Increases in prefrontal cortex activity when regulating negative emotion predicts symptom severity trajectory over six months in depression

Context: Emotion regulation is critically disrupted in depression and use of paradigms tapping these processes may uncover essential changes in neurobiology during treatment. In addition, as neuroimaging outcome studies of depression commonly utilize solely baseline and endpoint data – which is more prone to week-to week noise in symptomatology – we sought to use all data points over the course of a six month trial. Objective: To examine changes in neurobiology resulting from successful treatment. Design: Double-blind trial examining changes in the neural circuits involved in emotion regulation resulting from one of two antidepressant treatments over a six month trial. Participants were scanned pretreatment, at 2 months and 6 months posttreatment. Setting: University functional magnetic resonance imaging facility. Participants: 21 patients with Major Depressive Disorder and without other Axis I or Axis II diagnoses and 14 healthy controls. Interventions: Venlafaxine XR (doses up to 300mg) or Fluoxetine (doses up to 80mg). Main Outcome Measure: Neural activity, as measured using functional magnetic resonance imaging during performance of an emotion regulation paradigm as well as regular assessments of symptom severity by the Hamilton Rating Scale for Depression. To utilize all data points, slope trajectories were calculated for rate of change in depression severity as well as rate of change of neural engagement. Results: Those depressed individuals showing the steepest decrease in depression severity over the six months were those individuals showing the most rapid increases in BA10 and right DLPFC activity when regulating negative affect over the same time frame. This relationship was more robust than when using solely the baseline and endpoint data. Conclusions: Changes in PFC engagement when regulating negative affect correlate with changes in depression severity over six months. These results are buttressed by calculating these statistics which are more reliable and robust to week-to-week variation than difference scores.

Antidepressant treatment and emotional processing: can we dissociate the roles of serotonin and noradrenaline?

The ability to match individual patients to tailored treatments has the potential to greatly improve outcomes for individuals suffering from major depression. In particular, while the vast majority of antidepressant treatments affect either serotonin or noradrenaline or a combination of these two neurotransmitters, it is not known whether there are particular patients or symptom profiles which respond preferentially to the potentiation of serotonin over noradrenaline or vice versa. Experimental medicine models suggest that the primary mode of action of these treatments may be to remediate negative biases in emotional processing. Such models may provide a useful framework for interrogating the specific actions of antidepressants. Here, we therefore review evidence from studies examining the effects of drugs which potentiate serotonin, noradrenaline or a combination of both neurotransmitters on emotional processing. These results suggest that antidepressants targeting serotonin and noradrenaline may have some specific actions on emotion and reward processing which could be used to improve tailoring of treatment or to understand the effects of dual-reuptake inhibition. Specifically, serotonin may be particularly important in alleviating distress symptoms, while noradrenaline may be especially relevant to anhedonia. The data reviewed here also suggest that noradrenergic-based treatments may have earlier effects on emotional memory that those which affect serotonin.

Effects of physiotherapy on hemodynamic variables in newborns with Acute Respiratory Distress Syndrome

Background: Acute respiratory distress syndrome (ARDS) is a frequent respiratory disturbance in preterm newborns. Preceding investigations evaluated chronic physiotherapy effects on newborns with different lung diseases; however, no study analyzed acute physiotherapy treatment on premature newborns with ARDS. In this study we aimed to evaluate the acute effects of chest and motor physiotherapy treatment on hemodynamic variables in preterm newborns with ARDS. Methods: We evaluated heart rate (HR), respiratory rate (RR), systolic (SAP), mean (MAP) and diastolic arterial pressure (DAP), temperature and oxygen saturation (SO(2)%) in 44 newborns with ARDS. We compared all variables between six periods in one day: before first physiotherapy treatment vs. after first physiotherapy treatment vs. before second physiotherapy treatment vs. after second physiotherapy treatment vs. before third physiotherapy treatment vs. after third physiotherapy treatment. Variables were measured 2 minutes before and 5 minutes after each physiotherapy session. We applied Anova one way followed by post hoc Bonferroni test. Results: HR (147.5 +/- 9.5 bpm vs. 137.7 +/- 9.3 bpm; p<0.001), RR (45.5 +/- 8.7cpm vs. 41.5 +/- 6.7 cpm; p=0.001), SAP (70.3 +/- 10.4 mmHg vs. 60.1 +/- 7.1 mmHg; p=0.001) and MAP (55.7 +/- 10 mmHg vs. 46 +/- 6.6 mmHg; p=0.001) were significantly reduced after the third physiotherapy treatment compared to before the first session. There were no significant changes regarding temperature, DAP and SO(2) %. Conclusion: Chest and motor physiotherapy acutely improves HR, RR, SAP, MAP and SO(2) % in newborns with ARDS.

Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

Financial distress as a collapse of incentive scheme

This paper explaina why workers lack motivation near bankruptcy, why they tend to leave companies in financiai distreas, and why thoae who remam require higher compensation. Theae indirect costa of financiai diatresa adie becauae the optimal combination of debt and incentive achem.ea, deaigned to minimize agency costa, ends up underpaying managers when there ia a bankruptcy threat. The paper a1so providea new empirica1 implications on the intera.ction between financiai reatructuring and changea in managerial compensation. Theae predictions are supported by the findings of Gilson and Vetsuypens (1992).

