Consultations with complementary and alternative medicine practitioners amongst wider care options for back pain: a study of a nationally representative sample of 1,310 Australian women aged 60–65 years

Back pain is a significant health service issue in Australia and internationally. Back pain sufferers can draw upon a range of health care providers including complementary and alternative medicine (CAM) practitioners. Women are higher users of health services than men and tend to use CAM frequently for musculoskeletal conditions. However, there remain important gaps in our understanding of women's consultation patterns with CAM practitioners for back pain. The objective of this study is to examine the prevalence of use and characteristics of women who use CAM practitioners for back pain. The method used was a survey of a nationally representative sample of women aged 60-65 years from the Australian Longitudinal Study on Women's Health. Women consulted a massage therapist (44.1 %, n = 578) and a chiropractor (37.3 %, n = 488) more than other CAM practitioners for their back pain. Consultations with a chiropractor for back pain were lower for women who consulted a General Practitioner (GP) (OR, 0.56; 95 % CI 0.41, 0.76) or a physiotherapist (OR, 0.53; 95 % CI 0.39, 0.72) than for those who did not consult a GP or a physiotherapist. CAM practitioner consultations for back pain were greater for women who visited a pharmacist (OR, 1.99; 95 % CI 1.23, 3.32) than for women who did not visit a pharmacist. There is substantial use of CAM practitioners alongside conventional practitioners amongst women for back pain, and there is a need to provide detailed examination of the communication between patients and their providers as well as across the diverse range of health professionals involved in back pain care

Low back pain status in elite and semi-elite Australian football codes: a cross-sectional survey of football (soccer), Australian rules, rugby league, rugby union and non-athletic controls

<p>Abstract</p> <p>Background</p> <p>Our understanding of the effects of football code participation on low back pain (LBP) is limited. It is unclear whether LBP is more prevalent in athletic populations or differs between levels of competition. Thus it was the aim of this study to document and compare the prevalence, intensity, quality and frequency of LBP between elite and semi-elite male Australian football code participants and a non-athletic group.</p> <p>Methods</p> <p>A cross-sectional survey of elite and semi-elite male Australian football code participants and a non-athletic group was performed. Participants completed a self-reported questionnaire incorporating the Quadruple Visual Analogue Scale (QVAS) and McGill Pain Questionnaire (short form) (MPQ-SF), along with additional questions adapted from an Australian epidemiological study. Respondents were 271 elite players (mean age 23.3, range 17–39), 360 semi-elite players (mean age 23.8, range 16–46) and 148 non-athletic controls (mean age 23.9, range 18–39).</p> <p>Results</p> <p>Groups were matched for age (p = 0.42) and experienced the same age of first onset LBP (p = 0.40). A significant linear increase in LBP from the non-athletic group, to the semi-elite and elite groups for the QVAS and the MPQ-SF was evident (p < 0.001). Elite subjects were more likely to experience more frequent (daily or weekly OR 1.77, 95% CI 1.29–2.42) and severe LBP (discomforting and greater OR 1.75, 95% CI 1.29–2.38).</p> <p>Conclusion</p> <p>Foolers in Australia have significantly more severe and frequent LBP than a non-athletic group and this escalates with level of competition.</p

Prelimbic and Infralimbic Prefrontal Cortex Interact during Fast Network Oscillations

Background: The medial prefrontal cortex has been implicated in a variety of cognitive and executive processes such as decision making and working memory. The medial prefrontal cortex of rodents consists of several areas including the prelimbic and infralimbic cortex that are thought to be involved in different aspects of cognitive performance. Despite the distinct roles in cognitive behavior that have been attributed to prelimbic and infralimbic cortex, little is known about neuronal network functioning of these areas, and whether these networks show any interaction during fast network oscillations. Methodology/Principal Findings: Here we show that fast network oscillations in rat infralimbic cortex slices occur at higher frequencies and with higher power than oscillations in prelimbic cortex. The difference in oscillation frequency disappeared when prelimbic and infralimbic cortex were disconnected. Conclusions/Significance: Our data indicate that neuronal networks of prelimbic and infralimbic cortex can sustain fast network oscillations independent of each other, but suggest that neuronal networks of prelimbic and infralimbic cortex ar

