Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression

The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research, and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 datasets containing 38 802 European-ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analyzed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis1) with qualifying unpublished data were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction, and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalizable, but must be of modest effect size and only observable in limited situations

A sleep monitoring method with EEG signals

National audienceDiagnosis of sleep disorders is still a challenging issue for a large number of nerve diseases. In this sense, EEG is a powerful tool due to its non-invasive and real-time catacteristics. This modality is being more and more used for diagnosis such as for epilepsy. It is also becoming widely used for many redictive, Preventive and Personalized Medicine (PPPM) applications.To understand sleep disorders, we propose a method to classify EEG signals in order to detect abnormal behaviours that could refect a specificmodification of the sleep pattern. Our method consists of extracting the characteristics based on temporal and spectral analyses with different descriptors. A classifcation is then performed based on these features. Validation on a public available database show promizing results withhigh accuracy levels

Ellipsometric investigation of porous silicon layers for the design of a DBR

Porous silicon layers (PSL) were fabricated by electrochemical etching and investigated by spectroscopic ellipsometry (SE) in the energy range 0.6−5 eV. Within the effective medium approximation (EMA) and through an optical model consisting of a mixture of void and crystalline silicon (cSi), we were able to determine the porosity (void concentration) and the thicknesses of the PSL. The PSL were divided into several sublayers in order to obtain the best agreement between measured and simulated spectra. Once the etching parameters have been controlled and by choosing the appropriate conditions, it was possible to design a distributed Bragg reflector (DBR) with a high reflectivity band centered at 800 nm. This DBR consists on stacks of alternate PSL having two different refractive indices

Performance Study of Twisted Darrieus Hydrokinetic Turbine With Novel Blade Design

Twisted Darrieus water turbine is receiving growing attention for small-scale hydropower generation. Accordingly, the need for raised water energy conversion incentivizes researchers to focus on the blade shape optimization of twisted Darrieus turbine. In view of this, experimental analysis has been performed to appraise the efficiency of a spiral Darrieus water rotor in the present work. To better the performance parameters of the studied water rotor with twisted blades, three novel blade shapes, namely U-shaped blade, Vshaped blade, and W-shaped blade, have been numerically tested using a computational fluid dynamics three-dimensional numerical model. The maximum power coefficient of the Darrieus rotor reaches 0.17 at a 0.63 tip-speed ratio using twisted blades. Using Vshaped blades, the maximum power coefficient has risen to 0.185. The current study could be practically applied to provide more effective employment of twisted Darrieus turbines and to improve the generated power from flowing water such as river streams, tidal currents, or other man-made water canals

Detection of Epileptic High Frequency Oscillations Using Support Vector Machines

International audienceRecently, several studies have proved that High Frequency Oscillations (HFOs) of [80500] Hz are reliable biomarkers for delineating the epileptogenic zone. The total duration of HFOs is extremely short compared to the entire duration of EEG dataset to be analyzed. Therefore, visual marking of HFOs is timeconsuming and laborious process. In order to promote the clinical use of HFOs oscillations as reliable biomarkers of epileptogenic tissue and to conduct large-scale investigations on cerebral HFOs activities, several automatic detection techniques have been proposed over the past few years. In the present framework, we propose a novel approach for detecting HFOs based on Support Vector Machines (SVM). Our method is subsequently compared with six other methods. HFOs detection performance is evaluated in terms of sensitivity, false discovery rate, area under the ROC curve and execution time. Our results demonstrate that SVM approach yields low false detection (FDR = 6.36%) but, in its current implementation, is moderately sensitive to detect HFOs with a sensitivity of 71.06%. © 2020 IEEE

Affective lability mediates the association between childhood trauma and suicide attempts, mixed episodes and co-morbid anxiety disorders in bipolar disorders

International audienceBackground Many studies have shown associations between a history of childhood trauma and more severe or complex clinical features of bipolar disorders (BD), including suicide attempts and earlier illness onset. However, the psychopathological mechanisms underlying these associations are still unknown. Here, we investigated whether affective lability mediates the relationship between childhood trauma and the severe clinical features of BD. Method A total of 342 participants with BD were recruited from France and Norway. Diagnosis and clinical characteristics were assessed using the Diagnostic Interview for Genetic Studies (DIGS) or the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I). Affective lability was measured using the short form of the Affective Lability Scale (ALS-SF). A history of childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Mediation analyses were performed using the SPSS process macro. Results Using the mediation model and covariation for the lifetime number of major mood episodes, affective lability was found to statistically mediate the relationship between childhood trauma experiences and several clinical variables, including suicide attempts, mixed episodes and anxiety disorders. No significant mediation effects were found for rapid cycling or age at onset. Conclusions Our data suggest that affective lability may represent a psychological dimension that mediates the association between childhood traumatic experiences and the risk of a more severe or complex clinical expression of BD

Childhood trauma, dimensions of psychopathology and the clinical expression of bipolar disorders: A pathway analysis

International audienceBACKGROUND: This study aims at testing for paths from childhood abuse to clinical indicators of complexity in bipolar disorder (BD), through dimensions of affective dysregulation, impulsivity and hostility. METHOD: 485 euthymic patients with BD from the FACE-BD cohort were included from 2009 to 2014. We collect clinical indicators of complexity/severity: age and polarity at onset, suicide attempt, rapid cycling and substance misuse. Patients completed questionnaires to assess childhood emotional, sexual and physical abuses, affective lability, affect intensity, impulsivity, motor and attitudinal hostility.RESULTS: The path-analysis demonstrated significant associations between emotional abuse and all the affective/impulsive dimensions (p < 0.001). Sexual abuse was moderately associated with emotion-related dimensions but not with impulsivity nor motor hostility. In turn, affect intensity and attitudinal hostility were associated with high risk for lifetime presence of suicide attempts (p < 0.001), whereas impulsivity was associated with a higher risk of lifetime presence of substance misuse (p < 0.001). No major additional paths were identified when including Emotional and Physical Neglect in the model.CONCLUSIONS: This study provides refinement of the links between early adversity, dimensions of psychopathology and the complexity/severity of BD. Mainly, dimensions of affective dysregulation, impulsivity/hostility partially mediate the links between childhood emotional to suicide attempts and substance misuse in BD