284 resultados para Depression Severity Transition Probability Matrix
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
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Objectives: The absence of pathophysiologically relevant diagnostic markers of bipolar disorder (BD) leads to its frequent misdiagnosis as unipolar depression (UD). We aimed to determine whether whole brain white matter connectivity differentiated BD from UD depression. Methods: We employed a three-way analysis of covariance, covarying for age, to examine whole brain fractional anisotropy (FA), and corresponding longitudinal and radial diffusivity, in currently depressed adults: 15 with BD-type I (mean age 36.3 years, SD 12.0 years), 16 with recurrent UD (mean age 32.3 years, SD 10.0 years), and 24 healthy control adults (HC) (mean age 29.5 years, SD 9.43 years). Depressed groups did not differ in depression severity, age of illness onset, and illness duration. Results: There was a main effect of group in left superior and inferior longitudinal fasciculi (SLF and ILF) (all F >= 9.8; p <= .05, corrected). Whole brain post hoc analyses (all t >= 4.2; p <= .05, corrected) revealed decreased FA in left SLF in BD, versus UD adults in inferior temporal cortex and, versus HC, in primary sensory cortex (associated with increased radial and decreased longitudinal diffusivity, respectively); and decreased FA in left ILF in UD adults versus HC. A main effect of group in right uncinate fasciculus (in orbitofrontal cortex) just failed to meet significance in all participants but was present in women. Post hoc analyses revealed decreased right uncinate fasciculus FA in all and in women, BD versus HC. Conclusions: White matter FA in left occipitotemporal and primary sensory regions supporting visuospatial and sensory processing differentiates BD from UD depression. Abnormally reduced FA in right fronto-temporal regions supporting mood regulation, might underlie. predisposition to depression in BD. These measures might help differentiate pathophysiologic processes of BD versus UD depression.
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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.
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Background: Bipolar disorder is frequently misdiagnosed as major depressive disorder, delaying appropriate treatment and worsening outcome for many bipolar individuals. Emotion dysregulation is a core feature of bipolar disorder. Measures of dysfunction in neural systems supporting emotion regulation might therefore help discriminate bipolar from major depressive disorder. Methods: Thirty-one depressed individuals-15 bipolar depressed (BD) and 16 major depressed (MDD), DSM-IV diagnostic criteria, ages 18-55 years, matched for age, age of illness onset, illness duration, and depression severity-and 16 age- and gender-matched healthy control subjects performed two event-related paradigms: labeling the emotional intensity of happy and sad faces, respectively. We employed dynamic causal modeling to examine significant among-group alterations in effective connectivity (EC) between right- and left-sided neural regions supporting emotion regulation: amygdala and orbitomedial prefrontal cortex (OMPFC). Results: During classification of happy faces, we found profound and asymmetrical differences in EC between the OMPFC and amygdala. Left-sided differences involved top-down connections and discriminated between depressed and control subjects. Furthermore, greater medication load was associated with an amelioration of this abnormal top-down EC. Conversely, on the right side the abnormality was in bottom-up EC that was specific to bipolar disorder. These effects replicated when we considered only female subjects. Conclusions: Abnormal, left-sided, top-down OMPFC-amygdala and right-sided, bottom-up, amygdala-OMPFC EC during happy labeling distinguish BD and MDD, suggesting different pathophysiological mechanisms associated with the two types of depression.
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Nonsyndromic cleft lip and palate (NSCL/P) is a complex disease resulting from failure of fusion of facial primordia, a complex developmental process that includes the epithelial-mesenchymal transition (EMT). Detection of differential gene transcription between NSCL/P patients and control individuals offers an interesting alternative for investigating pathways involved in disease manifestation. Here we compared the transcriptome of 6 dental pulp stem cell (DPSC) cultures from NSCL/P patients and 6 controls. Eighty-seven differentially expressed genes (DEGs) were identified. The most significant putative gene network comprised 13 out of 87 DEGs of which 8 encode extracellular proteins: ACAN, COL4A1, COL4A2, GDF15, IGF2, MMP1, MMP3 and PDGFa. Through clustering analyses we also observed that MMP3, ACAN, COL4A1 and COL4A2 exhibit co-regulated expression. Interestingly, it is known that MMP3 cleavages a wide range of extracellular proteins, including the collagens IV, V, IX, X, proteoglycans, fibronectin and laminin. It is also capable of activating other MMPs. Moreover, MMP3 had previously been associated with NSCL/P. The same general pattern was observed in a further sample, confirming involvement of synchronized gene expression patterns which differed between NSCL/P patients and controls. These results show the robustness of our methodology for the detection of differentially expressed genes using the RankProd method. In conclusion, DPSCs from NSCL/P patients exhibit gene expression signatures involving genes associated with mechanisms of extracellular matrix modeling and palate EMT processes which differ from those observed in controls. This comparative approach should lead to a more rapid identification of gene networks predisposing to this complex malformation syndrome than conventional gene mapping technologies.
