Instantons and Yang-Mills Flows on Coset Spaces

We consider the Yang-Mills flow equations on a reductive coset space G/H and the Yang-Mills equations on the manifold R x G/H. On nonsymmetric coset spaces G/H one can introduce geometric fluxes identified with the torsion of the spin connection. The condition of G-equivariance imposed on the gauge fields reduces the Yang-Mills equations to phi^4-kink equations on R. Depending on the boundary conditions and torsion, we obtain solutions to the Yang-Mills equations describing instantons, chains of instanton-anti-instanton pairs or modifications of gauge bundles. For Lorentzian signature on R x G/H, dyon-type configurations are constructed as well. We also present explicit solutions to the Yang-Mills flow equations and compare them with the Yang-Mills solutions on R x G/H.Comment: 1+12 page

Biomarkers and longitudinal changes in lumbar spine degeneration and low back pain: the Johnston County Osteoarthritis Project

Objective: To determine if baseline biomarkers are associated with longitudinal changes in the worsening of disc space narrowing (DSN), vertebral osteophytes (OST), and low back pain (LBP). Design: Paired baseline (2003–2004) and follow-up (2006–2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for severity of DSN and OST. LBP severity was self-reported. Concentrations of analytes (cytokines, proteoglycans, and neuropeptides) were quantified by immunoassay. Pressure-pain threshold (PPT), a marker of sensitivity to pressure pain, was measured with a standard dolorimeter. Binary logistic regression models were used to estimate odd ratios (OR) and 95% confidence intervals (CI) of biomarker levels with DSN, OST, or LBP. Interactions were tested between biomarker levels and the number of affected lumbar spine levels or LBP. Results: We included participants (n = 723) with biospecimens, PPT, and paired lumbar spine radiographic data. Baseline Lumican, a proteoglycan reflective of extracellular matrix changes, was associated with longitudinal changes in DSN worsening (OR = 3.19 [95% CI 1.22, 8.01]). Baseline brain-derived neuropathic factor, a neuropeptide, (OR = 1.80 [95% CI 1.03, 3.16]) was associated with longitudinal changes in OST worsening, which may reflect osteoclast genesis. Baseline hyaluronic acid (OR = 1.31 [95% CI 1.01, 1.71]), indicative of systemic inflammation, and PPT (OR = 1.56 [95% CI 1.02, 2.31]) were associated with longitudinal increases in LBP severity. Conclusion: These findings suggest that baseline biomarkers are associated with longitudinal changes occurring in structures of the lumbar spine (DSN vs OST). Markers of inflammation and perceived pressure pain sensitivity were associated with longitudinal worsening of LBP

Joint hypermobility is not positively associated with prevalent multiple joint osteoarthritis: A cross-sectional study of older adults

Background: This cross-sectional study evaluated associations of joint hypermobility and multiple joint osteoarthritis (MJOA) in a community-based cohort of adults 45+ years of age. Methods: MJOA and joint hypermobility data were from 1677 participants (mean age 69 years, 68% women) who completed research clinic visits during 2003-2010. Prevalent MJOA was defined in four ways. Radiographic OA (rOA) was defined as Kellgren-Lawrence (KL) > 2 at any included study joint; symptomatic OA (sxOA) required both symptoms and rOA in a joint. Joint hypermobility was defined as a Beighton score of > 4. Separate logistic regression models were used to estimate odds ratios (OR) between joint hypermobility and each MJOA definition, adjusting for age, sex, race, body mass index, and baseline visit. Results: In this cohort, 4% had Beighton score > 4 and 63% met any definition of MJOA. Joint hypermobility was associated with significantly lower odds of radiographic and symptomatic MJOA-1 (multiple joint OA-definition 1: involvement of > 1 IP (interphalangeal) nodes and > 2 sites of hip, knee, and spine; 74 and 58% lower, respectively). However, for the other MJOA definitions (i.e., MJOA-2:involvement of > 2 IP joints, > 1 carpometacarpal [CMC] joints, and knee or hip sites; MJOA-3: involvement of > 5 joint sites from among distal interphalangeal, proximal interphalangeal, CMC, hip, knee, or spine sites; and MJOA-4:involvement of > 2 lower body sites (hip, knee, or spine), there were no statistically significant associations. For associations between site-specific hypermobility and any MJOA definition, most adjusted ORs were less than one, but few were statistically significant. Conclusions: Overall, joint hypermobility was not positively associated with any definition of prevalent MJOA in this cohort, and an inverse association existed with one definition of MJOA. Longitudinal studies are needed to determine the contribution of hypermobility to the incidence and progression of MJOA outcomes

