Finally, suggestions for selecting appropriate pSLM and future directions in this area are discussed. Cytologic features such as the shape and size of tumor cells can predict metastatic death in uveal melanoma and other cancers but suffer from poor reproducibility. In this study, we investigate the interobserver concordance of digital morphometry, and correlate the results with BRCA associated protein-1 (BAP-1) expression and BAP-1 gene mutation status, monosomy 3, gene expression classifications and patient survival in uveal melanoma. The average number of cells analyzed in each of 107 tumors, was 1957 (SD 349). Mean time consumption was less than 2.5 min per tumor. Identical morphometric classification was obtained for ≥85% of tumors in all twelve evaluated morphometric variables (κ 0.70-0.93). learn more The mean nucleus area, nucleus perimeter, nucleus max caliper and nucleus to cell area ratio were significantly greater in tumors with low BAP-1 expression and gene expression class 2. Patients had significantly shorter survival if their tumors had low BAP-1 (Log-Rank p = 0.002), gene expression class 2 (p = 0.004), long nucleus perimeters (p = 0.031), long nucleus max calipers (p = 0.029) and high mean nucleus to cell area ratios (p = 0.041) as defined in a training cohort and then tested in a validation cohort. Long nucleus perimeters and long nucleus max calipers correlated with monosomy 3 (Pearson Chi-Square p = 0.006 and p = 0.009, respectively). Long nucleus perimeters also correlated with BAP-1 mutation (p = 0.017). We conclude that digital morphometry can be fast and highly reproducible, that for the first time, morphometry parameters can be objectively quantitated in thousands of cells at a time in sub-μm resolutions, and that variables describing the shape and size tumor nuclei correlate to BAP-1 status, monosomy 3, gene expression class as well as patient survival. Biomarkers are well established for the diagnosis of myocardial infarction, heart failure and cardiac fibrosis. Different papers on cardiac biomarker evolution during exercise have been published in the literature and generally show mild to moderate elevations. However, the mechanism responsible for these elevations, reflecting physiological or even pathophysiological changes, still has to be clearly elucidated. There are also indications of higher cardiac risk in poorly trained athletes than in well-trained athletes. Whether regular repetition of intensive exercise might lead, in the longer term, to fibrosis and heart failure remains to be determined. In this review, we summarized the main research about the effects of intense exercise (in particular, running) on cardiac biomarkers (including troponins, natriuretic peptides, etc.). We found that cardiac fibrosis biomarkers seemed to be the most informative regarding the biological impact of intense physical activity. OBJECTIVES We aimed to identify serum level variations in protein-derived peptides between patients diagnosed with gastric adenocarcinoma (GAC) and non-cancer persons (control) to detect the activity changes of proteases and explore the auxiliary diagnostic value in the context of GAC physiopathology. METHODS The label-free quantitative peptidome approach was applied to identify variants in serum levels of peptides that can differentiate GAC patients from the control group. Peptide sequences were submitted against Proteasix tool predicting proteases potentially involved in their generation. The activity change of proteases was subsequently estimated based on the peptides with significantly altered relative abundance. In turn, activity change prediction of proteases was correlated with relevant protease expression data from the literature. RESULTS A total of 191 peptide sequences generated by the cleavage of 36 precursor proteins were identified. Using the label-free quantification approach, 33 peptides were differentially quantified (adjusted fold change ≥ 1.5 and p-value  less then  0.05) in which 19 were up-regulated and 14 were down-regulated in GAC samples. Of these peptides, fibrinopeptide A was significantly decreased and its phosphorylated form ADpSGEGDFLAEGGGVR was upregulated in GAC samples. Activity change prediction yielded 10 proteases including 6 Matrix Metalloproteinases (MMPs), Thrombin, Plasmin, and kallikreins 4 and 14. Among predicted proteases in our analysis, MMP-7 was presented as a more promising biomarker associated with useful assays of clinical practice for GAC diagnosis. CONCLUSION Our experimental results demonstrate that the serum levels of peptides were significantly differentiated in GAC physiopathology. The hypotheses built on protease regulation could be used for further investigations to measure proteases and their activity levels that have been poorly studied for GAC diagnosis. Antimicrobial resistance remains a serious problem that results in high mortality and increased healthcare costs globally. One of the major issues is that resistant pathogens decrease the efficacy of conventional antimicrobials. Accordingly, development of novel antimicrobial agents and therapeutic strategies is urgently needed to overcome the challenge of antimicrobial resistance. A potential strategy is to kill pathogenic microorganisms via the formation of reactive oxygen species (ROS). ROS are defined as a number of highly reactive molecules that comprise molecular oxygen (O2), superoxide anion (O2•-), hydrogen peroxide (H2O2) and hydroxyl radicals (•OH). ROS exhibit antimicrobial actions against a broad range of pathogens through the induction of oxidative stress, which is an imbalance between ROS and the ability of the antioxidant defence system to detoxify ROS. ROS-dependent oxidative stress can damage cellular macromolecules, including DNA, lipids and proteins. This article reviews the antimicrobial action of ROS, challenges to ROS hypothesis, work to solidify ROS-mediated antimicrobial lethality hypothesis, recent developments in antimicrobial agents using ROS as an antimicrobial strategy, safety concerns related to ROS, and future directions in ROS research.