The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Model for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic

Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.

The Potential Impact of Using Donations After Cardiac Death on the Liver Transplantation Program and Waiting List in the State of Sao Paulo, Brazil

Liver transplantation was first performed at the University of Sao Paulo School of Medicine in 1968. Since then, the patient waiting list for liver transplantation has increased at a rate of 150 new cases per month. Liver transplantation itself rose 1.84-fold (from 160 to 295) from 1988 to 2004. However, the number of patients on the liver waiting list jumped 2.71-fold (from 553 to 1500). Consequently, the number of deaths on the liver waiting list moved to a higher level, from 321 to 671, increasing 2.09-fold. We have applied a mathematical model to analyze the potential impact of using a donation after cardiac death (DCD) policy on our liver transplantation program and on the waiting list. Five thousand one hundred people died because of accidents and other violent causes in our state in 2004; of these, only 295 were donors of liver grafts that were transplanted. The model assumed that 5% of these grafts would have been DCD. We found a relative reduction of 27% in the size of the liver transplantation waiting list if DCD had been used by assuming that 248 additional liver transplants would have been performed annually. In conclusion, the use of DCD in our transplantation program would reduce the pressure on our liver transplantation waiting list, reducing it by at least 27%. On the basis of this model, the projected number of averted deaths is about 41,487 in the next 20 years. Liver Transpl 14:1732-1736, 2008. (C) 2008 AASLD.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

State-dependent microstructural white matter changes in bipolar I depression

Abnormalities in fronto-limbic-striatal white matter (WM) have been reported in bipolar disorder (BD), but results have been inconsistent across studies. Furthermore, there have been no detailed investigations as to whether acute mood states contribute to microstructural changes in WM tracts. In order to compare fiber density and structural integrity within WM tracts between BD depression and remission, whole-brain fractional anisotropy (FA) and mean diffusivity (MD) were assessed in 37 bipolar I disorder (BD-I) patients (16 depressed and 21 remitted), and 26 healthy individuals with diffusion tensor imaging. Significantly decreased FA and increased MD in bilateral prefronto-limbic-striatal white matter and right inferior fronto-occipital, superior and inferior longitudinal fasciculi were shown in all BD-I patients versus controls, as well as in depressed BD-I patients compared to both controls and remitted BD-I patients. Depressed BD-I patients also exhibited increased FA in the ventromedial prefrontal cortex. Remitted BD-I patients did not differ from controls in FA or MD. These findings suggest that BD-I depression may be associated with acute microstructural WM changes.

Limitations of the Mini-Mental State Examination for screening dementia in a community with low socioeconomic status

The Mini-Mental State Examination (MMSE) is the most widely used instrument for the screening of cognitive impairment worldwide, but its ability to produce valid estimates of dementia in populations of low socioeconomic status and minimal literacy skills has not been adequately established. The authors investigated the psychometric properties of the MMSE in a community-based sample of older Brazilians. Cross-sectional one-phase population-based study of all residents of pre-defined areas of the city of Sao Paulo, aged 65 years or over. The Brazilian version of the MMSE was compared with DSM-IV diagnosis of dementia assessed with a harmonized one-phase procedure developed by the 10/66 Dementia Research Group. Analyses were performed with 1,933 participants of the SPAH study. Receiver operating characteristic analysis showed that the MMSE cut-point of 14/15 was associated with 78.7% sensitivity and 77.8% specificity for the diagnosis of dementia amongst participants with no formal education, and the cut-point 17/18 with 91.9% sensitivity and 89.5% specificity for those with at least 1 year of formal education (areas under the curves 0.87 and 0.94, respectively; P = 0.03). Even with these best fitting cut-points, the MMSE estimate of the prevalence of dementia was four times higher than determined by the DSM-IV criteria. Education, age, sex and income influenced MMSE scores, independently of dementia caseness. The MMSE is an adequate tool for screening dementia in older adults with minimum literacy skills, but misclassification is unacceptably high for older adults who are illiterate, which has serious consequences for research and clinical practice in low and middle income countries, where the proportion of illiteracy among older adults is high.

