Sex differences in olfactory identification and Wisconsin Card Sorting performance in schizophrenia: relationship to attention and verbal ability

We investigated the hypothesis that different prefrontal brain systems (i.e., dorsal vs. ventral) and sex contribute differentially to cognitive deficit in schizophrenia. Performance was assessed among clinically stable, chronic schizophrenic outpatients and matched normal control subjects on olfactory identification [on the University of Pennsylvania Smell Identification Test (UPSIT)] and on executive functions [using the Wisconsin Card Sorting Test (WCST)]. Patients were impaired on both tests compared to controls, and male schizophrenics were impaired on the WCST compared to female schizophrenics. The pattern of results suggests that gender differences on the UPSIT are mildly accentuated in schizophrenia. The data support our previous study indicating that UPSIT performance is largely independent of the executive or attentional deficits typically associated with schizophrenia, with the exception of verbal ability. Further research with larger samples is required to test the hypothesis that there is a severely impaired subgroup of male patients with diffuse prefrontal dysfunctions.     

Overview of the Mars Pathfinder mission and assessment of landing site predictions

Chemical analyses returned by Mars Pathfinder indicate that some rocks may be high in silica, implying differentiated parent materials. Rounded pebbles and cobbles and a possible conglomerate suggest fluvial processes that imply liquid water in equilibrium with the atmosphere and thus a warmer and wetter past. The moment of inertia indicates a central metallic core of 1300 to 2000 kilometers in radius. Composite airborne dust particles appear magnetized by freeze-dried maghemite stain or cement that may have been leached from crustal materials by an active hydrologic cycle. Remote-sensing data at a scale of generally greater than approximately 1 kilometer and an Earth analog correctly predicted a rocky plain safe for landing and roving with a variety of rocks deposited by catastrophic floods that are relatively dust-free.     

Identifying latent dynamic components in biological systems

In computational systems biology, the general aim is to derive regulatory models from multivariate readouts, thereby generating predictions for novel experiments. In the past, many such models have been formulated for different biological applications. The authors consider the scenario where a given model fails to predict a set of observations with acceptable accuracy and ask the question whether this is because of the model lacking important external regulations. Real‐world examples for such entities range from microRNAs to metabolic fluxes. To improve the prediction, they propose an algorithm to systematically extend the network by an additional latent dynamic variable which has an exogenous effect on the considered network. This variable''s time course and influence on the other species is estimated in a two‐step procedure involving spline approximation, maximum‐likelihood estimation and model selection. Simulation studies show that such a hidden influence can successfully be inferred. The method is also applied to a signalling pathway model where they analyse real data and obtain promising results. Furthermore, the technique can be employed to detect incomplete network structures.Inspec keywords: biology computing, RNA, splines (mathematics), maximum likelihood estimation, approximation theory, biochemistryOther keywords: latent dynamic components, biological systems, computational system biology, regulatory models, multivariate readouts, biological applications, external regulations, real‐world examples, microRNA, metabolic fluxes, latent dynamic variables, variable time course, two‐step procedure, spline approximation, maximum‐likelihood estimation, model selection, signalling pathway model, real data, incomplete network structures