Sheep Model for Osteoporosis: Sustainability and Biomechanical Relevance of Low Turnover Osteoporosis Induced by Hypothalamic-Pituitary Disconnection.

Sheep Model for Osteoporosis: Sustainability and Biomechanical Relevance of Low Turnover Osteoporosis Induced by Hypothalamic-Pituitary Disconnection.

J Orthop Res. 2013 Feb 25;
Oheim R, Beil FT, Köhne T, Wehner T, Barvencik F, Ignatius A, Amling M, Clarke IJ, Pogoda P

Hypothalamo-pituitary disconnection (HPD) leads to low bone turnover and osteoporosis in sheep. To determine the sustainability of bone loss and its biomechanical relevance, we studied HPD-sheep 24 months after surgery (HPD?+?OVX-24) in comparison to untreated control (Control), ovariectomized sheep (OVX), and sheep 12 months after HPD (HPD?+?OVX-12). We performed histomorphometric, HR-pQCT, and qBEI analyses, as well as biomechanical testing of all ewes studied. Twenty-four months after HPD, histomorphometric analyses of the iliac crest showed a significant reduction of BV/TV by 60% in comparison to Control. Cortical thickness of the femora measured by HR-pQCT did not change between 12 and 24 months after HPD but remained decreased by 30%. These structural changes were caused by a persisting depression of osteoblast and osteoclast cellular activity. Biomechanical testing of the femora showed a significant reduction of bending strength, whereas calcium content and distribution was found to be unchanged. In conclusion, HPD surgery leads to a persisting low turnover status with negative turnover balance in sheep followed by dramatic cortical and trabecular bone loss with consequent biomechanical impairment. © 2013 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res. HubMed – depression


Interpreting meta-regression: application to recent controversies in antidepressants’ efficacy.

Stat Med. 2013 Feb 25;
Petkova E, Tarpey T, Huang L, Deng L

A recent meta-regression of antidepressant efficacy on baseline depression severity has caused considerable controversy in the popular media. A central source of the controversy is a lack of clarity about the relation of meta-regression parameters to corresponding parameters in models for subject-level data. This paper focuses on a linear regression with continuous outcome and predictor, a case that is often considered less problematic. We frame meta-regression in a general mixture setting that encompasses both finite and infinite mixture models. In many applications of meta-analysis, the goal is to evaluate the efficacy of a treatment from several studies, and authors use meta-regression on grouped data to explain variations in the treatment efficacy by study features. When the study feature is a characteristic that has been averaged over subjects, it is difficult not to interpret the meta-regression results on a subject level, a practice that is still widespread in medical research. Although much of the attention in the literature is on methods of estimating meta-regression model parameters, our results illustrate that estimation methods cannot protect against erroneous interpretations of meta-regression on grouped data. We derive relations between meta-regression parameters and within-study model parameters and show that the conditions under which slopes from these models are equal cannot be verified on the basis of group-level information only. The effects of these model violations cannot be known without subject-level data. We conclude that interpretations of meta-regression results are highly problematic when the predictor is a subject-level characteristic that has been averaged over study subjects. Copyright © 2013 John Wiley & Sons, Ltd. HubMed – depression


Sudarshan kriya yoga: Breathing for health.

Int J Yoga. 2013 Jan; 6(1): 4-10
Zope SA, Zope RA

Breathing techniques are regularly recommended for relaxation, stress management, control of psychophysiological states, and to improve organ function. Yogic breathing, defined as a manipulation of breath movement, has been shown to positively affect immune function, autonomic nervous system imbalances, and psychological or stress-related disorders. The aim of this study was to assess and provide a comprehensive review of the physiological mechanisms, the mind-body connection, and the benefits of Sudarshan Kriya Yoga (SKY) in a wide range of clinical conditions. Various online databases searched were Medline, Psychinfo, EMBASE, and Google Scholar. All the results were carefully screened and articles on SKY were selected. The references from these articles were checked to find any other potentially relevant articles. SKY, a unique yogic breathing practice, involves several types of cyclical breathing patterns, ranging from slow and calming to rapid and stimulating. There is mounting evidence to suggest that SKY can be a beneficial, low-risk, low-cost adjunct to the treatment of stress, anxiety, post-traumatic stress disorder, depression, stress-related medical illnesses, substance abuse, and rehabilitation of criminal offenders. HubMed – depression


Stability analysis of associative memory network composed of stochastic neurons and dynamic synapses.

Front Comput Neurosci. 2013; 7: 6
Katori Y, Otsubo Y, Okada M, Aihara K

We investigate the dynamical properties of an associative memory network consisting of stochastic neurons and dynamic synapses that show short-term depression and facilitation. In the stochastic neuron model used in this study, the efficacy of the synaptic transmission changes according to the short-term depression or facilitation mechanism. We derive a macroscopic mean field model that captures the overall dynamical properties of the stochastic model. We analyze the stability and bifurcation structure of the mean field model, and show the dependence of the memory retrieval performance on the noise intensity and parameters that determine the properties of the dynamic synapses, i.e., time constants for depressing and facilitating processes. The associative memory network exhibits a variety of dynamical states, including the memory and pseudo-memory states, as well as oscillatory states among memory patterns. This study provides comprehensive insight into the dynamical properties of the associative memory network with dynamic synapses. HubMed – depression



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