Bone marrow mesenchymal stem/stromal cells (BMSCs), which are known as multipotent cells, are widely used in the treatment of various diseases via their self-renewable, differentiation, and immunomodulatory properties. In-vitro and in-vivo studies have supported the understanding mechanisms, safety, and efficacy of BMSCs therapy in clinical applications. The number of clinical trials in phase I/II is accelerating; however, they are limited in the size of subjects, regulations, and standards for the preparation and transportation and administration of BMSCs, leading to inconsistency in the input and outcome of the therapy. Based on the International Society for Cellular Therapy guidelines, the characterization, isolation, cultivation, differentiation, and applications can be optimized and standardized, which are compliant with good manufacturing practice requirements to produce clinical-grade preparation of BMSCs. This review highlights and updates on the progress of production, as well as provides further challenges in the studies of BMSCs, for the approval of BMSCs widely in clinical application.

Overweight and obesity (OW and OB) have been on the increase globally and posed health risks to the world's population of all ages, including pre-born babies, children, adolescents, adults and elderly people, via their comorbid conditions. Excellent examples of comorbidities associated with obesity include cancer, cardiovascular diseases (CVD) and type 2 diabetes mellitus (T2DM). In this article, we aimed to review and update scientific evidence regarding the relationships between obesity and its common physical health consequences, including CVD, T2DM, hypertension, ischemic stroke, cancer, dyslipidemia and reproductive disorders. In addition, the economic burden of OW and OB will be discussed. Abundant evidence is found to support the associations between obesity and other diseases. In general, the odd ratios, risk ratios or hazard ratios are often higher in OW and OB people than in the normal-weight ones. However, the molecular mechanism of how OW and OB induce the development of other diseases has not been fully understood. Figures also showed that obesity and its-related disorders exert enormous pressure on the economy which is projected to increase. This review highlights the fact that obesity can lead to numerous lethal health problems; therefore, it requires a lot of economic resources to fight against this epidemic.

Adipose tissue stem cells (ASCs), known as multipotent stem cells, are most commonly used in the clinical applications in recent years. Adipose tissues (AT) have the advantage in the harvesting, isolation, and expansion of ASCs, especially an abundant amount of stem cells compared to bone marrow. ASCs can be found in stromal vascular fractions (SVF) which are easily obtained from the dissociation of adipose tissue. Both SVFs and culture-expanded ASCs exhibit the stem cell characteristics such as differentiation into multiple cell types, regeneration, and immune regulators. Therefore, SVFs and ASCs have been researched to evaluate the safety and benefits for human use. In fact, the number of clinical trials on ASCs is going to increase by years; however, most trials are in phase I and II, and lack phase III and IV. This systemic review highlights and updates the process of the harvesting, characteristics, isolation, culture, storage, and application of ASCs, as well as provides further directions on the therapeutic use of ASCs.

Obesity is a global pandemic and it is well evident that obesity is associated with the development of many disorders including many cancer types. Breast cancer is one of that associated with a high mortality rate. Adipocytes, a major cellular component in adipose tissue, are dysfunctional during obesity and also known to promote breast cancer development both in vitro and in vivo. Dysfunctional adipocytes can release metabolic substrates, adipokines, and cytokines, which promote proliferation, progression, invasion, and migration of breast cancer cells. The secretion of adipocytes can alter gene expression profile, induce inflammation and hypoxia, as well as inhibit apoptosis. It is known that excessive free fatty acids, cholesterol, triglycerides, hormones, leptin, interleukins, and chemokines upregulate breast cancer development. Interestingly, adiponectin is the only adipokine that has anti-tumor properties. Moreover, adipocytes are also related to chemotherapeutic resistance, resulting in the poorer outcome of treatment and advanced stages in breast cancer. Evaluation of the adipocyte secretion levels in the circulation can be useful for prognosis and evaluation of the effectiveness of cancer therapy in the patients. Therefore, understanding about functions of adipocytes as well as obesity in breast cancer may reveal novel targets that support the development of new anti-tumor therapy. In this systemic review, we summarize and update the effects of secreted factors by adipocytes on the regulation of breast cancer in the tumor microenvironment.

Smoking-induced noncommunicable diseases (SiNCDs) have become a significant threat to public health and cause of death globally. In the last decade, numerous studies have been proposed using artificial intelligence techniques to predict the risk of developing SiNCDs. However, determining the most significant features and developing interpretable models are rather challenging in such systems. In this study, we propose an efficient extreme gradient boosting (XGBoost) based framework incorporated with the hybrid feature selection (HFS) method for SiNCDs prediction among the general population in South Korea and the United States. Initially, HFS is performed in three stages: (I) significant features are selected by t-test and chi-square test; (II) multicollinearity analysis serves to obtain dissimilar features; (III) final selection of best representative features is done based on least absolute shrinkage and selection operator (LASSO). Then, selected features are fed into the XGBoost predictive model. The experimental results show that our proposed model outperforms several existing baseline models. In addition, the proposed model also provides important features in order to enhance the interpretability of the SiNCDs prediction model. Consequently, the XGBoost based framework is expected to contribute for early diagnosis and prevention of the SiNCDs in public health concerns.