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Consider a continuous-time Markov process with transition rates matrix Q in the state space Lambda boolean OR {0}. In In the associated Fleming-Viot process N particles evolve independently in A with transition rates matrix Q until one of them attempts to jump to state 0. At this moment the particle jumps to one of the positions of the other particles, chosen uniformly at random. When Lambda is finite, we show that the empirical distribution of the particles at a fixed time converges as N -> infinity to the distribution of a single particle at the same time conditioned on not touching {0}. Furthermore, the empirical profile of the unique invariant measure for the Fleming-Viot process with N particles converges as N -> infinity to the unique quasistationary distribution of the one-particle motion. A key element of the approach is to show that the two-particle correlations are of order 1/N.
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We propose an alternative fidelity measure (namely, a measure of the degree of similarity) between quantum states and benchmark it against a number of properties of the standard Uhlmann-Jozsa fidelity. This measure is a simple function of the linear entropy and the Hilbert-Schmidt inner product between the given states and is thus, in comparison, not as computationally demanding. It also features several remarkable properties such as being jointly concave and satisfying all of Jozsa's axioms. The trade-off, however, is that it is supermultiplicative and does not behave monotonically under quantum operations. In addition, metrics for the space of density matrices are identified and the joint concavity of the Uhlmann-Jozsa fidelity for qubit states is established.
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We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.
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Background: Little is known about the treatment of depression in older patients with heart failure. This Study was developed to investigate the effectiveness of antidepressant treatment for major depressive disorder (MDD) in the elderly with heart failure. Methods: We enrolled 72 older outpatients with ejection fraction < 50 and diagnosed with MDD by the structured clinical interview for DSM-IV. Thirty-seven patients, 19 on citalopram and 18 on placebo, initiated an 8-week double-blind treatment phase. Measurements were performed with the 31-item Hamilton Rating Scale for Depression (Ham-D-31), the Montgomery-Asberg rating scale (MADRS) and the Systematic Assessment for Treatment Emergent Effects (SAFTEE). A psychiatrist followed up the patients weekly, performing a consultation for about 20 min to field complaints after the measurements. Results: A trend toward superiority of citalopram over placebo in reducing depression was observed in MADRS scores (15.05 + 9.74 vs 9.44 + 9.25, P = .082) but not on HAM-D scores. The depressive symptomatology significantly decreased in both groups (P < .001). The high rate of placebo response during the double-blind phase (56.3%) led us to conclude the study at the interim analysis with 37 patients. Conclusion: Citalopram treatment of MDD in older patients with heart failure is well-tolerated with low rates of side effects, but was not significantly more effective than placebo in the treatment of depression. Weekly psychiatric follow-up including counseling may contribute to the improvement of depression in this population. Scales weighted on psychological symptoms such as the MADRS are possibly better suited to measure depression severity and improvement in patients with heart failure. (C) 2009 Elsevier Inc. All rights reserved.
