Sleep disorders in children with cerebral palsy.

To determine the frequency and predictors of sleep disorders in children with cerebral palsy (CP) we analyzed the responses of 173 parents who had completed the Sleep Disturbance Scale for Children. The study population included 100 males (57.8%) and 73 females (42.2%; mean age 8y 10mo [SD 1y 11mo]; range 6y-11y 11mo). Eighty-three children (48.0%) had spastic diplegia, 59 (34.1%) congenital hemiplegia, 18 (10.4%) spastic quadriplegia, and 13 (7.5%) dystonic/dyskinetic CP. Seventy-three children (42.2%) were in Gross Motor Function Classification System Level I, 33 (19.1%) in Level II, 30 (17.3%) in Level III, 23 (13.3%) in Level IV, and 14 (8.1%) in Level V. Thirty children (17.3%) had epilepsy. A total sleep problem score and six factors indicative of the most common areas of sleep disorder in childhood were obtained. Of the children in our study, 23% had a pathological total sleep score, in comparison with 5% of children in the general population. Difficulty in initiating and maintaining sleep, sleep-wake transition, and sleep breathing disorders were the most frequently identified problems. Active epilepsy was associated with the presence of a sleep disorder (odds ratio [OR]=17.1, 95% confidence interval [CI] 2.5-115.3), as was being the child of a single-parent family (OR=3.9, 95% CI 1.3-11.6). Disorders of initiation and maintenance of sleep were more frequent in children with spastic quadriplegia (OR=12.9, 95% CI 1.9-88.0), those with dyskinetic CP (OR=20.6, 95% CI 3.1-135.0), and those with severe visual impairment (OR=12.5, 95% CI 2.5-63.1). Both medical and environmental factors seem to contribute to the increased frequency of chronic sleep disorders in children with CP.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Outcome at two years of age in a Swiss national cohort of extremely preterm infants born between 2000 and 2008.

BACKGROUND: While survival rates of extremely preterm infants have improved over the last decades, the incidence of neurodevelopmental disability (ND) in survivors remains high. Representative current data on the severity of disability and of risk factors associated with poor outcome in this growing population are necessary for clinical guidance and parent counselling. METHODS: Prospective longitudinal multicentre cohort study of preterm infants born in Switzerland between 24(0/7) and 27(6/7) weeks gestational age during 2000-2008. Mortality, adverse outcome (death or severe ND) at two years, and predictors for poor outcome were analysed using multilevel multivariate logistic regression. Neurodevelopment was assessed using Bayley Scales of Infant Development II. Cerebral palsy was graded after the Gross Motor Function Classification System. RESULTS: Of 1266 live born infants, 422 (33%) died. Follow-up information was available for 684 (81%) survivors: 440 (64%) showed favourable outcome, 166 (24%) moderate ND, and 78 (11%) severe ND. At birth, lower gestational age, intrauterine growth restriction and absence of antenatal corticosteroids were associated with mortality and adverse outcome (p < 0.001). At 36(0/7) weeks postmenstrual age, bronchopulmonary dysplasia, major brain injury and retinopathy of prematurity were the main predictors for adverse outcome (p < 0.05). Survival without moderate or severe ND increased from 27% to 39% during the observation period (p = 0.02). CONCLUSIONS: In this recent Swiss national cohort study of extremely preterm infants, neonatal mortality was determined by gestational age, birth weight, and antenatal corticosteroids while neurodevelopmental outcome was determined by the major neonatal morbidities. We observed an increase of survival without moderate or severe disability.

Intrinsically photosensitive retinal ganglion cells: classification, function and clinical implications.

PURPOSE OF REVIEW: The discovery of a new class of intrinsically photosensitive retinal ganglion cells (ipRGCs) revealed their superior role for various nonvisual biological functions, including the pupil light reflex, and circadian photoentrainment. RECENT FINDINGS: Recent works have identified and characterized several anatomically and functionally distinct ipRGC subtypes and have added strong new evidence for the accessory role of ipRGCs in the visual system in humans. SUMMARY: This review summarizes current concepts related to ipRGC morphology, central connections and behavioural functions and highlights recent studies having clinical relevance to ipRGCs. Clinical implications of the melanopsin system are widespread, particularly as related to chronobiology.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Bayesian classification criterion for forensic multivariate data

This study presents a classification criteria for two-class Cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland, law enforcement authorities regularly ask laboratories to determine cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. In this study, the classification analysis is based on data obtained from the relative proportion of three major leaf compounds measured by gas-chromatography interfaced with mass spectrometry (GC-MS). The aim is to discriminate between drug type (illegal) and fiber type (legal) cannabis at an early stage of the growth. A Bayesian procedure is proposed: a Bayes factor is computed and classification is performed on the basis of the decision maker specifications (i.e. prior probability distributions on cannabis type and consequences of classification measured by losses). Classification rates are computed with two statistical models and results are compared. Sensitivity analysis is then performed to analyze the robustness of classification criteria.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Persistence of retinal function after intravitreal melphalan injection for retinoblastoma.

