Inserimento eterofamigliare supportato di adulti sofferenti di disturbi psichici: Valutazione degli esiti

L’Inserimento Eterofamigliare Supportato di Adulti (IESA) sofferenti di disturbi psichici consiste nell’accogliere persone in cura presso i servizi psichiatrici territoriali, nel proprio domicilio, integrandole nelle proprie relazioni famigliari. Obiettivo è migliorare la qualità di vita dell’utente e favorirne l’integrazione nella comunità. Obiettivo. Valutare gli esiti dello IESA, con un disegno di ricerca longitudinale, considerando: psicopatologia, benessere psicologico, funzionamento sociale e familiare. Metodologia. 40 soggetti: 20 pazienti e 20 ospitanti. La valutazione clinica è stata effettuata all’inizio della convivenza e al follow-up di 1, 3, 6 e 12 mesi. Strumenti utilizzati: BPRS, VGF, PWB, SQ, FAD. Analisi statistica: Modello Lineare Generale (GLM) con l’Analisi della Varianza per prove ripetute e calcolo dell’effect-size. Risultati. 15 pazienti maschi e 5 femmine, 17 italiani. 11 soddisfano i criteri diagnostici (DSM-IV-TR) per schizofrenia e disturbi psicotici, 5 per i disturbi dell’umore e 4 per i disturbi di personalità. Dopo l’inserimento 3 sono stati i ricoveri e 4 le visite psichiatriche urgenti. 8 pazienti modificano/diminuiscono la terapia e 3 la sospendono. Aumenta il benessere psicologico (PWB); diminuiscono i sintomi psicopatologici (BPRS ed SQ) e migliora il funzionamento globale (VFG). Il gruppo dei famigliari composto da 11 uomini e 9 donne, 19 di nazionalità italiana; con età media di 55 anni. 8 sono coniugati, 6 celibi/nubili, 4 divorziati e 2 vedovi. 9 hanno figli, 11 lavorano e 8 sono pensionati. Nei famigliari aumenta il benessere psicologico (PWB), migliora il funzionamento famigliare (FAD) e la valutazione del funzionamento globale (VGF) rimane costante nel tempo. Discussioni e conclusioni. Il progetto IESA sembra migliorare la psicopatologia, con una diminuzione dei comportamenti maladattativi e un aumento delle capacità relazionali dell’ospite favorendone l’integrazione. Inoltre, lo IESA sembra diminuire i costi della cronicità psichiatrica: diminuzione degli accessi al Pronto Soccorso, delle visite psichiatriche urgenti e delle giornate di ricovero.

Dynamics and control issues of multi-rotor platforms

This thesis deals with the analytic study of dynamics of Multi--Rotor Unmanned Aerial Vehicles. It is conceived to give a set of mathematical instruments apt to the theoretical study and design of these flying machines. The entire work is organized in analogy with classical academic texts about airplane flight dynamics. First, the non--linear equations of motion are defined and all the external actions are modeled, with particular attention to rotors aerodynamics. All the equations are provided in a form, and with personal expedients, to be directly exploitable in a simulation environment. This has requited an answer to questions like the trim of such mathematical systems. All the treatment is developed aiming at the description of different multi--rotor configurations. Then, the linearized equations of motion are derived. The computation of the stability and control derivatives of the linear model is carried out. The study of static and dynamic stability characteristics is, thus, addressed, showing the influence of the various geometric and aerodynamic parameters of the machine and in particular of the rotors. All the theoretic results are finally utilized in two interesting cases. One concerns the design of control systems for attitude stabilization. The linear model permits the tuning of linear controllers gains and the non--linear model allows the numerical testing. The other case is the study of the performances of an innovative configuration of quad--rotor aircraft. With the non--linear model the feasibility of maneuvers impossible for a traditional quad--rotor is assessed. The linear model is applied to the controllability analysis of such an aircraft in case of actuator block.

Alterations of white matter integrity related to motor activity in schizophrenia

Altered structural connectivity is a key finding in schizophrenia, but the meaning of white matter alterations for behavior is rarely studied. In healthy subjects, motor activity correlated with white matter integrity in motor tracts. To explore the relation of motor activity and fractional anisotropy (FA) in schizophrenia, we investigated 19 schizophrenia patients and 24 healthy control subjects using Diffusion Tensor Imaging (DTI) and actigraphy on the same day. Schizophrenia patients had lower activity levels (AL). In both groups linear relations of AL and FA were detected in several brain regions. Schizophrenia patients had lower FA values in prefrontal and left temporal clusters. Furthermore, using a general linear model, we found linear negative associations of FA and AL underneath the right supplemental motor area (SMA), the right precentral gyrus and posterior cingulum in patients. This effect within the SMA was not seen in controls. This association in schizophrenia patients may contribute to the well known dysfunctions of motor control. Thus, structural disconnectivity could lead to disturbed motor behavior in schizophrenia.

