Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Geomodelling of a fluvial system with semi-supervised support vector regression

Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Identifying the unmet health needs of patients with congenital hypogonadotropic hypogonadism using a web-based needs assessment: implications for online interventions and peer-to-peer support.

BACKGROUND: Patients with rare diseases such as congenital hypogonadotropic hypogonadism (CHH) are dispersed, often challenged to find specialized care and face other health disparities. The internet has the potential to reach a wide audience of rare disease patients and can help connect patients and specialists. Therefore, this study aimed to: (i) determine if web-based platforms could be effectively used to conduct an online needs assessment of dispersed CHH patients; (ii) identify the unmet health and informational needs of CHH patients and (iii) assess patient acceptability regarding patient-centered, web-based interventions to bridge shortfalls in care. METHODS: A sequential mixed-methods design was used: first, an online survey was conducted to evaluate health promoting behavior and identify unmet health and informational needs of CHH men. Subsequently, patient focus groups were held to explore specific patient-identified targets for care and to examine the acceptability of possible online interventions. Descriptive statistics and thematic qualitative analyses were used. RESULTS: 105 male participants completed the online survey (mean age 37 ± 11, range 19-66 years) representing a spectrum of patients across a broad socioeconomic range and all but one subject had adequate healthcare literacy. The survey revealed periods of non-adherence to treatment (34/93, 37%) and gaps in healthcare (36/87, 41%) exceeding one year. Patient focus groups identified lasting psychological effects related to feelings of isolation, shame and body-image concerns. Survey respondents were active internet users, nearly all had sought CHH information online (101/105, 96%), and they rated the internet, healthcare providers, and online community as equally important CHH information sources. Focus group participants were overwhelmingly positive regarding online interventions/support with links to reach expert healthcare providers and for peer-to-peer support. CONCLUSION: The web-based needs assessment was an effective way to reach dispersed CHH patients. These individuals often have long gaps in care and struggle with the psychosocial sequelae of CHH. They are highly motivated internet users seeking information and tapping into online communities and are receptive to novel web-based interventions addressing their unmet needs.

Extracorporeal membrane oxygenation support after heart explantation: a proposal on how to deal with hyperacute rejection of heart transplant

Purpose: In extreme situations, such as hyperacute rejection of heart transplant or major bleeding per-operating complications, an urgent heart explantation might be the only means of survival. The aim of this experimental study was to improve the surgical technique and the hemodynamics of an Extracorporeal Membrane Oxygenation (ECMO) support through a peripheral vascular access in an acardia model. Methods: An ECMO support was established in 7 bovine experiments (59±6.1 kg) by the transjugular insertion to the caval axis of a self-expanded cannula, with return through a carotid artery. After baseline measurements of pump flow and arterial and central venous pressure, ventricular fibrillation was induced (B), the great arteries were clamped, the heart was excised and right and left atria remnants, containing the pulmonary veins, were sutured together leaving an atrial septal defect (ASD) over the cannula in the caval axis. Measurements were taken with the pulmonary artery (PA) clamped (C) and anastomosed with the caval axis (D). Regular arterial and central venous blood gases tests were performed. The ANOVA test for repeated measures was used to test the null hypothesis and a Bonferroni t method for assessing the significance in the between groups pairwise comparison of mean pump flow. Results: Initial pump flow (A) was 4.3±0.6 L/min dropping to 2.8±0.7 L/min (P B-A= 0.003) 10 minutes after induction of ventricular fibrillation (B). After cardiectomy, with the pulmonary artery clamped (C) it augmented not significantly to 3.5±0.8 L/min (P C-B= 0.33, P C-A= 0.029). Finally, PA anastomosis to the caval axis was followed by an almost to baseline pump flow augmentation (4.1±0.7 L/min, P D-B= 0.009, P D-C= 0.006, P D-A= 0.597), permitting a full ECMO support in acardia by a peripheral vascular access. Conclusions: ECMO support in acardia is feasible, providing new opportunities in situations where heart must urgently be explanted, as in hyperacute rejection of heart transplant. Adequate drainage of pulmonary circulation is pivotal in order to avoid pulmonary congestion and loss of volume from the normal right to left shunt of bronchial vessels. Furthermore, the PA anastomosis to the caval axis not only improves pump flow but it also permits an ECMO support by a peripheral vascular access and the closure of the chest.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Adhésion thérapeutique aux traitements oncologiques oraux et prise en charge interdisciplinaire [Therapeutic adherence to oral cancer therapy and interdisciplinary management].

Medication adherence is a well-known risk factor in internal medicine. However in oncology this dimension is emerging due to the increasing number of oral formulations. First results in the oral oncology literature suggest that patients' ability to cope with medical prescription decreases with time. This might preclude patients from reaching clinical outcomes. Factors impacting on medication adherence to oral oncology treatments have not been yet extensively described neither strategies to address them and support patient's needs. Oncologists and pharmacists in our University outpatient settings performed a pilot study which aimed at measuring and facilitating adherence to oral oncology treatments and at understanding determinants of patient's adherence. The ultimate purpose of such a patient-centered and interdisciplinary collaboration would be to promote patient self-management and complement the standard medical follow-up.