Relationship of joint hypermobility with low Back pain and lumbar spine osteoarthritis

Background: Chronic low back pain (cLBP) affects millions of Americans and costs billions. Studies suggest a link between cLBP and joint hypermobility. Methods: We conducted cross-sectional primary analyses of joint hypermobility and cLBP, lumbar spine osteoarthritis (OA), and lumbar facet joint OA (FOA) in 3 large studies - the Generalized Osteoarthritis Study, Genetics of Generalized Osteoarthritis Study, and Johnston County Osteoarthritis Project (total n = 5072). Associations of joint hypermobility and Beighton trunk flexion with cLBP and lumbar OA were estimated using separate adjusted logistic regression models. Adjusted pooled odds ratios (pORs) and 95% confidence intervals (CIs) were then summarized - using random effect univariate, multivariate crude, and adjusted models - and heterogeneity was determined (I 2 statistic). Results: In univariate models, hypermobility was associated with symptomatic FOA (pOR = 0.64 [95% CI 0.44, 0.93]) but this result was not found in the multivariate models. In multivariate adjusted models, hypermobility was not significantly associated with cLBP and lumbar OA, but trunk flexion was inversely associated with cLBP (pOR = 0.40 [95% 0.26, 0.62]), spine OA (pOR = 0.66 [95% CI 0.50, 0.87]), symptomatic spine OA (pOR = 0.39 [95% CI 0.28, 0.53]), and symptomatic FOA (pOR = 0.53 [95% CI 0.37, 0.77]). Generally, between-study heterogeneity was moderate-high. Conclusions: Hypermobility was not associated with cLBP or lumbar OA. The inverse association of trunk flexion with cLBP and lumbar OA may indicate a role for a flexible spine in avoiding or managing these conditions. © 2019 The Author(s)

Relationship of joint hypermobility with ankle and foot radiographic osteoarthritis and symptoms in a community-based cohort

Objective. To explore associations of joint hypermobility (a condition where range of motion is greater than normal) with ankle and foot radiographic osteoarthritis (OA) and symptoms in a large community-based cohort of African American and white adults ages 55-94 years old. Methods. Ankle and foot radiographs and joint hypermobility data (Beighton score for joint hypermobility criteria) were available for 848 participants (from 2003 to 2010) in this cross-sectional study. General joint hypermobility was defined as a Beighton score ≥4 (range 0-9); knee hypermobility was defined as hyperextension of at least 1 knee. Standing anteroposterior and lateral foot radiographs were read with standard atlases for Kellgren-Lawrence grade, osteophytes, and joint space narrowing (JSN) at the tibiotalar joint, and for osteophytes and JSN to define OA at 5 foot joints. Ankle or foot symptoms were self-reported. Separate person-based logistic regression models were used to estimate associations of ankle and foot OA and symptom outcomes with hypermobility measures, adjusting for age, sex, race, body mass index, and history of ankle/foot injury. Results. This sample cohort included 577 women (68%) and 280 African Americans (33%). The mean age of the participants was 71 years, with a mean body mass index of 31 kg/m2. The general joint hypermobility of the participants was 7% and knee hypermobility was 4%. Having a history of ankle injury was 11.5%, and foot injury was 3.8%. Although general joint hypermobility was not associated with ankle and foot outcomes, knee hypermobility was associated with ankle symptoms, foot symptoms, and talonavicular OA (adjusted odds ratios of 4.4, 2.4, and 3.0, respectively). Conclusion. Knee joint hypermobility may be related to talonavicular OA and to ankle and foot symptoms

