245 resultados para discrimination training
Resumo:
Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.
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With the free movement of people in the European Union, medical mobility has increased significantly. This is notably the case for disciplines for which shortage of well-trained staff has occurred. Pathology is among those specialties and effectively the discipline is confronted with a striking increase in mobility among trainees and qualified specialists. The presumption underlying unlimited mobility is that the competencies of the medical specialists in the European countries are more or less equal, including significant similarities in the postgraduate training programs. In order to assess whether reality corresponds with this presumption, we conducted a survey of the content and practice requirements of the curricula in the EU and affiliated countries. The results indicate a striking heterogeneity in the training program content and practice requirements. To name a few elements: duration of the training program varied between 4 and 6 years; the number of autopsies required varied between none at all and 300; the number of biopsies required varied between none at all and 15,000. We conclude that harmonization of training outcomes in Europe is a goal that needs to be pursued. This will be difficult to reach through harmonization of training programs, as these are co-determined by political, cultural, and administrative factors, difficult to influence. Harmonization might be attained by defining the general and specific competencies at the end of training and subsequent testing them through a test to which all trainees in Europe are subjected.
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Introduction: Discrimination of species-specific vocalizations is fundamental for survival and social interactions. Its unique behavioral relevance has encouraged the identification of circumscribed brain regions exhibiting selective responses (Belin et al., 2004), while the role of network dynamics has received less attention. Those studies that have examined the brain dynamics of vocalization discrimination leave unresolved the timing and the inter-relationship between general categorization, attention, and speech-related processes (Levy et al., 2001, 2003; Charest et al., 2009). Given these discrepancies and the presence of several confounding factors, electrical neuroimaging analyses were applied to auditory evoked-potential (AEPs) to acoustically and psychophysically controlled non-verbal human and animal vocalizations. This revealed which region(s) exhibit voice-sensitive responses and in which sequence. Methods: Subjects (N=10) performed a living vs. man-made 'oddball' auditory discrimination task, such that on a given block of trials 'target' stimuli occurred 10% of the time. Stimuli were complex, meaningful sounds of 500ms duration. There were 120 different sound files in total, 60 of which represented sounds of living objects and 60 man-made objects. The stimuli that were the focus of the present investigation were restricted to those of living objects within blocks where no response was required. These stimuli were further sorted between human non-verbal vocalizations and animal vocalizations. They were also controlled in terms of their spectrograms and formant distributions. Continuous 64-channel EEG was acquired through Neuroscan Synamps referenced to the nose, band-pass filtered 0.05-200Hz, and digitized at 1000Hz. Peri-stimulus epochs of continuous EEG (-100ms to 900ms) were visually inspected for artifacts, 40Hz low-passed filtered and baseline corrected using the pre-stimulus period . Averages were computed from each subject separately. AEPs in response to animal and human vocalizations were analyzed with respect to differences of Global Field Power (GFP) and with respect to changes of the voltage configurations at the scalp (reviewed in Murray et al., 2008). The former provides a measure of the strength of the electric field irrespective of topographic differences; the latter identifies changes in spatial configurations of the underlying sources independently of the response strength. In addition, we utilized the local auto-regressive average distributed linear inverse solution (LAURA; Grave de Peralta Menendez et al., 2001) to visualize and statistically contrast the likely underlying sources of effects identified in the preceding analysis steps. Results: We found differential activity in response to human vocalizations over three periods in the post-stimulus interval, and this response was always stronger than that to animal vocalizations. The first differential response (169-219ms) was a consequence of a modulation in strength of a common brain network localized into the right superior temporal sulcus (STS; Brodmann's Area (BA) 22) and extending into the superior temporal gyrus (STG; BA 41). A second difference (291-357ms) also followed from strength modulations of a common network with statistical differences localized to the left inferior precentral and prefrontal gyrus (BA 6/45). These two first strength modulations correlated (Spearman's rho(8)=0.770; p=0.009) indicative of functional coupling between temporally segregated stages of vocalization discrimination. A third difference (389-667ms) followed from strength and topographic modulations and was localized to the left superior frontal gyrus (BA10) although this third difference did not reach our spatial criterion of 12 continuous voxels. Conclusions: We show that voice discrimination unfolds over multiple temporal stages, involving a wide network of brain regions. The initial stages of vocalization discrimination are based on modulations in response strength within a common brain network with no evidence for a voice-selective module. The latency of this effect parallels that of face discrimination (Bentin et al., 2007), supporting the possibility that voice and face processes can mutually inform one another. Putative underlying sources (localized in the right STS; BA 22) are consistent with prior hemodynamic imaging evidence in humans (Belin et al., 2004). Our effect over the 291-357ms post-stimulus period overlaps the 'voice-specific-response' reported by Levy et al. (Levy et al., 2001) and the estimated underlying sources (left BA6/45) were in agreement with previous findings in humans (Fecteau et al., 2005). These results challenge the idea that circumscribed and selective areas subserve con-specific vocalization processing.