The link between visual exploration and neuronal activity: A multi-modal study combining eye tracking, functional magnetic resonance imaging and transcranial magnetic stimulation

In the present multi-modal study we aimed to investigate the role of visual exploration in relation to the neuronal activity and performance during visuospatial processing. To this end, event related functional magnetic resonance imaging er-fMRI was combined with simultaneous eye tracking recording and transcranial magnetic stimulation (TMS). Two groups of twenty healthy subjects each performed an angle discrimination task with different levels of difficulty during er-fMRI. The number of fixations as a measure of visual exploration effort was chosen to predict blood oxygen level-dependent (BOLD) signal changes using the general linear model (GLM). Without TMS, a positive linear relationship between the visual exploration effort and the BOLD signal was found in a bilateral fronto-parietal cortical network, indicating that these regions reflect the increased number of fixations and the higher brain activity due to higher task demands. Furthermore, the relationship found between the number of fixations and the performance demonstrates the relevance of visual exploration for visuospatial task solving. In the TMS group, offline theta bursts TMS (TBS) was applied over the right posterior parietal cortex (PPC) before the fMRI experiment started. Compared to controls, TBS led to a reduced correlation between visual exploration and BOLD signal change in regions of the fronto-parietal network of the right hemisphere, indicating a disruption of the network. In contrast, an increased correlation was found in regions of the left hemisphere, suggesting an intent to compensate functionality of the disturbed areas. TBS led to fewer fixations and faster response time while keeping accuracy at the same level, indicating that subjects explored more than actually needed.

Population-based analysis of 4113 patients with acute cholecystitis: defining the optimal time-point for laparoscopic cholecystectomy

Objective: To compare clinical outcomes after laparoscopic cholecystectomy (LC) for acute cholecystitis performed at various time-points after hospital admission. Background: Symptomatic gallstones represent an important public health problem with LC the treatment of choice. LC is increasingly offered for acute cholecystitis, however, the optimal time-point for LC in this setting remains a matter of debate. Methods: Analysis was based on the prospective database of the Swiss Association of Laparoscopic and Thoracoscopic Surgery and included patients undergoing emergency LC for acute cholecystitis between 1995 and 2006, grouped according to the time-points of LC since hospital admission (admission day (d0), d1, d2, d3, d4/5, d ≥6). Linear and generalized linear regression models assessed the effect of timing of LC on intra- or postoperative complications, conversion and reoperation rates and length of postoperative hospital stay. Results: Of 4113 patients, 52.8% were female, median age was 59.8 years. Delaying LC resulted in significantly higher conversion rates (from 11.9% at d0 to 27.9% at d ≥6 days after admission, P < 0.001), surgical postoperative complications (5.7% to 13%, P < 0.001) and re-operation rates (0.9% to 3%, P = 0.007), with a significantly longer postoperative hospital stay (P < 0.001). Conclusions: Delaying LC for acute cholecystitis has no advantages, resulting in significantly increased conversion/re-operation rate, postoperative complications and longer postoperative hospital stay. This investigation—one of the largest in the literature—provides compelling evidence that acute cholecystitis merits surgery within 48 hours of hospital admission if impact on the patient and health care system is to be minimized.

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

Regional mRNA expression of key gluconeogenic enzymes in the liver of dairy cows

Liver tissue was collected from eight random dairy cows at a slaughterhouse to test if gene expression of pyruvate carboxylase (PC), mitochondrial phosphoenolpyruvate carboxykinase (PEPCKm) and cytosolic phosphoenolpyruvate carboxykinase (PEPCKc) is different at different locations in the liver. Obtained liver samples were analysed for mRNA expression levels of PC, PEPCKc and PEPCKm and subjected to the MIXED procedure of SAS to test for the sampled locations with cow liver as repeated subject. Additionally, the general linear model procedure (GLM) for analysis of variance was applied to test for significant differences for mRNA abundance of PEPCKm, PEPCKc and bPC between the livers. In conclusion, this study demonstrated that mRNA abundance of PC, PEPCKc and PEPCKm is not different between locations in the liver but may differ between individual cows.