BACKGROUND: The risk/benefit profile of intravitreal melphalan injection for treatment of active vitreous seeds in retinoblastoma remains uncertain. We report clinical and electroretinography results after 6 months of one patient who has shown a favorable initial clinical response to intravitreal melphalan injections for treatment of refractory vitreous seeds. METHODS: Clinical case report. PATIENT: The patient presented at age 17 months with bilateral retinoblastoma [OD: International Classification (ICRB) group E, Reese-Ellsworth (R-E) class Vb; OS: ICRB D, R-E Vb] with no known prior family history. The right eye was enucleated primarily. The patient received systemic chemotherapy and extensive local treatment to the left eye. Ten months later, she presented with recurrent disease, including fine, diffuse vitreous seeds. Tumor control was established with intra-arterial chemotherapy and local treatment. Subsequent recurrence was treated with further intra-arterial chemotherapy, local treatment, and plaque radiotherapy with iodine-125. Persistent free-floating spherical vitreous seeds were treated with 4 cycles of intravitreal melphalan injection via the pars plana, with doses of 30, 30, 30, and 20 μg. RESULTS: After 6 months of follow-up, the left eye remained free of active tumor. Visual acuity was 20/40. Photopic ERGs amplitudes were unchanged compared with those recorded prior to the intravitreal injection treatments. CONCLUSIONS: Intravitreal melphalan injection for refractory spherical vitreous seeds of retinoblastoma with favorable tumor response is compatible with good central visual acuity and preservation of retinal function as indicated by photopic ERG recordings.

Right Hepatectomy in Patients over 70 Years of Age: An Analysis of Liver Function and Outcome.

BACKGROUND: As a consequence of the increase in life expectancy, hepatobiliary surgeons have to deal with an emerging aged population. We aimed to analyze the liver function and outcome after right hepatectomy (RH) in patients over 70 years of age. METHODS: From January 2006 to December 2009, we prospectively collected data of 207 consecutive elective hepatectomies. In patients who had RH, cardiac risk was assessed by a dedicated preoperative workup. Liver failure (LF) was defined by the "fifty-fifty" criteria at postoperative day 5 (POD) and morbidity by the Clavien-Dindo classification. Liver function tests (LFTs) and short-term outcome were retrospectively analyzed in patients over (elderly group, EG) and younger (young group, YG) than 70 years of age. RESULTS: Eighty-seven consecutive RH were performed during the study period. Indication for surgery included 90 % malignancy in 47 % of patients requiring preoperative chemotherapy. ASA grade > 2 (44 vs. 16 %, p = 0.027), ischemic heart disease (17 vs. 5 %, p = 0.076), and preoperative cardiac failure (26 vs. 2 %, p < 0.001) were more frequent in the EG (n = 23) than in the YG (n = 64). Both groups were similar regarding rates of normal liver parenchyma, chemotherapy and intraoperative parameters. The overall morbidity rates were comparable, but the serious complication (grades III-V) rate was relatively higher in the EG (39 vs. 25 %, p = 0.199), particularly in patients with diabetes mellitus (100 vs. 29 %, p = 0.04) and those who had additional nonhepatic surgery (67 vs. 35 %, p = 0.110) and transfusions (44 vs. 30 %, p = 0.523). The 90-day mortality rate was similar (9 % in the EG vs. 3 % in the YG, p = 0.28) and was related to heart failure in the EG. LFTs showed a similar trend from POD 1 to 8, and patients ≥70 years of age had no liver failure. CONCLUSIONS: Age ≥70 years alone is not a contraindication to RH. However, major morbidity is particularly higher in the elderly with diabetes. This high-risk group should be closely monitored in the postoperative course. Liver function is not altered in the elderly patient after RH.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

The extended GLUT-family of sugar/polyol transport facilitators: nomenclature, sequence characteristics, and potential function of its novel members (review).

