Whole Health Options and Pain Education (wHOPE): A pragmatic trial comparing Whole Health Team vs Primary Care Group Education to promote nonpharmacological strategies to improve pain, functioning, and quality of life in veterans-Rationale, methods, and implementation

BACKGROUND: The Whole Health model of the U.S. Department of Veterans Affairs (VA) emphasizes holistic self-care and multimodal approaches to improve pain, functioning, and quality of life. wHOPE (Whole Health Options and Pain Education) seeks to be the first multisite pragmatic trial to establish evidence for the VA Whole Health model for chronic pain care. DESIGN: wHOPE is a pragmatic randomized controlled trial comparing a Whole Health Team (WHT) approach to Primary Care Group Education (PC-GE); both will be compared to Usual VA Primary Care (UPC). The WHT consists of a medical provider, a complementary and integrative health (CIH) provider, and a Whole Health coach, who collaborate with VA patients to create a Personalized Health Plan emphasizing CIH approaches to chronic pain management. The active comparator, PC-GE, is adapted group cognitive behavioral therapy for chronic pain. The first aim is to test whether the WHT approach is superior to PC-GE and whether both are superior to UPC in decreasing pain interference in functioning in 750 veterans with moderate to severe chronic pain (primary outcome). Secondary outcomes include changes in pain severity, quality of life, mental health symptoms, and use of nonpharmacological and pharmacological therapies for pain. Outcomes will be collected from the VA electronic health record and patient-reported data over 12 months of follow-up. Aim 2 consists of an implementation-focused process evaluation and budget impact analysis. SUMMARY: This trial is part of the Pain Management Collaboratory, which seeks to create national-level infrastructure to support evidence-based nonpharmacological pain management approaches for veterans and military service personnel

Gut Microbiota Dysbiosis and Their Impact on Biochemical and Inflammatory Profiles in Cafeteria Diet Fed Sprague Dawley Rats

Gut microbiota plays a major role in regulating the host metabolism and immune system. However, the structure of microbiome population is altered constantly by diverse factors including diet and environment. In particular, the gut microbiome dynamics is influenced by diet composition and their associated metabolites. Many studies in the recent past reported on diet induced dysbiosis in the gut microbiome, the modulating ratio between Firmicutes and Bacteroidetes plays a central role in maintaining the microbiome diversity in the gut and their abundance regulates obese conditions. Although there are several reports on gut microbial dysbiosis (Firmicutes/Bacteroidetes) at phylum level but only few of them highlight at the genera level. In the present study, we focused more on the impact of cafeteria diet (CAF) with respect to the gut microbiome richness at the genera level in SD rats. Three weeks old Sprague Dawley (SD) rats were fed with normal chow diet and cafeteria diet (CAF). After 10 weeks, serum, tissue samples (small intestine and cecum), cecum fecal and fecal pellet were collected. Biochemical analysis from serum, Gene expression analysis of pro-inflammatory markers from tissues and microbiome analysis from fecal samples were analysed. CAF diet fed rat in the present study developed obesity with increased body weight, few of them developed the resistance to weight gain (WGR) and these animal shows significantly increased abundance of Bacteriodetes-Prevotella compared to obese animals. This study suggests that detailed research needed to address the contribution of microbiota abundance at the genera level. We further explored the influence of diet induced microbiota changes on immune response; increase in Bacteroidetes leads to increased LPS and this in turn elicit immune reaction in the gut. Moreover, variation in gut microbiota also affects the gut barrier function (Tight junction proteins) and increase metabolic endotoxemia that leads to activation of innate immune system and low-grade inflammation. Further studies on these lines targeting the microbiota changes in the gut at the genera level is warranted to gain more knowledge

LABORATORY ANIMAL RESEARCH CENTRE (LARC) “A SPECIFIC PATHOGEN FREE RODENT FACILITY” - COVID – 19 PANDEMIC RESPONSE PLAN

Laboratory Animal Research Centre (LARC) has developed an early emergency operational plan for COVID-19 pandemic situation. Biosafety and biosecurity measures were planned and implemented ahead of time to check the functional requirement to prevent the infection. Identified necessary support for IT, Transport, Procurement, Finance, Admin and Research to make the operations remotely and successfull