Scan statistics analysis of forest fire clusters

Spatio-temporal clusters in 1997?2003 fire sequences of Tuscany region (central Italy) have been identified and analysed by using the scan statistic, a method which was devised to evidence clusters in epidemiology. Results showed that the method is reliable to find clusters of events and to evaluate their significance via Monte Carlo replication. The evaluation of the presence of spatial and temporal patterns in fire occurrence and their significance could have a great impact in forthcoming studies on fire occurrences prediction.

Surfactant protein-D and exposure to bioaerosols in wastewater and garbage workers.

PURPOSE: Bioaerosols and their constituents, such as endotoxins, are capable of causing an inflammatory reaction at the level of the lung-blood barrier, which becomes more permeable. Thus, it was hypothesized that occupational exposure to bioaerosols can increase leakage of surfactant protein-D (SP-D), a lung-specific protein, into the bloodstream. METHODS: SP-D was determined by ELISA in 316 wastewater workers, 67 garbage collectors, and 395 control subjects. Exposure was assessed with four interview-based indicators and by preliminary endotoxin measurements using the Limulus amoebocyte lysate assay. Influence of exposure on serum SP-D was assessed by multiple linear regression considering smoking, glomerular function, lung diseases, obesity, and other confounders. RESULTS: Overall, mean exposure levels to endotoxins were below 100 EU/m(3). However, special tasks of wastewater workers caused higher endotoxin exposure. SP-D concentration was slightly increased in this occupational group and associated with the occurrence of splashes and contact to raw sewage. No effect was found in garbage collectors. Smoking increased serum SP-D. No clinically relevant correlation between spirometry results and SP-D concentrations appeared. CONCLUSIONS: These results support the hypothesis that inhalation of bioaerosols, even at low concentrations, has a subclinical effect on the lung-blood barrier, the permeability of which increases without associated spirometric changes.

EuroDia: a beta-cell gene expression resource.

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.

Relations of the job demands-control-support model of job strain with personality attributes : a cross-cultural study in Switzerland and South Africa

Among the various work stress models, one of the most popular to date is the job demands-­‐control (JDC) model developed by Karasek (1979), which postulates that work-­‐related strain will be the highest under work conditions characterized by high demands and low autonomy. The absence of social support at work will further increase negative outcomes. However, this model does not apply equally to all individuals and to all cultures. In the following studies, we assessed work characteristics, personality traits, culture-­‐driven individual attributes, and work-­‐related health outcomes, through the administration of questionnaires. The samples consist of Swiss (n = 622) and South African (n = 879) service-­‐oriented employees (from health, finance, education and commerce sectors) and aged from 18 to 65 years old. Results generally confirm the universal contribution of high psychological demands, low decision latitude and low supervisor support at work, as well as high neuroticism predict the worse health outcomes among employees in both countries. Furthermore, low neuroticism plays a moderating role between psychological demands and burnout, while high openness and high conscientiousness each play a moderating role between decision latitude and burnout in South Africa. Results also reveal that culture-­‐driven individual attributes play a role in both countries, but in a unique manner and according to the ethnic group of belonging. Given that organizations are increasingly characterized with multicultural employees as well as increasingly adverse and complex job conditions, our results help in identifying more updated and refined dynamics that are key between the employee and the work environment in today's context. -- L'un des modèles sur le stress au travail des plus répandus est celui développé par Karasek (1979), qui postule qu'une mauvaise santé chez les employés résulte d'une combinaison de demandes psychologiques élevées, d'une latitude décisionnelle faible et de l'absence de soutien social au travail. Néanmoins, ce modèle ne s'applique pas de façon équivalente chez tous les individus et dans toutes les cultures. Dans les études présentées, nous avons mesuré les caractéristiques de travail, les traits de personnalité, les traits culturels et les effets lies à la santé à l'aide de questionnaires. L'échantillon provient de la Suisse (n = 622) et de l'Afrique du Sud (n = 879) et comprend des employés de domaines divers en lien avec le service (notamment des secteurs de la santé, finance, éducation et commerce) tous âgés entre 18 et 65 ans. Les résultats confirment l'universalité des effets directs des demandes au travail, la latitude décisionnelle faible, le soutien social faible provenant du supérieur hiérarchique, ainsi que le névrosisme élevé qui contribuent à un niveau de santé faible au travail, et ce, dans les deux pays. De plus, un niveau faible de névrosisme a un effet de modération entre les demandes au travail et l'épuisement professionnel, alors que l'ouverture élevée et le caractère consciencieux élevé modèrent la relation entre la latitude décisionnelle et l'épuisement professionnel en Afrique du Sud. Nous avons aussi trouvé que les traits culturels jouent un rôle dans les deux pays, mais de façon unique et en fonction du groupe ethnique d'appartenance. Sachant que les organisations sont de plus en plus caractérisées par des employés d'origine ethnique variées, et que les conditions de travail se complexifient, nos résultats contribuent à mieux comprendre les dynamiques entre l'employé et l'environnement de travail contemporain. personnalité, différences individuelles, comparaisons culturelles, culture, stress au travail, épuisement professionnel, santé des employés.