Comparison of Two Different Sprint Interval Training Work-to-Rest Ratios on Acute Metabolic and Inflammatory Responses

High intensity exercise is believed to yield greater results on health and human performance than moderate intensity exercise. Extensive research indicates that not only do high-intensity interval training (HIT) and sprint interval training (SIT) produce significant improvements in cardiovascular fitness and disease, they may be more effective at improving long-term metabolic function, including insulin sensitivity (Si), by producing more mitochondria. Moreover, compliance rates for HIT and SIT participation are reported to be the same or better than traditional moderate intensity exercise. Because lack of time is often cited as major hindrance to exercise participation, SIT is also seen as a time efficient option to improve health and performance. It does appear, however, that repeated sessions of SIT are needed before overall improvements can be measured. SIT protocols employing maximal 30 sec sprints with ~5 min rest [a 1:9 work-to-rest ratio (W:R)], have garnered much of the research focus, while those using minimal rest periods, like Tabata which uses 20 sec sprints and 10 sec rest (2:1 W:R), have been ignored. This may omit a possible SIT option that could influence acute and chronic adaptations. The role of inflammatory cytokines on Si remains an area of continued research. While endurance exercise is thought to create an overall anti-inflammatory environment that stimulates improvement in Si, SIT is often viewed as pro-inflammatory. However, few studies have provided significant insight into cytokine release following SIT, and none haveexplored its impact on Si. In addition, the impact of W:R on cytokine remains speculative at best. Therefore, the examination of the effect of different sprint protocols of similar total work (kJ) on performance, metabolic function, and inflammatory response may provide valuable insight into these adaptive processes

Elucidating dipeptide utilization and metabolism by CHO cells for improved cell culture performance

Please click Additional Files below to see the full abstract

Exploration of PET and MRI radiomic features for decoding breast cancer phenotypes and prognosis.

Radiomics is an emerging technology for imaging biomarker discovery and disease-specific personalized treatment management. This paper aims to determine the benefit of using multi-modality radiomics data from PET and MR images in the characterization breast cancer phenotype and prognosis. Eighty-four features were extracted from PET and MR images of 113 breast cancer patients. Unsupervised clustering based on PET and MRI radiomic features created three subgroups. These derived subgroups were statistically significantly associated with tumor grade (p = 2.0 × 10-6), tumor overall stage (p = 0.037), breast cancer subtypes (p = 0.0085), and disease recurrence status (p = 0.0053). The PET-derived first-order statistics and gray level co-occurrence matrix (GLCM) textural features were discriminative of breast cancer tumor grade, which was confirmed by the results of L2-regularization logistic regression (with repeated nested cross-validation) with an estimated area under the receiver operating characteristic curve (AUC) of 0.76 (95% confidence interval (CI) = [0.62, 0.83]). The results of ElasticNet logistic regression indicated that PET and MR radiomics distinguished recurrence-free survival, with a mean AUC of 0.75 (95% CI = [0.62, 0.88]) and 0.68 (95% CI = [0.58, 0.81]) for 1 and 2 years, respectively. The MRI-derived GLCM inverse difference moment normalized (IDMN) and the PET-derived GLCM cluster prominence were among the key features in the predictive models for recurrence-free survival. In conclusion, radiomic features from PET and MR images could be helpful in deciphering breast cancer phenotypes and may have potential as imaging biomarkers for prediction of breast cancer recurrence-free survival

Elucidating amino acid metabolism in CHO cells

CHO cells require complex media for cell growth and protein production. The major components of industrial media are amino acids, however, relatively little is known about the metabolism of amino acids in CHO cell cultures. Here, we applied advanced 13C-flux analysis tools to elucidate the metabolic flow of the amino acids in a fed-batch CHO culture that overproduced IgG. Carbon flows were tracked throughout the growth phase and changes in metabolism were quantified when cells transitioned from growth phase to stationary phase. In addition, we quantified how changes in amino acids profiles in the medium translated to changes in cell growth, protein production and product quality attributes. To trace each amino acid individually, custom media formulations were used, where each medium formulation was depleted of a specific amino acid. A labeled 13C variant of the depleted amino acid was then added to the medium at the desired concentration. CHO cells were then grown in fed-batch culture. As the cells metabolized the labeled amino acids, this resulted in a redistribution of 13C-atoms which we quantified using GC-MS for both extracellular metabolites (including lactate, amino acids and the IgG product) and intracellular metabolites (including free intracellular metabolites, cell proteins, lipids and carbohydrates). We then estimated metabolic fluxes using state-of-the-art 13C-metabolic flux analysis. This allowed us to calculate the fraction of each amino acid that was used for cell growth, protein production, lactate formation and energy generation. We also investigated the effects of labeling in both the batch and fed-batch stationary phase. Finally, we investigated the effects of varying amino acid concentrations. Each 13C-labeled amino acid was added to the medium at a lower or higher concentration compared to the base medium. 13C-metabolic flux analysis was again performed and changes in fluxes were compared in order to determine the precise impacts of amino acid concentration changes on the flux profiles. Taking all of this data together, we are now building a predictive kinetic model that relates how the metabolism of CHO cells can be predicted from amino acid profiles. In future work, model predictions will be experimentally validated as a means of optimizing the amino acid composition of industrial culture media