Predictors of Lumbar Spine Degeneration and Low Back Pain in the Community: The Johnston County Osteoarthritis Project

Objective: To determine the incidence and worsening of lumbar spine structure and low back pain (LBP) and whether they are predicted by demographic characteristics or clinical characteristics or appendicular joint osteoarthritis (OA). Methods: Paired baseline (2003–2004) and follow-up (2006–2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for osteophytes (OST), disc space narrowing (DSN), spondylolisthesis, and presence of facet joint OA (FOA). Spine OA was defined as at least mild OST and mild DSN at the same level for any level of the lumbar spine. LBP, comorbidities, and back injury were self-reported. Weibull models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of spine phenotypes accounting for potential predictors including demographic characteristics, clinical characteristics, comorbidities, obesity, and appendicular OA. Results: Obesity was a consistent and strong predictor of incidence of DSN (HR 1.80 [95% CI 1.09–2.98]), spine OA (HR 1.56 [95% CI 1.01–2.41]), FOA (HR 4.99 [95% CI 1.46–17.10]), spondylolisthesis (HR 1.87 [95% CI 1.02–3.43]), and LBP (HR 1.75 [95% CI 1.19–2.56]), and worsening of DSN (HR 1.51 [95% CI 1.09–2.09]) and LBP (HR 1.51 [95% CI 1.12–2.06]). Knee OA was a predictor of incident FOA (HR 4.18 [95% CI 1.44–12.2]). Spine OA (HR 1.80 [95% CI 1.24–2.63]) and OST (HR 1.85 [95% CI 1.02–3.36]) were predictors of incidence of LBP. Hip OA (HR 1.39 [95% CI 1.04–1.85]) and OST (HR 1.58 [95% CI 1.00–2.49]) were predictors of LBP worsening. Conclusion: Among the multiple predictors of spine phenotypes, obesity was a common predictor for both incidence and worsening of lumbar spine degeneration and LBP

Inflammatory, Structural, and Pain Biochemical Biomarkers May Reflect Radiographic Disc Space Narrowing: The Johnston County Osteoarthritis Project

The purpose of this work is to determine the relationship between biomarkers of inflammation, structure, and pain with radiographic disc space narrowing (DSN) in community-based participants. A total of 74 participants (37 cases and 37 controls) enrolled in the Johnston County Osteoarthritis Project during 2006–2010 were selected. The cases had at least mild radiographic DSN and low back pain (LBP). The controls had neither radiographic evidence of DSN nor LBP. The measured analytes from human serum included N-cadherin, Keratin-19, Lumican, CXCL6, RANTES, IL-17, IL-6, BDNF, OPG, and NPY. A standard dolorimeter measured pressure-pain threshold. The coefficients of variation were used to evaluate inter- and intra-assay reliability. Participants with similar biomarker profiles were grouped together using cluster analysis. The binomial regression models were used to estimate risk ratios (RR) and 95% confidence intervals (CI) in propensity score-matched models. Significant associations were found between radiographic DSN and OPG (RR = 3.90; 95% CI: 1.83, 8.31), IL-6 (RR = 2.54; 95% CI: 1.92, 3.36), and NPY (RR = 2.06 95% CI: 1.62, 2.63). Relative to a cluster with low levels of biomarkers, a cluster representing elevated levels of OPG, RANTES, Lumican, Keratin-19, and NPY (RR = 3.04; 95% CI: 1.22, 7.54) and a cluster representing elevated levels of NPY (RR = 2.91; 95% CI: 1.15, 7.39) were significantly associated with radiographic DSN. Clinical Significance: These findings suggest that individual and combinations of biochemical biomarkers may reflect radiographic DSN. This is just one step toward understanding the relationships between biochemical biomarkers and DSN that may lead to improved intervention delivery

