Effect of different exercise modalities plus a hypocaloric diet on inflammation markers in overweight patients

Summary Background & aims Inflammation markers (IM) have been associated with the development of chronic diseases. This study compares the effects on IM of three exercise programs combined with a hypocaloric diet. Methods 119 overweight participants (73 women, 46 men) aged 18–50 years were randomised into four treatment groups: strength training (S; n = 30), endurance training (E; n = 30), combined S + E (SE; n = 30), and a diet and physical activity recommendations group (D; n = 29). Energy intake, anthropometric variables (AV), training variables (VO2peak, strength index, dynamometric strength index [DSI]) and plasma IM were recorded at baseline and after 22 weeks of treatment. Results 84 participants completed the study. At 22 weeks, all groups showed a significantly reduced energy intake (P < 0.001) and improved AV (P < 0.001). VO2peak significantly increased in all groups (P < 0.01). DSI increased in the exercise groups only (P < 0.05). Plasma leptin fell significantly (P < 0.001) in the S and E groups, but not significantly in the SE group (P = 0.029) (no significant differences between these groups). Tumour necrosis factor-α (TNF-α), and C-reactive protein (CRP) concentrations decreased in all groups when examined together, but not when examined separately. No significant differences were seen in interleukin-6 (IL-6). Conclusions Combining strength or endurance training with a hypocaloric diet improved AV and reduced plasma leptin concentrations. No differences were seen between groups in terms of TNF-α, IL-6 or CRP reduction. This trial was registered at clinical trials.gov as NCT01116856. http://clinicaltrials.gov/.

Merging person-specific bio-markers for predicting oral cancer recurrence through an ontology

One of the major problems related to cancer treatment is its recurrence. Without knowing in advance how likely the cancer will relapse, clinical practice usually recommends adjuvant treatments that have strong side effects. A way to optimize treatments is to predict the recurrence probability by analyzing a set of bio-markers. The NeoMark European project has identified a set of preliminary bio-markers for the case of oral cancer by collecting a large series of data from genomic, imaging, and clinical evidence. This heterogeneous set of data needs a proper representation in order to be stored, computed, and communicated efficiently. Ontologies are often considered the proper mean to integrate biomedical data, for their high level of formality and for the need of interoperable, universally accepted models. This paper presents the NeoMark system and how an ontology has been designed to integrate all its heterogeneous data. The system has been validated in a pilot in which data will populate the ontology and will be made public for further research.