Genetic Signatures in the Envelope Glycoproteins of HIV-1 that Associate with Broadly Neutralizing Antibodies

A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, we explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. We analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1

Gene-Gene and Gene-Environmental Interactions of Childhood Asthma: A Multifactor Dimension Reduction Approach

Background: The importance of gene-gene and gene-environment interactions on asthma is well documented in literature, but a systematic analysis on the interaction between various genetic and environmental factors is still lacking. Methodology/Principal Findings: We conducted a population-based, case-control study comprised of seventh-grade children from 14 Taiwanese communities. A total of 235 asthmatic cases and 1,310 non-asthmatic controls were selected for DNA collection and genotyping. We examined the gene-gene and gene-environment interactions between 17 singlenucleotide polymorphisms in antioxidative, inflammatory and obesity-related genes, and childhood asthma. Environmental exposures and disease status were obtained from parental questionnaires. The model-free and non-parametrical multifactor dimensionality reduction (MDR) method was used for the analysis. A three-way gene-gene interaction was elucidated between the gene coding glutathione S-transferase P (GSTP1), the gene coding interleukin-4 receptor alpha chain (IL4Ra) and the gene coding insulin induced gene 2 (INSIG2) on the risk of lifetime asthma. The testing-balanced accuracy on asthma was 57.83 % with a cross-validation consistency of 10 out of 10. The interaction of preterm birth and indoor dampness had the highest training-balanced accuracy at 59.09%. Indoor dampness also interacted with many genes, including IL13, beta-2 adrenergic receptor (ADRB2), signal transducer and activator of transcription 6 (STAT6). We also used likelihood ratio tests for interaction and chi-square tests to validate our results and all tests showed statistical significance

Order in Spontaneous Behavior

Brains are usually described as input/output systems: they transform sensory input into motor output. However, the motor output of brains (behavior) is notoriously variable, even under identical sensory conditions. The question of whether this behavioral variability merely reflects residual deviations due to extrinsic random noise in such otherwise deterministic systems or an intrinsic, adaptive indeterminacy trait is central for the basic understanding of brain function. Instead of random noise, we find a fractal order (resembling Lévy flights) in the temporal structure of spontaneous flight maneuvers in tethered Drosophila fruit flies. Lévy-like probabilistic behavior patterns are evolutionarily conserved, suggesting a general neural mechanism underlying spontaneous behavior. Drosophila can produce these patterns endogenously, without any external cues. The fly's behavior is controlled by brain circuits which operate as a nonlinear system with unstable dynamics far from equilibrium. These findings suggest that both general models of brain function and autonomous agents ought to include biologically relevant nonlinear, endogenous behavior-initiating mechanisms if they strive to realistically simulate biological brains or out-compete other agents

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Black hole spin: theory and observation

In the standard paradigm, astrophysical black holes can be described solely by their mass and angular momentum - commonly referred to as `spin' - resulting from the process of their birth and subsequent growth via accretion. Whilst the mass has a standard Newtonian interpretation, the spin does not, with the effect of non-zero spin leaving an indelible imprint on the space-time closest to the black hole. As a consequence of relativistic frame-dragging, particle orbits are affected both in terms of stability and precession, which impacts on the emission characteristics of accreting black holes both stellar mass in black hole binaries (BHBs) and supermassive in active galactic nuclei (AGN). Over the last 30 years, techniques have been developed that take into account these changes to estimate the spin which can then be used to understand the birth and growth of black holes and potentially the powering of powerful jets. In this chapter we provide a broad overview of both the theoretical effects of spin, the means by which it can be estimated and the results of ongoing campaigns.Comment: 55 pages, 5 figures. Published in: "Astrophysics of Black Holes - From fundamental aspects to latest developments", Ed. Cosimo Bambi, Springer: Astrophysics and Space Science Library. Additional corrections mad