The multispecies coalescent provides an elegant theoretical framework for estimating species trees and species demographics from genetic markers. However, practical applications of the multispecies coalescent model are limited by the need to integrate or sample over all gene trees possible for each genetic marker. Here we describe a polynomial-time algorithm that computes the likelihood of a species tree directly from the markers under a finite-sites model of mutation effectively integrating over all possible gene trees. The method applies to independent (unlinked) biallelic markers such as well-spaced single nucleotide polymorphisms, and we have implemented it in SNAPP, a Markov chain Monte Carlo sampler for inferring species trees, divergence dates, and population sizes. We report results from simulation experiments and from an analysis of 1997 amplified fragment length polymorphism loci in 69 individuals sampled from six species of Ourisia (New Zealand native foxglove).

“Orangutan” is derived from the Malay term “man of the forest” and aptly describes the Southeast Asian great apes native to Sumatra and Borneo. The orangutan species, Pongo abelii (Sumatran) and Pongo pygmaeus (Bornean), are the most phylogenetically distant great apes from humans, thereby providing an informative perspective on hominid evolution. Here we present a Sumatran orangutan draft genome assembly and short read sequence data from five Sumatran and five Bornean orangutan genomes. Our analyses reveal that, compared to other primates, the orangutan genome has many unique features. Structural evolution of the orangutan genome has proceeded much more slowly than other great apes, evidenced by fewer rearrangements, less segmental duplication, a lower rate of gene family turnover and surprisingly quiescent Alu repeats, which have played a major role in restructuring other primate genomes. We also describe the first primate polymorphic neocentromere, found in both Pongo species, emphasizing the gradual evolution of orangutan genome structure. Orangutans have extremely low energy usage for a eutherian mammal1, far lower than their hominid relatives. Adding their genome to the repertoire of sequenced primates illuminates new signals of positive selection in several pathways including glycolipid metabolism. From the population perspective, both Pongo species are deeply diverse; however, Sumatran individuals possess greater diversity than their Bornean counterparts, and more species-specific variation. Our estimate of Bornean/Sumatran speciation time, 400k years ago (ya), is more recent than most previous studies and underscores the complexity of the orangutan speciation process. Despite a smaller modern census population size, the Sumatran effective population size (Ne) expanded exponentially relative to the ancestral Ne after the split, while Bornean Ne declined over the same period. Overall, the resources and analyses presented here offer new opportunities in evolutionary genomics, insights into hominid biology, and an extensive database of variation for conservation efforts.

Our data show that a reduction in sleep increases energy and fat intakes, which may explain the associations observed between sleep and obesity. If sustained, as observed, and not compensated by increased energy expenditure, the dietary intakes of individuals undergoing short sleep predispose to obesity. This trial is registered at clinicaltrials.gov as NCT00935402.

Trial registration on http://www.clinicaltrials.gov. #NCT00935402.

Background Coronavirus disease 2019 (COVID-19) is a growing pandemic that confers augmented risk for right ventricular (RV) dysfunction and dilation; the prognostic utility of adverse RV remodeling in COVID-19 patients is uncertain. Objectives The purpose of this study was to test whether adverse RV remodeling (dysfunction/dilation) predicts COVID-19 prognosis independent of clinical and biomarker risk stratification. Methods Consecutive COVID-19 inpatients undergoing clinical transthoracic echocardiography at 3 New York City hospitals were studied; images were analyzed by a central core laboratory blinded to clinical and biomarker data. Results In total, 510 patients (age 64 ± 14 years, 66% men) were studied; RV dilation and dysfunction were present in 35% and 15%, respectively. RV dysfunction increased stepwise in relation to RV chamber size (p = 0.007). During inpatient follow-up (median 20 days), 77% of patients had a study-related endpoint (death 32%, discharge 45%). RV dysfunction (hazard ratio [HR]: 2.57; 95% confidence interval [CI]: 1.49 to 4.43; p = 0.001) and dilation (HR: 1.43; 95% CI: 1.05 to 1.96; p = 0.02) each independently conferred mortality risk. Patients without adverse RV remodeling were more likely to survive to hospital discharge (HR: 1.39; 95% CI: 1.01 to 1.90; p = 0.041). RV indices provided additional risk stratification beyond biomarker strata; risk for death was greatest among patients with adverse RV remodeling and positive biomarkers and was lesser among patients with isolated biomarker elevations (p ≤ 0.001). In multivariate analysis, adverse RV remodeling conferred a >2-fold increase in mortality risk, which remained significant (p < 0.01) when controlling for age and biomarker elevations; the predictive value of adverse RV remodeling was similar irrespective of whether analyses were performed using troponin, D-dimer, or ferritin. Conclusions Adverse RV remodeling predicts mortality in COVID-19 independent of standard clinical and biomarker-based assessment.

Few studies have addressed changes in physical activity participation over time among the elderly. The authors hypothesized that there were distinct trajectories of physical activity level over time and identifiable predictors of such trajectories, as well as that the maintenance of regular physical activity, even below recommended levels, was associated with lower mortality risk. Using longitudinal data (1994-2009) from 433 initially high-functioning older women aged 70-79 years at baseline, a joint latent class and survival mixture model identified 4 activity trajectory classes: always active (16.6%), fast declining (19.2%), stable moderate (32.3%), and always sedentary (31.9%). Obesity, coronary artery disease, chronic obstructive pulmonary disease, depressive symptoms, low self-efficacy, mobility disability, and low energy were associated with sedentary behavior and/or a fast decline in activity. Women in the fast declining and always sedentary classes had hazard ratios for death of 2.34 (95% confidence interval: 1.20, 4.59) and 3.34 (95% confidence interval: 1.72, 6.47), respectively, compared with the always active class; no mortality difference was found between the stable moderate and always active groups (hazard ratio = 1.24, 95% confidence interval: 0.63, 2.47). Our findings suggest that physical activity does not have to be vigorous to be beneficial and that the gain may be the greatest among women who reported the lowest levels of activity.

We have developed a pruning algorithm for likelihood estimation of a tree of populations. This algorithm enables us to compute the likelihood for large trees. Thus, it gives an efficient way of obtaining the maximum-likelihood estimate (MLE) for a given tree topology. Our method utilizes the differences accumulated by random genetic drift in allele count data from single-nucleotide polymorphisms (SNPs), ignoring the effect of mutation after divergence from the common ancestral population. The computation of the maximum-likelihood tree involves both maximizing likelihood over branch lengths of a given topology and comparing the maximum-likelihood across topologies. Here our focus is the maximization of likelihood over branch lengths of a given topology. The pruning algorithm computes arrays of probabilities at the root of the tree from the data at the tips of the tree; at the root, the arrays determine the likelihood. The arrays consist of probabilities related to the number of coalescences and allele counts for the partially coalesced lineages. Computing these probabilities requires an unusual twostage algorithm. Our computation is exact and avoids time-consuming Monte Carlo methods. We can also correct for ascertainment bias.A LLELE-COUNT data, the number of occurrences of each allele, are often used by researchers to estimate the evolutionary tree. Likelihood estimation of the evolutionary tree from allele-count data was introduced by Edwards and Cavalli-Sforza (1964) and Cavalli-Sforza and Edwards (1967), followed by D. Gomberg (unpublished results). They used a Brownian-motion approximation for genetic drift.Felsenstein (1968, 1973a,b) introduced the ''pruning'' algorithm, for the Brownian-motion approximation leading to an efficient calculation. Thompson (1975) also used a form of pruning algorithm for likelihood estimation of branch lengths of an evolutionary tree. The idea of pruning (or ''peeling,'' as it is commonly known in studies of pedigrees in statistical genetics) also appears in the work of Hilden (1970). Elston and Stewart (1971) introduced peeling upward in a pedigree. Heuch and Li (1972) introduced peeling upward and downward alternately for an unlooped pedigree. Nielsen et al. (1998) and Nielsen and Slatkin (2000) introduced an exact likelihood-based method of estimating the evolutionary tree using the coalescent. They devised a method of computing the likelihood of trees with specified structures (called topologies) and specified branch lengths. The branch lengths are time in generations, scaled by effective population size. They computed the likelihood for a given combination of numbers of coalescent events in each branch and then summed over all possible combinations of these numbers. They ignored the effect of mutation after divergence from the common ancestral population. They maximized the likelihood first over the branch lengths within each topology and then over the topologies. However, their summations over the number of coalescent events of the branches have a complicated n...

Objective To retrospectively validate and compare a modified frailty index predicting adverse outcomes to other risk stratification tools among patients undergoing urologic oncological surgeries. Materials and Methods The American College of Surgeons National Surgical Quality Improvement Program was queried from 2005–2013 to identify patients undergoing cystectomy, prostatectomy, nephrectomy, and nephroureterectomy. Using the Canadian Study of Health & Aging Frailty Index, 11 variables were matched to the database; 4 were also added due to their relevance in oncology patients. The incidence of mortality, Clavien-Dindo IV complications, and adverse events were assessed with patients grouped according to their modified frailty index score. Results A total of 41,681 cases of patients were identified undergoing surgery for presumed urological malignancy. Patients with a high frailty index score of >0.20 had a 3.70 odds of a Clavien-Dindo IV event (CI: 2.865–4.788, p<0.0005) and a 5.95 odds of 30-day mortality (CI: 3.72–9.51, p<0.0005) in comparison to non-frail patients after adjusting for race, gender, age, smoking history and procedure. Using C-statistics to compare the sensitivity and specificity of the predictive ability of different models per risk stratification tool and Akaiki Information Criteria to assess for the fit of the models with the data, the modified frailty index was comparable or superior to the Charlson Comorbidity Index but inferior to the American Society of Anesthesiologists Risk Class in predicting 30-day mortality or Clavien-Dindo IV events. When the modified frailty index was augmented with the American Society of Anesthesiologists Risk Class, the new index was superior in all regards in comparison to risk stratification tools. Conclusion Existing risk stratification tools may be improved by incorporating variables in our 15 point modified frailty index as well as other factors such as walking speed, exhaustion, and sarcopenia to fully assess frailty. This is relevant in diseases like kidney and prostate cancer, where surveillance and other non-surgical interventions exist as alternatives to a potentially complicated surgery. In these scenarios, our modified frailty index augmented by the American Society of Anesthesiologists Risk Class may help inform which patients do not benefit from surgery although this index needs prospective validation.