Platelet-Rich Plasma Promotes the Proliferation of Human Muscle Derived Progenitor Cells and Maintains Their Stemness

Human muscle-derived progenitor cells (hMDPCs) offer great promise for muscle cell-based regenerative medicine; however, prolonged ex-vivo expansion using animal sera is necessary to acquire sufficient cells for transplantation. Due to the risks associated with the use of animal sera, the development of a strategy for the ex vivo expansion of hMDPCs is required. The purpose of this study was to investigate the efficacy of using platelet-rich plasma (PRP) for the ex-vivo expansion of hMDPCs. Pre-plated MDPCs, myoendothelial cells, and pericytes are three populations of hMDPCs that we isolated by the modified pre-plate technique and Fluorescence Activated Cell Sorting (FACS), respectively. Pooled allogeneic human PRP was obtained from a local blood bank, and the effect that thrombin-activated PRP-releasate supplemented media had on the ex-vivo expansion of the hMDPCs was tested against FBS supplemented media, both in vitro and in vivo. PRP significantly enhanced short and long-term cell proliferation, with or without FBS supplementation. Antibody-neutralization of PDGF significantly blocked the mitogenic/proliferative effects that PRP had on the hMDPCs. A more stable and sustained expression of markers associated with stemness, and a decreased expression of lineage specific markers was observed in the PRP-expanded cells when compared with the FBS-expanded cells. The in vitro osteogenic, chondrogenic, and myogenic differentiation capacities of the hMDPCs were not altered when expanded in media supplemented with PRP. All populations of hMDPCs that were expanded in PRP supplemented media retained their ability to regenerate myofibers in vivo. Our data demonstrated that PRP promoted the proliferation and maintained the multi-differentiation capacities of the hMDPCs during ex-vivo expansion by maintaining the cells in an undifferentiated state. Moreover, PDGF appears to be a key contributing factor to the beneficial effect that PRP has on the proliferation of hMDPCs. © 2013 Li et al

Probiotic Bifidobacterium breve Induces IL-10-Producing Tr1 Cells in the Colon

Specific intestinal microbiota has been shown to induce Foxp3+ regulatory T cell development. However, it remains unclear how development of another regulatory T cell subset, Tr1 cells, is regulated in the intestine. Here, we analyzed the role of two probiotic strains of intestinal bacteria, Lactobacillus casei and Bifidobacterium breve in T cell development in the intestine. B. breve, but not L. casei, induced development of IL-10-producing Tr1 cells that express cMaf, IL-21, and Ahr in the large intestine. Intestinal CD103+ dendritic cells (DCs) mediated B. breve-induced development of IL-10-producing T cells. CD103+ DCs from Il10−/−, Tlr2−/−, and Myd88−/− mice showed defective B. breve-induced Tr1 cell development. B. breve-treated CD103+ DCs failed to induce IL-10 production from co-cultured Il27ra−/− T cells. B. breve treatment of Tlr2−/− mice did not increase IL-10-producing T cells in the colonic lamina propria. Thus, B. breve activates intestinal CD103+ DCs to produce IL-10 and IL-27 via the TLR2/MyD88 pathway thereby inducing IL-10-producing Tr1 cells in the large intestine. Oral B. breve administration ameliorated colitis in immunocompromised mice given naïve CD4+ T cells from wild-type mice, but not Il10−/− mice. These findings demonstrate that B. breve prevents intestinal inflammation through the induction of intestinal IL-10-producing Tr1 cells

The impact of mortality development on the number of centenarians in England and wales

The world is ageing both at an individual and a population level, and population ageing is truly a global phenomenon. Life expectancies at birth have increased at the global level from 47 years in the mid-20th century to around 70 years today, and are expected to rise to 76 years by the mid-21st century. The proportion of the world’s population aged 60 years and over has increased from 8% in the mid-20th century to 12%, and by 2050 it is expected to reach 21%. The emergence of large numbers of centenarians has accompanied this development. This paper outlines this emergence historically and the likely growth in the number of centenarians in the 21st century, in particular in England and Wales, analysing mortality trends since 1840 and the rise in the number of centenarians in the 20th and 21st centuries. The number of centenarians in England and Wales increased from around 160 in 1922 to almost 12,500 by 2012, but if mortality at all ages had remained constant from 1912 to 2012, then by 2012 the number of centenarians would only have been around 720. By 2100, the number of centenarians is expected to reach around 1.4 million, but if future mortality at all ages were to remain constant, then by 2100 the number of centenarians would be around 78,000. However, if predicted mortality for those aged 55 years and over was to decrease by an additional 5% every 5 years until 2100, then the number of centenarians in England and Wales would reach around 1.8 million by the end of the century

Artificial Intelligence and Internet of Things for autonomous vehicles

Artificial Intelligence (AI) is a machine intelligence tool providing enormous possibilities for smart industrial revolution. It facilitates gathering relevant data/information, identifying the alternatives, choosing among alternatives, taking some actions, making a decision, reviewing the decision, and predicting smartly. On the other hand, Internet of Things (IoT) is the axiom of industry 4.0 revolution, including a worldwide infrastructure for collecting and processing of the data/information from storage, actuation, sensing, advanced services and communication technologies. The combination of high-speed, resilient, low-latency connectivity, and technologies of AI and IoT will enable the transformation towards fully smart Autonomous Vehicle (AV) that illustrate the complementary between real world and digital knowledge for industry 4.0. The purpose of this book chapter is to examine how the latest approaches in AI and IoT can assist in the search for the AV. It has been shown that human errors are the source of 90% of automotive crashes, and the safest drivers drive ten times better than the average [1]. The automated vehicle safety is significant, and users are requiring 1000 times smaller acceptable risk level. Some of the incredible benefits of AVs are: (1) increasing vehicle safety, (2) reduction of accidents, (3) reduction of fuel consumption, (4) releasing of driver time and business opportunities, (5) new potential market opportunities, and (6) reduced emissions and dust particles. However, AVs must use large-scale data/information from their sensors and devices