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Background: Obsessive-compulsive disorder (OCD) is a clinically heterogenous disorder characterized by temporally stable symptom dimensions. Past inconsistent results from structural neuroimaging studies of OCD may have resulted from the effects of these specific symptom dimensions as well as other socio-demographic and clinical variables upon gray matter (GM) volume. Methods: GM volume was measured in 25 adult OCD patients and 20 adult healthy controls using voxel-based morphometry (VBM), controlling for age and total brain GM volume. Univariate and multivariate regression analyses were carried out between regions of GM difference and age, age of onset, medication load, OCD severity, depression severity, and separate symptom dimension scores. Results: Significant GM volumetric differences in OCD patients relative to controls were found in dorsal cortical regions, including bilateral BA6, BA46, BA9 and right BA8 (controls > patients), and bilateral midbrain (patients > controls). Stepwise regression analyses revealed highly significant relationships between greater total OCD symptom severity and smaller GM volumes in dorsal cortical regions and larger GM volumes in bilateral midbrain. Greater age was independently associated with smaller GM volumes in right BA6, left BA9, left BA46 and larger GM volumes in right midbrain. Greater washing symptom severity was independently associated with smaller GM volume in right BA6, while there was a trend association between greater hoarding symptom severity and lower GM volume in left BA6. Limitations: The sample was relatively small to examine the relationship between symptom scores and GM volumes. Multiple patients were taking medication and had comorbid disorders. Conclusions: These analyses suggest dorsal prefrontal cortical and bilateral midbrain GM abnormalities in OCD that appear to be primarily driven by the effects of total OCD symptom severity. The results regarding the relationship between GM volumes and symptom dimension scores require examination in larger samples. (C) 2008 Elsevier B.V. All rights reserved.
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In this work, we investigate the control of the two-photon absorption process of a series of organic compounds via spectral phase modulation of the excitation pulse. We analyzed the effect of the pulse central wavelength on the control of the two-photon absorption process for each compound. Depending on the molecules` two-photon absorption position relative to the excitation pulse wavelength, different levels of coherent control were observed. By simulating the two-photon transition probability in molecular systems, taking into account the band structure and its positions, we could explain the experimental results trends. We observed that the intrapulse coherent interference plays an important role in the nonlinear process control besides just the pulse intensity modulation.
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One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.
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Objective. Increased GSK3B activity has been reported as a state marker of major affective episodes in patients with depression and bipolar disorder. No study so far has addressed GSK3B activity in late-life depression. The aims of the present study were to determine GSK3B activity in platelets of elderly patients with major depression, and the association between GSK3B activity and the severity of depressive symptoms and cognitive impairment. Methods. Forty drug-free elderly patients with major depressive episode were compared to healthy older adults (n == 13). Severity of the depressive episode and current cognitive state were determined by the Hamilton Depression Scale (HAM-D) and the Cambridge Cognitive Test (CAMCOG), respectively. Total- and ser-9-phosphorylated GSK3B (tGSK3B and pGSK3B) were determined in platelets by enzyme immunometric assays (EIA). GSK3B activity was indirectly inferred by the GSK3B ratio (i.e. pGSK3B/tGSK3B). Results. Elderly depressed patients had significantly lower pGSK3B levels (P == 0.03) and GSK3B ratio (P == 0.03), indicating higher GSK3B activity. Higher GSK3B activity were observed in patients with severe depressive episode (HAM-D scores > 22, P == 0.03) and with cognitive impairment (CAMCOG scores < 86, P == 0.01). Conclusion. The present findings provide additional evidence of the involvement of GSK3B in the pathophysiology of late-life major depression. Higher GSK3B activity may be more relevant in those patients with more severe depressive symptoms and cognitive impairment.
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Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.
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The structure of probability currents is studied for the dynamical network after consecutive contraction on two-state, nonequilibrium lattice systems. This procedure allows us to investigate the transition rates between configurations on small clusters and highlights some relevant effects of lattice symmetries on the elementary transitions that are responsible for entropy production. A method is suggested to estimate the entropy production for different levels of approximations (cluster sizes) as demonstrated in the two-dimensional contact process with mutation.
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In random matrix theory, the Tracy-Widom (TW) distribution describes the behavior of the largest eigenvalue. We consider here two models in which TW undergoes transformations. In the first one disorder is introduced in the Gaussian ensembles by superimposing an external source of randomness. A competition between TW and a normal (Gaussian) distribution results, depending on the spreading of the disorder. The second model consists of removing at random a fraction of (correlated) eigenvalues of a random matrix. The usual formalism of Fredholm determinants extends naturally. A continuous transition from TW to the Weilbull distribution, characteristic of extreme values of an uncorrelated sequence, is obtained.