The Influence of Menopause and Cardiorespiratory Fitness on Lipoprotein Particles in Midlife Women

Lipoprotein particles may provide better information about cardiovascular risk than standard cholesterol measures for women. Whether lipoprotein subclasses change with menopausal stage is unclear. Given the high prevalence of low cardiorespiratory fitness in midlife women and benefit to cardiovascular risk, it is also important to understand the effect of fitness on lipoprotein profiles. Purpose: To evaluate the influence of menopausal status and fitness on lipoprotein particles in healthy midlife women. Methods: Lipoprotein particles were measured in high-(HIGH,n=25) and low-fit(LOW,n=13) perimenopausal and late postmenopausal women, and in HIGH premenopausal(n=10), perimenopausal(n=12), and late postmenopausal women(n=13). Results: There were larger low-density lipoprotein particles(LDL-P, 21.7±0.06vs.21.3±0.1nm, p=0.002), more large LDL-P(623.1±32.8vs.500.2±52.6nmol/L, p=0.045), and fewer small LDL-P(145.5±31.4vs. 311.5±44.7nmol/L, p=0.001) in HIGH vs. LOW. High-density lipoprotein particles(HDL-P) were larger(10.1±0.1vs.9.7±0.1nm, p=0.002) in HIGH, with more large(14.8±0.7vs.11.0±0.9μmol/L, p=0.002), medium(12.9±0.8vs. 8.4±0.9μmol/L, p=0.002), and fewer small HDL-P(10.2±1.1vs.15.4±1.6μmol/L, p=0.009) compared to LOW. HIGH postmenopausal women had more large LDL-P(662.9±47.5nmol/L) compared to premenopausal women(479.1±52.6nmol/L, p=0.035), and more HDL-P(40.2±1.1μmol/L) compared to premenopausal(34.9±1.5μmol/L, p=0.023) and perimenopausal women(35.4±1.3μmol/L, p=0.033). Conclusion: High fitness positively influences lipoprotein particles in healthy perimenopausal and late postmenopausal women. In healthy fit women, menopause may not have a large influence on lipoprotein particles. Novelty Bullets: • In highly-fit women, menopause may not have a negative influence on lipoprotein particle subclasses. • High fitness is associated with a less atherogenic lipoprotein profile in perimenopausal and late postmenopausal women.

Analysis of the leaf metabolome in Arabidopsis thaliana mutation accumulation lines reveals association of pleiotropy and fitness consequences

Understanding the mechanisms by which mutations affect fitness and the distribution of mutational effects are central goals in evolutionary biology. Mutation accumulation (MA) lines have long been an important tool for understanding the effect of new mutations on fitness, phenotypic variation, and mutational parameters. However, there is a clear gap in predicting the effect of specific new mutations to their effects on fitness. Here, we complete gene ontology analysis and metabolomics experiments on Arabidopsis thaliana MA lines to determine how spontaneous mutations directly affect global metabolic output in lines that have measured fitness consequences. For these analyses, we compared three lines with relative fitness consistently higher than the unmutated progenitor and three lines with lower relative fitness as measured in four different field trials. In a gene ontology analysis, we find that the high fitness lines were significantly enriched in mutations in or near genes with transcription regulator activity. We also find that although they do not have an average difference in the number of mutations, low fitness lines have significantly more metabolic subpathways disrupted than high fitness lines. Taken together, these results suggest that the effect of a new mutation on fitness depends less on the specific metabolic pathways disrupted and more on the pleiotropic effects of those mutations, and that organisms can explore a considerable amount of physiological space with only a few mutations.

