Microvesicles as vehicles for tissue regeneration: Changing of the guards

Purpose of Review: Microvesicles (MVs) have been recognised as mediators of stem cell function, enabling and guiding their regenerative effects. Recent Findings: MVs constitute one unique size class of extracellular vesicles (EVs) directly shed from the cell plasma membrane. They facilitate cell-to-cell communication via intercellular transfer of proteins, mRNA and microRNA (miRNA). MVs derived from stem cells, or stem cell regulatory cell types, have proven roles in tissue regeneration and repair processes. Their role in the maintenance of healthy tissue function throughout the life course and thus in age related health span remains to be elucidated. Summary: Understanding the biogenesis and mechanisms of action of MVs may enable the development of cell-free therapeutics capable of assisting in tissue maintenance and repair for a variety of age-related degenerative diseases. This review critically evaluates recent work published in this area and highlights important new findings demonstrating the use of MVs in tissue regeneration

Colouring random graphs and maximising local diversity

We study a variation of the graph colouring problem on random graphs of finite average connectivity. Given the number of colours, we aim to maximise the number of different colours at neighbouring vertices (i.e. one edge distance) of any vertex. Two efficient algorithms, belief propagation and Walksat are adapted to carry out this task. We present experimental results based on two types of random graphs for different system sizes and identify the critical value of the connectivity for the algorithms to find a perfect solution. The problem and the suggested algorithms have practical relevance since various applications, such as distributed storage, can be mapped onto this problem.Comment: 10 pages, 10 figure

Deleterious consequences of antioxidant supplementation on lifespan in a wild-derived mammal

Peer reviewedPublisher PD

Putting a strain on diversity.

Human life expectancy is increasing on a global scale, but healthspan—the period of life free from age‐associated ill health—is not improving at a comparable rate. This disconnect means that a greater proportion of the general population will spend a longer period of their life suffering from one or more debilitating age‐associated diseases, such as cardiovascular disease, Alzheimer's disease, osteoporosis, sarcopenia and various cancers. Understanding the processes underlying ageing and age‐related diseases is therefore a major and pressing research challenge in biomedical research

Mammalian models of extended healthy lifespan

Over the last two centuries, there has been a significant increase in average lifespan expectancy in the developed world. One unambiguous clinical implication of getting older is the risk of experiencing age-related diseases including various cancers, dementia, type-2 diabetes, cataracts and osteoporosis. Historically, the ageing process and its consequences were thought to be intractable. However, over the last two decades or so, a wealth of empirical data has been generated which demonstrates that longevity in model organisms can be extended through the manipulation of individual genes. In particular, many pathological conditions associated with the ageing process in model organisms, and importantly conserved from nematodes to humans, are attenuated in long-lived genetic mutants. For example, several long-lived genetic mouse models show attenuation in age-related cognitive decline, adiposity, cancer and glucose intolerance. Therefore, these long-lived mice enjoy a longer period without suffering the various sequelae of ageing. The greatest challenge in the biology of ageing is to now identify the mechanisms underlying increased healthy lifespan in these model organisms. Given that the elderly are making up an increasingly greater proportion of society, this focused approach in model organisms should help identify tractable interventions that can ultimately be translated to humans

Focused Local Search for Random 3-Satisfiability

A local search algorithm solving an NP-complete optimisation problem can be viewed as a stochastic process moving in an 'energy landscape' towards eventually finding an optimal solution. For the random 3-satisfiability problem, the heuristic of focusing the local moves on the presently unsatisfiedclauses is known to be very effective: the time to solution has been observed to grow only linearly in the number of variables, for a given clauses-to-variables ratio $\alpha$ sufficiently far below the critical satisfiability threshold $\alpha_c \approx 4.27$. We present numerical results on the behaviour of three focused local search algorithms for this problem, considering in particular the characteristics of a focused variant of the simple Metropolis dynamics. We estimate the optimal value for the ``temperature'' parameter $\eta$ for this algorithm, such that its linear-time regime extends as close to $\alpha_c$ as possible. Similar parameter optimisation is performed also for the well-known WalkSAT algorithm and for the less studied, but very well performing Focused Record-to-Record Travel method. We observe that with an appropriate choice of parameters, the linear time regime for each of these algorithms seems to extend well into ratios $\alpha > 4.2$ -- much further than has so far been generally assumed. We discuss the statistics of solution times for the algorithms, relate their performance to the process of ``whitening'', and present some conjectures on the shape of their computational phase diagrams.Comment: 20 pages, lots of figure