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Introgression allows polyploid species to acquire new genomic content from diploid progenitors or from other unrelated diploid or polyploid lineages, contributing to genetic diversity and facilitating adaptive allele discovery. In some cases, high levels of introgression elicit the replacement of large numbers of alleles inherited from the polyploid’s ancestral species, profoundly reshaping the polyploid’s genomic composition. In such complex polyploids, it is often difficult to determine which taxa were the progenitor species and which taxa provided additional introgressive blocks through subsequent hybridization. Here, we use population-level genomic data to reconstruct the phylogenetic history of Betula pubescens (downy birch), a tetraploid species often assumed to be of allopolyploid origin and which is known to hybridize with at least four other birch species. This was achieved by modeling polyploidization and introgression events under the multispecies coalescent and then using an approximate Bayesian computation rejection algorithm to evaluate and compare competing polyploidization models. We provide evidence that B. pubescens is the outcome of an autoploid genome doubling event in the common ancestor of B. pendula and its extant sister species, B. platyphylla, that took place approximately 178,000–188,000 generations ago. Extensive hybridization with B. pendula, B. nana, and B. humilisfollowed in the aftermath of autopolyploidization, with the relative contribution of each of these species to the B. pubescens genome varying markedly across the species’ range. Functional analysis of B. pubescens loci containing alleles introgressed from B. nana identified multiple genes involved in climate adaptation, while loci containing alleles derived from B. humilis revealed several genes involved in the regulation of meiotic stability and pollen viability in plant species.

OBJECTIVES: Most type 2 diabetes simulation models utilise equations mapping out lifetime trajectories of risk factors [e.g. glycated haemoglobin (HbA1c)]. Existing equations, using historic data or assuming constant risk factors, frequently underestimate or overestimate complication rates. Updated risk factor time path equations are needed for simulation models to more accurately predict complication rates. AIMS: (1) Update United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2) risk factor time path equations; (2) compare quality-adjusted life-years (QALYs) using original and updated equations; and (3) compare QALY gains for reference case simulations using different risk factor equations. METHODS: Using pooled contemporary data from two randomised trials EXSCEL and TECOS (n = 28,608), we estimated: dynamic panel models of seven continuous risk factors (high-density lipoprotein cholesterol, low density lipoprotein cholesterol, HbA1c, haemoglobin, heart rate, blood pressure and body mass index); two-step models of estimated glomerular filtration rate; and survival analyses of peripheral arterial disease, atrial fibrillation and albuminuria. UKPDS-OM2-derived lifetime QALYs were extrapolated over 70 years using historical and the new risk factor equations. RESULTS: All new risk factor equation predictions were within 95% confidence intervals of observed values, displaying good agreement between observed and estimated values. Historical risk factor time path equations predicted trial participants would accrue 9.84 QALYs, increasing to 10.98 QALYs using contemporary equations. DISCUSSION: Incorporating updated risk factor time path equations into diabetes simulation models could give more accurate predictions of long-term health, costs, QALYs and cost-effectiveness estimates, as well as a more precise understanding of the impact of diabetes on patients' health, expenditure and quality of life. TRIAL REGISTRATION: ClinicalTrials.gov NCT01144338 and NCT0079

OBJECTIVES: The Mount Hood Diabetes Challenge Network aimed to examine the impact of model structural uncertainty on the estimated cost-effectiveness of interventions for type 2 diabetes. METHODS: Ten independent modeling groups completed a blinded simulation exercise to estimate the cost-effectiveness of 3 interventions in 2 type 2 diabetes populations. Modeling groups were provided with a common baseline population, cost and utility values associated with different model health states, and instructions regarding time horizon and discounting. We collated the results to identify variation in predictions of net monetary benefit (NMB) and the drivers of those differences. RESULTS: Overall, modeling groups agreed which interventions had a positive NMB (ie, were cost-effective), Although estimates of NMB varied substantially-by up to £23 696 for 1 intervention. Variation was mainly driven through differences in risk equations for complications of diabetes and their implementation between models. The number of modeled health states was also a significant predictor of NMB. CONCLUSIONS: This exercise demonstrates that structural uncertainty between different health economic models affects cost-effectiveness estimates. Although it is reassuring that a decision maker would likely reach similar conclusions on which interventions were cost-effective using most models, the range in numerical estimates generated across different models would nevertheless be important for price-setting negotiations with intervention developers. Minimizing the impact of structural uncertainty on healthcare decision making therefore remains an important priority. Model registries, which record and compare the impact of structural assumptions, offer one potential avenue to improve confidence in the robustness of health economic modeling.

Este foco fue preparado durante la conmemoración de los 50 años del golpe civil militar en Chile, momento de gran reflexión y, lamentablemente, pocos consensos respecto a la memoria histórica. Ante lo cual, estas seis funciones están pensadas en resarcir las trizas de una memoria que mediante películas —como suturas— nos ayudan a comprender las tristezas, las violencias y las ausencias provocadas por el plan sistemático a nivel regional de desestabilización e intervención de los gobiernos izquierdistas democráticamente electos.

This paper presents results on the protective properties of different coatings over metals representative of those found in scientific and technical heritage collections. An examination of several objects in the collection of the Spanish National Museum of Science and Technology have allowed the identification of brass and steel as the most representative metals, and the existence of coatings (mainly shellac and acrylic resins) applied for aesthetic and/or conservation purposes. Based on these findings, brass and steel coupons coated with Paraloid B-44, B-48, B-67, B-72, Incralac, Cosmolloid H80, B-72 + H80 double layer and shellac have been studied to carry out a first screening in order to select the most promising candidates and determine the most appropriate methodology and key factors for the study. Coatings have been aged up to 336 h using cycles of UV light and water condensation. The change in the aspect of the coupons has been assessed via visual examination, optical microscopy and colorimetric measurements, with B-44 and Incralac showing the least change. EIS has been used for a quantitative evaluation of the protective properties and FTIR to measure chemical changes experienced by some coatings, such as B-48 and B-67. These evaluations allowed us to follow, understand and compare the behaviour of the different coatings and substrates after artificial ageing.