Background: Low back pain (LBP) is a common musculoskeletal problem globally. Updating the prevalence and burden of LBP is important for researchers and policy makers. This paper presents, compares and contextualizes the global prevalence and years lived with disability (YLDs) of LBP by age, sex and region, from 1990 to 2017. Methods: Data were extracted from the GBD (the Global Burden of Disease, Injuries, and Risk Factors Study) 2017 Study. Age, sex and region-specific analyses were conducted to estimate the global prevalence and YLDs of LBP, with the uncertainty intervals (UIs). Results: The age-standardized point prevalence of LBP was 8.20% (95% UI: 7.31-9.10%) in 1990 and decreased slightly to 7.50% (95% UI: 6.75-8.27%) in 2017. The prevalent numbers of people with LBP at any one point in time in 1990 was 377.5 million, and this increased to 577.0 million in 2017. Agestandardized prevalence of LBP was higher in females than males. LBP prevalence increased with age, and peaked around the ages of 80 to 89 years, and then decreased slightly. Global YLDs were 42.5 million (95% UI: 30.2 million-57.2 million) in 1990 and increased by 52.7% to 64.9 million (95% UI: 46.5 million-87.4 million) in 2017. YLDs were also higher in females than males and increased initially with age; they peaked at 35-39 years of age in 1990, before decreasing, whereas in 2017, they peaked at 45-49 years of age, before decreasing. Western Europe had the highest number of LBP YLDs. Conclusions: Globally, LBP is the leading global cause of YLDs. Greater attention is urgently needed to mitigate this increasing burden and the impact it is having on health and social systems.

We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, but current hill-climbing rough set approaches to feature selection are inadequate at finding optimal reductions as no perfect heuristic can guarantee optimality. On the other hand, complete searches are not feasible for even medium-sized datasets. So, stochastic approaches provide a promising feature selection mechanism. Like Genetic Algorithms, PSO is a new evolutionary computation technique, in which each potential solution is seen as a particle with a certain velocity flying through the problem space. The Particle Swarms find optimal regions of the complex search space through the interaction of individuals in the population. PSO is attractive for feature selection in that particle swarms will discover best feature combinations as they fly within the subset space. Compared with GAs, PSO does not need complex operators such as crossover and mutation, it requires only primitive and simple mathematical operators, and is computationally inexpensive in terms of both memory and runtime. Experimentation is carried out, using UCI data, which compares the proposed algorithm with a GA-based approach and other deterministic rough set reduction algorithms. The results show that PSO is efficient for rough set-based feature selection.

Intervertebral disc degeneration (IDD) is a complicated process that involves both cellular apoptosis and senescence. Metformin has been reported to stimulate autophagy, whereas autophagy is shown to protect against apoptosis and senescence. Therefore, we hypothesize that metformin may have therapeutic effect on IDD through autophagy stimulation. The effect of metformin on IDD was investigated both in vitro and in vivo. Our study showed that metformin attenuated cellular apoptosis and senescence induced by tert-butyl hydroperoxide in nucleus pulposus cells. Autophagy, as well as its upstream regulator AMPK, was activated by metformin in nucleus pulposus cells in a dose- and time-dependent manner. Inhibition of autophagy by 3-MA partially abolished the protective effect of metformin against nucleus pulposus cells' apoptosis and senescence, indicating that autophagy was involved in the protective effect of metformin on IDD. In addition, metformin was shown to promote the expression of anabolic genes such as Col2a1 and Acan expression while inhibiting the expression of catabolic genes such as Mmp3 and Adamts5 in nucleus pulposus cells. In vivo study illustrated that metformin treatment could ameliorate IDD in a puncture-induced rat model. Thus, our study showed that metformin could protect nucleus pulposus cells against apoptosis and senescence via autophagy stimulation and ameliorate disc degeneration in vivo, revealing its potential to be a therapeutic agent for IDD.

Cancer cells undergo metabolic reprogramming such as enhanced aerobic glycolysis, mutations in the tricarboxylic acid cycle enzymes, and upregulation of de novo lipid synthesis and glutaminolysis. These alterations are pivotal to the development and maintenance of the malignant phenotype of cancer cells in unfavorable tumor microenvironment or metastatic sites. Although mitochondrial fatty acid β-oxidation (FAO) is a primary bioenergetic source, it has not been generally recognized as part of the metabolic landscape of cancer. The last few years, however, have seen a dramatic change in the view of cancer relevance of the FAO pathway. Many recent studies have provided significant evidence to support a "lipolytic phenotype" of cancer. FAO, like other well-defined metabolic pathways involved in cancer, is dysregulated in diverse human malignancies. Cancer cells rely on FAO for proliferation, survival, stemness, drug resistance, and metastatic progression. FAO is also reprogrammed in cancer-associated immune and other host cells, which may contribute to immune suppression and tumor-promoting microenvironment. This article reviews and puts into context our current understanding of multi-faceted roles of FAO in oncogenesis as well as anti-cancer therapeutic opportunities posed by the FAO pathway.

Therapeutic vaccines represent a viable option for active immunotherapy of cancers that aim to treat late stage disease by using a patient's own immune system. The promising results from clinical trials recently led to the approval of the first therapeutic cancer vaccine by the U.S. Food and Drug Administration. This major breakthrough not only provides a new treatment modality for cancer management, but also paves the way for rationally designing and optimizing future vaccines with improved anticancer efficacy. Numerous vaccine strategies are currently being evaluated both pre-clinically and clinically. This review discusses therapeutic cancer vaccines of diverse platforms or targets as well as the preclinical and clinical studies employing these therapeutic vaccines. We will also consider tumor-induced immune suppression that hinders the potency of therapeutic vaccines, and potential strategies to counteract these mechanisms for generating more robust and durable antitumor immune responses.