Effects of total and regional fat loss on plasma CRP and IL-6 in overweight and obese, older adults with knee osteoarthritis

SummaryObjectiveTo describe associations between total and regional body fat mass loss and reduction of systemic levels of inflammation (C-reactive protein (CRP) and interleukin-6 (IL-6)) in obese, older adults with osteoarthritis (OA), undergoing intentional weight loss.DesignData come from a single-blind, 18-month, randomized controlled trial in adults (age: 65.6 ± 6.2; Body mass index (BMI): 33.6 ± 3.7) with knee OA. Participants were randomized to diet-induced weight loss plus exercise (D + E; n = 150), diet-induced weight loss-only (D; n = 149), or exercise-only (E; n = 151). Total body and region-specific (abdomen and thigh) fat mass were measured at baseline and 18 months. High-sensitivity CRP and IL-6 were measured at baseline, six and 18 months. Intervention effects were assessed using mixed models and associations between inflammation and adiposity were compared using logistic and mixed linear regression models.ResultsIntentional total body fat mass reduction was associated with significant reductions in log-adjusted CRP (β = 0.06 (95% CI = 0.04, 0.08) mg/L) and IL-6 (β = 0.02 (95% CI = 0.01, 0.04) pg/mL). Loss of abdominal fat volume was also associated with reduced inflammation, independent of total body fat mass; although models containing measures of total adiposity yielded the best fit. The odds of achieving clinically desirable levels of CRP (<3.0 mg/L) and IL-6 (<2.5 pg/mL) were 3.8 (95% CI = 1.6, 8.9) and 2.2 (95% CI = 1.1, 4.6), respectively, with 5% total weight and fat mass loss.ConclusionsAchievement of clinically desirable levels of CRP and IL-6 more than double with intentional 5% loss of total body weight and fat mass. Global, rather than regional, measures of adiposity are better predictors of change in inflammatory burden.Clinical Trial Registration NumberNCT00381290

Is increased joint loading detrimental to obese patients with knee osteoarthritis? A secondary data analysis from a randomized trial

SummaryObjectiveTo investigate whether increased knee joint loading due to improved ambulatory function and walking speed following weight loss achieved over 16 weeks accelerates symptomatic and structural disease progression over a subsequent 1 year weight maintenance period in an obese population with knee osteoarthritis (OA).MethodsData from a prospective study of weight loss in obese patients with knee OA (the CARtilage in obese knee OsteoarThritis (CAROT) study) were used to determine changes in knee joint compressive loadings (model estimated) during walking after a successful 16 week weight loss intervention. The participants were divided into ‘Unloaders’ (participants that reduced joint loads) and ‘Loaders’ (participants that increased joint loads). The primary symptomatic outcome was changes in knee symptoms, measured with the Knee injury and Osteoarthritis Outcome Score (KOOS) questionnaire, during a subsequent 52 weeks weight maintenance period. The primary structural outcome was changes in tibiofemoral cartilage loss assessed semi-quantitatively (Boston Leeds Knee Osteoarthritis Score (BLOKS) from MRI after the 52 weight maintenance period.Results157 participants (82% of the CAROT cohort) with medial and/or lateral knee OA were classified as Unloaders (n = 100) or Loaders (n = 57). The groups showed similar significant changes in symptoms (group difference: −2.4 KOOS points [95% CI −6.8:1.9]) and cartilage loss (group difference: −0.06 BLOKS points [95% CI −0.22:0.11) after 1 year, with no statistically significant differences between Loaders and Unloaders.ConclusionFor obese patients undergoing a significant weight loss, increased knee joint loading for 1 year was not associated with accelerated symptomatic and structural disease progression compared to a similar weight loss group that had reduced ambulatory compressive knee joint loads.Clinicaltrials.govNCT00655941

The Intensive Diet and Exercise for Arthritis (IDEA) Trial: 18-Month Radiographic and MRI Outcomes

SummaryPurposeReport the radiographic and magnetic resonance imaging (MRI) structural outcomes of an 18-month study of diet-induced weight loss, with or without exercise, compared to exercise alone in older, overweight and obese adults with symptomatic knee osteoarthritis (OA).MethodsProspective, single-blind, randomized controlled trial that enrolled 454 overweight and obese (body mass index, BMI = 27–41 kg m−2) older (age ≥ 55 yrs) adults with knee pain and radiographic evidence of femorotibial OA. Participants were randomized to one of three 18-month interventions: diet-induced weight loss only (D); diet-induced weight loss plus exercise (D + E); or exercise-only control (E). X-rays (N = 325) and MRIs (N = 105) were acquired at baseline and 18 months follow-up. X-ray and MRI (cartilage thickness and semi-quantitative (SQ)) results were analyzed to compare change between groups at 18-month follow-up using analysis of covariance (ANCOVA) adjusted for baseline values, baseline BMI, and gender.ResultsMean baseline descriptive characteristics of the cohort included: age, 65.6 yrs; BMI 33.6 kg m−2; 72% female; 81% white. There was no significant difference between groups in joint space width (JSW) loss; D −0.07 (SE 0.22) mm, D + E −0.27 (SE 0.22) mm and E −0.16 (SE 0.24) mm (P = 0.79). There was also no significant difference in MRI cartilage loss between groups; D −0.10(0.05) mm, D + E −0.13(0.04) mm and E −0.05(0.04) mm (P = 0.42).ConclusionDespite the potent effects of weight loss in this study on symptoms as well as mechanistic outcomes (such as joint compressive force and markers of inflammation), there was no statistically significant difference between the three active interventions on the rate of structural progression either on X-ray or MRI over 18-months

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Volume I. Introduction to DUNE

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE\u27s physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology

Deep Underground Neutrino Experiment (DUNE), far detector technical design report, volume III: DUNE far detector technical coordination

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype