Sex enhances adaptation by unlinking beneficial from detrimental mutations in experimental yeast populations

<p>Abstract</p> <p>Background</p> <p>The maintenance of sexuality is a classic problem in evolutionary biology because it is a less efficient mode of reproduction compared with asexuality; however, many organisms are sexual. Theoretical work suggests sex facilitates natural selection, and experimental data support this. However, there are fewer experimental studies that have attempted to determine the mechanisms underlying the advantage of sex. Two main classes of hypotheses have been proposed to explain its advantage: detrimental mutation clearance and beneficial mutation accumulation. Here we attempt to experimentally differentiate between these two classes by evolving <it>Saccharomyces cerevisiae </it>populations that differ only in their ability to undergo sex, and also manipulate mutation rate. We cannot manipulate the types of mutation that occur, but instead propagate populations in both stressful and permissive environments and assume that the extent of detrimental mutation clearance and beneficial mutation incorporation differs between them.</p> <p>Results</p> <p>After 300 mitotic generations interspersed with 11 rounds of sex we found there was no change or difference in fitness between sexuals and asexuals propagated in the permissive environment, regardless of mutation rate. Sex conferred a greater extent of adaptation in the stressful environment, and wild-type and elevated mutation rate sexual populations adapted equivalently. However, the asexual populations with an elevated mutation rate appeared more retarded in their extent of adaptation compared to asexual wild-type populations.</p> <p>Conclusions</p> <p>Sex provided no advantage in the permissive environment where beneficial mutations were rare. We could not evaluate if sex functioned to clear detrimental mutations more effectively or not here as no additional fitness load was observed in the mutator populations. However, in the stressful environment, where detrimental mutations were likely of more consequence, and where beneficial mutations were apparent, sex provided an advantage. In the stressful environment asexuals were increasingly constrained in their extent of adaptation with increasing mutation rate. Sex appeared to facilitate adaptation not just by more rapidly combining beneficial mutations, but also by unlinking beneficial from detrimental mutations: sex allowed selection to operate on both types of mutations more effectively compared to asexual populations.</p

Improvements for Vision-based Navigation of Small, Fixed-wing Unmanned Aerial Vehicles

Investigating alternative navigation approaches for use when GPS signals are unavailable is an active area of research across the globe. In this paper we focus on the navigation of small, fixed-wing unmanned aerial vehicles (UAVs) that employ vision-based approaches combined with other measurements as a replacement for GPS. We demonstrate with flight test data that vehicle attitude information, derived from cheap, MEMS-based IMUs is sufficient to improve two different types of vision processing algorithms. Secondly, we show analytically and with flight test data that range measurements to one other vehicle with global pose is sufficient to constrain the global drift of a visual inertial odometry-based navigation solution. Further, we demonstrate that such ranging information is not needed at a fast rate; that bounding can occur using data as infrequent as 0.01Hz

Real-world evidence was feasible for estimating effectiveness of chemotherapy in breast cancer; a cohort study

Objective: Evidence-based guidelines recommend adjuvant chemotherapy in early stage breast cancer whenever treatment benefit is considered sufficient to outweigh the associated risks. However, many groups of patients were either excluded from or underrepresented in the clinical trials that form the evidence base for this recommendation. This study aims to determine whether using administrative healthcare data – Real World Data (RWD) - and econometric methods for causal analysis to provide ‘Real World Evidence’ (RWE) are feasible methods for addressing this gap.Methods: Cases of primary breast cancer in women from 2001 to 2015 were extracted from the Scottish cancer registry (SMR06) and linked to other routine health records (inpatient and outpatient visits). Four methods were used to estimate the effect of adjuvant chemotherapy on disease-specific and overall mortality: (1) regression with adjustment for covariates (2) propensity score matching (3) instrumental variables analysis and (4) regression discontinuity design. Hazard ratios for breast cancer mortality and all-cause mortality were compared to those from a meta-analysis of randomised trials.Results: 39,805 cases included in the analyses. Regression adjustment, propensity score matching and instrumental variables were feasible while regression discontinuity was not. Effectiveness estimates were similar between RWE and randomised trials for breast cancer mortality but not for all-cause mortality.Conclusions: RWE methods are a feasible means to generate estimates of effectiveness of adjuvant chemotherapy in early stage breast cancer. However, such estimates must be interpreted in the context of the available randomised evidence and the potential biases of the observational methods.<br/

