necessary to complete the treatment and restore adequate sinusal function.

Gastrointestinal malformations: impact of prenatal diagnosis on gestational age at birth.

The aim of the study was to analyse the degree to which gestational age (GA) has been shortened due to prenatal diagnosis of gastrointestinal malformations (GIM). The data source for the study was 14 population-based registries of congenital malformations (EUROCAT). All liveborn infants with GIMs and without chromosomal anomalies, born 1997-2002, were included. The 14 registries identified 1047 liveborn infants with one or more GIMs (oesophageal atresia, duodenal atresia, omphalocele, gastroschisis and diaphragmatic hernia). Median GA at birth was lower in prenatally diagnosed cases for all five malformations, although not statistically significant for gastroschisis. There was little difference in median birthweight by GA for the pre- and postnatally diagnosed infants. The difference in GA at birth between prenatally and postnatally diagnosed infants with GIMs is enough to increase the risk of mortality for the prenatally diagnosed infants. Clinicians need to balance the risk of early delivery against the benefits of clinical convenience when making case management decisions after prenatal diagnosis. Very few studies have been able to show benefits of prenatal diagnosis of congenital malformations for liveborn infants. This may be because the benefits of prenatal diagnosis are outweighed by the problems arising from a lower GA at birth.

Personalized modeling for drug concentration prediction using Support Vector Machine

Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

Towards a user-friendly webservice architecture for statistical machine translation in the PANACEA project

This paper presents a webservice architecture for Statistical Machine Translation aimed at non-technical users. A workfloweditor allows a user to combine different webservices using a graphical user interface. In the current state of this project,the webservices have been implemented for a range of sentential and sub-sententialaligners. The advantage of a common interface and a common data format allows the user to build workflows exchanging different aligners.

Interobserver and intraobserver variability of the apparent diffusion coefficient in treated malignant hepatic lesions on a 3.0T machine: measurements in the whole lesion versus in the area with the most restricted diffusion.

PURPOSE: To assess the inter/intraobserver variability of apparent diffusion coefficient (ADC) measurements in treated hepatic lesions and to compare ADC measurements in the whole lesion and in the area with the most restricted diffusion (MRDA). MATERIALS AND METHODS: Twenty-five patients with treated malignant liver lesions were examined on a 3.0T machine. After agreeing on the best ADC image, two readers independently measured the ADC values in the whole lesion and in the MRDA. These measurements were repeated 1 month later. The Bland-Altman method, Spearman correlation coefficients, and the Wilcoxon signed-rank test were used to evaluate the measurements. RESULTS: Interobserver variability for ADC measurements in the whole lesion and in the MRDA was 0.17 x 10(-3) mm(2)/s [-0.17, +0.17] and 0.43 x 10(-3) mm(2)/s [-0.45, +0.41], respectively. Intraobserver limits of agreement could be as low as [-0.10, +0.12] 10(-3) mm(2)/s and [-0.20, +0.33] 10(-3) mm(2)/s for measurements in the whole lesion and in the MRDA, respectively. CONCLUSION: A limited variability in ADC measurements does exist, and it should be considered when interpreting ADC values of hepatic malignancies. This is especially true for the measurements of the minimal ADC.

Diagnosis of muscular dystrophies at the nanometer scale

The diagnosis of muscular dystrophies or the assessment of the functional benefit of gene or cell therapies can be difficult, especially for poorly accessible muscles, and it often lacks a singlefiber resolution. In the present study, we evaluated whether muscle diseases can be diagnosed from small biopsies using atomic force microscopy (AFM). AFM was shown to provide a sensitive and quantitative description of the resistance of normal and dystrophic myofibers within live muscle tissues explanted from Duchenne mdx mice. The rescue of dystrophin expression by gene therapy approaches led to the functional recovery of treated dystrophic muscle fibers, as probed using AFM and by in situ wholemuscle strength measurements. Comparison of muscles treated with viral or non-viral vectors indicated that the efficacy of the gene transfer approaches could be distinguished with a single myofiber resolution. This indicated full correction of the resistance to deformation in nearly all of the muscle fibers treated with an adeno-associated viral vector that mediates exon-skipping on the dystrophin mRNA. Having shown that AFM can provide a quantitative assessment of the expression of muscle proteins and of the muscular function in animal models, we assessed myofiber resistance in the context of human muscular dystrophies and myopathies. Thus, various forms of human Becker syndrome can also be detected using AFM in blind studies of small frozen biopsies from human patients. Interestingly, it also allowed the detection of anomalies in a fraction of the muscle fibers from patients showing a muscle weakness that could not be attributed to a known molecular or genetic defect. Overall, we conclude that AFM may provide a useful method to complement current diagnosis tools of known and unknown muscular diseases, in research and in a clinical context.

Validation of diagnosis criteria for acquired sensory neuronopathy. a francophone multicenter study

Recently published criteria using clinical (ataxia or asymmetrical distribution at onset or full development, and sensory loss not restricted to the lower limbs) and electrophysiological items (less than two abnormal lower limb motor nerves and at least an abolished SAP or three SAP below 30% of lower limit of normal in the upper limbs) were sensitive and specific for the diagnosis of sensory neuronopathy (SNN) (Camdessanche et al., Brain, 2009). However, these criteria need to be validated on a large multicenter population. For this, a database collecting cases from fifteen Reference Centers for Neuromuscular diseases in France and Switzerland is currently developed. So far, data from 120 patients with clinically pure sensory neuropathy have been collected. Cases were classified independently from the evaluated criteria as SNN (53), non-SNN (46) or suspected SNN (21) according to the expert's diagnosis. Using the criteria, SNN was possible in 83% (44/53), 23.9% (11/46) and 71.4% (15/21) of cases, respectively. In the non-SSN group, half of the patients with a diagnosis of possible SSN had an ataxic form of inflammatory demyelinating neuropathy. In the SNN group, half of those not retained as possible SNN had CANOMAD, paraneoplasia, or B12 deficiency. In a second step, after application of the items necessary to reach the level of probable SNN (no biological or electrophysiological abnormalities excluding SNN; presence of onconeural antibody, cisplatin treatment, Sj ¨ ogren's syndrome or spinal cord MRI high signal in the posterior column), a final diagnosis of possible or probable SNN was obtained in, respectively, 90.6% (48/53), 8.8% (4/45), and 71.4% (15/21) of patients in the three groups. Among the 5 patients with a final non-SNN but initial SNN diagnosis, 3 had motor conduction abnormalities (one with CANOMAD) and among the 4 patients with a final SNN but initial non-SSN diagnosis, one had anti-Hu antibody and one was discussed as a possible ataxic CIDP. These preliminary results confirm the sensitivity and specificity of the proposed criteria for the diagnosis of SNN.

Predicting clinical scores from magnetic resonance scans in Alzheimer's disease.

Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.