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OBJECTIVE: We applied paired transcranial magnetic stimulation (pTMS) to patients with post-traumatic stress disorder (PTSD) secondary to minor accidental head trauma. Our purpose was to determine the potential abnormality of motor cortex excitability in this pathologic condition. METHODS: pTMS stimulation, according to the conditioning-test paradigm employing interstimulus intervals (ISIs) of 1-6 ms, was used to investigate intracortical inhibition in control subjects and patients with PTSD. The study population consisted of 14 patients who had developed PTSD following minor head trauma, 12 healthy volunteers without a clinical history of head trauma and 11 healthy subjects who had reported accidental minor head trauma 1-4 months before the study. This clinical electrophysiologic study was performed at the Department of Neuroscience, University of Rome 'Tor Vergata.' RESULTS: All patients with PTSD exhibited a significantly lower motor evoked potential (MEP) inhibition than controls at 2 ms, 3 ms and 4 ms ISI. The statistical analysis of the pTMS protocol showed a significant effect (F2,36 = 25.63, p < 0.001) of the factor 'group,' because patients with PTSD showed a mean conditioned MEP amplitude higher than that observed in both control groups for all 6 ISIs analyzed. The 'ISI' factor was also significant (F5,180 = 89.85, Greenhouse-Geisser epsilon = 0.35; p < 0.001), with the mean conditioned MEP amplitude increasing from 22.5% to 127.8% as the ISI increased from 1 ms to 6 ms. Finally, the interaction of group with ISI was also significant (F10,180 = 8.97, p < 0.001), showing that the condition of PTSD secondary to head trauma was able to affect the MEP amplitude at different ISIs. CONCLUSIONS: Our results demonstrate that PTSD can give rise to abnormalities in intracortical inhibition. Our results provide further evidence that alterations in cortical inhibitory circuits may underlie specific forms of neuroticism in humans. [ABSTRACT FROM AUTHOR]

The variation of viscosities with respect to the pressure for [C4mim][NTf2]. The solid lines are current modeling values, and the dashed lines are the RHS model of Hossieni et al., both were compared with the experimental values and then extended to the wider pressures up to 120 MPa. [Display omitted] • Extension of Fiction theory + PHC EoS and ANN models to 20 pure ILs. • Correlation and prediction of viscosity data of 20 pure ILs compiled from 125 data sources. • Correlation of viscosity data of 9 mixtures of ILs by the help of some binary parameter. • Superiority of our FT-based model against RHS theory-based models and group-contribution method. • Very low AAD of 1.44% from ANN for 3074 viscosity data points. Fast and accurate prediction and correlation of thermophysical properties are always important concerns for researchers and engineers. This work is the extension of our earlier friction theory (FT)-based approach for estimating the dynamic viscosities of pure ionic liquids using a perturbed hard-chain equation of state. The model used three molecular parameters along with 5 correlation coefficients in the friction terms. The correlation coefficients were obtained using 167 data points at 0.1 MPa with an average absolute deviation (AAD) of 0.61 % and then used to predict the viscosity values at higher pressures. Using the FT-based model, 2907 experimental viscosity data for 20 pure ILs were predicted. The calculations were carried out in 273–373 K range and pressures up to 298.9 MPa for 2907 data points with an AAD of 2.63 %. The present FT-based model was not able to accurately predict the viscosities of ILs outside the temperature range used for the fit procedure. Also, comparing the precision of our FT-based model with two rough-hard-sphere theory-based models of Hosseini et al. and Hossain-Teja as well as the group-contribution method led to AADs of 2.46 % (for 2664 data points), 2.65 % (for 1605 data points), 3.25 % (for 890 data points), and 7.73 % (for 2558 data points, respectively. Viscosities of several mixtures of IL + IL type were also correlated using the present model along with some simple combining equations and a binary interaction parameter as well. The AAD of the calculated viscosities from the experimental ones was found to be 5.10 % for 960 data points examined. In addition, a neural network was trained on 3074 data points to represent the viscosity of studied pure ILs. The artificial neural network (ANN) structure utilized two layers, four input parameters, and 13 neurons for each layer. This specific structure of ANN was carefully designed to ensure an optimal performance in predicting the viscosity of ILs. The overall AAD was obtained 1.44 %. [ABSTRACT FROM AUTHOR]