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Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise. Structural brain adaptations in musicians have been repeatedly demonstrated in areas involved in auditory perception and motor skills. However, musical activities are not confined to auditory perception and motor performance, but are entangled with higher-order cognitive processes. In consequence, neuronal systems involved in such higher-order processing may also be shaped by experience-driven plasticity. We modelled expertise as a three-level regressor to study possible linear relationships of expertise with grey matter density. The key finding of this study resides in a functional dissimilarity between areas exhibiting increase versus decrease of grey matter as a function of musical expertise. Grey matter density increased with expertise in areas known for their involvement in higher-order cognitive processing: right fusiform gyrus (visual pattern recognition), right mid orbital gyrus (tonal sensitivity), left inferior frontal gyrus (syntactic processing, executive function, working memory), left intraparietal sulcus (visuo-motor coordination) and bilateral posterior cerebellar Crus II (executive function, working memory) and in auditory processing: left Heschl's gyrus. Conversely, grey matter density decreased with expertise in bilateral perirolandic and striatal areas that are related to sensorimotor function, possibly reflecting high automation of motor skills. Moreover, a multiple regression analysis evidenced that grey matter density in the right mid orbital area and the inferior frontal gyrus predicted accuracy in detecting fine-grained incongruities in tonal music.
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The aim of this study was to examine the effect of an individualized overground walking interval training on gait performance [i.e., speed and energy cost (C(w))] in healthy elderly individuals. Twenty-two older adults were assigned to either a training group (TG; n=12, 73.4+/-3.9yr) or a non-training control group (CG; n=10, 70.9+/-9.6yr). TG participated in a 7-week individualized walking interval training at intensities progressing from 50 to 100% of ventilatory threshold (T (VE)). Aerobic fitness [maximal oxygen uptake (V O(2max)) and T (VE)], preferred walking speed (PWS), gross and net C(w) (GC(w) and NC(w), respectively) and relative effort (%V O(2max)) at PWS measured before training (PWS(1)) were assessed prior and following the intervention. All outcomes were measured on a treadmill. Significant improvements in GC(w) (-8%; P=0.007), NC(w) (-12%; P=0.003), relative effort (%V O(2max): -12%; P<0.001) and PWS (+12%; P<0.001) were observed in TG but not in CG (P>0.71). V O(2max) and T (VE) remained unchanged in both groups (P>0.57). Changes in GC(w) at PWS(1) (difference between GC(w) at PWS(1) measured pre and post intervention) were inversely correlated with changes in PWS (difference between pre and post PWS; r=-0.67; P=0.02). The decreased C(w) at PWS(1), with no concomitant improvement in aerobic fitness, represents the main contributing factor for the reduction of the relative effort at this speed. This also allows elderly people to increase their PWS post training. Therefore, the present walking training may be an effective way to improve walking performance and delay mobility impairment in older adults.
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The use of observer-rated scales requires that raters be trained until they have become reliable in using the scales. However, few studies properly report how training in using a given rating scale is conducted or indeed how it should be conducted. This study examined progress in interrater reliability over 6 months of training with two observer-rated scales, the Cognitive Errors Rating Scale and the Coping Action Patterns Rating Scale. The evolution of the intraclass correlation coefficients was modeled using hierarchical linear modeling. Results showed an overall training effect as well as effects of the basic training phase and of the rater calibration phase, the latter being smaller than the former. The results are discussed in terms of implications for rater training in psychotherapy research.
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Cognitive biases may be one of the explaining factor underlying psychotic symptoms like delusions and hallucinations. Metacognitive training (MCT) was demonstrated, in adults with schizophrenia, to reduce these cognitive biases. However, to the best of our knowledge, there has been no research on adolescents with psychosis. The current study aimed at assessing the feasibility, treatment adherence and its benefi cial effects on psychotic symptoms, depression, social functioning and self-esteem of a MCT. Participants were fi ve psychotic adolescents with psychosis, aged 16-18, who attended the Day Care Unit for Adolescents (DCUA). The MCT, delivered in group, corresponds to 2x8 modules, lasting between 45 and 60 minutes once a week. To measure MCT's effi ciency, the Positive And Negative Syndrome Scale (PANSS), the Social and Occupational Functioning Assessment Scale (SOFAS), the Health of Nation Outcome Scale for Children and Adolescent (HoNOSCA), the depression scale of Calgary and the self-esteem scale of Rosenberg have been used. The results of the 5 patients indicate that MCT is feasible and the treatment adherence is moderate. The schedule of the MCT needs to be adapted to the availability of the participants. At a descriptive level, the MCT allows to reduce psychotic and depressive symptoms (PANSS & Calgary) as well as to improve the social functioning (SOFAS & HoNOSCA) and self-esteem (Rosenberg). To sum up, MCT seem to be an interesting alternative and/or a good additional treatment to reduce cognitive bias, psychotic symptoms as well as improving social functioning
Resumo:
Osteoporotic hip fractures increase dramatically with age and are responsible for considerable morbidity and mortality. Several treatments to prevent the occurrence of hip fracture have been validated in large randomized trials and the current challenge is to improve the identification of individuals at high risk of fracture who would benefit from therapeutic or preventive intervention. We have performed an exhaustive literature review on hip fracture predictors, focusing primarily on clinical risk factors, dual X-ray absorptiometry (DXA), quantitative ultrasound, and bone markers. This review is based on original articles and meta-analyses. We have selected studies that aim both to predict the risk of hip fracture and to discriminate individuals with or without fracture. We have included only postmenopausal women in our review. For studies involving both men and women, only results concerning women have been considered. Regarding clinical factors, only prospective studies have been taken into account. Predictive factors have been used as stand-alone tools to predict hip fracture or sequentially through successive selection processes or by combination into risk scores. There is still much debate as to whether or not the combination of these various parameters, as risk scores or as sequential or concurrent combinations, could help to better predict hip fracture. There are conflicting results on whether or not such combinations provide improvement over each method alone. Sequential combination of bone mineral density and ultrasound parameters might be cost-effective compared with DXA alone, because of fewer bone mineral density measurements. However, use of multiple techniques may increase costs. One problem that precludes comparison of most published studies is that they use either relative risk, or absolute risk, or sensitivity and specificity. The absolute risk of individuals given their risk factors and bone assessment results would be a more appropriate model for decision-making than relative risk. Currently, a group appointed by the World Health Organization and lead by Professor John Kanis is working on such a model. It will therefore be possible to further assess the best choice of threshold to optimize the number of women needed to screen for each country and each treatment.
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Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.
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OBJECTIVE: Little is known about the influence of different training types on relative fat mobilization with exercise. The purpose of this study was to analyze the changes induced by aerobic training (AT), resistance (RT) or a combination of both (AT+RT) on total fat mass (TFM) and regional fat mass (RFM). Further, the relative contribution of different regions, upper limbs (UL), lower limbs (LL), and trunk (Tr), were compared. DESIGN AND METHODS: Forty-five overweight and premenopausal women were randomized in either AT, RT or AT+RT. All training groups exercised for the same duration (60 min), 3 times per week for 5 months. Body composition was estimated using dual energy X-ray absorptiometry. RESULTS: TFM decreased significantly in all groups (-4.6 ± 1.9 kg; -3.8 ± 2.6 kg, and -4.7 ± 3.0 kg in AT, RT, and AT+RT groups respectively; P < 0.001). The relative contribution of FM into each segment changed significantly: TrFM represented 46.6% ± 5.8% of TFM at baseline and reduced to 43.1% ± 5.5% (P < 0.001); LLFM was 39.7% ± 5.8% vs. 41.6% ± 5.7% (P < 0.01); ULFM was 11.3% ± 1.3% vs. 12.2% ± 1.4% (P < 0.01). CONCLUSION: Training type did not influence changes of TFM and RFM. Fat mobilization came predominantly from Tr in all training protocols. These findings suggest that overweight and obese women can reduce TFM and RFM, independently of training type.