Humanistic Health Management and Cancer: Associations of Psychology, Nutrition, and Exercise with Cancer Progression and Pathogenesis.

The incidence rate of cancer is increasing year by year due to the aging of the population, unhealthy living, and eating habits. At present, surgery and medication are still the main treatments for cancer, without paying attention to the impact of individual differences in health management on cancer. However, increasing evidence suggests that individual psychological status, dietary habits, and exercise frequency are closely related to the risk and prognosis of cancer. The reminder to humanity is that the medical concept of the unified treatment plan is insufficient in cancer treatment, and a personalized treatment plan may become a breakthrough point. On this basis, the concept of "Humanistic Health Management" (HHM) is proposed. This concept is a healthcare plan that focuses on self-health management, providing an accurate and comprehensive evaluation of individual lifestyle habits, psychology, and health status, and developing personalized and targeted comprehensive cancer prevention and treatment plans. This review will provide a detailed explanation of the relationship between psychological status, dietary, and exercise habits, and the regulatory mechanisms of cancer. Intended to emphasize the importance of HHM concept in cancer prevention and better prognostic efficacy, providing new ideas for the new generation of cancer treatment.

DNA self-assembly nanoflower reverse P-glycoprotein mediated drug resistance in chronic myelogenous leukemia therapy.

Introduction: Chronic myelogenous leukemia (CML) is a clonal myeloproliferative disorder caused by the BCR-ABL chimeric tyrosine kinase. Vincristine (VCR) is widely used in leukemia therapy but is hindered by multidrug resistance (MDR). Methods: We prepared DNA nanoflower via self-assembly for the delivery of VCR and P-glycoprotein small interfering RNA (P-gp siRNA). Results and Discussion: The as-prepared nanoflower had a floriform shape with high loading efficiency of VCR (80%). Furthermore, the nanoflower could deliver VCR and P-gp siRNA into MDR CML cells and induce potent cytotoxicity both in vitro and in vivo, thus overcoming MDR of CML. Overall, this nanoflower is a promising tool for resistant CML therapy.

Identification of Differentially Expressed Genes in the Longissimus Dorsi Muscle of Luchuan and Duroc Pigs by Transcriptome Sequencing.

The Duroc pig originated in the United States and is a typical lean-meat pig. The breed grows fast, and the body size is large, but the meat quality is poor. The Luchuan pig is one of eight excellent local breeds in China; it has tender meat but is small in size. To study the factors that determine growth, we selected the longissimus dorsi muscle of Luchuan and Duroc pigs for transcriptome sequencing. The results of the transcriptome showed that 3682 genes were differentially expressed (DEGs) in the longissimus dorsi muscle of Duroc and Luchuan pigs. We screened out genes related to muscle development and selected the MYL2 (Myosin light chain-2) gene to perform preliminary research. Gene Ontology (GO) enrichment of biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the gene products were mainly involved in the Akt/FoxO signaling pathway, fatty acid metabolism, arachidonic acid metabolism and glycine, serine and threonine metabolism. Such pathways contributed to skeletal muscle growth, fatty acid metabolism and intramuscular fat deposition. These results provide insight into the mechanisms underlying the formation of skeletal muscle and provide candidate genes to improve growth traits, as well as contribute to improving the growth and development traits of pigs through molecular breeding.

Reconstruction and in silico analysis of metabolic network for an oleaginous yeast, Yarrowia lipolytica.

With the emergence of energy scarcity, the use of renewable energy sources such as biodiesel is becoming increasingly necessary. Recently, many researchers have focused their minds on Yarrowia lipolytica, a model oleaginous yeast, which can be employed to accumulate large amounts of lipids that could be further converted to biodiesel. In order to understand the metabolic characteristics of Y. lipolytica at a systems level and to examine the potential for enhanced lipid production, a genome-scale compartmentalized metabolic network was reconstructed based on a combination of genome annotation and the detailed biochemical knowledge from multiple databases such as KEGG, ENZYME and BIGG. The information about protein and reaction associations of all the organisms in KEGG and Expasy-ENZYME database was arranged into an EXCEL file that can then be regarded as a new useful database to generate other reconstructions. The generated model iYL619_PCP accounts for 619 genes, 843 metabolites and 1,142 reactions including 236 transport reactions, 125 exchange reactions and 13 spontaneous reactions. The in silico model successfully predicted the minimal media and the growing abilities on different substrates. With flux balance analysis, single gene knockouts were also simulated to predict the essential genes and partially essential genes. In addition, flux variability analysis was applied to design new mutant strains that will redirect fluxes through the network and may enhance the production of lipid. This genome-scale metabolic model of Y. lipolytica can facilitate system-level metabolic analysis as well as strain development for improving the production of biodiesels and other valuable products by Y. lipolytica and other closely related oleaginous yeasts.