During the last 2 years, several novel genes that encode glucose transporter-like proteins have been identified and characterized. Because of their sequence similarity with GLUT1, these genes appear to belong to the family of solute carriers 2A (SLC2A, protein symbol GLUT). Sequence comparisons of all 13 family members allow the definition of characteristic sugar/polyol transporter signatures: (1) the presence of 12 membrane-spanning helices, (2) seven conserved glycine residues in the helices, (3) several basic and acidic residues at the intracellular surface of the proteins, (4) two conserved tryptophan residues, and (5) two conserved tyrosine residues. On the basis of sequence similarities and characteristic elements, the extended GLUT family can be divided into three subfamilies, namely class I (the previously known glucose transporters GLUT1-4), class II (the previously known fructose transporter GLUT5, the GLUT7, GLUT9 and GLUT11), and class III (GLUT6, 8, 10, 12, and the myo-inositol transporter HMIT1). Functional characteristics have been reported for some of the novel GLUTs. Like GLUT1-4, they exhibit a tissue/cell-specific expression (GLUT6, leukocytes, brain; GLUT8, testis, blastocysts, brain, muscle, adipocytes; GLUT9, liver, kidney; GLUT10, liver, pancreas; GLUT11, heart, skeletal muscle). GLUT6 and GLUT8 appear to be regulated by sub-cellular redistribution, because they are targeted to intra-cellular compartments by dileucine motifs in a dynamin dependent manner. Sugar transport has been reported for GLUT6, 8, and 11; HMIT1 has been shown to be a H+/myo-inositol co-transporter. Thus, the members of the extended GLUT family exhibit a surprisingly diverse substrate specificity, and the definition of sequence elements determining this substrate specificity will require a full functional characterization of all members.

Classification of urban multi-angular image sequences by aligning their manifolds

When dealing with multi-angular image sequences, problems of reflectance changes due either to illumination and acquisition geometry, or to interactions with the atmosphere, naturally arise. These phenomena interplay with the scene and lead to a modification of the measured radiance: for example, according to the angle of acquisition, tall objects may be seen from top or from the side and different light scatterings may affect the surfaces. This results in shifts in the acquired radiance, that make the problem of multi-angular classification harder and might lead to catastrophic results, since surfaces with the same reflectance return significantly different signals. In this paper, rather than performing atmospheric or bi-directional reflection distribution function (BRDF) correction, a non-linear manifold learning approach is used to align data structures. This method maximizes the similarity between the different acquisitions by deforming their manifold, thus enhancing the transferability of classification models among the images of the sequence.

Cross-species analysis of the replication complex of Old World arenaviruses reveals two nucleoprotein sites involved in L protein function.

Lassa virus (LASV) causing hemorrhagic Lassa fever in West Africa, Mopeia virus (MOPV) from East Africa, and lymphocytic choriomeningitis virus (LCMV) are the main representatives of the Old World arenaviruses. Little is known about how the components of the arenavirus replication machinery, i.e., the genome, nucleoprotein (NP), and L protein, interact. In addition, it is unknown whether these components can function across species boundaries. We established minireplicon systems for MOPV and LCMV in analogy to the existing LASV system and exchanged the components among the three systems. The functional and physical integrity of the resulting complexes was tested by reporter gene assay, Northern blotting, and coimmunoprecipitation studies. The minigenomes, NPs, and L proteins of LASV and MOPV could be exchanged without loss of function. LASV and MOPV L protein was also active in conjunction with LCMV NP, while the LCMV L protein required homologous NP for activity. Analysis of LASV/LCMV NP chimeras identified a single LCMV-specific NP residue (Ile-53) and the C terminus of NP (residues 340 to 558) as being essential for LCMV L protein function. The defect of LASV and MOPV NP in supporting transcriptional activity of LCMV L protein was not caused by a defect in physical NP-L protein interaction. In conclusion, components of the replication complex of Old World arenaviruses have the potential to functionally and physically interact across species boundaries. Residue 53 and the C-terminal domain of NP are important for function of L protein during genome replication and transcription.

Evolving techniques to evaluate ejaculatory function.

