Multiple primary lung cancer (MPLC) refers to the simultaneous occurrence of two or more lung primary malignant tumors in one individual. The detection rate of MPLC has increased significantly in recent years, and the distinction between MPLC and lung metastasis has strong clinical significance. Whole exome sequencing (WES) can clearly identify the heterogeneity between MPLC nodules.  https://www.selleckchem.com/products/tph104m.html  Here, we report a case of a 50-year-old Asian female without a history of smoking. She underwent a lung computed tomography (CT) scan and three ground-glass nodules (GGNs) were found which were pathologically confirmed as atypical adenomatous hyperplasia (AAH), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA), respectively. We performed WES on the three pulmonary nodules and analyzed the sequencing results. We believe that this is the first published report of a case of "three phases" of lung adenocarcinoma analyzed by WES. Under the same genetic background and internal environment, these three nodules showed significant genetic differences and developed into "three phases" of lung adenocarcinoma. Analysis of the WES results supported the lung adenocarcinoma model from AAH to MIA and IA, and explored possible potential driver genes and therapeutic targets. KEY POINTS SIGNIFICANT FINDINGS OF THE STUDY We used WES to analyze the gene mutation status of three tumors in one individual. We found that even if under the same genetic background, AAH, MIA and IA showed significant genetic differences and developed into "three phases" of lung adenocarcinoma. WHAT THIS STUDY ADDS Analysis of the WES results supported the lung adenocarcinoma model from AAH to MIA and IA, and explored possible potential driver genes and therapeutic targets.Genome-wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome-wide genetic variants across diverse genetic materials. The development of the mixed model framework for GWAS dramatically reduced the number of false positives compared with naïve methods. Building on this foundation, many methods have since been developed to increase computational speed or improve statistical power in GWAS. These methods have allowed the detection of genomic variants associated with either traditional agronomic phenotypes or biochemical and molecular phenotypes. In turn, these associations enable applications in gene cloning and in accelerated crop breeding through marker assisted selection or genetic engineering. Current topics of investigation include rare-variant analysis, synthetic associations, optimizing the choice of GWAS model, and utilizing GWAS results to advance knowledge of biological processes. Ongoing research in these areas will facilitate further advances in GWAS methods and their applications.Understanding the social and environmental influencers of eating behaviours has the potential to improve health outcomes for young people. This review aims to explore the effectiveness of school nutrition interventions and the perceptions of young people experiencing a nutrition focused intervention or change in school food policy. A comprehensive systematic search identified studies published between 1 December 2007 to 20 February 2020. Twenty-seven studies were included 22 quantitative studies of nutrition related outcomes and five qualitative studies reporting views and perceptions of young people (combined sample of 22,138 participants, mean ages 12-18 years). The primary outcome was nutrition knowledge/dietary behaviours, with secondary outcomes exploring body mass index (BMI) and wellbeing. Due to the heterogeneity of studies, a narrative results description is presented. The findings demonstrate that school nutrition programmes can be effective in reducing sugar, sugar sweetened beverages (SSB) and saturated fat and increasing fruit and vegetable (FV) intake. The lived experiences of young people in a school context provide valuable insights that should be considered in the development of effective school food policy and interventions. This review affirms the significant role that schools can play in supporting good nutrition in all young people and provides opportunities to inform the school food agenda.Skeletal muscle possesses dramatic metabolic plasticity that allows for the rapid adaptation in cellular energy transduction to meet the demands of the organism. Obesity elicits changes in skeletal muscle structure and function, resulting in the accumulation of intramuscular lipids. The accumulation of intramuscular lipids in obesity is associated with impaired skeletal muscle mitochondrial content and function. Mitochondria exist as a dynamic network that is regulated by the processes of biogenesis, fusion, fission, and mitophagy. In this review, we outline adaptations in molecular pathways that regulate mitochondrial structure and function in obesity. We highlight the emerging role of dysregulated skeletal muscle macroautophagy and mitochondrial turnover in obesity. Future research should further elucidate the role of mitophagy in observed reductions in mitochondrial content and function during obesity.Protein-RNA interactions play essential roles in a wide variety of biological processes. Recognition of RNA-binding residues on proteins has been a challenging problem. Most of methods utilize the position-specific scoring matrix (PSSM). It has been found that considering the evolutionary information of sequence neighboring residues can improve the prediction. In this work, we introduce a novel method SNB-PSSM (spatial neighbor-based PSSM) combined with the structure window scheme where the evolutionary information of spatially neighboring residues is considered. The results show our method consistently outperforms the standard and smoothed PSSM methods. Tested on multiple datasets, this approach shows an encouraging performance compared with RNABindRPlus, BindN+, PPRInt, xypan, Predict_RBP, SpaPF, PRNA, and KYG, although is inferior to RNAProSite, RBscore, and aaRNA. In addition, since our method is not sensitive to protein structure changes, it can be applied well on binding site predictions of modeled structures.