Appendix to "Approximating perpetuities"

An algorithm for perfect simulation from the unique solution of the distributional fixed point equation $Y=_d UY + U(1-U)$ is constructed, where $Y$ and $U$ are independent and $U$ is uniformly distributed on $[0,1]$. This distribution comes up as a limit distribution in the probabilistic analysis of the Quickselect algorithm. Our simulation algorithm is based on coupling from the past with a multigamma coupler. It has four lines of code

The effects of socioeconomic status and indices of physical environment on reduced birth weight and preterm births in Eastern Massachusetts

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Air pollution and social characteristics have been shown to affect indicators of health. While use of spatial methods to estimate exposure to air pollution has increased the power to detect effects, questions have been raised about potential for confounding by social factors.Methods: A study of singleton births in Eastern Massachusetts was conducted between 1996 and 2002 to examine the association between indicators of traffic, land use, individual and area-based socioeconomic measures (SEM), and birth outcomes ( birth weight, small for gestational age and preterm births), in a two-level hierarchical model.Results: We found effects of both individual ( education, race, prenatal care index) and area-based ( median household income) SEM with all birth outcomes. The associations for traffic and land use variables were mainly seen with birth weight, with an exception for an effect of cumulative traffic density on small for gestational age. Race/ethnicity of mother was an important predictor of birth outcomes and a strong confounder for both area-based SEM and indices of physical environment. The effects of traffic and land use differed by level of education and median household income.Conclusion: Overall, the findings of the study suggested greater likelihood of reduced birth weight and preterm births among the more socially disadvantaged, and a greater risk of reduced birth weight associated with traffic exposures. Results revealed the importance of controlling simultaneously for SEM and environmental exposures as the way to better understand determinants of health.This work is supported by the Harvard Environmental Protection Agency (EPA) Center, Grants R827353 and R-832416, and National Institute for Environmental Health Science (NIEHS) ES-0002

Integrated population models poorly estimate the demographic contribution of immigration

Estimating the contribution of demographic parameters to changes in population growth is essential for understanding why populations fluctuate. Integrated population models (IPMs) offer a possibility to estimate the contributions of additional demographic parameters, for which no data have been explicitly collected—typically immigration. Such parameters are often subsequently highlighted as important drivers of population growth. Yet, accuracy in estimating their temporal variation, and consequently their contribution to changes in population growth rate, has not been investigated. To quantify the magnitude and cause of potential biases when estimating the contribution of immigration using IPMs, we simulated data (using northern wheatear Oenanthe oenanthe population estimates) from controlled scenarios to examine potential biases and how they depend on IPM parameterization, formulation of priors, the level of temporal variation in immigration and sample size. We also used empirical data on populations with known rates of immigration: Soay sheep Ovis aries and Mauritius kestrel Falco punctatus with zero immigration and grey wolf Canis lupus in Scandinavia with near-zero immigration. IPMs strongly overestimated the contribution of immigration to changes in population growth in scenarios when immigration was simulated with zero temporal variation (proportion of variance attributed to immigration = 63% for the more constrained formulation and real sample size) and in the wild populations, where the true number of immigrants was zero or near-zero (kestrel 19.1%–98.2%, sheep 4.2%–36.1% and wolf 84.0%–99.2%). Although the estimation of the contribution of immigration in the simulation study became more accurate with increasing temporal variation and sample size, it was often not possible to distinguish between an accurate estimation from data with high temporal variation versus an overestimation from data with low temporal variation. Unrealistically, large sample sizes may be required to estimate the contribution of immigration well. To minimize the risk of overestimating the contribution of immigration (or any additional parameter) in IPMs, we recommend to: (a) look for evidence of variation in immigration before investigating its contribution to population growth, (b) simulate and model data for comparison to the real data and (c) use explicit data on immigration when possible

Rare and common vertebrates span a wide spectrum of population trends

Conservation biologists often assume that rare (or less abundant) species are more likely to be declining under anthropogenic change. Here, the authors synthesise population trend data for ~2000 animal species to show that population trends cover a wide spectrum of change from losses to gains, which are not related to species rarity

Clinical and virological characteristics of hospitalised COVID-19 patients in a German tertiary care centre during the first wave of the SARS-CoV-2 pandemic: a prospective observational study

Purpose: Adequate patient allocation is pivotal for optimal resource management in strained healthcare systems, and requires detailed knowledge of clinical and virological disease trajectories. The purpose of this work was to identify risk factors associated with need for invasive mechanical ventilation (IMV), to analyse viral kinetics in patients with and without IMV and to provide a comprehensive description of clinical course. Methods: A cohort of 168 hospitalised adult COVID-19 patients enrolled in a prospective observational study at a large European tertiary care centre was analysed. Results: Forty-four per cent (71/161) of patients required invasive mechanical ventilation (IMV). Shorter duration of symptoms before admission (aOR 1.22 per day less, 95% CI 1.10-1.37, p < 0.01) and history of hypertension (aOR 5.55, 95% CI 2.00-16.82, p < 0.01) were associated with need for IMV. Patients on IMV had higher maximal concentrations, slower decline rates, and longer shedding of SARS-CoV-2 than non-IMV patients (33 days, IQR 26-46.75, vs 18 days, IQR 16-46.75, respectively, p < 0.01). Median duration of hospitalisation was 9 days (IQR 6-15.5) for non-IMV and 49.5 days (IQR 36.8-82.5) for IMV patients. Conclusions: Our results indicate a short duration of symptoms before admission as a risk factor for severe disease that merits further investigation and different viral load kinetics in severely affected patients. Median duration of hospitalisation of IMV patients was longer than described for acute respiratory distress syndrome unrelated to COVID-19

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

Methods for Monitoring Matrix-Induced Autophagy.

A growing body of research demonstrates modulation of autophagy by a variety of matrix constituents, including decorin, endorepellin, and endostatin. These matrix proteins are both pro-autophagic and anti-angiogenic. Here, we detail a series of methods to monitor matrix-induced autophagy and its concurrent effects on angiogenesis. We first discuss cloning and purifying proteoglycan fragment and core proteins in the laboratory and review relevant techniques spanning from cell culture to treatment with these purified proteoglycans in vitro and ex vivo. Further, we cover protocols in monitoring autophagic progression via morphological and microscopic characterization, biochemical western blot analysis, and signaling pathway investigation. Downstream angiogenic effects using in vivo approaches are then discussed using wild-type mice and the GFP-LC3 transgenic mouse model. Finally, we explore matrix-induced mitophagy via monitoring changes in mitochondrial DNA and permeability