A recent study by Leonard, Lebecque, Dingemanse, and Leal [1] tested the effect of Miglustat, an alpha inhibitor on the cystic fibrosis conductance regulator gene using total chloride secretion in the nasal epithelium as the key variable estimated from basal nasal potential differences. The conclusion was drawn that “There was no evidence of a treatment effect on any nasal potential difference variable.” This conclusion may not be correct because of a slight misinterpretation of their statistical results. There also is a question of whether longer exposure periods than 8 days would have produced a more pronounced effect.

Excerpt: The study by Lee and Jung (2012) recently published in Workplace Health and Safety concluded that, “A collective effort is needed on the parts of employers, employees, occupational health nurses, and the government to protect working women from lifting heavy items while pregnant” (p. 25). However, that conclusion over-reaches their data and consequently is not supported. First, inconsistencies existed in the odds ratios (ORs), indicating uncertainties in the stability of the statistical findings. Second, the study used a nonexperimental design with low internal validity, preventing conclusions about causation due to the possibility of external intervening variables.

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Figueroa-Ramosa et al. (2013) concluded that the combination of sedation withdrawal and mechanical ventilation withdrawal trial was feasible and well tolerated. The conclusion is not well supported because of the absence of a comparison to the uncombined protocol and due to evidence that the patients did not tolerate them particularly well.

Artificial Neural Networks are models of interacting neurons that can be used as classifiers with large data sets. They can also be used for feature extraction and for reducing the dimensionality of large data sets. Den-Dritic electrotonic models can be used to suggest more robust artificial neural network models that are amenable to data mining and feature extraction.

Book Summary: Computational models of neural networks have proven insufficient to accurately model brain function, mainly as a result of simplifications that ignore the physical reality of neuronal structure in favor of mathematically tractable algorithms and rules. Even the more biologically based "integrate and fire" and "compartmental" styles of modeling suffer from oversimplification in the former case and excessive discretization in the second. This book introduces an integrative approach to modeling neurons and neuronal circuits that retains the integrity of the biological units at all hierarchical levels. With contributions from more than 40 renowned experts, Modeling in the Neurosciences, Second Edition is essential for those interested in constructing more structured and integrative models with greater biological insight. Focusing on new mathematical and computer models, techniques, and methods, this book represents a cohesive and comprehensive treatment of various aspects of the neurosciences from the molecular to the network level. Many state-of-the-art examples illustrate how mathematical and computer modeling can contribute to the understanding of mechanisms and systems in the neurosciences. Each chapter also includes suggestions of possible refinements for future modeling in this rapidly changing and expanding field. This book will benefit and inspire the advanced modeler, and will give the beginner sufficient confidence to model a wide selection of neuronal systems at the molecular, cellular, and network levels.

This study focused on the identification of entry-level competencies needed by bachelor of science in nursing (BSN) graduates who will begin working in acute health care agencies in Tennessee within 10 years. The purpose of this study was to increase awareness of the competencies needed by graduates of BSN programs in Tennessee to meet the demands of acute health care agencies, considering current and anticipated changes in the health care delivery system. The opinions of nurse educators, nurse administrators, recent BSN graduates, and experienced BSN graduates were solicited to assess congruency of perceptions. This study found there was a statistically significant difference in the perceptions of nurses in acute health care agencies and faculty in BSN programs about the importance of entry-level competencies needed by BSN graduates.

Background. Obesity has reached epidemic proportions over the past 20 years. Methods. This study investigated the differences in rates of obesity and perceptions of health status between rural, urban, and suburban Southern women based on selected socioeconomic factors. Using data from a national health survey, the reports from 4,391 women aged 40 to 64 years were included in the study. Results. Significantly more rural women lived in poverty, reported a poorer health status, and had a greater prevalence of obesity. Urban women had the next highest obesity rate and a moderate health status. The healthiest group with the lowest obesity and poverty rates were suburban women. Conclusion. Obesity and poor overall health are closely related in rural women. The greatest challenge to health care providers is to provide appropriate community-based weight-management programs.