The between and within day variation in gross efficiency

Before the influence of divergent factors on gross efficiency (GE) [the ratio of mechanical power output (PO) to metabolic power input (PI)] can be assessed, the variation in GE between days, i.e. the test–retest reliability, and the within day variation needs to be known. Physically active males (n = 18) performed a maximal incremental exercise test to obtain VO2max and PO at VO2max (PVO2max), and three experimental testing days, consisting of seven submaximal exercise bouts evenly distributed over the 24 h of the day. Each submaximal exercise bout consisted of six min cycling at 45, 55 and 65% PVO2max, during which VO2 and RER were measured. GE was determined from the final 3 min of each exercise intensity with: GE = (PO/PI) × 100%. PI was calculated by multiplying VO2 with the oxygen equivalent. GE measured during the individually highest exercise intensity with RER <1.0 did not differ significantly between days (F = 2.70, p = 0.08), which resulted in lower and upper boundaries of the 95% limits of agreement of 19.6 and 20.8%, respectively, around a mean GE of 20.2%. Although there were minor within day variations in GE, differences in GE over the day were not significant (F = 0.16, p = 0.99). The measurement of GE during cycling at intensities approximating VT is apparently very robust, a change in GE of ~0.6% can be reliably detected. Lastly, GE does not display a circadian rhythm so long as the criteria of a steady-state VO2 and RER <1.0 are applied

Proteomic-based identification of haptoglobin-1 precursor as a novel circulating biomarker of ovarian cancer

Screening for specific biomarkers of early-stage detection of ovarian cancer is a major health priority due to the asymptomatic nature and poor survival characteristic of the disease. We utilised two-dimensional gel electrophoresis (2DE) to identify differentially expressed proteins in the serum of ovarian cancer patients that may be useful as biomarkers of this disease. In this study, 38 ovarian cancer patients at different pathological grades (grade 1 (n=6), grade 2 (n=8) and grade 3 (n=24)) were compared to a control group of eight healthy women. Serum samples were treated with a mixture of Affigel-Blue and protein A (5 : 1) for 1 h to remove high abundance protein (e.g. immunoglobulin and albumin) and were displayed using 11 cm, pH 4-7 isoelectric focusing strips for the first dimension and 10% acrylamide gel electrophoresis for the second dimension. Protein spots were visualised by SYPRO-Ruby staining, imaged by FX-imager and compared and analysed by PDQuest software. A total of 24 serum proteins were differentially expressed in grade 1 (P<0.05), 31 in grade 2 (P<0.05) and 25 in grade 3 (P<0.05) ovarian cancer patients. Six of the protein spots that were significantly upregulated in all groups of ovarian cancer patients were identified by nano-electrospray quadrupole quadrupole time-of-flight mass spectrometry (n-ESIQ(q)TOFMS) and matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOFMS) as isoforms of haptoglobin-1 precursor (HAP1), a liver glycoprotein present in human serum. Further identification of the spots at different pathological grades was confirmed by Western blotting using monoclonal antibody against a haptoglobin epitope contained within HAP1. Immunohistochemical localisation of HAP1-like activity was present in malignant ovarian epithelium and stroma but strong immunostaining was present in blood vessels, areas with myxomatous stroma and vascular spaces. No tissue localisation of HAP1-like immunoreactivity was observed in normal ovarian surface epithelium. These data highlight the need to assess circulating concentration of HAP1 in the serum of ovarian cancer patients and evaluate its potential as a biomarker in the early diagnosis of ovarian cancer.N Ahmed, G Barker, KT Oliva, P Hoffmann, C Riley, S Reeve, AI Smith, BE Kemp, MA Quinn and GE Ric

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field