Disorders of diminished motivation occur frequently in individuals with traumatic brain injury. Motivation is an ever-present, essential determinant of behavior and adaptation. The major syndromes of diminished motivation are apathy, abulia, and akinetic mutism. Depending on their etiology, disorders of diminished motivation may be a primary clinical disturbance, a symptom of another disorder, or a coexisting second disorder. This article presents a biopsychosocial approach to the assessment and management of motivational impairments in patients with traumatic brain injury. The recognition and differential diagnosis of disorders of diminished motivation, as well as the mechanism and clinical pathogenesis, are discussed.

Background Late-onset Alzheimer disease (LOAD) is a clinically heterogeneous complex disease defined by progressively disabling cognitive impairment. Psychotic symptoms which affect approximately one-half of LOAD subjects have been associated with more rapid cognitive decline. However, the variety of cognitive trajectories in LOAD, and their correlates have not been well defined. We therefore used latent class modeling to characterize trajectories of cognitive and behavioral decline in a cohort of AD subjects. Methods 201 Caucasian subjects with possible or probable AD were evaluated for cognitive and psychotic symptoms at regular intervals for up to 13.5 years. Cognitive symptoms were evaluated serially with the Mini-Mental State Examination (MMSE), and psychotic symptoms were rated using the CERAD behavioral rating scale (CBRS). Analyses undertaken were latent class mixture models of quadratic trajectories including a random intercept, with initial MMSE score, age, gender, education, and APOE ε4 count modeled as concomitant variables. In a secondary analysis, psychosis status was also included. Results AD subjects showed six trajectories with significantly different courses and rates of cognitive decline. The concomitant variables included in the best latent class trajectory model were initial MMSE and age. Greater burden of psychotic symptoms increased the probability of following a trajectory of more rapid cognitive decline in all age and initial MMSE groups. APOE ε4 was not associated with any trajectory. Conclusion Trajectory modeling of longitudinal cognitive and behavioral data may provide enhanced resolution of phenotypic variation in Alzheimer disease.

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Background-Psychotic symptoms in Alzheimer Disease (AD+P) identify a heritable phenotype associated with greater cognitive impairment. Knowing when the cognitive course of AD+P subjects diverges from that of subjects without psychosis would enhance understanding of how genetic variation results in AD+P and its associated cognitive burden. We specifically sought to determine if degree of cognitive impairment and cognitive decline in early AD predict subsequent AD+P onset.

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The crystallization of a new macromolecule is still very much a trial-and-error process. As is well known, it requires the search of a large parameter space of experimental settings to find the relatively few idiosyncratic conditions that lead to diffraction-quality crystals. Crystallographers have developed a variety of screens to help identify initial crystallization conditions, including those based on systematic grids, incomplete factorial and sparse-matrix approaches. These are somewhat subjectively formulated based on accumulated data from past crystallization experiments. Ideally, one would prefer as objective a procedure as possible; however, that requires objective methods that incorporate a broad source of crystallization data. The Biological Macromolecular Crystallization Database (BMCD), a repository of all published crystallization conditions, is an obvious source of this data. This database has been augmented with a hierarchical classification of the macromolecules contained in the BMCD as well as extensive data on the additives used with them. A statistical analysis of the augmented BMCD shows the existence of significant correlations between families of macromolecules and the experimental conditions under which they crystallize. This in turn leads to a Bayesian technique for determining the probability of success of a set of experimental conditions based on the data in the BMCD as well as facts about a macromolecule known prior to crystallization. This has been incorporated into software that enables users to rank experimental conditions for new macromolecules generated by a dense partial factorial design. Finally, an additional advantage of the software described here is that it also facilitates the accumulation of the data required for improving the accuracy of estimation of the probabilities of success - knowledge of the conditions which lead to failure of crystallization.

Background-Psychotic symptoms in Alzheimer Disease (AD+P) identify a heritable phenotype associated with a more severe course. We recently found an association of AD+P with depression symptom severity. Reports have shown an association of a serotonin-2A receptor (HTR2A) gene T102C polymorphism with AD+P and with depression during AD. We examined the interaction of this common genetic polymorphism with depression and increased psychosis risk.