PURPOSE OF REVIEW: Recent findings in the physiology and neurobiology of ejaculation have expanded our understanding of male sexual function and have allowed the development of new instruments to investigate ejaculatory and orgasmic disorders. RECENT FINDINGS: The evidence-based definition of lifelong premature ejaculation has set a model in the evaluation and treatment outcome of sexual dysfunction. New instruments to objectively assess arousal, orgasm and the expulsion phase of ejaculation such as functional MRI, dynamic pelvic ultrasound, PET scans and validated questionnaires have lead to a better understanding of sexual dysfunction in men. Animal models, developments in neurobiology and clinical experience have transformed a purely psychoanalytical approach to ejaculatory and orgasmic function into a novel multidisciplinary, scientifically sound and evidence-based discipline of medicine. SUMMARY: Ejaculation is an integral part of normal sexual function. Ejaculatory dysfunction is common and may cause substantial disruption to the quality of a patient's life. A better understanding of the epidemiology, pathophysiology, neuroscience and genetics of ejaculatory and orgasmic function will eventually lead to the development of new, effective methods of treatment of disorders of ejaculation and orgasm in men.

Estimation of glomerular filtration rate in hospitalized patients : are we overestimating renal function?

Estimer la filtration glomérulaire chez les personnes âgées, tout en tenant compte de la difficulté supplémentaire d'évaluer leur masse musculaire, est difficile et particulièrement important pour la prescription de médicaments. Le taux plasmatique de la creatinine dépend à la fois de la fraction d'élimination rénale et extra-rénale et de la masse musculaire. Actuellement, pour estimer là filtration glomérulaire différentes formules sont utilisées, qui se fondent principalement sur la valeur de la créatinine. Néanmoins, en raison de la fraction éliminée par les voies tubulaires et intestinales la clairance de la créatinine surestime généralement le taux de filtration glomérulaire (GFR). Le but de cette étude est de vérifier la fiabilité de certains marqueurs et algorithmes de la fonction rénale actuellement utilisés et d'évaluer l'avantage additionnel de prendre en considération la masse musculaire mesurée par la bio-impédance dans une population âgée (> 70 ans) et avec une fonction rénale chronique compromise basée sur MDRD eGFR (CKD stades lll-IV). Dans cette étude, nous comparons 5 équations développées pour estimer la fonction rénale et basées respectivement sur la créatinine sérique (Cockcroft et MDRD), la cystatine C (Larsson), la créatinine combinée à la bêta-trace protéine (White), et la créatinine ajustée à la masse musculaire obtenue par analyse de la bio-impédance (MacDonald). La bio-impédance est une méthode couramment utilisée pour estimer la composition corporelle basée sur l'étude des propriétés électriques passives et de la géométrie des tissus biologiques. Cela permet d'estimer les volumes relatifs des différents tissus ou des fluides dans le corps, comme par exemple l'eau corporelle totale, la masse musculaire (=masse maigre) et la masse grasse corporelle. Nous avons évalué, dans une population âgée d'un service interne, et en utilisant la clairance de l'inuline (single shot) comme le « gold standard », les algorithmes de Cockcroft (GFR CKC), MDRD, Larsson (cystatine C, GFR CYS), White (beta trace protein, GFR BTP) et Macdonald (GFR = ALM, la masse musculaire par bio-impédance. Les résultats ont montré que le GFR (mean ± SD) mesurée avec l'inuline et calculée avec les algorithmes étaient respectivement de : 34.9±20 ml/min pour l'inuline, 46.7±18.5 ml/min pour CKC, 47.2±23 ml/min pour CYS, 54.4±18.2ml/min pour BTP, 49±15.9 ml/min pour MDRD et 32.9±27.2ml/min pour ALM. Les courbes ROC comparant la sensibilité et la spécificité, l'aire sous la courbe (AUC) et l'intervalle de confiance 95% étaient respectivement de : CKC 0 68 (055-0 81) MDRD 0.76 (0.64-0.87), Cystatin C 0.82 (0.72-0.92), BTP 0.75 (0.63-0.87), ALM 0.65 (0.52-0.78). ' En conclusion, les algorithmes comparés dans cette étude surestiment la GFR dans la population agee et hospitalisée, avec des polymorbidités et une classe CKD lll-IV. L'utilisation de l'impédance bioelectrique pour réduire l'erreur de l'estimation du GFR basé sur la créatinine n'a fourni aucune contribution significative, au contraire, elle a montré de moins bons résultats en comparaison aux autres equations. En fait dans cette étude 75% des patients ont changé leur classification CKD avec MacDonald (créatinine et masse musculaire), contre 49% avec CYS (cystatine C), 56% avec MDRD,52% avec Cockcroft et 65% avec BTP. Les meilleurs résultats ont été obtenus avec Larsson (CYS C) et la formule de Cockcroft.