Population Dynamics in the Penna Model

We build upon the recent steady-state Penna model solution, Phys.Rev.Lett. 89, 288103 (2002), to study the population dynamics within the Penna model. We show, that any perturbation to the population can be broken into a collection of modes each of which decay exponentially with its respective time constant. The long time behaviour of population is therefore likely to be dominated by the modes with the largest time constants. We confirm our analytical approach with simulation data.Comment: 6 figure

Proposal for a Model State Watershed Management Act

During the Montana Constitutional Convention of 1889, John Wesley Powell, envisioning a landscape of watershed commonwealths, proposed that Montana adopt watersheds as the boundaries of its counties. The idea did not catch on. Over time, the power of local governments to regulate land use has grown immensely, but the misfit between their political boundaries and environmental policy problem sheds has persisted. As our understanding of ecosystem dynamics improves, however, natural resources management policy is gravitating, once again, to the watershed as an appropriate unit of governance. Many federal and state natural resource management initiatives have come on line in the past five years using watersheds as their primary focus. Yet, these new programs lack coherence and invest inadequate authority in watershed-based units of government. Representing perspectives from law, geography, economics, and anthropology, the authors propose the framework for a model state watershed management law. They conclude that the federal government is ill-equipped to take on the role of comprehensive watershed management czar as it has for pollution control and other environmental programs. Yet, local governments, even if organized around watershed boundaries, are unlikely to provide the platform for effective policy implementation. Rather, the authors propose a multi-tiered governance system linking state, regional, and local units of government through careful distribution of planning responsibilities and policy implementation authorities. Although for many states this framework would introduce a new layer of governance, its superior correspondence to the inescapable realities of ecosystem dynamics makes it worth serious consideration

An Infrared Divergence Problem in the cosmological measure theory and the anthropic reasoning

An anthropic principle has made it possible to answer the difficult question of why the observable value of cosmological constant ($\Lambda\sim 10^{-47}$ GeV${}^4$) is so disconcertingly tiny compared to predicted value of vacuum energy density $\rho_{SUSY}\sim 10^{12}$ GeV${}^4$. Unfortunately, there is a darker side to this argument, as it consequently leads to another absurd prediction: that the probability to observe the value $\Lambda=0$ for randomly selected observer exactly equals to 1. We'll call this controversy an infrared divergence problem. It is shown that the IRD prediction can be avoided with the help of a Linde-Vanchurin {\em singular runaway measure} coupled with the calculation of relative Bayesian probabilities by the means of the {\em doomsday argument}. Moreover, it is shown that while the IRD problem occurs for the {\em prediction stage} of value of $\Lambda$, it disappears at the {\em explanatory stage} when $\Lambda$ has already been measured by the observer.Comment: 9 pages, RevTe

Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study

Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention

Clinical Conditions “Suggestive of Progressive Supranuclear Palsy”—Diagnostic Performance

Background: The Movement Disorder Society diagnostic criteria for progressive supranuclear palsy introduced the diagnostic certainty level “suggestive of progressive supranuclear palsy” for clinical conditions with subtle signs, suggestive of the disease. This category aims at the early identification of patients, in whom the diagnosis may be confirmed as the disease evolves. Objective: To assess the diagnostic performance of the defined clinical conditions suggestive of progressive supranuclear palsy in an autopsy-confirmed cohort. Methods: Diagnostic performance of the criteria was analyzed based on retrospective clinical data of 204 autopsy-confirmed patients with progressive supranuclear palsy and 216 patients with other neurological diseases. Results: The conditions suggestive of progressive supranuclear palsy strongly increased the sensitivity compared to the National Institute of Neurological Disorders and Stroke and Society for Progressive Supranuclear Palsy criteria. Within the first year after symptom onset, 40% of patients with definite progressive supranuclear palsy fulfilled criteria for suggestive of progressive supranuclear palsy. Two-thirds of patients suggestive of progressive supranuclear palsy evolved into probable progressive supranuclear palsy after an average of 3.6 years. Application of the criteria for suggestive of progressive supranuclear palsy reduced the average time to diagnosis from 3.8 to 2.2 years. Conclusions: Clinical conditions suggestive of progressive supranuclear palsy allow earlier identification of patients likely to evolve into clinically possible or probable progressive supranuclear and to have underlying progressive supranuclear palsy pathology. Further work needs to establish the specificity and positive predictive value of this category in real-life clinical settings, and to develop specific biomarkers that enhance their diagnostic accuracy in early disease stages

Improved prediction of fracture risk leveraging a genome-wide polygenic risk score

Background Accurately quantifying the risk of osteoporotic fracture is important for directing appropriate clinical interventions. While skeletal measures such as heel quantitative speed of sound (SOS) and dual-energy X-ray absorptiometry bone mineral density are able to predict the risk of osteoporotic fracture, the utility of such measurements is subject to the availability of equipment and human resources. Using data from 341,449 individuals of white British ancestry, we previously developed a genome-wide polygenic risk score (PRS), called gSOS, that captured 25.0% of the total variance in SOS. Here, we test whether gSOS can improve fracture risk prediction. Methods We examined the predictive power of gSOS in five genome-wide genotyped cohorts, including 90,172 individuals of European ancestry and 25,034 individuals of Asian ancestry. We calculated gSOS for each individual and tested for the association between gSOS and incident major osteoporotic fracture and hip fracture. We tested whether adding gSOS to the risk prediction models had added value over models using other commonly used clinical risk factors. Results A standard deviation decrease in gSOS was associated with an increased odds of incident major osteoporotic fracture in populations of European ancestry, with odds ratios ranging from 1.35 to 1.46 in four cohorts. It was also associated with a 1.26-fold (95% confidence interval (CI) 1.13–1.41) increased odds of incident major osteoporotic fracture in the Asian population. We demonstrated that gSOS was more predictive of incident major osteoporotic fracture (area under the receiver operating characteristic curve (AUROC) = 0.734; 95% CI 0.727–0.740) and incident hip fracture (AUROC = 0.798; 95% CI 0.791–0.805) than most traditional clinical risk factors, including prior fracture, use of corticosteroids, rheumatoid arthritis, and smoking. We also showed that adding gSOS to the Fracture Risk Assessment Tool (FRAX) could refine the risk prediction with a positive net reclassification index ranging from 0.024 to 0.072. Conclusions We generated and validated a PRS for SOS which was associated with the risk of fracture. This score was more strongly associated with the risk of fracture than many clinical risk factors and provided an improvement in risk prediction. gSOS should be explored as a tool to improve risk stratification to identify individuals at high risk of fracture

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu