Advanced glycation end-products (AGEs) are a heterogeneous group of compounds formed by the Maillard chemical process of non- enzymatic glycation of free amino groups of proteins, lipids and nucleic acids. This chemical modification of biomolecules is triggered by endogeneous hyperglycaemic or oxidative stress-related processes. Additionally, AGEs can derive from exogenous, mostly diet-related, sources. Considering that AGE accumulation in tissues correlates with ageing and is a hallmark in several age-related diseases it is not surprising that the role of AGEs in ageing and pathology has become increasingly evident. The receptor for AGEs (RAGE) is a single transmembrane protein being expressed in a wide variety of human cells. RAGE binds a broad repertoire of extracellular ligands and mediates responses to stress conditions by activating multiple signal transduction pathways being mostly responsible for acute and/or chronic inflammation. RAGE activation has been implicated in ageing as well as in a number of age-related diseases, including atherosclerosis, neurodegeneration, arthritis, stoke, diabetes and cancer. Here we present a synopsis of findings that relate to AGEs-reported implication in cell signalling pathways and ageing, as well as in pathology. Potential implications and opportunities for translational research and the development of new therapies are also discussed.

With the volume of manuscripts submitted for publication growing every year, the deficiencies of peer review (e.g. long review times) are becoming more apparent. Editorial strategies, sets of guidelines designed to speed up the process and reduce editors’ workloads, are treated as trade secrets by publishing houses and are not shared publicly. To improve the effectiveness of their strategies, editors in small publishing groups are faced with undertaking an iterative trial-and-error approach. We show that Cartesian Genetic Programming, a nature-inspired evolutionary algorithm, can dramatically improve editorial strategies. The artificially evolved strategy reduced the duration of the peer review process by 30%, without increasing the pool of reviewers (in comparison to a typical human-developed strategy). Evolutionary computation has typically been used in technological processes or biological ecosystems. Our results demonstrate that genetic programs can improve real-world social systems that are usually much harder to understand and control than physical systems.

Resveratrol is a phytoalexin produced by many plants as a defense mechanism against stress-inducing conditions. The richest dietary sources of resveratrol are berries and grapes, their juices and wines. Good bioavailability of resveratrol is not reflected in its high biological activity in vivo because of resveratrol isomerization and its poor solubility in aqueous solutions. Proteins, cyclodextrins and nanomaterials have been explored as innovative delivery vehicles for resveratrol to overcome this limitation. Numerous in vitro and in vivo studies demonstrated beneficial effects of resveratrol in cardiovascular diseases (CVD). Main beneficial effects of resveratrol intake are cardioprotective, anti-hypertensive, vasodilatory, anti-diabetic, and improvement of lipid status. As resveratrol can alleviate the numerous factors associated with CVD, it has potential as a functional supplement to reduce COVID-19 illness severity in patients displaying poor prognosis due to cardio-vascular complications. Resveratrol was shown to mitigate the major pathways involved in the pathogenesis of SARS-CoV-2 including regulation of the renin-angiotensin system and expression of angiotensin-converting enzyme 2, stimulation of immune system and downregulation of pro-inflammatory cytokine release. Therefore, several studies already have anticipated potential implementation of resveratrol in COVID-19 treatment. Regular intake of a resveratrol rich diet, or resveratrol-based complementary medicaments, may contribute to a healthier cardio-vascular system, prevention and control of CVD, including COVID-19 disease related complications of CVD.

In this paper, we undertake a data-driven theoretical investigation of editorial workflows. We analyse a dataset containing information about 58 papers submitted to the Biochemistry and Biotechnology section of the Journal of the Serbian Chemical Society. We separate the peer review process into stages that each paper has to go through and introduce the notion of completion rate - the probability that an invitation sent to a potential reviewer will result in a finished review. Using empirical transition probabilities and probability distributions of the duration of each stage we create a directed weighted network, the analysis of which allows us to obtain the theoretical probability distributions of review time for different classes of reviewers. These theoretical distributions underlie our numerical simulations of different editorial strategies. Through these simulations, we test the impact of some modifications of the editorial policy on the efficiency of the whole review process. We discover that the distribution of review time is similar for all classes of reviewers, and that the completion rate of reviewers known personally by the editor is very high, which means that they are much more likely to answer the invitation and finish the review than other reviewers. Thus, the completion rate is the key factor that determines the efficiency of each editorial policy. Our results may be of great importance for editors and act as a guide in determining the optimal number of reviewers.