Association of Biomarkers with Individual and Multiple Body Sites of Pain: The Johnston County Osteoarthritis Project

Introduction: Biochemical biomarkers may provide insight into musculoskeletal pain reported at individual or multiple body sites. The purpose of this study was to determine if biomarkers or pressure-pain threshold (PPT) were associated with individual or multiple sites of pain. Methods: This cross-sectional analysis included 689 community-based participants. Self-reported symptoms (ie, pain, aching, or stiffness) were ascertained about the neck, upper back/thoracic, low back, shoulders, elbows, wrist, hands, hips, knees, ankles, and feet. Measured analytes included CXCL-6, RANTES, HA, IL-6, BDNF, OPG and NPY. A standard dolorimeter measured PPT. Logistic regression was used determine the association between biomarkers and PPT with individual and summed sites of pain. Results: Increased IL-6 and HA were associated with knee pain (OR=1.30, 95% CI 1.03, 1.64) and (OR=1.32, 95% CI 1.01, 1.73) respectively; HA was also associated with elbow/wrist/hand pain (OR=1.60, 95% CI 1.22, 2.09). Those with increased NPY levels were less likely to have shoulder pain (OR=0.56, 95% CI 0.33, 0.93). Biomarkers HA (OR=1.50, 95% CI 1.07, 2.10), OPG (OR=1.74, 95% CI 1.00, 3.03), CXCL-6 (OR=1.75, 95% CI 1.02, 3.01) and decreased PPT (OR=3.97, 95% CI 2.22, 7.12) were associated with multiple compared to no sites of pain. Biomarker HA (OR=1.57, 95% CI 1.06, 2.32) and decreased PPT (OR=3.53, 95% CI 1.81, 6.88) were associated with multiple compared to a single site of pain. Conclusion: Biomarkers of inflammation (HA, OPG, IL-6 and CXCL-6), pain (NPY) and PPT may help to understand the etiology of single and multiple pain sites

Results on correlations and fluctuations from NA49

The large acceptance and high momentum resolution as well as the significant particle identification capabilities of the NA49 experiment at the CERN SPS allow for a broad study of fluctuations and correlations in hadronic interactions. In the first part recent results on event-by-event charge and p_t fluctuations are presented. Charge fluctuations in central Pb+Pb reactions are investigated at three different beam energies (40, 80, and 158 AGeV), while for the p_t fluctuations the focus is put on the system size dependence at 158 AGeV. In the second part recent results on Bose Einstein correlations of h-h- pairs in minimum bias Pb+Pb reactions at 40 and 158 AGeV, as well as of K+K+ and K-K- pairs in central Pb+Pb collisions at 158 AGeV are shown. Additionally, other types of two particle correlations, namely pi p, Lambda p, and Lambda Lambda correlations, have been measured by the NA49 experiment. Finally, results on the energy and system size dependence of deuteron coalescence are discussed.Comment: 10 pages, 12 figures, Presented at Quark Matter 2002, Nantes, France, Corrected error in Eq.

Event-by-Event Fluctuations of Particle Ratios in Central Pb+Pb Collisions at 20 to 158 AGeV

In the vicinity of the QCD phase transition, critical fluctuations have been predicted to lead to non-statistical fluctuations of particle ratios, depending on the nature of the phase transition. Recent results of the NA49 energy scan program show a sharp maximum of the ratio of K+ to Pi+ yields in central Pb+Pb collisions at beam energies of 20-30 AGeV. This observation has been interpreted as an indication of a phase transition at low SPS energies. We present first results on event-by-event fluctuations of the kaon to pion and proton to pion ratios at beam energies close to this maximum.Comment: 4 pages, 4 figures, Quark Matter 2004 proceeding