Graph analysis of dream reports is especially informative about psychosis

Early psychiatry investigated dreams to understand psychopathologies. Contemporary psychiatry, which neglects dreams, has been criticized for lack of objectivity. In search of quantitative insight into the structure of psychotic speech, we investigated speech graph attributes (SGA) in patients with schizophrenia, bipolar disorder type I, and non-psychotic controls as they reported waking and dream contents. Schizophrenic subjects spoke with reduced connectivity, in tight correlation with negative and cognitive symptoms measured by standard psychometric scales. Bipolar and control subjects were undistinguishable by waking reports, but in dream reports bipolar subjects showed significantly less connectivity. Dream-related SGA outperformed psychometric scores or waking-related data for group sorting. Altogether, the results indicate that online and offline processing, the two most fundamental modes of brain operation, produce nearly opposite effects on recollections: While dreaming exposes differences in the mnemonic records across individuals, waking dampens distinctions. The results also demonstrate the feasibility of the differential diagnosis of psychosis based on the analysis of dream graphs, pointing to a fast, low-cost and language-invariant tool for psychiatric diagnosis and the objective search for biomarkers. The Freudian notion that ‘‘dreams are the royal road to the unconscious’’ is clinically useful, after all.

Graph analysis of verbal fluency test discriminate between patients with Alzheimer’s disease, Mild Cognitive Impairment and normal elderly controls

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

Síntese e caracterização de aluminofosfato impregnado com molibdênio/zinco visando a dessulfurização por adsorção

Discussions about pollution caused by vehicles emission are old and have been developed along the years. The search for cleaner technologies and frequent weather alterations have been inducing industries and government organizations to impose limits much more rigorous to the contaminant content in fuels, which have an direct impact in atmospheric emissions. Nowadays, the quality of fuels, in relation to the sulfur content, is carried out through the process of hydrodesulfurization. Adsorption processes also represent an interesting alternative route to the removal of sulfur content. Both processes are simpler and operate to atmospheric temperatures and pressures. This work studies the synthesis and characterization of aluminophosphate impregnate with zinc, molybdenum or both, and its application in the sulfur removal from the gasoline through the adsorption process, using a pattern gasoline containing isooctane and thiophene. The adsorbents were characterized by x-ray diffraction, differential thermal analysis (DTG), x-ray fluorescence and scanning electron microscopy (SEM). The specific area, volume and pore diameter were determined by BET (Brunauer- Emmet-Teller) and the t-plot method. The sulfur was quantified by elementary analysis using ANTEK 9000 NS. The adsorption process was evaluated as function of the temperature variation and initial sulfur content through the adsorption isotherm and its thermodynamic parameters. The parameters of entropy (ΔS), enthalpy variation (ΔH) and free Gibbs energy (ΔG) were calculated through the graph ln(Kd) versus 1/T. Langmuir, Freundlich and Langmuir-Freundlich models were adjusted to the experimental data, and the last one had presented better results. The thermodynamic tests were accomplished in different temperatures, such as 30, 40 and 50ºC, where it was concluded the adsorption process is spontaneous and exothermic. The kinetic of adsorption was studied by 24 h and it showed that the capability adsorption to the adsorbents studied respect the following order: MoZnPO > MoPO > ZnPO > AlPO. The maximum adsorption capacity was 4.91 mg/g for MoZnPO with an adsorption efficiency of 49%.

Graph analysis of verbal fluency test discriminate between patients with Alzheimer’s disease, Mild Cognitive Impairment and normal elderly controls

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment – subtypes amnestic(aMCI) and amnestic multiple domain (a+mdMCI) - and patients with Alzheimer’s disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGAs). The individuals were compared when divided in three (NC – MCI – AD) and four (NC – aMCI – a+mdMCI – AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.