Body image dissatisfaction and eating symptoms in mothers of adolescents with eating disorders

The purpose of the present study was to assess body dissatisfaction and eating symptoms in mothers of eating disorder (ED) female patients and to compare results with those of a control group. The case group consisted of 35 mothers of female adolescents (aged between 10 and 17 yrs) diagnosed with ED who attended the Interdisciplinary Project for Care, Teaching and Research on Eating Disorders in Childhood and Adolescence (PROTAD) at Clinicas Hospital Institute of Psychiatry of the Universidade de Sao Paulo Medical School. Demographic and socioeconomic data were collected. Eating symptoms were assessed using the Eating Attitudes Test (EAT-26) and body image was assessed by the Body Image Questionnaire (BSQ) and Stunkard Figure Rating Scale (FRS). The case group was compared to a control group consisting of 35 mothers of female adolescents (between 10 and 17 years) who attended a private school in the city of Sao Paulo, southeastern Brazil. With regard to EAT, BSQ and FRS scores, we found no statistically significant differences between the two groups. However, we found a positive correlation between BMI and BSQ scores in the control group (but not in the case group) and a positive correlation between EAT and FRS scores in the case group (but not in the control group). It appears to be advantageous to assess body image by combining more than one scale to evaluate additional components of the construct. (Eating Weight Disord. 15: e219-e225, 2010). (C)2010, Editrice Kurtis

HTR1B and HTR2C in autism spectrum disorders in Brazilian families

Autism spectrum disorders (ASD) is a group of behaviorally defined neuro developmental disabilities characterized by multiple genetic etiologies and a complex presentation. Several studies suggest the involvement of the serotonin system in the development of ASD, but only few have investigated serotonin receptors. We have performed a case-control and a family-based study with 9 polymorphisms mapped to two serotonin receptor genes (HTR1B and HTR2C) in 252 Brazilian male ASD patients of European ancestry. These analyses showed evidence of undertransmission of the HTR1B haplotypes containing alleles -161G and -261A at HTR1B gene to ASD (P=0.003), but no involvement of HTR2C to the predisposition to this disease. Considering the relatively low level of statistical significance and the power of our sample, further studies are required to confirm the association of these serotonin-related genes and ASD. (C) 2008 Elsevier B.V. All rights reserved.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

A Meeting of East and West: Can Eastern-Influenced Therapies be Effective in the Treatment of Stress and Mood Disorders?

Given that the human brain is plastic and that structural alterations have been seen in monks who meditate on a regular basis, the question arises of whether these two facts are actually related. Furthermore, if this is in fact the case, would it be possible to apply these findings to the public? In this paper I will present the different conditions that induce neuroplasticity as well as give an overview of meditation and the ways that it is practiced nowadays. To this end I will argue that if monks are able to alter the structure of their brains and the brain is naturally inclined to heal itself then incorporating eastern practices, such as mindfulness and imagery, into western therapies could benefit patients suffering from mood disorders and, in particular, stress.