Concomitant Vascular Reconstruction During Pancreatectomy for Malignant Disease: A Propensity Score-Adjusted, Population-Based Trend Analysis Involving 10 206 Patients

OBJECTIVE To assess trends in the frequency of concomitant vascular reconstructions (VRs) from 2000 through 2009 among patients who underwent pancreatectomy, as well as to compare the short-term outcomes between patients who underwent pancreatic resection with and without VR. DESIGN Single-center series have been conducted to evaluate the short-term and long-term outcomes of VR during pancreatic resection. However, its effectiveness from a population-based perspective is still unknown. Unadjusted, multivariable, and propensity score-adjusted generalized linear models were performed. SETTING Nationwide Inpatient Sample from 2000 through 2009. PATIENTS A total of 10 206 patients were involved. MAIN OUTCOME MEASURES Incidence of VR during pancreatic resection, perioperative in-hospital complications, and length of hospital stay. RESULTS Overall, 10 206 patients were included in this analysis. Of these, 412 patients (4.0%) underwent VR, with the rate increasing from 0.7% in 2000 to 6.0% in 2009 (P < .001). Patients who underwent pancreatic resection with VR were at a higher risk for intraoperative (propensity score-adjusted odds ratio, 1.94; P = .001) and postoperative (propensity score-adjusted odds ratio, 1.36; P = .008) complications, while the mortality and median length of hospital stay were similar to those of patients without VR. Among the 25% of hospitals with the highest surgical volume, patients who underwent pancreatic surgery with VR had significantly higher rates of postoperative complications and mortality than patients without VR. CONCLUSIONS The frequency of VR during pancreatic surgery is increasing in the United States. In contrast with most single-center analyses, this population-based study demonstrated that patients who underwent VR during pancreatic surgery had higher rates of adverse postoperative outcomes than their counterparts who underwent pancreatic resection only. Prospective studies incorporating long-term outcomes are warranted to further define which patients benefit from VR.

Whither PQL?

Generalized linear mixed models (GLMM) are generalized linear models with normally distributed random effects in the linear predictor. Penalized quasi-likelihood (PQL), an approximate method of inference in GLMMs, involves repeated fitting of linear mixed models with “working” dependent variables and iterative weights that depend on parameter estimates from the previous cycle of iteration. The generality of PQL, and its implementation in commercially available software, has encouraged the application of GLMMs in many scientific fields. Caution is needed, however, since PQL may sometimes yield badly biased estimates of variance components, especially with binary outcomes. Recent developments in numerical integration, including adaptive Gaussian quadrature, higher order Laplace expansions, stochastic integration and Markov chain Monte Carlo (MCMC) algorithms, provide attractive alternatives to PQL for approximate likelihood inference in GLMMs. Analyses of some well known datasets, and simulations based on these analyses, suggest that PQL still performs remarkably well in comparison with more elaborate procedures in many practical situations. Adaptive Gaussian quadrature is a viable alternative for nested designs where the numerical integration is limited to a small number of dimensions. Higher order Laplace approximations hold the promise of accurate inference more generally. MCMC is likely the method of choice for the most complex problems that involve high dimensional integrals.

Increased sensitivity in mapping task demand in visuospatial processing using reaction-time-dependent hemodynamic response predictors in rapid event-related fMRI

Searching for the neural correlates of visuospatial processing using functional magnetic resonance imaging (fMRI) is usually done in an event-related framework of cognitive subtraction, applying a paradigm comprising visuospatial cognitive components and a corresponding control task. Besides methodological caveats of the cognitive subtraction approach, the standard general linear model with fixed hemodynamic response predictors bears the risk of being underspecified. It does not take into account the variability of the blood oxygen level-dependent signal response due to variable task demand and performance on the level of each single trial. This underspecification may result in reduced sensitivity regarding the identification of task-related brain regions. In a rapid event-related fMRI study, we used an extended general linear model including single-trial reaction-time-dependent hemodynamic response predictors for the analysis of an angle discrimination task. In addition to the already known regions in superior and inferior parietal lobule, mapping the reaction-time-dependent hemodynamic response predictor revealed a more specific network including task demand-dependent regions not being detectable using the cognitive subtraction method, such as bilateral caudate nucleus and insula, right inferior frontal gyrus and left precentral gyrus.

Semiparametric Estimation in General Repeated Measures Problems

This paper considers a wide class of semiparametric problems with a parametric part for some covariate effects and repeated evaluations of a nonparametric function. Special cases in our approach include marginal models for longitudinal/clustered data, conditional logistic regression for matched case-control studies, multivariate measurement error models, generalized linear mixed models with a semiparametric component, and many others. We propose profile-kernel and backfitting estimation methods for these problems, derive their asymptotic distributions, and show that in likelihood problems the methods are semiparametric efficient. While generally not true, with our methods profiling and backfitting are asymptotically equivalent. We also consider pseudolikelihood methods where some nuisance parameters are estimated from a different algorithm. The proposed methods are evaluated using simulation studies and applied to the Kenya hemoglobin data.

Multiple Testing With an Empirical Alternative Hypothesis

An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for use of an empirical alternative hypothesis to increase by 50% or more the number of true positives identified at a given significance level.

DECOMPOSITION OF REGRESSION ESTIMATORS TO EXPLORE THE INFLUENCE OF "UNMEASURED" TIME-VARYING CONFOUNDERS

In environmental epidemiology, exposure X and health outcome Y vary in space and time. We present a method to diagnose the possible influence of unmeasured confounders U on the estimated effect of X on Y and to propose several approaches to robust estimation. The idea is to use space and time as proxy measures for the unmeasured factors U. We start with the time series case where X and Y are continuous variables at equally-spaced times and assume a linear model. We define matching estimator b(u)s that correspond to pairs of observations with specific lag u. Controlling for a smooth function of time, St, using a kernel estimator is roughly equivalent to estimating the association with a linear combination of the b(u)s with weights that involve two components: the assumptions about the smoothness of St and the normalized variogram of the X process. When an unmeasured confounder U exists, but the model otherwise correctly controls for measured confounders, the excess variation in b(u)s is evidence of confounding by U. We use the plot of b(u)s versus lag u, lagged-estimator-plot (LEP), to diagnose the influence of U on the effect of X on Y. We use appropriate linear combination of b(u)s or extrapolate to b(0) to obtain novel estimators that are more robust to the influence of smooth U. The methods are extended to time series log-linear models and to spatial analyses. The LEP plot gives us a direct view of the magnitude of the estimators for each lag u and provides evidence when models did not adequately describe the data.

Reduced neuronal efficacy in progressive mild cognitive impairment: a prospective fMRI study on visuospatial processing

Mild cognitive impairment (MCI) often refers to the preclinical stage of dementia, where the majority develop Alzheimer's disease (AD). Given that neurodegenerative burden and compensatory mechanisms might exist before accepted clinical symptoms of AD are noticeable, the current prospective study aimed to investigate the functioning of brain regions in the visuospatial networks responsible for preclinical symptoms in AD using event-related functional magnetic resonance imaging (fMRI). Eighteen MCI patients were evaluated and clinically followed for approximately 3 years. Five progressed to AD (PMCI) and eight remained stable (SMCI). Thirteen age-, gender- and education-matched controls also participated. An angle discrimination task with varying task demands was used. Brain activation patterns as well as task demand-dependent and -independent signal changes between the groups were investigated by using an extended general linear model including individual performance (reaction time [RT]) of each single trial. Similar behavioral (RT and accuracy) responses were observed between MCI patients and controls. A network of bilateral activations, e.g. dorsal pathway, which increased linearly with increasing task demand, was engaged in all subjects. Compared with SMCI patients and controls, PMCI patients showed a stronger relation between task demand and brain activity in left superior parietal lobules (SPL) as well as a general task demand-independent increased activation in left precuneus. Altered brain function can be detected at a group level in individuals that progress to AD before changes occur at the behavioral level. Increased parietal activation in PMCI could reflect a reduced neuronal efficacy due to accumulating AD pathology and might predict future clinical decline in patients with MCI.

Cortical and subcortical correlates of electroencephalographic alpha rhythm modulation

Neural correlates of electroencephalographic (EEG) alpha rhythm are poorly understood. Here, we related EEG alpha rhythm in awake humans to blood-oxygen-level-dependent (BOLD) signal change determined by functional magnetic resonance imaging (fMRI). Topographical EEG was recorded simultaneously with fMRI during an open versus closed eyes and an auditory stimulation versus silence condition. EEG was separated into spatial components of maximal temporal independence using independent component analysis. Alpha component amplitudes and stimulus conditions served as general linear model regressors of the fMRI signal time course. In both paradigms, EEG alpha component amplitudes were associated with BOLD signal decreases in occipital areas, but not in thalamus, when a standard BOLD response curve (maximum effect at approximately 6 s) was assumed. The part of the alpha regressor independent of the protocol condition, however, revealed significant positive thalamic and mesencephalic correlations with a mean time delay of approximately 2.5 s between EEG and BOLD signals. The inverse relationship between EEG alpha amplitude and BOLD signals in primary and secondary visual areas suggests that widespread thalamocortical synchronization is associated with decreased brain metabolism. While the temporal relationship of this association is consistent with metabolic changes occurring simultaneously with changes in the alpha rhythm, sites in the medial thalamus and in the anterior midbrain were found to correlate with short time lag. Assuming a canonical hemodynamic response function, this finding is indicative of activity preceding the actual EEG change by some seconds.