This work deals with the equation of state (EOS) and artificial neural network (ANN) modeling prediction of the volumetric properties of several pure and mixtures of amino acid ionic liquids (AAILs). Concerning EOS modeling, we extended a perturbed hard-sphere (PHS) EOS to predict the densities of pure and their mixtures of AAILs. The PHS EOS used the surface tension and liquid densities both at room temperature as the scaling constants. The accuracy of the PHS EOS has been checked by comparing the results with 344 experimental data points of 28 AAILs in 283–373.15 K temperature range. The overall average absolute deviation (AAD) of the calculated densities from the literature data was found to be 0.55%. The PHS EOS has also been employed to calculate the densities and excess volumetric properties of 8 mixtures including AAIL + solvent in 298.15–318.15 K temperature range. From 279 data points examined, the AAD of the predicted densities from the measurements was found to be 1.73%. Also, the ANN has been trained to predict the density of pure compounds and mixtures of interest. The optimized network contains one hidden layer for each layer and 29 and 37 neurons for pure and mixture respectively and a sigmoid transfer function. The results obtained reveal that the developed ANN technique is able to estimate accurately the density of AAILs providing an AAD of 0.26% and 0.025% for pure and mixtures, respectively. Unlabelled Image • Prediction of volumetric properties of pure and mixtures of AAILs • Prediction from PHS equation of state • Prediction from artificial neural network (ANN) modeling [ABSTRACT FROM AUTHOR]

L-dopa-carbidopa intestinal gel (LCIG) is a validated method of optimizing levodopa (LD) administration in advanced Parkinson's disease (PD). Of these 35 patients (Table 1) seven male patients (20%) and one female patients (2.8%) discontinued LCIG therapy and two died (1 M and 1F), with a global dropout rate (22.8%) similar to those reported in the literature [1],[2]. The analysis of the pharmacological treatment of these four patients that discontinued LCIG showed no relevant changes in therapy before and after implantation (Table 1). [Extracted from the article]

[Display omitted] • Extension of molecular thermodynamic and neural network models to surface tension correlation. • Application to 7 homopolymers. • Simultaneous calculation of bulk properties and surface tension. A combined molecular thermodynamic model with an equation of state was successfully extended for correlating the surface tension of 7 molten polymers. The model was coming from the combination of a statistical mechanical expression according to Fowler-Kirkwood-Buff approximation with the perturbed hard-sphere-chain equation of statistical association fluid theory by an attractive term of Yukawa tail. The systems under study were of homopolymers type including Poly(ethylene oxide), High-Density Poly(ethylene), Poly(dimethyl siloxane), Poly(vinyl methyl ether), Poly(ethylene glycol), Atactic-Poly(propylene glycol), and Isotactic-Poly(propylene glycol). The model also used the dipole moment of the monomer molecule of those systems as an adjustable coefficient. The model was able to correlate 65 surface tension data points of the above-mentioned polymers in 297–532.2 K range with the average absolute relative deviation (AARD) of 2.00%. In addition, a single layer neural network comprising two input parameters (temperature and soft-core diameter of Lennard-Jones fluid) and 11 neurons was applied to complete the research, achieving more than satisfactory results with the AARD of 0.88%. [ABSTRACT FROM AUTHOR]

Objectives: To investigate, in patients with Alzheimer’s Disease (AD), the possible interplay linking alteration of neuronal energy metabolism, as measured via cerebrospinal fluid (CSF) lactate concentration, to severity of AD neurodegenerative processes and impairment of cognitive abilities. Methods: In this study we measured and correlated CSF lactate concentrations, AD biomarker levels (τ- proteins and β-amyloid) and Mini-Mental State Examination (MMSE) score in a population of drug-naïve patients with AD ranging from mild (MMSE≥21/30) to moderate-severe (MMSE<21/30) cognitive decline. They were compared to healthy controls and patients with vascular dementia (VaD). Results: Patients with AD (n=145) showed a significant increase of CSF lactate concentration compared to controls (n=80) and patients with VaD (n=44), which was higher in mild (n=67) than in patients with moderate–severe AD (n=78). Moreover, we found, in either the whole AD population or both subgroups, a CSF profile in which higher CSF levels of t-τ and p-τ proteins corresponded to lower concentrations of lactate. Conclusions: We verified the occurrence of high CSF lactate levels in patients with AD, which may be ascribed to mitochondria impairment. Hypothesising that τ proteins may exert a detrimental effect on the entire cellular energy metabolism, the negative correlation found between lactate and τ-protein levels may allow speculation that τ toxicity, already demonstrated to have affected mitochondria, could also impair glycolytic metabolism with a less evident increase of lactate levels in more severe AD. Thus, we suggest a dynamic relationship between neuronal energy metabolism, τ proteins and cognitive decline in AD and propose the clinical potential of assessing CSF lactate levels in patients with AD to better define the neuronal brain metabolism damage. [ABSTRACT FROM AUTHOR]

