Exercise for Weight Loss: Further Evaluating Energy Compensation with Exercise

PURPOSE: This study assessed how individuals compensate for energy expended during a 12-wk aerobic exercise intervention, elucidating potential mechanisms and the role exercise dose plays in the compensatory response. PARTICIPANTS AND DESIGN: Three-arm, randomized controlled trial among sedentary adults age 18 to 40 yr, body mass index of 25 to 35. Groups included six exercise sessions per week, two sessions per week, and sedentary control. METHODS: Rate of exercise energy expenditure was calculated from a graded exercise test averaged across five heart rate zones. Energy compensation was calculated as the difference between expected weight loss (based on exercise energy expenditure) and changes in fat and fat-free mass (DXA). Resting energy expenditure was assessed via indirect calorimetry and concentrations of acylated ghrelin, leptin, insulin, and Glucagon-like peptide 1 (GLP-1) were assessed fasting and postprandial (six timepoints over 2 h). RESULTS: The 6-d·wk−1 group expended more energy (2753.5 kcal) and exercised longer (320.5 min) per week than the 2-d·wk−1 group (1490.7 kcal, 1888.8 min, P \u3c 0.05), resulting in greater fat loss compared with the 2-d or control groups (P \u3c 0.05). Exercise groups did not differ in the % or total kcal compensated. Greater decreases in area under the curve (AUC) for acylated ghrelin predicted greater fat loss, regardless of group, energy expended per week, exercise duration, or exercise intensity. Changes in leptin AUC was the only independent predictor for energy compensation, with a greater decrease in leptin AUC predicting less energy compensation. Exercise frequency, energy expended, duration, or intensity did not influence energy compensation. CONCLUSIONS: Leptin is an important factor in successful weight loss through exercise, with greater postprandial decreases promoting less compensation. Greater amounts of exercise do not influence the compensatory response to an exercise-induced energy deficit

Longitudinal-Transverse Separations of Structure Functions at Low Q2Q^{2} for Hydrogen and Deuterium

We report on a study of the longitudinal to transverse cross section ratio, $R=\sigma_L/\sigma_T$, at low values of $x$ and $Q^{2}$, as determined from inclusive inelastic electron-hydrogen and electron-deuterium scattering data from Jefferson Lab Hall C spanning the four-momentum transfer range 0.06 $< Q^{2} < 2.8$ GeV$^{2}$. Even at the lowest values of $Q^{2}$, $R$ remains nearly constant and does not disappear with decreasing $Q^{2}$, as expected. We find a nearly identical behaviour for hydrogen and deuterium.Comment: 4 pages, 2 gigure

A proteomic study of human Merkel Cell Carcinoma

Merkel Cell Carcinoma (MCC) is an aggressive neuroendocrine cancer of the skin. The incidence has been quadrupled with a 5-year mortality rate of 46%, presently there is no cure for metastatic disease. Despite the contribution of Merkel cell polyomavirus, the molecular events of MCC carcinogenesis are poorly defined. To better understand MCC carcinogensis, we have performed the first quantitative proteomic comparison of formalin-fixed, paraffin-embedded (FFPE) MCC tissues using another neuroendocrine tumor (carcinoid tumor of the lung) as controls. Bioinformatic analysis of the proteomic data has revealed that MCCs carry distinct protein expression patterns. Further analysis of significantly over-expressed proteins suggested the involvement of MAPK, PI3K/Akt/mTOR, wnt, and apoptosis signaling pathways. Our previous study and that from others have shown mTOR activation in MCCs. Therefore, we have focused on two downstream molecules of the mTOR pathway, lactate dehydrogenase B (LDHB) and heterogeneous ribonucleoprotein F (hnRNPF). We confirm over-expression of LDHB and hnRNPF in two primary human MCC cell lines, 16 fresh tumors, and in the majority of 80 tissue microarray samples. Moreover, mTOR inhibition suppresses LDHB and hnRNPF expression in MCC cells. The results of the current study provide insight into MCC carcinogenesis and provide rationale for mTOR inhibition in pre-clinical studies

