Geometry of the sample frequency spectrum and the perils of demographic inference

The sample frequency spectrum (SFS), which describes the distribution of mutant alleles in a sample of DNA sequences, is a widely used summary statistic in population genetics. The expected SFS has a strong dependence on the historical population demography and this property is exploited by popular statistical methods to infer complex demographic histories from DNA sequence data. Most, if not all, of these inference methods exhibit pathological behavior, however. Specifically, they often display runaway behavior in optimization, where the inferred population sizes and epoch durations can degenerate to 0 or diverge to infinity, and show undesirable sensitivity of the inferred demography to perturbations in the data. The goal of this paper is to provide theoretical insights into why such problems arise. To this end, we characterize the geometry of the expected SFS for piecewise-constant demographic histories and use our results to show that the aforementioned pathological behavior of popular inference methods is intrinsic to the geometry of the expected SFS. We provide explicit descriptions and visualizations for a toy model with sample size 4, and generalize our intuition to arbitrary sample sizes n using tools from convex and algebraic geometry. We also develop a universal characterization result which shows that the expected SFS of a sample of size n under an arbitrary population history can be recapitulated by a piecewise-constant demography with only k(n) epochs, where k(n) is between n/2 and 2n-1. The set of expected SFS for piecewise-constant demographies with fewer than k(n) epochs is open and non-convex, which causes the above phenomena for inference from data.Comment: 21 pages, 5 figure

Evaluation of four different strategies to characterize plasma membrane proteins from banana roots

Plasma membrane proteins constitute a very important class of proteins. They are involved in the transmission of external signals to the interior of the cell and selective transport of water, nutrients and ions across the plasma membrane. However, the study of plasma membrane proteins is challenging because of their poor solubility in aqueous media and low relative abundance. In this work, we evaluated four different strategies for the characterization of plasma membrane proteins from banana roots: (i) the aqueous-polymer two-phase system technique (ATPS) coupled to gelelectrophoresis (gel-based), and (ii) ATPS coupled to LC-MS/MS (gel free), (iii) a microsomal fraction and (iv) a full proteome, both coupled to LC-MS/ MS. Our results show that the gel-based strategy is useful for protein visualization but has major limitations in terms of time reproducibility and efficiency. From the gel-free strategies, the microsomal-based strategy allowed the highest number of plasma membrane proteins to be identified, followed by the full proteome strategy and by the ATPS based strategy. The high yield of plasma membrane proteins provided by the microsomal fraction can be explained by the enrichment of membrane proteins in this fraction and the high throughput of the gel-free approach combined with the usage of a fast high-resolution mass spectrometer for the identification of proteins

Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses

The purpose of this study was to examine the relationships between movement behaviours (sleep duration, sedentary time, physical activity) and health indicators in a representative sample of children and youth using compositional analyses. Cross-sectional findings are based on 4169 children and youth (aged 6–17 years) from cycles 1 to 3 of the Canadian Health Measures Survey. Sedentary time (SB), light-intensity physical activity (LPA), and moderate- to vigorous-intensity physical activity (MVPA) were accelerometer-derived. Sleep duration was subjectively measured. Body mass index z scores, waist circumference, blood pressure, behavioural strengths and difficulties, and aerobic fitness were measured in the full sample. Triglycerides, high-density lipoprotein-cholesterol, C-reactive protein, and insulin were measured in a fasting subsample. The composition of movement behaviours was entered into linear regression models via an isometric log ratio transformation and was found to be associated with all health indicators (p &lt; 0.01). Relative to other movement behaviours, time spent in SB or LPA was positively associated (p &lt; 0.04) and time spent in MVPA or sleep was negatively associated (p &lt; 0.02) with obesity risk markers. Similarly, LPA was positively associated (p &lt; 0.005) and sleep was negatively associated (p &lt; 0.03) with unfavourable behavioural strengths and difficulties scores and systolic blood pressure. Relative to other movement behaviours, time spent in SB was negatively associated (p &lt; 0.001) and time spent in MVPA (p &lt; 0.001) was positively associated with aerobic fitness. Likewise, MVPA was also negatively associated with several cardiometabolic risk markers (p &lt; 0.008). Compositional data analyses provide novel insights into collective health implications of 24-h movement behaviours and can facilitate interesting avenues for future investigations. </jats:p

Compositional analyses of the associations between sedentary time, different intensities of physical activity, and cardiometabolic biomarkers among children and youth from the United States

Introduction : Compositional data analysis is one appropriate method for co-dependent data, even when data are collected for a subdivision of the 24-hour period, such as the waking day. Objectives were to use compositional analyses to examine the combined and relative associations of sedentary time (ST), light-intensity physical activity (LPA), moderate-intensity physical activity (MPA), and vigorous-intensity physical activity (VPA) with cardiometabolic biomarkers in a representative sample of children and youth. Methods : This cross-sectional study included 2544 participants aged 6-17 years from the 2003-2006 United States National Health and Nutrition Examination Survey. ST (= 7 METs) were accelerometer-derived. Cardiometabolic biomarkers included waist circumference, body mass index (BMI) z-score, HDL-cholesterol, C-reactive protein, and blood pressure. Triglycerides, glucose, insulin, and LDL-cholesterol were measured in a fasting sub-sample of adolescents (n = 670). Compositional linear regression models were conducted. Results : The composition of ST, LPA, MPA, and VPA was significantly associated with BMI z-score, log waist circumference, systolic and diastolic blood pressure, HDL-cholesterol, and log plasma glucose (variance explained: 1-29%). Relative to the other three behaviors, VPA was negatively associated with BMI z-score (gamma VPA = -0.206, p = 0.005) and waist circumference (gamma VPA = -0.03, p = 0.001). Conversely, ST was positively associated with waist circumference (gamma ST = 0.029, p = 0.013). ST and VPA were also positively associated with diastolic blood pressure (gamma ST = 2.700, p = 0.018; gamma VPA = 1.246, p = 0.038), relative to the other behaviors, whereas negative associations were observed for LPA (gamma LPA = -2.892, p = 0.026). Finally, VPA was positively associated with HDL-cholesterol, relative to other behaviors (gamma VPA = 0.058, p<0.001). Conclusions : The ST and physical activity composition appears important for many aspects of cardiometabolic health in children and youth. Compositions with more time in higher-intensity activities may be better for some aspects of cardiometabolic health

Thermometry and signatures of strong correlations from Raman spectroscopy of fermionic atoms in optical lattices

We propose a method to directly measure the temperature of a gas of weakly interacting fermionic atoms loaded into an optical lattice. This technique relies on Raman spectroscopy and is applicable to experimentally relevant temperature regimes. Additionally, we show that a similar spectroscopy scheme can be used to obtain information on the quasiparticle properties and Hubbard bands of the metallic and Mott-insulating states of interacting fermionic spin mixtures. These two methods provide experimentalists with novel probes to accurately characterize fermionic quantum gases confined to optical lattices.Comment: 13 pages, 22 figure

A stable, single-photon emitter in a thin organic crystal for application to quantum-photonic devices

Single organic molecules offer great promise as bright, reliable sources of identical single photons on demand, capable of integration into solid-state devices. It has been proposed that such molecules in a crystalline organic matrix might be placed close to an optical waveguide for this purpose, but so far there have been no demonstrations of sufficiently thin crystals, with a controlled concentration of suitable dopant molecules. Here we present a method for growing very thin anthracene crystals from super-saturated vapour, which produces crystals of extreme flatness and controlled thickness. We show how this crystal can be doped with a widely adjustable concentration of dibenzoterrylene (DBT) molecules and we examine the optical properties of these molecules to demonstrate their suitability as quantum emitters in nanophotonic devices. Our measurements show that the molecules are available in the crystal as single quantum emitters, with a well-defined polarisation relative to the crystal axes, making them amenable to alignment with optical nanostructures. We find that the radiative lifetime and saturation intensity vary little within the crystal and are not in any way compromised by the unusual matrix environment. We show that a large fraction of these emitters are able to deliver more than $10^{12}$ photons without photo-bleaching, making them suitable for real applications.Comment: 12 pages, 10 figures, comments welcom

Supporting Treatment Adherence Readiness through Training (START) for patients with HIV on antiretroviral therapy: study protocol for a randomized controlled trial.

BackgroundFew HIV antiretroviral adherence interventions target patients before they start treatment, assess adherence readiness to determine the timing of treatment initiation, or tailor the amount of adherence support. The Supporting Treatment Adherence Readiness through Training (START) intervention, based on the information-motivation-behavioral skills model of behavior change, is designed to address these gaps with the inclusion of (1) brief pill-taking practice trials for enhancing pretreatment adherence counseling and providing a behavioral criterion for determining adherence readiness and the timing of treatment initiation and (2) a performance-driven dose regulation mechanism to tailor the amount of counseling to the individual needs of the patient and conserve resources. The primary aim of this randomized controlled trial is to examine the effects of START on antiretroviral adherence and HIV virologic suppression.Methods/designA sample of 240 patients will be randomized to receive START or usual care at one of two HIV clinics. Primary outcomes will be optimal dose-taking adherence (&gt;85 % prescribed doses taken), as measured with electronic monitoring caps, and undetectable HIV viral load. Secondary outcomes will include dose-timing adherence (&gt;85 % prescribed doses taken on time) and CD4 count. Primary endpoints will be month 6 (short-term effect) and month 24 (to test durability of effect), though electronic monitoring will be continuous and a fully battery of assessments will be administered every 6 months for 24 months.DiscussionIf efficacious and cost-effective, START will provide clinicians with a model for assessing patient adherence readiness and helping patients to achieve and sustain readiness and optimal treatment benefits.Trial registrationClinicalTrials.gov identifier NCT02329782 . Registered on 22 December 2014