A new electrophysiological index for working memory load in humans.

Working memory, the ability to store and simultaneously manipulate information, is affected in several neuropsychiatric disorders which lead to severe cognitive and functional deficits. An electrophysiological marker for this process could help identify early cerebral function abnormalities. In subjects performing working memory-specific n-back tasks, event-related potential analysis revealed a positive-negative waveform (PNwm) component modulated in amplitude by working memory load. It occurs in the expected time range for this process, 140-280 ms after stimulus onset, superimposed on the classical P200 and N200 components. Independent Component Analysis extracted two functional components with latencies and topographical scalp distributions similar to the PNwm. Our results imply that the PNwm represents a new electrophysiological index for working memory load in humans.

Metabolic effects of diets differing in glycaemic index depend on age and endogenous glucose-dependent insulinotrophic polypeptide in mice.

AIMS/HYPOTHESIS: High- vs low-glycaemic index (GI) diets unfavourably affect body fat mass and metabolic markers in rodents. Different effects of these diets could be age-dependent, as well as mediated, in part, by carbohydrate-induced stimulation of glucose-dependent insulinotrophic polypeptide (GIP) signalling. METHODS: Young-adult (16 weeks) and aged (44 weeks) male wild-type (C57BL/6J) and GIP-receptor knockout (Gipr ( -/- )) mice were exposed to otherwise identical high-carbohydrate diets differing only in GI (20-26 weeks of intervention, n = 8-10 per group). Diet-induced changes in body fat distribution, liver fat, locomotor activity, markers of insulin sensitivity and substrate oxidation were investigated, as well as changes in the gene expression of anorexigenic and orexigenic hypothalamic factors related to food intake. RESULTS: Body weight significantly increased in young-adult high- vs low-GI fed mice (two-way ANOVA, p < 0.001), regardless of the Gipr genotype. The high-GI diet in young-adult mice also led to significantly increased fat mass and changes in metabolic markers that indicate reduced insulin sensitivity. Even though body fat mass also slightly increased in high- vs low-GI fed aged wild-type mice (p < 0.05), there were no significant changes in body weight and estimated insulin sensitivity in these animals. However, aged Gipr ( -/- ) vs wild-type mice on high-GI diet showed significantly lower cumulative net energy intake, increased locomotor activity and improved markers of insulin sensitivity. CONCLUSIONS/INTERPRETATION: The metabolic benefits of a low-GI diet appear to be more pronounced in younger animals, regardless of the Gipr genotype. Inactivation of GIP signalling in aged animals on a high-GI diet, however, could be beneficial.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Mortality risk of obesity and underweight is overestimated with self-reported body mass index.

Obese persons (those with a body mass index [BMI] ≥30 kg/m2) tend to underestimate their weight, leading to an underestimation of their true (measured) BMI and obesity prevalence.1,2 In contrast, underweight people (BMI <18.5 kg/m2) tend to report themselves heavier, resulting in a higher BMI compared with measured BMI and an underestimation of underweight prevalence.

The inter-rater reliability of the Pulmonary Embolism Severity Index.

The Pulmonary Embolism Severity Index (PESI) is a validated clinical prognostic model for patients with acute pulmonary embolism (PE). Our goal was to assess the PESI's inter-rater reliability in patients diagnosed with PE. We prospectively identified consecutive patients diagnosed with PE in the emergency department of a Swiss teaching hospital. For all patients, resident and attending physician raters independently collected the 11 PESI variables. The raters then calculated the PESI total point score and classified patients into one of five PESI risk classes (I-V) and as low (risk classes I/II) versus higher-risk (risk classes III-V). We examined the inter-rater reliability for each of the 11 PESI variables, the PESI total point score, assignment to each of the five PESI risk classes, and classification of patients as low versus higher-risk using kappa (κ) and intra-class correlation coefficients (ICC). Among 48 consecutive patients with an objective diagnosis of PE, reliability coefficients between resident and attending physician raters were > 0.60 for 10 of the 11 variables comprising the PESI. The inter-rater reliability for the PESI total point score (ICC: 0.89, 95% CI: 0.81-0.94), PESI risk class assignment (κ: 0.81, 95% CI: 0.66-0.94), and the classification of patients as low versus higher-risk (κ: 0.92, 95% CI: 0.72-0.98) was near perfect. Our results demonstrate the high reproducibility of the PESI, supporting the use of the PESI for risk stratification of patients with PE.