Early-Life Sugar Consumption Affects the Microbiome in Juvenile Mice

Scope: The composition of the gut microbiota is influenced by the dietary nutrient. Sugar has been linked with many metabolic health disorders such as heart disease, metabolic syndrome, and immune disorders. Long-term consumption of sugar influences the landscape of gut microbiota by altering the gut microbial population called dysbiosis. This study aims to evaluate the impact of long-term consumption of high sugar diet (HSD) on the diversity of gut microbiota. Methods and results: CD1 mice are given high concentration of sugar for 15 weeks followed by a recovery period of 10 weeks. Real-time polymerase chain reaction and 16S rRNA next-generation sequencing methods employ to identify microbiome diversity. The results show that Firmicutes and Bacteroidetes are the predominant phyla in control, cecum, and fecal samples. Firmicutes population are gradually increased in treated samples even after the recovery period, whereas Bacteroidetes abundance slightly reduces throughout the study. Conclusion: The present study shows that the impact of long period of high sugar diet consumption alters the diversity of normal gut flora which can be restored after 10 weeks of sugar withdrawal. This indicates that the intervention of healthy and nutritious diet influences gut microbes and this can be beneficial in reducing the implication of early life metabolic disorders such as obesity.The authors would like to acknowledge LARC for their support and LARC vivarium team, for their support in animal care and husbandry. The research is funded by Qatar University

Gut Microbiota Dysbiosis in Cafeteria Diet Fed Sprague Dawley Rats

Diet plays a major role in the body physiology and metabolism. The quantity, nature and stability of the macronutrients present in the diet have a major impact on the composition of gut microbiota. Gut microbiota plays a major role in the body metabolism and leads to obese or lean phenotype. Bacteriodetes, Firmicutes, Proteobacteria and Actinobacteria are the major microbes that inhabit in the region of the gut. We made an attempt to study the effects of Cafeteria (CAF) diets and normal chow diets on diet consumption, weight gain, metabolism and composition of gut microbiota in fecal and cecum samples from three weeks old Sprague Dawley (SD) rats (n = 18/group) using 16S rDNA high throughput sequencing. Results revealed that distinctive diet based phenotypical changes were observed in some of the Cafeteria diet fed rats. Interestingly, some weight gain resistant (WGR) animals in Cafeteria diet fed groups show similar trend like that of control normal chow fed rats. Fecal microbiome analysis indicates that the ratio of Bacteriodetes is higher than the Firmicutes in cecum samples of Cafeteria diet fed rats whereas no significant difference is found in fecal samples of Cafeteria diet fed rats and as well as in control rats. Further analysis of other taxa at the level of family and genus of microbial abundance are also discussed. Our study suggests that contribution of gut microbiota towards obesity is not at the phylum level, and microbiome composition even at the level of species or strain may exert impact on the metabolism of the Cafeteria diet

Cadmium: An Emerging Role in Adipose Tissue Dysfunction

Cadmium (Cd) is a toxic heavy metal that is widespread in the environment due to the substantial anthropogenic inputs from the agriculture and industrial sectors. The toxic impact of Cd adversely affects human health and is linked with endocrine disruption, carcinogenicity, diabetes-related diseases, and metabolic disorder. One of the main characterizations of Cd is bioaccumulation where its half-life reaches 40 years with an unknown biological role. Several organs were found to be targets for Cd accumulation such as the liver, kidneys, and adipose tissue. Adipose tissue (AT) is a dynamic organ that plays a significant role in the body’s homeostasis through the maintenance of energy storage. Another vital function for AT is the secretion of adipokines which provides a metabolic cross-talk with the whole body’s organs. Cd is found to adversely impact the function of AT. This includes the disruption of adipogenesis, lipogenesis, and lipolysis. As a consequence, dysfunctional AT has disruptive patterns of adipokines secretions. The main adipokines produced from AT are leptin and adiponectin. Both were found to be significantly declined under the Cd exposure. Additionally, adipose tissue macrophages can produce either anti-inflammatory markers or pro-inflammatory markers depending on the local AT condition. Cadmium exposure was reported to upregulate pro-inflammatory markers and downregulate anti-inflammatory markers. However, the exact mechanisms of Cd’s adverse role on AT structure, function, and secretion patterns of adipokines are not totally clarified. Therefore, in this review, we present the current findings related to Cd detrimental effects on adipose tissues.Open Access funding provided by Qatar University

Cycle-based Cluster Variational Method for Direct and Inverse Inference

We elaborate on the idea that loop corrections to belief propagation could be dealt with in a systematic way on pairwise Markov random fields, by using the elements of a cycle basis to define region in a generalized belief propagation setting. The region graph is specified in such a way as to avoid dual loops as much as possible, by discarding redundant Lagrange multipliers, in order to facilitate the convergence, while avoiding instabilities associated to minimal factor graph construction. We end up with a two-level algorithm, where a belief propagation algorithm is run alternatively at the level of each cycle and at the inter-region level. The inverse problem of finding the couplings of a Markov random field from empirical covariances can be addressed region wise. It turns out that this can be done efficiently in particular in the Ising context, where fixed point equations can be derived along with a one-parameter log likelihood function to minimize. Numerical experiments confirm the effectiveness of these considerations both for the direct and inverse MRF inference.Comment: 47 pages, 16 figure