Reed Falk (beadtip1)

5 months and 87.3 months, respectively ( < 0.001). However, the presence of PNI was not an independent prognostic factor for gastric cancer, except for patients in stage III ( = 0.037, hazard ratio 1.21, 95% confidence interval 1.01-1.44). PNI occurs frequently in patients with gastric cancer, and the incidence of PNI increases with the staging of the tumor. The presence of PNI can provide additional information in predicting the survival outcome for those with stage III tumors. PNI occurs frequently in patients with gastric cancer, and the incidence of PNI increases with the staging of the tumor. The presence of PNI can provide additional information in predicting the survival outcome for those with stage III tumors. To understand the extent to which apathy, cognition, and social support predict participation in activities with cognitive demands. Prospective, quantitative correlational, cross-sectional study. . Outpatient treatment centers and community stroke support groups located in St. Louis, MO, and Boston, MA. . 81 community-dwelling individuals ≥ 6-month poststroke with and without aphasia. Smad3 phosphorylation . Participants completed the Activity Card Sort (ACS), Apathy Evaluation Scale (AES), Medical Outcomes Study Social Support Survey (MOS-SSS), and Delis-Kaplan Executive Function System (DKEFS) Design Fluency and Trail-Making subtests. Cognitive deficits limit participation in activities with high cognitive demands. Apathy and positive social interaction influence participation, regardless of high or low cognitive demands. Poststroke aphasia did not impact return to participation in activities with high and low cognitive demands. . Cognitive deficits seen poststroke contribute to participation only for activities wiwell recognized. The availability of companionship from others to enjoy time with can facilitate participation.Experimental observations of simultaneous activity in large cortical areas have seemed to justify a large network approach in early studies of neural information codes and memory capacity. This approach has overlooked, however, the segregated nature of cortical structure and functionality. Employing graph-theoretic results, we show that, given the estimated number of neurons in the human brain, there are only a few primal sizes that can be attributed to neural circuits under probabilistically sparse connectivity. The significance of this finding is that neural circuits of relatively small primal sizes in cyclic interaction, implied by inhibitory interneuron potentiation and excitatory inter-circuit potentiation, generate relatively long non-repetitious sequences of asynchronous primal-length periods. The meta-periodic nature of such circuit interaction translates into meta-periodic firing-rate dynamics, representing cortical information. It is finally shown that interacting neural circuits of primal sizes 7 or less exhaust most of the capacity of the human brain, with relatively little room to spare for circuits of larger primal sizes. This also appears to ratify experimental findings on the human working memory capacity.Relationships among near set theory, shape maps and recent accounts of the Quantum Hall effect pave the way to neural networks computations performed in higher dimensions. We illustrate the operational procedure to build a real or artificial neural network able to detect, assess and quantify a fourth spatial dimension. We show how, starting from two-dimensional shapes embedded in a 2D topological charge pump, it is feasible to achieve the corresponding four-dimensional shapes, which encompass a larger amount of information. Synthesis of surface shape components, viewed topologically as shape descriptions in the form of feature vectors that vary over time, leads to a 4D view of cerebral activity. This novel, relatively straightforward architecture permits to increase the amount of ava