Prefabrication of composite grafts for long-segment tracheal reconstruction.

OBJECTIVE: To investigate the prefabrication of vascularized mucosa-lined composite grafts intended to replace circumferential tracheal defects. DESIGN: Plane grafts composed of ear cartilage and full-thickness oral mucosa were revascularized by the laterothoracic fascia. The use of meshed vs nonmeshed mucosa to improve the epithelial coverage was examined. We also investigated the creation of a vascular bed over the cartilage and the subsequent application of meshed mucosa. Macroscopic aspects, viability, and degree of mucosal lining were analyzed. SUBJECTS: Twenty male New Zealand white rabbits. INTERVENTIONS: Ten animals underwent placement of auricular cartilage under the laterothoracic fascia. Intact (group 1) or meshed mucosa (group 2) was applied over the fascia and protected by a silicone sheet. After 3 weeks, prefabricated grafts were removed for comparison. In 10 other animals, a sheet of perforated cartilage was placed under the laterothoracic fascia. Two weeks later, 5 grafts (group 3) were harvested. The remaining 5 grafts were reopened for mucosal application over the cartilage and revascularized for 3 additional weeks (group 4). RESULTS: Vascularized plane grafts were obtained in all groups. Mucosal lining increased significantly with meshed mucosa (14%-68%; mean, 40%) compared with nonmeshed mucosa (3%-15%; mean, 10%) (P = .008). Induction of a vascular bed over perforated cartilage was achieved, but survival of secondary implanted mucosa was variable. CONCLUSIONS: A reliable technique to prefabricate composite grafts with cartilaginous support and mucosal lining is presented. The use of meshed mucosa significantly improves epithelial coverage.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

Paranasal sinuses in children: size evaluation of maxillary, sphenoid, and frontal sinuses by magnetic resonance imaging and proposal of volume index percentile curves.

Our objective was to establish the age-related 3D size of maxillary, sphenoid, and frontal sinuses. A total of 179 magnetic resonance imaging (MRI) of children under 17 years (76 females, 103 males) were included and sinuses were measured in the three axes. Maxillary sinuses measured at birth (mean+/-standard deviation) 7.3+/-2.7 mm length (or antero-posterior)/4.0+/-0.9 mm height (or cranio-caudal)/2.7+/-0.8 mm width (or transverse). At 16 years old, maxillary sinus measured 38.8+/-3.5 mm/36.3+/-6.2 mm/27.5+/-4.2 mm. Sphenoid sinus pneumatization starts in the third year of life after conversion from red to fatty marrow with mean values of 5.8+/-1.4 mm/8.0+/-2.3 mm/5.8+/-1.0 mm. Pneumatization progresses gradually to reach at 16 years 23.0+/-4.5 mm/22.6+/-5.8 mm/12.8+/-3.1 mm. Frontal sinuses present a wide variation in size and most of the time are not valuable with routine head MRI techniques. They are not aerated before the age of 6 years. Frontal sinuses dimensions at 16 years were 12.8+/-5.0 mm/21.9+/-8.4 mm/24.5+/-13.3 mm. A sinus volume index (SVI) of maxillary and sphenoid sinus was computed using a simplified ellipsoid volume formula, and a table with SVI according to age with percentile variations is proposed for easy clinical application. Percentile curves of maxillary and sphenoid sinuses are presented to provide a basis for objective determination of sinus size and volume during development. These data are applicable to other techniques such as conventional X-ray and CT scan.

Validation of the instability shoulder index score in a multicenter reliability study in 114 consecutive cases.

