Determination of ploidy among yam (Dioscorea spp.) landraces in Kenya by flow cytometry

Yam (Dioscorea spp.), a traditional crop in Kenya has not undergone improvement and little has been done to understand its genetic background. The taxonomy and phylogeny of the local landraces has not been fully studied. The main cultivated species is Dioscorea minutiflora Engl. Others found with low distribution are Dioscorea alata L., Dioscorea bulbifera L. and Dioscorea odoratissima Pax. Flow cytometry was used to estimate the ploidy level of 155 accessions of Kenyan yam including two checks, TDr.18544 a tetraploid and TDc.98136 an octoploid from International Institute of Tropical Agriculture (IITA), Nigeria. Also included in the study were Dioscorea dumetorum Pax, Dioscorea asteriscus Burkill and Dioscorea schimperiana Kunth which are yam wild relatives. Leaf samples were harvested from the field genebank and nuclei extracted using an extraction buffer (Partec GmbH, Munster Germany). Plant nuclei were isolated and stained with propidium iodide then analyzed in a flow cytometer. Seven ploidy levels of 3x (11.4%), 4x(37.5%), 5x(29.2%), 6x(14.6), 7x(3.1%); 8x(3.1%) and 10x(0.6%) were observed. Tetraploids (4x) formed the highest proportion followed by pentaploids (5x). The highest ploidy, decaploid, (10x), was found in D. odoratissima Pax, a conspecific form of Dioscorea preahensilis found under cultivation in two farms in Western Kenya. No diploids were observed in the study. Ploidy level was not associated with geographical habitat of the landraces while farmer-named varieties were not associated with ploidy levels. The findings generated new knowledge and form a basis for future yam research and improvement in the country. Further work is required to establish the phylogeny of Kenyan yam landrace

PrEP and HIV prevention decision-making among social network members of women who have experienced incarceration: a qualitative study

Incarceration and HIV are a syndemic for US women, yet very few women who have experienced incarceration use pre-exposure prophylaxis (PrEP) for HIV. We conducted semi-structured interviews with 32 participants recruited by women who have experienced incarceration from their social networks, informed by the modified social ecological model for PrEP. Emergent themes from the interviews included individual-level (low personal HIV risk assessment, personal responsibility for HIV prevention, and decisions in addiction versus recovery), network-level (influential sex partners and the importance of trust, supportive treatment peers, and high-risk but indifferent drug use networks), community-level (stigma, and mitigation of stigma in supportive substance use disorder treatment environments), and public policy-level (incarceration and PrEP cost and access) determinants. PrEP interventions for women who have experienced incarceration and their networks will need to incorporate contingency planning into HIV risk assessment, navigate complex network dynamics, and be situated in trusted contexts to address structural barriers

Frequency dependence of Delta_nu of solar-like oscillators investigated: Influence of HeII ionization zone

Oscillations in solar-like oscillators tend to follow an approximately regular pattern in which oscillation modes of a certain degree and consecutive order appear at regular intervals in frequency, i.e. the so-called large frequency separation. This is true to first order approximation for acoustic modes. However, to a second order approximation it is evident that the large frequency separation changes as a function of frequency. This frequency dependence has been seen in the Sun and in other main-sequence stars. However, from observations of giant stars, this effect seemed to be less pronounced. We investigate the difference in frequency dependence of the large frequency separation between main-sequence and giant stars using YREC evolutionary models.Comment: 4 pages, 1 figure, to appear in Astrophysics and Space Science Proceedings series of the 20th Stellar pulsation conference held in Granada (Spain) from 6 to 10 September 201

Stellar evolution and modelling stars

In this chapter I give an overall description of the structure and evolution of stars of different masses, and review the main ingredients included in state-of-the-art calculations aiming at reproducing observational features. I give particular emphasis to processes where large uncertainties still exist as they have strong impact on stellar properties derived from large compilations of tracks and isochrones, and are therefore of fundamental importance in many fields of astrophysics.Comment: Lecture presented at the IVth Azores International Advanced School in Space Sciences on "Asteroseismology and Exoplanets: Listening to the Stars and Searching for New Worlds" (arXiv:1709.00645), which took place in Horta, Azores Islands, Portugal in July 201

ASTEC -- the Aarhus STellar Evolution Code

The Aarhus code is the result of a long development, starting in 1974, and still ongoing. A novel feature is the integration of the computation of adiabatic oscillations for specified models as part of the code. It offers substantial flexibility in terms of microphysics and has been carefully tested for the computation of solar models. However, considerable development is still required in the treatment of nuclear reactions, diffusion and convective mixing.Comment: Astrophys. Space Sci, in the pres

Recent Advances in Modeling Stellar Interiors

Advances in stellar interior modeling are being driven by new data from large-scale surveys and high-precision photometric and spectroscopic observations. Here we focus on single stars in normal evolutionary phases; we will not discuss the many advances in modeling star formation, interacting binaries, supernovae, or neutron stars. We review briefly: 1) updates to input physics of stellar models; 2) progress in two and three-dimensional evolution and hydrodynamic models; 3) insights from oscillation data used to infer stellar interior structure and validate model predictions (asteroseismology). We close by highlighting a few outstanding problems, e.g., the driving mechanisms for hybrid gamma Dor/delta Sct star pulsations, the cause of giant eruptions seen in luminous blue variables such as eta Car and P Cyg, and the solar abundance problem.Comment: Proceedings for invited talk at conference High Energy Density Laboratory Astrophysics 2010, Caltech, March 2010, submitted for special issue of Astrophysics and Space Science; 7 pages; 5 figure

Apolipoprotein E epsilon 4 (APOE-ε4) genotype is associated with decreased 6-month verbal memory performance after mild traumatic brain injury

Introduction: The apolipoprotein E (APOE) ε4 allele associates with memory impairment in neurodegenerative diseases. Its association with memory after mild traumatic brain injury (mTBI) is unclear. Methods: mTBI patients (Glasgow Coma Scale score 13–15, no neurosurgical intervention, extracranial Abbreviated Injury Scale score ≤1) aged ≥18 years with APOE genotyping results were extracted from the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study. Cohorts determined by APOE-ε4(+/−) were assessed for associations with 6-month verbal memory, measured by California Verbal Learning Test, Second Edition (CVLT-II) subscales: Immediate Recall Trials 1–5 (IRT), Short-Delay Free Recall (SDFR), Short-Delay Cued Recall (SDCR), Long-Delay F

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types