Estruturas de governança corporativa e financial distress: há relação entre conselho de administração e empresas em financial distress?

Nesta dissertação foi analisada se há uma relação significante entre estruturas de governança (estrutura e composição de conselho) e financial distress. Este trabalho focou neste tema porque os estudos acadêmicos em governança corporativa e sua relação com financial distress ainda são pouco explorados. Além disso, o tema tem relevância no mundo corporativo, pois entender quais estruturas e composições de conselho seriam mais eficientes para evitar financial distress é interessante para diversos stakeholders, principalmente para os acionistas e os credores. Para verificar a existência dessa relação, foram utilizados dados de empresas brasileiras de capital aberto e foram desenvolvidos modelos logit de financial distress. Sendo a variável resposta financial distress, partiu-se de um modelo base com variáveis financeiras de controle e, por etapas, foram adicionadas novos determinantes e combinações dessas variáveis para montar modelos intermediários. Por fim, o modelo final contou com todas as variáveis explicativas mais relevantes. As variáveis de estudo podem ser classificadas em variáveis de estrutura de governança (DUA, GOV e COF), qualidade do conselho (QUA) e estrutura de propriedade (PRO1 e PRO2). Os modelos base utilizados foram: Daily e Dalton (1994a) e um próprio, desenvolvido para modelar melhor financial distress e sua relação com as variáveis de estrutura de governança. Nos diversos modelos testados foram encontradas relações significativas no percentual de conselheiros dependentes (GOV), percentual de conselheiros da elite educacional (QUA), percentual de ações discriminadas (PRO1) e percentual de ações de acionista estatal relevante (PRO2). Portanto, não se descartam as hipóteses de que mais conselheiros dependentes, menos conselheiros da elite educacional e estrutura de propriedade menos concentrada contribuem para uma situação de financial distress futura. Entretanto, as variáveis dummy de dualidade (DUA) e de conselho fiscal (COF) não apresentaram significância estatística.

Estruturas de governança corporativa e financial distress: há relação entre conselho de administração e empresas em financial distress?

Nesta dissertação foi analisada se há uma relação significante entre estruturas de governança (estrutura e composição de conselho) e financial distress. Este trabalho focou neste tema porque os estudos acadêmicos em governança corporativa e sua relação com financial distress ainda são pouco explorados. Além disso, o tema tem relevância no mundo corporativo, pois entender quais estruturas e composições de conselho seriam mais eficientes para evitar financial distress é interessante para diversos stakeholders, principalmente para os acionistas e os credores. Para verificar a existência dessa relação, foram utilizados dados de empresas brasileiras de capital aberto e foram desenvolvidos modelos logit de financial distress. Sendo a variável resposta financial distress, partiu-se de um modelo base com variáveis financeiras de controle e, por etapas, foram adicionadas novos determinantes e combinações dessas variáveis para montar modelos intermediários. Por fim, o modelo final contou com todas as variáveis explicativas mais relevantes. As variáveis de estudo podem ser classificadas em variáveis de estrutura de governança (DUA, GOV e COF), qualidade do conselho (QUA) e estrutura de propriedade (PRO1 e PRO2). Os modelos base utilizados foram: Daily e Dalton (1994a) e um próprio, desenvolvido para modelar melhor financial distress e sua relação com as variáveis de estrutura de governança. Nos diversos modelos testados foram encontradas relações significativas no percentual de conselheiros dependentes (GOV), percentual de conselheiros da elite educacional (QUA), percentual de ações discriminadas (PRO1) e percentual de ações de acionista estatal relevante (PRO2). Portanto, não se descartam as hipóteses de que mais conselheiros dependentes, menos conselheiros da elite educacional e estrutura de propriedade menos concentrada contribuem para uma situação de financial distress futura. Entretanto, as variáveis dummy de dualidade (DUA) e de conselho fiscal (COF) não apresentaram significância estatística

Positive end-expiratory pressure in acute respiratory distress syndrome: should the 'open lung strategy' be replaced by a 'protective lung strategy'?

In patients with acute respiratory distress syndrome, positive end-expiratory pressure is associated with alveolar recruitment and lung hyperinflation despite the administration of a low tidal volume. The best positive end-expiratory pressure should correspond to the best compromise between recruitment and distension, a condition that coincides with the best respiratory elastance.

Lung ultrasound in acute respiratory distress syndrome and acute lung injury

Purpose of reviewLung ultrasound at the bedside can provide accurate information on lung status in critically ill patients with acute respiratory distress syndrome.Recent findingsLung ultrasound can replace bedside chest radiography and lung computed tomography for assessment of pleural effusion, pneumothorax, alveolar- interstitial syndrome, lung consolidation, pulmonary abscess and lung recruitment/de-recruitment. It can also accurately determine the type of lung morphology at the bedside (focal or diffuse aeration loss), and therefore it is useful for optimizing positive end-expiratory pressure. The learning curve is brief, so most intensive care physicians will be able to use it after a few weeks of training.SummaryLung ultrasound is noninvasive, easily repeatable and allows assessment of changes in lung aeration induced by the various therapies. It is among the most promising bedside techniques for monitoring patients with acute respiratory distress syndrome.