BACKGROUND: Anterior shoulder stabilization surgery with the arthroscopic Bankart procedure can have a high recurrence rate in certain patients. Identifying these patients to modify outcomes has become a focal point of research. PURPOSE: The Instability Shoulder Index Score (ISIS) was developed to predict the success of arthroscopic Bankart repair. Scores range from 0 to 10, with higher scores predicting a higher risk of recurrence after stabilization. The interobserver reliability of the score is not known. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 2. METHODS: This is a prospective multicenter (North America and Europe) study of patients suffering from shoulder instability and waiting for stabilization surgery. Five pairs of independent evaluators were asked to score patient instability severity with the ISIS. Patients also completed functional scores (Western Ontario Shoulder Instability Index [WOSI], Disabilities of the Arm, Shoulder and Hand-short version [QuickDASH], and Walch-Duplay test). Data on age, sex, number of dislocations, and type of surgery were collected. The test-retest method and intraclass correlation coefficient (ICC: >0.75 = good, >0.85 = very good, and >0.9 = excellent) were used for analysis. RESULTS: A total of 114 patients with anterior shoulder instability were included, of whom 89 (78%) were men. The mean age was 28 years. The ISIS was very reliable, with an ICC of 0.933. The mean number of dislocations per patient was higher in patients who had an ISIS of ≥6 (25 vs 14; P = .05). Patients who underwent more complex arthroscopic procedures such as Hill-Sachs remplissage or open Latarjet had higher preoperative ISIS outcomes, with a mean score of 4.8 versus 3.4, respectively (P = .002). There was no correlation between the ISIS and the quality-of-life questionnaires, with Pearson correlations all >0.05 (WOSI = 0.39; QuickDASH = 0.97; Walch-Duplay = 0.08). CONCLUSION: Our results show that the ISIS is reliable when used in a multicenter study with anterior traumatic instability populations. There was no correlation between the ISIS and the quality-of-life questionnaires, but surgical decisions reflected its increased use.

Depression with atypical features and increase in obesity, body mass index, waist circumference, and fat mass: a prospective, population-based study.

IMPORTANCE: Depression and obesity are 2 prevalent disorders that have been repeatedly shown to be associated. However, the mechanisms and temporal sequence underlying this association are poorly understood. OBJECTIVE: To determine whether the subtypes of major depressive disorder (MDD; melancholic, atypical, combined, or unspecified) are predictive of adiposity in terms of the incidence of obesity and changes in body mass index (calculated as weight in kilograms divided by height in meters squared), waist circumference, and fat mass. DESIGN, SETTING, AND PARTICIPANTS: This prospective population-based cohort study, CoLaus (Cohorte Lausannoise)/PsyCoLaus (Psychiatric arm of the CoLaus Study), with 5.5 years of follow-up included 3054 randomly selected residents (mean age, 49.7 years; 53.1% were women) of the city of Lausanne, Switzerland (according to the civil register), aged 35 to 66 years in 2003, who accepted the physical and psychiatric baseline and physical follow-up evaluations. EXPOSURES: Depression subtypes according to the DSM-IV. Diagnostic criteria at baseline and follow-up, as well as sociodemographic characteristics, lifestyle (alcohol and tobacco use and physical activity), and medication, were elicited using the semistructured Diagnostic Interview for Genetic Studies. MAIN OUTCOMES AND MEASURES: Changes in body mass index, waist circumference, and fat mass during the follow-up period, in percentage of the baseline value, and the incidence of obesity during the follow-up period among nonobese participants at baseline. Weight, height, waist circumference, and body fat (bioimpedance) were measured at baseline and follow-up by trained field interviewers. RESULTS: Only participants with the atypical subtype of MDD at baseline revealed a higher increase in adiposity during follow-up than participants without MDD. The associations between this MDD subtype and body mass index (β = 3.19; 95% CI, 1.50-4.88), incidence of obesity (odds ratio, 3.75; 95% CI, 1.24-11.35), waist circumference in both sexes (β = 2.44; 95% CI, 0.21-4.66), and fat mass in men (β = 16.36; 95% CI, 4.81-27.92) remained significant after adjustments for a wide range of possible cofounding. CONCLUSIONS AND RELEVANCE: The atypical subtype of MDD is a strong predictor of obesity. This emphasizes the need to identify individuals with this subtype of MDD in both clinical and research settings. Therapeutic measures to diminish the consequences of increased appetite during depressive episodes with atypical features are advocated.

Skinfold thickness and adiposity index in premature infants.

In order to assess the validity of the weight per square of length ratio as an index of adiposity during the neonatal period, 37 premature infants (gestational age, mean +/- SD, = 31.5 +/- 1.1 weeks, birthweight, mean +/- SD, = 1.448 +/- 147 g) were studied for weight, length and skinfold thickness at 5 sites (biceps, triceps, subscapular, suprailiac and quadriceps) during their stay in the Neonatal Unit of the University Hospital in Lausanne. The results show a significant correlation between the adiposity index and the sum of 5 skinfold thickness sites in premature infants. The adiposity index gives a fair estimate of the body fat mass during the postnatal growth in premature infants.