A hypothesis for explaining single outbreaks (like the Black Death in European cities) of vector-borne infections

We propose a mechanism by which single outbreaks of vector-borne infections can happen even when the value of the basic reproduction number, R(o), of the infection is below one. With this hypothesis we have shown that dynamical models simulations demonstrate that the arrival of a relatively small (with respect to the host population) number of infected vectors can trigger a short-lived epidemic but with a huge number of cases. These episodes are characterized by a sudden outbreak in a previously virgin area that last from weeks to a few months, and then disappear without leaving vestiges. The hypothesis proposed in this paper to explain those single outbreaks of vector-borne infections, even when total basic reproduction number, Ro, is less than one (which explain the fact that those infections fail to establish themselves at endemic levels), is that the vector-to-host component of Ro is greater than one and that a sufficient amount of infected vectors are imported to the vulnerable area, triggering the outbreak. We tested the hypothesis by performing numerical simulations that reproduce the observed outbreaks of chikungunya in Italy in 2007 and the plague in Florence in 1348. The theory proposed provides an explanation for isolated outbreaks of vector-borne infections, ways to calculate the size of those outbreaks from the number of infected vectors arriving in the affected areas. Given the ever-increasing worldwide transportation network, providing a high degree of mobility from endemic to virgin areas, the proposed mechanism may have important implications for public health planning. (C) 2009 Elsevier Ltd. All rights reserved.

Elevated Amygdala Activity to Sad Facial Expressions: A State Marker of Bipolar but Not Unipolar Depression

Background: Difficulties in emotion processing and poor social function are common to bipolar disorder (BD) and major depressive disorder (MDD) depression, resulting in many BID depressed individuals being misdiagnosed with MDD. The amygdala is a key region implicated in processing emotionally salient stimuli, including emotional facial expressions. It is unclear, however, whether abnormal amygdala activity during positive and negative emotion processing represents a persistent marker of BD regardless of illness phase or a state marker of depression common or specific to BID and MDD depression. Methods: Sixty adults were recruited: 15 depressed with BID type 1 (BDd), 15 depressed with recurrent MDD, 15 with BID in remission (BDr), diagnosed with DSM-IV and Structured Clinical Interview for DSM-IV Research Version criteria; and 15 healthy control subjects (HC). Groups were age- and gender ratio-matched; patient groups were matched for age of illness onset and illness duration; depressed groups were matched for depression severity. The BDd were taking more psychotropic medication than other patient groups. All individuals participated in three separate 3T neuroimaging event-related experiments, where they viewed mild and intense emotional and neutral faces of fear, happiness, or sadness from a standardized series. Results: The BDd-relative to HC, BDr, and MDD-showed elevated left amygdala activity to mild and neutral facial expressions in the sad (p < .009) but not other emotion experiments that was not associated with medication. There were no other significant between-group differences in amygdala activity. Conclusions: Abnormally elevated left amygdala activity to mild sad and neutral faces might be a depression-specific marker in BID but not MDD, suggesting different pathophysiologic processes for BD versus MDD depression.

Abnormal Left and Right Amygdala-Orbitofrontal Cortical Functional Connectivity to Emotional Faces: State Versus Trait Vulnerability Markers of Depression in Bipolar Disorder

Background: Amygdala-orbitofrontal cortical (OFC) functional connectivity (FC) to emotional stimuli and relationships with white matter remain little examined in bipolar disorder individuals (BD). Methods: Thirty-one BD (type 1; n = 17 remitted; n = 14 depressed) and 24 age- and gender-ratio-matched healthy individuals (HC) viewed neutral, mild, and intense happy or sad emotional faces in two experiments. The FC was computed as linear and nonlinear dependence measures between amygdala and OFC time series. Effects of group, laterality, and emotion intensity upon amygdala-OFC FC and amygdala-OFC FC white matter fractional anisotropy (FA) relationships were examined. Results: The BD versus HC showed significantly greater right amygdala-OFC FC (p <= .001) in the sad experiment and significantly reduced bilateral amygdala-OFC FC (p = .007) in the happy experiment. Depressed but not remitted female BD versus female HC showed significantly greater left amygdala-OFC FC (p = .001) to all faces in the sad experiment and reduced bilateral amygdala-OFC FC to intense happy faces (p = .01). There was a significant nonlinear relationship (p = .001) between left amygdala-OFC FC to sad faces and FA in HC. In BD, antidepressants were associated with significantly reduced left amygdala-OFC FC to mild sad faces (p = .001). Conclusions: In BD, abnormally elevated right amygdala-OFC FC to sad stimuli might represent a trait vulnerability for depression, whereas abnormally elevated left amygdala-OFC FC to sad stimuli and abnormally reduced amygdala-OFC FC to intense happy stimuli might represent a depression state marker. Abnormal FC measures might normalize with antidepressant medications in BD. Nonlinear amygdala-OFC FC-FA relationships in BID and HC require further study.