Fluid intelligence and brain functional organization in aging yoga and meditation practitioners

Numerous studies have documented the normal age-related decline of neural structure, function, and cognitive performance. Preliminary evidence suggests that meditation may reduce decline in specific cognitive domains and in brain structure. Here we extended this research by investigating the relation between age and fluid intelligence and resting state brain functional network architecture using graph theory, in middle-aged yoga and meditation practitioners, and matched controls. Fluid intelligence declined slower in yoga practitioners and meditators combined than in controls. Resting state functional networks of yoga practitioners and meditators combined were more integrated and more resilient to damage than those of controls. Furthermore, mindfulness was positively correlated with fluid intelligence, resilience, and global network efficiency. These findings reveal the possibility to increase resilience and to slow the decline of fluid intelligence and brain functional architecture and suggest that mindfulness plays a mechanistic role in this preservation

Independent validation of the PREDICT breast cancer prognosis prediction tool in 45,789 patients using Scottish Cancer Registry data

PREDICT is a widely used online prognostication and treatment benefit tool for patients with early stage breast cancer. The aim of this study was to conduct an independent validation exercise of the most up-to-date version of the PREDICT algorithm (version 2) using real-world outcomes from the Scottish population of women with breast cancer. Patient data were obtained for all Scottish Cancer Registry (SCR) records with a diagnosis of primary invasive breast cancer diagnosed in the period between January 2001 and December 2015. Prognostic scores were calculated using the PREDICT version 2 algorithm. External validity was assessed by statistical analysis of discrimination and calibration. Discrimination was assessed by area under the receiver-operator curve (AUC). Calibration was assessed by comparing the predicted number of deaths to the observed number of deaths across relevant sub-groups. A total of 45,789 eligible cases were selected from 61,437 individual records. AUC statistics ranged from 0.74 to 0.77. Calibration results showed relatively close agreement between predicted and observed deaths. The 5-year complete follow-up sample reported some overestimation (11.5%), while the 10-year complete follow-up sample displayed more limited overestimation (1.7%). Validation results suggest that the PREDICT tool remains essentially relevant for contemporary patients with early stage breast cancer

N-acetylaspartate supports the energetic demands of developmental myelination via oligodendroglial aspartoacylase

Breakdown of neuro-glial N-acetyl-aspartate (NAA) metabolism results in the failure of developmental myelination, manifest in the congenital pediatric leukodystrophy Canavan disease caused by mutations to the sole NAA catabolizing enzyme aspartoacylase. Canavan disease is a major point of focus for efforts to define NAA function, with available evidence suggesting NAA serves as an acetyl donor for fatty acid synthesis during myelination. Elevated NAA is a diagnostic hallmark of Canavan disease, which contrasts with a broad spectrum of alternative neurodegenerative contexts in which levels of NAA are inversely proportional to pathological progression. Recently generated data in the nur7 mouse model of Canavan disease suggests loss of aspartoacylase function results in compromised energetic integrity prior to oligodendrocyte death, abnormalities in myelin content, spongiform degeneration, and motor deficit. The present study utilized a next-generation “oligotropic” adeno-associated virus vector (AAV-Olig001) to quantitatively assess the impact of aspartoacylase reconstitution on developmental myelination. AAV-Olig001-aspartoacylase promoted normalization of NAA, increased bioavailable acetyl-CoA, and restored energetic balance within a window of postnatal development preceding gross histopathology and deteriorating motor function. Long-term effects included increased oligodendrocyte numbers, a global increase in myelination, reversal of vacuolation, and rescue of motor function. Effects on brain energy observed following AAV-Olig001-aspartoacylase gene therapy are shown to be consistent with a metabolic profile observed in mild cases of Canavan disease, implicating NAA in the maintenance of energetic integrity during myelination via oligodendroglial aspartoacylase

The SDSS-III Baryon Oscillation Spectroscopic Survey: Quasar Target Selection for Data Release Nine

The SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS), a five-year spectroscopic survey of 10,000 deg^2, achieved first light in late 2009. One of the key goals of BOSS is to measure the signature of baryon acoustic oscillations in the distribution of Ly-alpha absorption from the spectra of a sample of ~150,000 z>2.2 quasars. Along with measuring the angular diameter distance at z\approx2.5, BOSS will provide the first direct measurement of the expansion rate of the Universe at z > 2. One of the biggest challenges in achieving this goal is an efficient target selection algorithm for quasars over 2.2 < z < 3.5, where their colors overlap those of stars. During the first year of the BOSS survey, quasar target selection methods were developed and tested to meet the requirement of delivering at least 15 quasars deg^-2 in this redshift range, out of 40 targets deg^-2. To achieve these surface densities, the magnitude limit of the quasar targets was set at g <= 22.0 or r<=21.85. While detection of the BAO signature in the Ly-alpha absorption in quasar spectra does not require a uniform target selection, many other astrophysical studies do. We therefore defined a uniformly-selected subsample of 20 targets deg^-2, for which the selection efficiency is just over 50%. This "CORE" subsample will be fixed for Years Two through Five of the survey. In this paper we describe the evolution and implementation of the BOSS quasar target selection algorithms during the first two years of BOSS operations. We analyze the spectra obtained during the first year. 11,263 new z>2.2 quasars were spectroscopically confirmed by BOSS. Our current algorithms select an average of 15 z > 2.2 quasars deg^-2 from 40 targets deg^-2 using single-epoch SDSS imaging. Multi-epoch optical data and data at other wavelengths can further improve the efficiency and completeness of BOSS quasar target selection. [Abridged]Comment: 33 pages, 26 figures, 12 tables and a whole bunch of quasars. Submitted to Ap

Chemotherapy effectiveness in trial-underrepresented groups with early breast cancer:A retrospective cohort study

BACKGROUND: Adjuvant chemotherapy in early stage breast cancer has been shown to reduce mortality in a large meta-analysis of over 100 randomised trials. However, these trials largely excluded patients aged 70 years and over or with higher levels of comorbidity. There is therefore uncertainty about whether the effectiveness of adjuvant chemotherapy generalises to these groups, hindering patient and clinician decision-making. This study utilises administrative healthcare data-real world data (RWD)-and econometric methods for causal analysis to estimate treatment effectiveness in these trial-underrepresented groups. METHODS AND FINDINGS: Women with early breast cancer aged 70 years and over and those under 70 years with a high level of comorbidity were identified and their records extracted from Scottish Cancer Registry (2001-2015) data linked to other routine health records. A high level of comorbidity was defined as scoring 1 or more on the Charlson comorbidity index, being in the top decile of inpatient stays, and/or having 5 or more visits to specific outpatient clinics, all within the 5 years preceding breast cancer diagnosis. Propensity score matching (PSM) and instrumental variable (IV) analysis, previously identified as feasible and valid in this setting, were used in conjunction with Cox regression to estimate hazard ratios for death from breast cancer and death from all causes. The analysis adjusts for age, clinical prognostic factors, and socioeconomic deprivation; the IV method may also adjust for unmeasured confounding factors. Cohorts of 9,653 and 7,965 were identified for women aged 70 years and over and those with high comorbidity, respectively. In the ≥70/high comorbidity cohorts, median follow-up was 5.17/6.53 years and there were 1,935/740 deaths from breast cancer. For women aged 70 years and over, the PSM-estimated HR was 0.73 (95% CI 0.64-0.95), while for women with high comorbidity it was 0.67 (95% CI 0.51-0.86). This translates to a mean predicted benefit in terms of overall survival at 10 years of approximately3% (percentage points) and 4%, respectively. A limitation of this analysis is that use of observational data means uncertainty remains both from sampling uncertainty and from potential bias from residual confounding. CONCLUSIONS: The results of this study, as RWD, should be interpreted with caution and in the context of existing and emerging randomised data. The relative effectiveness of adjuvant chemotherapy in reducing mortality in patients with early stage breast cancer appears to be generalisable to the selected trial-underrepresented groups.</p