Investigation of LiFeAs by means of "Break-junction" Technique

In our tunneling investigation using Andreev superconductor - normal metal - superconductor contacts on LiFeAs single crystals we observed two reproducible independent subharmonic gap structures at dynamic conductance characteristics. From these results, we can derive the energy of the large superconducting gap $\Delta_L=(2.5 \div 3.4)$ meV and the small gap $\Delta_L=(0.9 \div 1)$ meV at $T = 4.2$ K for the $T_C^{local} \approx (10.5 \div 14)$ K (the contact area critical temperature which deviation causes the variation of $\Delta_L$). The BCS-ratio is found to be $2\Delta_L/k_BT_C = (4.6 \div 5.6)$, whereas $2\Delta_S/k_BT_C \ll 3.52$ results from induced superconductivity in the bands with the small gap.Comment: 7 pages, 5 figures. Published in Pis'ma v ZhETF 95, 604-610 (2012

Evolutionary profiling reveals the heterogeneous origins of classes of human disease genes: implications for modeling disease genetics in animals

Background: The recent expansion of whole-genome sequence data available from diverse animal lineages provides an opportunity to investigate the evolutionary origins of specific classes of human disease genes. Previous studies have observed that human disease genes are of particularly ancient origin. While this suggests that many animal species have the potential to serve as feasible models for research on genes responsible for human disease, it is unclear whether this pattern has meaningful implications and whether it prevails for every class of human disease. Results: We used a comparative genomics approach encompassing a broad phylogenetic range of animals with sequenced genomes to determine the evolutionary patterns exhibited by human genes associated with different classes of disease. Our results support previous claims that most human disease genes are of ancient origin but, more importantly, we also demonstrate that several specific disease classes have a significantly large proportion of genes that emerged relatively recently within the metazoans and/or vertebrates. An independent assessment of the synonymous to non-synonymous substitution rates of human disease genes found in mammals reveals that disease classes that arose more recently also display unexpected rates of purifying selection between their mammalian and human counterparts. Conclusions: Our results reveal the heterogeneity underlying the evolutionary origins of (and selective pressures on) different classes of human disease genes. For example, some disease gene classes appear to be of uncommonly recent (i.e., vertebrate-specific) origin and, as a whole, have been evolving at a faster rate within mammals than the majority of disease classes having more ancient origins. The novel patterns that we have identified may provide new insight into cases where studies using traditional animal models were unable to produce results that translated to humans. Conversely, we note that the larger set of disease classes do have ancient origins, suggesting that many non-traditional animal models have the potential to be useful for studying many human disease genes. Taken together, these findings emphasize why model organism selection should be done on a disease-by-disease basis, with evolutionary profiles in mind

Patient-specific RF safety assessment in MRI: Progress in creating surface-based human head and shoulder models

The interaction of electromagnetic (EM) fields with the human body during magnetic resonance imaging (MRI) is complex and subject specific. MRI radiofrequency (RF) coil performance and safety assessment typically includes numerical EM simulations with a set of human body models. The dimensions of mesh elements used for discretization of the EM simulation domain must be adequate for correct representation of the MRI coil elements, different types of human tissue, and wires and electrodes of additional devices. Examples of such devices include those used during electroencephalography, transcranial magnetic stimulation, and transcranial direct current stimulation, which record complementary information or manipulate brain states during MRI measurement. The electrical contact within and between tissues, as well as between an electrode and the skin, must also be preserved. These requirements can be fulfilled with anatomically correct surface-based human models and EM solvers based on unstructured meshes. Here, we report (i) our workflow used to generate the surface meshes of a head and torso model from the segmented AustinMan dataset, (ii) head and torso model mesh optimization for three-dimensional EM simulation in ANSYS HFSS, and (iii) several case studies of MRI RF coil performance and safety assessment

Toward optimal implementation of cancer prevention and control programs in public health: A study protocol on mis-implementation

Abstract Background Much of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes. Methods This is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation. Discussion This study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas