How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables

1. Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g., individual size) are commonly used in demographic analyses to represent the effect of past22 environments on demographic rates. 2. We quantified how well the size of individuals captures the effects of a population’s past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. 3. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life-history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. 4. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; i.e., different measures of body size (e.g., length, volume, mass, fat stores) will be better or worse proxies for various life-history processes

Disentangling evolutionary, plastic and demographic processes underlying trait dynamics: a review of four frameworks

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Biologists are increasingly interested in decomposing trait dynamics into underlying processes, such as evolution, plasticity and demography. Four important frameworks that allow for such a decomposition are the quantitative genetic animal model (AM), the ‘Geber’ method (GM), the age-structured Price equation (APE) and the integral projection model (IPM). However, as these frameworks have largely been developed independently, they differ in the assumptions they make, the data they require, as well as their outcomes and interpretation. Here, we evaluate how each framework decomposes trait dynamics into underlying processes. To do so, we apply them to simulated data for a hypothetical animal population. Individual body size was affected by, among others, genes, maternal effects and food intake. We simulated scenarios with and without selection on body size and with high and low heritability. The APE and IPM provided similar results, as did the AM and GM, with important differences between the former and the latter. All frameworks detected positive contributions of selection in the high but not in the low selection scenarios. However, only the AM and GM distinguished between the high and low heritability scenarios. Furthermore, the AM and GM revealed a high contribution of plasticity. The APE and IPM attributed most of the change in body size to ontogenetic growth and inheritance, where the latter captures the combined effects of plasticity, maternal effects and heritability. We show how these apparent discrepancies are mostly due to differences in aims and definitions. For example, the APE and IPM capture selection, whereas the AM and GM focus on the response to selection. Furthermore, the frameworks differ in the processes that are ascribed to plasticity and in how they take into account demography. We conclude that no single framework provides the ‘true’ contributions of evolution, plasticity and demography. Instead, different research questions require different frameworks. A thorough understanding of the different definitions of their components is necessary for selecting the most appropriate framework for the question at hand and for making biologically meaningful inferences. This work thus supports both future analysis and the careful interpretation of existing work.This work was funded by the Swiss NationalScience Foundation project grants (31003A_141110 and 31003A_159462/1 toEP, 31003A_146445 to AO) and an ERC starting grant (#337785 to AO)

Association of polymorphisms in APOE, p53, and p21 with primary open-angle glaucoma in Turkish patients

Purpose To investigate the association between Apolipoprotein E (APOE), tumor suppressor protein p53 (p53), and cyclin-dependent kinase inhibitor 1A (p21) genes and primary open-angle glaucoma (POAG) in a cohort of Turkish subjects. Methods Seventy-five POAG patients (49 women, 26 men) and 119 healthy subjects (67 women, 52 men) were genotyped with polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Allele and genotype frequencies between healthy subjects and glaucoma patients were compared by the χ2 test, and intraocular pressure (IOP), cup/disc ratio (C/D) and visual field indices (MD and PSD) were compared among different APOE, p53, and p21 genotypes in POAG group. A p value 0.05). POAG subjects with the ε2ε3 genotype had a worse PSD value (median=2.2) than those with the ε3ε4 genotype (median=1.77; p=0.01) and POAG subjects with the ε3ε3 genotype had worse MD and PSD values (median= -7.4 and 3.4, respectively) than those with the ε3ε4 genotype (median= -4.1 and 1.77, respectively; p=0.034 and 0.028, respectively). Conclusions Our study found no link between polymorphisms in APOE, p53, and p21 genes and POAG in Turkish patients, although a larger sample is required to elucidate the role of these polymorphisms in the pathogenesis and course of glaucoma

"Medicine is still against Black people": Mapping and visualising intersections of social inequalities, community mistrust, and vaccine hesitancy in online and physical spaces in the UK and US

Funded by the British Academy, this report is part of a research project entitled “Mapping and visualising intersections of social inequalities, community mistrust, and vaccine hesitancy in online and physical spaces in the UK and US”. The report investigates social, cultural, and political factors underlying vaccine hesitant beliefs and ideas among minoritised communities in the United Kingdom (UK) and the United States of America (US). The data is collected through interviews and focus groups with vaccine-hesitant individuals within various religiously, ethnically, and racially minoritised communities, interviews with medical practitioners, and through thematic analysis of vaccine communication in Twitter and Telegram during the COVID-19 pandemic

Biodiesel production from jatropha seeds: Solvent extraction and in situ transesterification in a single step

The objective of this study was to investigate solvent extraction and in situ transesterification in a single step to allow direct production of biodiesel from jatropha seeds. Experiments were conducted using milled jatropha seeds, and n-hexane as extracting solvent. The influence of methanol to seed ratio (2:1–6:1), amount of alkali (KOH) catalyst (0.05–0.1 mol/L in methanol), stirring speed (700–900 rpm), temperature (40–60 °C) and reaction time (3–5 h) was examined to define optimum biodiesel yield and biodiesel quality after water washing and drying. When stirring speed, temperature and reaction time were fixed at 700 rpm, 60 °C and 4 h respectively, highest biodiesel yield (80% with a fatty acid methyl ester purity of 99.9%) and optimum biodiesel quality were obtained with a methanol to seed ratio of 6:1 and 0.075 mol/L KOH in methanol. Subsequently, the influence of stirring speed, temperature and reaction time on biodiesel yield and biodiesel quality was studied, by applying the randomized factorial experimental design with ANOVA (F-test at p = 0.05), and using the optimum values previously found for methanol to seed ratio and KOH catalyst level. Most experimental runs conducted at 50 °C resulted to high biodiesel yields, while stirring speed and reaction time did not give significantly effect. The highest biodiesel yield (87% with a fatty acid methyl ester purity of 99.7%) was obtained with a methanol to seed ratio of 6:1, KOH catalyst of 0.075 mol/L in methanol, a stirring speed of 800 rpm, a temperature of 50 °C, and a reaction time of 5 h. The effects of stirring speed, temperature and reaction time on biodiesel quality were not significant. Most of the biodiesel quality obtained in this study conformed to the Indonesian Biodiesel Standard

The Cross-Cultural Dementia Screening (CCD):A new neuropsychological screening instrument for dementia in elderly immigrants

Objective: Currently, approximately 3.9% of the European population are non-EU citizens, and a large part of these people are from "non-Western" societies, such as Turkey and Morocco. For various reasons, the incidence of dementia in this group is expected to increase. However, cognitive testing is challenging due to language barriers and low education and/or illiteracy. The newly developed Cross-Cultural Dementia Screening (CCD) can be administered without an interpreter. It contains three subtests that assess memory, mental speed, and executive function. We hypothesized the CCD to be a culture-fair test that could discriminate between demented patients and cognitively healthy controls. Method: To test this hypothesis, 54 patients who had probable dementia were recruited via memory clinics. Controls (N = 1625) were recruited via their general practitioners. All patients and controls were aged 55 years and older and of six different self-defined ethnicities (Dutch, Turkish, Moroccan-Arabic, Moroccan-Berber, Surinamese-Creole, and Surinamese-Hindustani). Exclusion criteria included current or previous conditions that affect cognitive functioning. Results: There were performance differences between the ethnic groups, but these disappeared after correcting for age and education differences between the groups, which supports our central hypothesis that the CCD is a culture-fair test. Receiver-operating characteristic (ROC) and logistic regression analyses showed that the CCD has high predictive validity for dementia (sensitivity: 85%; specificity: 89%). Discussion: The CCD is a sensitive and culture-fair neuropsychological instrument for dementia screening in low-educated immigrant populations.</p

Detecting context dependence in the expression of life history trade-offs

1. Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. 2. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. 3. Here, we present a hierarchical multivariate 'covariance reaction norm' model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. 4. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. 5. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general

Schwannoma of the external auditory canal: a case report

BACKGROUND: Schwannomas are uncommon benign tumors of the external auditory canal. The clinical features, the differential diagnosis, and the surgical treatment of these lesions are discussed. CASE PRESENTATION: A 51-year-old patient presented with a mass obliterating the external auditory meatus. Excisional biopsy was performed. Diagnosis was reported to be schwannoma by histopathologic examination. CONCLUSION: Schwannoma, rarely seen in the external auditory canal, can be managed by a precise excision of the tumor via transmeatal approach

Assessing seasonal demographic covariation to understand environmental‐change impacts on a hibernating mammal

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development and reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor‐analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual‐based demography from yellow‐bellied marmots (Marmota flaviventer ) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneously, negative responses of winter survival and reproductive‐status change to declining environmental quality result in a higher risk of population quasi‐extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments

Detecting context dependence in the expression of life history trade‐offs

Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. Here, we present a hierarchical multivariate ‘covariance reaction norm’ model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general