Insulin resistance is associated with skeletal muscle weakness in COPD.

BACKGROUND AND OBJECTIVE: Quadriceps weakness is seen across all GOLD stages of COPD and is associated with increased morbidity and mortality. As quadriceps weakness is only weakly associated with FEV1 , mechanisms other than airflow obstruction are implicated. We tested the hypothesis that insulin resistance contributes to skeletal muscle weakness in people with stable COPD. METHODS: Fifty-one COPD patients (no exacerbations preceding 6 weeks, no rehabilitation preceding 3 months) without known diabetes mellitus underwent assessment of skeletal muscle, including measurement of quadriceps maximal voluntary contraction (QMVC). Physical activity was measured for 7 days using a multisensory biaxial accelerometer armband. Insulin resistance (HOMA2 IR) was calculated from fasting blood glucose and insulin concentrations. RESULTS: QMVC was 30 ± 13 kg (74 ± 25% predicted) and 16 (31%) participants had quadriceps weakness. There was a negative univariate correlation between HOMA2 IR and QMVC (r = -0.446, P = 0.002). HOMA2 IR was greater in people with quadriceps weakness (1.59 ± 0.99) than in those without (1.11 ± 0.55, P = 0.032). On multivariate analysis, with age, sex, weight, BODE index and step count per day included in the model, a one-unit increase in insulin resistance was associated with a 5.9 (2.0-9.8)-kg decrease in QMVC (P = 0.004) and a 4.2 (1.3-14.3)-fold increased risk of quadriceps weakness (P = 0.02). CONCLUSION: Insulin resistance is associated with skeletal muscle weakness in COPD, independent of potential confounders. Further studies are required to explore underlying mechanisms and determine whether insulin-sensitizing drugs could augment pulmonary rehabilitation in building skeletal muscle strength in COPD.

Computer Vision Evidence Supporting Craniometric Alignment of Rat Brain Atlases to Streamline Expert-Guided, First-Order Migration of Hypothalamic Spatial Datasets Related to Behavioral Control.

The rat has arguably the most widely studied brain among all animals, with numerous reference atlases for rat brain having been published since 1946. For example, many neuroscientists have used the atlases of Paxinos and Watson (PW, first published in 1982) or Swanson (S, first published in 1992) as guides to probe or map specific rat brain structures and their connections. Despite nearly three decades of contemporaneous publication, no independent attempt has been made to establish a basic framework that allows data mapped in PW to be placed in register with S, or vice versa. Such data migration would allow scientists to accurately contextualize neuroanatomical data mapped exclusively in only one atlas with data mapped in the other. Here, we provide a tool that allows levels from any of the seven published editions of atlases comprising three distinct PW reference spaces to be aligned to atlas levels from any of the four published editions representing S reference space. This alignment is based on registration of the anteroposterior stereotaxic coordinate (z) measured from the skull landmark, Bregma (ß). Atlas level alignments performed along the z axis using one-dimensional Cleveland dot plots were in general agreement with alignments obtained independently using a custom-made computer vision application that utilized the scale-invariant feature transform (SIFT) and Random Sample Consensus (RANSAC) operation to compare regions of interest in photomicrographs of Nissl-stained tissue sections from the PW and S reference spaces. We show that z-aligned point source data (unpublished hypothalamic microinjection sites) can be migrated from PW to S space to a first-order approximation in the mediolateral and dorsoventral dimensions using anisotropic scaling of the vector-formatted atlas templates, together with expert-guided relocation of obvious outliers in the migrated datasets. The migrated data can be contextualized with other datasets mapped in S space, including neuronal cell bodies, axons, and chemoarchitecture; to generate data-constrained hypotheses difficult to formulate otherwise. The alignment strategies provided in this study constitute a basic starting point for first-order, user-guided data migration between PW and S reference spaces along three dimensions that is potentially extensible to other spatial reference systems for the rat brain.

Growth differentiation factor-15 is associated with muscle mass in chronic obstructive pulmonary disease and promotes muscle wasting in vivo.

BACKGROUND: Loss of muscle mass is a co-morbidity common to a range of chronic diseases including chronic obstructive pulmonary disease (COPD). Several systemic features of COPD including increased inflammatory signalling, oxidative stress, and hypoxia are known to increase the expression of growth differentiation factor-15 (GDF-15), a protein associated with muscle wasting in other diseases. We therefore hypothesized that GDF-15 may contribute to muscle wasting in COPD. METHODS: We determined the expression of GDF-15 in the serum and muscle of patients with COPD and analysed the association of GDF-15 expression with muscle mass and exercise performance. To determine whether GDF-15 had a direct effect on muscle, we also determined the effect of increased GDF-15 expression on the tibialis anterior of mice by electroporation. RESULTS: Growth differentiation factor-15 was increased in the circulation and muscle of COPD patients compared with controls. Circulating GDF-15 was inversely correlated with rectus femoris cross-sectional area (P < 0.001) and exercise capacity (P < 0.001) in two separate cohorts of patients but was not associated with body mass index. GDF-15 levels were associated with 8-oxo-dG in the circulation of patients consistent with a role for oxidative stress in the production of this protein. Local over-expression of GDF-15 in mice caused wasting of the tibialis anterior muscle that expressed it but not in the contralateral muscle suggesting a direct effect of GDF-15 on muscle mass (P < 0.001). CONCLUSIONS: Together, the data suggest that GDF-15 contributes to the loss of muscle mass in COPD.