Few studies focused on the effects of cabergoline on sleep-wake cycle in PD. Twelve patients affected by PD treated with levodopa as monotherapy underwent two 24-hour ambulatory polysomnographic (A-PSG) sessions twice: in baseline condition (levodopa as monotherapy) and after addition of cabergoline. In each condition, a subjective evaluation of sleep quality and daytime sleepiness was obtained by means of Parkinson’s disease Sleep Scale (PDSS) and the Epworth Sleepiness Scale. The statistical analysis of sleep parameters revealed a significant increase of sleep efficiency and slow wave sleep under cabergoline. The PDSS total score showed a significant improvement of overall sleep quality after cabergoline. No significant changes in daytime sleepiness were observed. No patient referred and/or showed sleep attacks before and after addition of cabergoline. We hypothesize that the long-lasting effect of cabergoline may improve the objective quality of nocturnal sleep in PD patients complaining nocturnal motor disability without inducing daytime sleepiness. [ABSTRACT FROM AUTHOR]

In the present study, we evaluated the effect of pergolide, a mixed D1/D2 agonist, on cognitive function in mild Parkinson’s disease (PD). After a two-week wash-out phase, twenty patients with a Hoehn and Yahr score =2.5 entered a 16-week, cross-over study in which the order of administration of pergolide or 1-dopa was randomly assigned. Cognitive assessment was performed after the wash-out phase and repeated after eight weeks (before patients were switched to the other drug) and at the end of the study. There were no significant differences in test scores among the three experimental modalities (off-treatment vs. l-dopa, off-treatment vs. pergolide, pergolide vs. l-dopa).In another cohort of comparably mild PD patients we had previously demonstrated that pramipexole, a mixed D2/D3 agonist, slightly but significantly worsened verbal fluency in comparison to l-dopa; moreover, pramipexole impaired short term verbal memory and attentional-executive functions in comparison to both l-dopa and the off-treatment condition. Taken together, these findings suggest that dopamine agonists may influence cognition in PD according to their pharmacological characteristics. Unlike the D2/D3 agonist pramipexole, pergolide and l-dopa, both of which stimulate D1- and D2-receptor subtypes, do not appear to impair cognitive function. [ABSTRACT FROM AUTHOR]

Summary. Twenty right-handed patients affected by early/mild Parkinson's disease were evaluated in a randomised study using neuropsychological and clinical assessements during three treatment modalities: when in the off treatment condition, when on pramipexole, and when on l-dopa. In comparison to the off treatment condition, the DA-agonist pramipexole produced a significant impairment of short term verbal memory, attentional-executive functions and verbal fluency, while l-dopa did not. Moreover, pramipexole opposite to l-dopa, failed to improve FAS and Stroop tests. Present findings indicate that pramipexole may worsen cognitive functions although not exceeding normative values. [ABSTRACT FROM AUTHOR]

In this study, the application of a semi-empirical model for the prediction of dynamic viscosities of liquid refrigerants has been explored for both saturated and compressed states. The model used rough hard-sphere (RHS) theory in the model development; a smooth hard-sphere expression and a coupling parameter of translational–rotational motions were employed. Also, the model used the three inputs, the critical temperature, critical density, as well as the liquid densities, for which the values were taken from Carnahan-Starling-vdW-β equation of state (EoS). Most of the refrigerants investigated herein are those based on methane, ethane, and propane. The ability of the RHS-based model been checked by the calculation of dynamic viscosities of 26 liquid refrigerants at compressed states in the 200 K to 420 K range and pressures up to 50 MPa. The average absolute deviation of 4.47 % (for 1539 data points) and 5.22 % (for 121 data points), respectively, were obtained for the cases of compressed and saturated liquid refrigerants studied. The degree of accuracy of the present semi-empirical model has also been compared with the literature RHS-based models as well as other approach based on the viscosity EoS. [ABSTRACT FROM AUTHOR]