Vigorous physical activity is important in maintaining a favourable health trajectory in active children: the CHAMPS Study-DK

Physical activity (PA) is critical to improving health factors such as weight, adiposity, and aerobic fitness. However, children who meet PA guideline recommendations demonstrate developmental differences in health-related outcomes. To investigate prospective associations between PA behaviour (overall PA and PA intensity) and trajectories of health-related factors among physically active children. This prospective study (2.5 years) included 391 children (baseline age: 8.1 ± 1.4 years; girls 36.3%) from ten public schools. All children performed 60-min or more of moderate-to-vigorous physical activity (MVPA) per day objectively measured. Trajectories of BMI, waist circumference, and aerobic fitness were constructed with a group-based multi-trajectory model. Three trajectory subgroups were identified: ‘high fitness/normal weight’ (48.4% of children), ‘moderate fitness /normal weight’ (42.5% of children), and ‘low fitness/overweight-obese’ (9.1% of children). Children performing higher overall PA, were less likely of being classified as members of the ‘Low Fitness/Overweight-Obese’ [Relative Risk Ratio (RRR and 95% CI) = 0.56 (0.37 to 0.85) compared to ‘high fitness/normal weight’ subgroup. Each additional 5% in light PA time was associated with approximately twofold [RRR 2.12 (1.24–3.61)] increased risk of being in the ‘low fitness/overweight-obese’ trajectory relative to the ‘high fitness/normal weight’ trajectory. Each additional 2% in vigorous-PA time was associated with a 42% and 85% reduced risk (relative to ‘high fitness/normal weight’) of being in the ‘moderate fitness/normal weight’ [RRR 0.58 (0.38–0.96)] and ‘low fitness/overweight-obesity’ [RRR 0.15 (0.06–0.37)] trajectory, respectively. Overall PA and additional time in vigorous-PA was associated with improved health-related outcomes, while light PA was negatively associated with health-related outcomes among children who adhere to PA guideline recommendations. Vigorous PA was the strongest predictor of the health trajectories. All PA guidelines for children should place greater emphasis on the importance of vigorous PA.

Opposition-based learning Multi-Verse Optimizer with disruption operator for optimization problems

Multi-Verse Optimizer (MVO) algorithm is one of the recent metaheuristic algorithms used to solve various problems in different fields. However, MVO suffers from a lack of diversity which may trapping of local minima, and premature convergence. This paper introduces two steps of improving the basic MVO algorithm. The first step using Opposition-based learning (OBL) in MVO, called OMVO. The OBL aids to speed up the searching and improving the learning technique for selecting a better generation of candidate solutions of basic MVO. The second stage, called OMVOD, combines the disturbance operator (DO) and OMVO to improve the consistency of the chosen solution by providing a chance to solve the given problem with a high fitness value and increase diversity. To test the performance of the proposed models, fifteen CEC 2015 benchmark functions problems, thirty CEC 2017 benchmark functions problems, and seven CEC 2011 real-world problems were used in both phases of the enhancement. The second step, known as OMVOD, incorporates the disruption operator (DO) and OMVO to improve the accuracy of the chosen solution by giving a chance to solve the given problem with a high fitness value while also increasing variety. Fifteen CEC 2015 benchmark functions problems, thirty CEC 2017 benchmark functions problems and seven CEC 2011 real-world problems were used in both phases of the upgrade to assess the accuracy of the proposed models.

Pleiotropy is associated with fitness consequences of new mutations in mutation accumulation lines

Understanding the mechanisms by which mutations affect fitness and the distribution of mutational effects are central goals in evolutionary biology. Mutation accumulation (MA) lines have long been an important tool for understanding the effect of new mutations on fitness, phenotypic variation, and mutational parameters. However, there is a clear gap in predicting the effect of new mutations to their effects on fitness. Here we complete gene ontology analysis and metabolomics experiments on Arabidopsis thaliana MA lines to determine how spontaneous mutations affect global metabolic output in lines that have measured fitness consequences. For these analyses, we compared three lines with relative fitness consistently higher than the unmutated progenitor and three lines with lower relative fitness. In a gene ontology analysis, we find that the high fitness lines were significantly enriched in mutations in or near genes with transcription regulator activity. We also find that although they do not have an average difference in the number of mutations, low fitness lines have significantly more metabolic subpathways disrupted than high fitness lines. Taken together, these results suggest that the effect of a new mutation on fitness depends less on the specific metabolic pathways disrupted and more on the pleiotropic effects of those mutations and that organisms can explore a considerable amount of physiological space with only a few mutations.

Reversing Antibiotic Resistance Caused by Mobile Resistance Genes of High Fitness Cost

The dissemination of bacterial antibiotic resistance is a serious threat to human health. The development of new antibiotics faces both economic and technological challenges.