Folding transition of the triangular lattice in a discrete three--dimensional space

A vertex model introduced by M. Bowick, P. Di Francesco, O. Golinelli, and E. Guitter (cond-mat/9502063) describing the folding of the triangular lattice onto the face centered cubic lattice has been studied in the hexagon approximation of the cluster variation method. The model describes the behaviour of a polymerized membrane in a discrete three--dimensional space. We have introduced a curvature energy and a symmetry breaking field and studied the phase diagram of the resulting model. By varying the curvature energy parameter, a first-order transition has been found between a flat and a folded phase for any value of the symmetry breaking field.Comment: 11 pages, latex file, 2 postscript figure

Folding transitions of the triangular lattice with defects

A recently introduced model describing the folding of the triangular lattice is generalized allowing for defects in the lattice and written as an Ising model with nearest-neighbor and plaquette interactions on the honeycomb lattice. Its phase diagram is determined in the hexagon approximation of the cluster variation method and the crossover from the pure Ising to the pure folding model is investigated, obtaining a quite rich structure with several multicritical points. Our results are in very good agreement with the available exact ones and extend a previous transfer matrix study.Comment: 16 pages, latex, 5 postscript figure

First-order transition of tethered membranes in 3d space

We study a model of phantom tethered membranes, embedded in three-dimensional space, by extensive Monte Carlo simulations. The membranes have hexagonal lattice structure where each monomer is interacting with six nearest-neighbors (NN). Tethering interaction between NN, as well as curvature penalty between NN triangles are taken into account. This model is new in the sense that NN interactions are taken into account by a truncated Lennard-Jones potential including both repulsive and attractive parts. The main result of our study is that the system undergoes a first-order crumpling transition from low temperature flat phase to high temperature crumpled phase, in contrast with early numerical results on models of tethered membranes.Comment: 5 pages, 6 figure

Folding of the Triangular Lattice with Quenched Random Bending Rigidity

We study the problem of folding of the regular triangular lattice in the presence of a quenched random bending rigidity + or - K and a magnetic field h (conjugate to the local normal vectors to the triangles). The randomness in the bending energy can be understood as arising from a prior marking of the lattice with quenched creases on which folds are favored. We consider three types of quenched randomness: (1) a ``physical'' randomness where the creases arise from some prior random folding; (2) a Mattis-like randomness where creases are domain walls of some quenched spin system; (3) an Edwards-Anderson-like randomness where the bending energy is + or - K at random independently on each bond. The corresponding (K,h) phase diagrams are determined in the hexagon approximation of the cluster variation method. Depending on the type of randomness, the system shows essentially different behaviors.Comment: uses harvmac (l), epsf, 17 figs included, uuencoded, tar compresse

An Effective Model for Crumpling in Two Dimensions?

We investigate the crumpling transition for a dynamically triangulated random surface embedded in two dimensions using an effective model in which the disordering effect of the $X$ variables on the correlations of the normals is replaced by a long-range ``antiferromagnetic'' term. We compare the results from a Monte Carlo simulation with those obtained for the standard action which retains the $X$'s and discuss the nature of the phase transition.Comment: 5 page

Maternal Depression, Paternal Psychopathology, and Adolescent Diagnostic Outcomes

The authors examined the relationship between maternal depression, paternal psychopathology, and adolescent diagnostic outcomes in a community sample of 522 Australian families. They also examined whether chronic family stress, father's expressed emotion, and parents' marital satisfaction mediated the relationship between parental psychopathology and adolescent outcomes. Mother's education, child's gender, and family income were covaried in all analyses. Results revealed that maternal depression and paternal depression had an additive effect on youth externalizing disorders. In addition, maternal depression interacted with both paternal depression and paternal substance abuse in predicting youth depression but not youth nondepressive disorders. Chronic family stress and father's expressed emotion appeared to mediate the relationship between parental psychopathology and youth depression