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the findings from these varying sources with reference to Rheumatoid arthritis (RA). Additionally it aims to identify implications of the results for research and clinical practice of Ayurveda. Methods: Four systematic reviews including one Cochrane review on efficacy of Ayurvedic interventions in management of Rheumatoid arthritis was (RA) reviewed to compare the findings. Rigorous clinical trials evaluating Ayurvedic interventions in RA published in high impact journals that were not included in the systematic reviews were analyzed independently. Outcomes of Ayurvedic treatments in real life clinical practice (20 doctors) were also carefully documented for comparison. Results: There is a discrepancy between the conclusions of systematic reviews, independent clinical trials and reports from actual point of care. Systematic reviews unanimously agree that there is no evidence indicating efficacy of Ayurvedic treatments in RA. On the other hand, the independent high quality clinical trials, one of which won an award for excellence in methodology contradict one another with respect to the reported clinical outcomes. The findings from real life clinical practice indicate not only strikingly different outcomes, but also treatment methods that have not been adequately studied before. Conclusion: There is a gap between research and clinical practice in Ayurveda, which is clearly demonstrated by this study on Rheumatoid arthritis. An over reliance on reductionistic methods of research leads to piece meal evaluation of Ayurveda ignoring its complex whole system approach in actual clinical practice. Variations in traditional diagnosis, the choice of treatments and the methodology of research are responsible for the contradictions in the research findings. Best clinical practices at the point of actual care should be identified and studied using appropriate research methodologies. Contact: Ram Manohar,Purpose: To characterize complementary and alternative medicine (CAM) studies for posttraumatic stress disorder (PTSD), evaluate the quality of these studies, and systematically grade the scientific evidence for individual CAM modalities for PTSD. Methods: Systematic Review. Data sources included MED-LINE, PsycINFO, CINAHL, Alt HealthWatch, Allied and Complementary Medicine Database, Cochrane Library, Database of Abstracts of Reviews of Effects, Health Technology Assessment Database. Methodological quality was assessed using the Reisch Quality Assessment Tool and Cochrane Risk of Bias. Selection criteria included any study design assessing PTSD outcomes and any CAM intervention. The body of evidence for each modality was assessed with the Natural Standard evidence-based, validated grading rationale.TM Results: Thirty-two studies with 1289 participants were reviewed, 16 of which were randomized controlled trials. The mean Reisch quality score for all included studies was 78 -10 (median 80, range 54-95) out of 100. Most studies used mindbody therapies, including biofeedback (4 studies), hypnosis (3), meditation (9), relaxation (...

covariance (ANCOVA) on a per-protocol sample, there were no differences between MBCR and SET groups on T/S ratios, but a trend effect was observed between the combined intervention group and controls (p = .054) whereby TL in the intervention group was maintained, whereas TL decreased for control participants. Similarly cortisol slopes in both intervention groups were maintained over time but became flatter in control participants (p < .05). Stress scores also improved significantly over time in the MBCR group. Conclusion: Psychosocial interventions providing stress reduction and emotional support resulted in TL and cortisol slope maintenance in distressed breast cancer survivors, compared to decreases in usual care. MBCR participants improved the most on psychosocial outcomes. Implications of this finding require further exploration.Purpose: Mindfulness meditation (MM) has increasing evidence of benefit for a variety of health conditions. EEG changes have been noted short-term during a meditation session as well as long-term from continued practice. Most studies examine EEG changes alone and do not include other physiological measures. The purpose of this study was to analyze EEG and respiration changes during meditation using advanced signal processing techniques and machine learning. Methods: EEG and respiration data were collected and analyzed from novice meditators after a 6-week one-on-one MM intervention previously reported on (Wahbeh et al., 2012). The meditation was a guided mindfulness of breath meditation delivered with an audio recording; no specific instructions to slow breathing were given. Research participants were relatively healthy adults aged 50-75 years with Perceived Stress Scale > 8. Collected data were analyzed with spectral analysis using a Stockwell transform, synchrony using phase locked value, and support vector machine (SVM) classifier to evaluate an objective marker for meditation. Results: Data are reported from 34 participants (mean age 61 years). There was a higher power and greater synchrony in alpha, theta and beta bands during meditation. There was slower respiration frequency during meditation. Using EEG or respiration signals individually in the SVM, the best classifier averaged across participants was 78% and 76% respectively but using an SVM classifier that included both signals, the best classifier across participants was 85% (ANOVA using the three within subject accuracies, p < .001).) Conclusion: Similar to other studies, we observed increased power in theta and alpha power during meditation and additionally found increased beta power which has been less consistently observed. While individually the EEG and respiration signals helped a classifier differentiate recordings during meditation from control recordings, a classifier using EEG and respiration signals together had a higher discrimination accuracy than one using the EEG or respiration signal alone.Purpose: Diminished control of standing posture, as indicated by traditional measures of postural sway, including increa...