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Breaking Out of the Pack
Published in Phillip Joy, Megan Aston, Queering Nutrition and Dietetics, 2023
It's been 14 months, two days, 12 hours, and 13 minutes since the world shut down, and we were all forced to let go of the lives we once knew. Now we all exist in this new reality of isolation, physical distance, and the unknown; for the greater good, we let go of people, plans, dreams, and expectations. Possibly the scariest part of the pandemic for someone like me is the loss of control, not knowing. While many people perfected their sourdough recipes, for those of us who navigate issues with food, body image, and exercise, the pandemic brought on new challenges; being home with food and mirrors, staring at ourselves on zoom, then of course being disconnected from physical support systems and coping mechanisms. My whole life has been a battle with food, exercise, and a general disdain for my body. Even a few stints at treatment weren't enough to “fix” me, and I was resigned that I would move through my life with this shameful secret. It's been 14 months, two days, 12 hours, and 14 minutes since we lost derby. A sport, community, and lifestyle that deeply altered the trajectory of my life. I mourn the loss of roller derby more than you probably should for a recreational sport, but this wacky sport repaired my relationship with food, my body, and my identity in ways that years of mainstream therapy couldn't.
Island Ecosystems
Published in Kezia Barker, Robert A. Francis, Routledge Handbook of Biosecurity and Invasive Species, 2021
Island biogeography has been a key topic in research related to species diversity and distribution and the underlying ecological processes and mechanisms. A central theme of island biogeography is the theory of island biogeography developed by Robert H. MacArthur and E. O. Wilson (1967) and its implications for application. This was partly based upon the species-area curves reported much earlier in accumulated field observations of many naturalists and ecologists during their explorations around the world (e.g., Preston, 1962; Wu and Vankat, 1995) but jointly considered area with distance (or isolation; Figure 8.1). Their theory effectively integrates ecology, evolution and population biology of island species with broad implications for conservation biology. The theory predicts that the number of species (richness) usually increases with island area but decreases with isolation (i.e., distance from outside species pools; Wu and Vankat, 1991b, 1995). In addition to area and isolation, some recent studies have also adopted other measures to examine the effects of specific island features – such as fragmentation, time, the perimeter to area ratio of the islands and economics – on species diversity (e.g., Wu and Vankat, 1991a; Hu et al., 2011; Helmus et al., 2014).
Classification and Systematics
Published in Jacques Derek Charlwood, The Ecology of Malaria Vectors, 2019
In South America the picture is, if anything, more complicated (Conn et al., 2013). Thus, in a recent study examining Anophelinae species diversity from settler communities in the Amazonas region of Brazil, 23 species were collected, of which up to 13 appeared to be new. The contraction of the Amazon rainforest into isolated patches, so-called forest refugia (Haffer, 1974), during the Pleistocene (0.01–2.6 mya), with secondary intergradiation when rainfall increased is considered to be the primary driver for divergence in these mosquitoes (as well as butterflies, Drosophila and lizards). Isolation by distance is also likely to be important because most species do not have continuously distributed populations and gene flow between clumped demes is generally leptokurtic (because more individuals move smaller distances than they would if they moved at random). Hence, species with broad ranges are more likely to be divided by changes in geomorphology and climate than species with limited ranges. They are also more likely to have greater habitat diversity and so may develop clines and subspecies.
Evaluation of the genetic structure of Bromus inermis populations from chemically and radioactively polluted areas using microsatellite markers from closely related species
Published in International Journal of Radiation Biology, 2022
Elena V. Antonova, Marion S. Röder
The frequency of null alleles was estimated using the first algorithm of the Brookfield method (Brookfield 1996), as implemented in the MICRO-CHECKER package v. 2.2.3 (Van Oosterhout et al. 2004). The following parameters of genetical variability were used: allele frequency, observed (NA) and effective (NE) number of alleles per locus, the proportion of polymorphic loci, average observed heterozygosity (HO), the average expected heterozygosity (HE), and test of the genotype distribution by the Hardy–Weinberg ratio. Also, nonparametric (Mann–Whitney U-test, Wilcoxon matched pairs Z-test) and parametric (t-test) tests were used to compare the populations using the STATISTICA 10.0 software (StatSoft, Inc 2011). Since the HO and HE parameters were correlated with each other, the variables were considered to be dependent. Therefore, we used the t-test for dependent samples. Wright’s F-statistics coefficients were used to analyze the population structure. The Mantel test was used to assess the hypothesis of the effect of isolation by distance on genetic diversity. The level of statistical significance of the Mantel test was determined using 999 permutations. The calculation of these genetic parameters was carried out in the GenAlex 6.51b2 software package (Smouse et al. 2017). To visualize the obtained data, a dendrogram based on Nei’s standard genetic distance (Bias corrected) was drawn using the neighbor-joining method in POPTREE2 (Takezaki et al. 2010).
‘Other patients become a secondary priority:’ perceptions of Estonian frontline healthcare professionals on the influence of COVID-19 on health (in)equality and ethical decision-making
Published in Journal of Communication in Healthcare, 2022
Kadi Lubi, Kadri Simm, Kaja Lempu, Jay Zameska, Angela Eensalu-Lind
Participants also noticed that people who were infected in spring 2020 suffered the most, as they were ‘unwanted’ among their colleagues and teams: People who were two months at home since the PCR-test was positive / … / the ones that fall into that period when a negative test (for return) was requested have definitely lost … even economically.These statements indicate the lack of knowledge which was prevailing globally. On the other hand, public health communication that stressed isolation, social distance and symptoms of the disease might have contributed unwittingly to these perceptions and behaviors. This highlights the responsibility of public health communicators in shaping messages and related explanations [15].
Gut microbiota composition explains more variance in the host cardiometabolic risk than genetic ancestry
Published in Gut Microbes, 2020
Sandra J. Guzmán-Castañeda, Esteban L. Ortega-Vega, Jacobo de la Cuesta-Zuluaga, Eliana P. Velásquez-Mejía, Winston Rojas, Gabriel Bedoya, Juan S. Escobar
On average, the ancestral genetic composition of each individual of our cohort was (mean ± SD) 0.674 ± 0.057 European (range: 0.469–0.788), 0.209 ± 0.048 Native American (0.089–0.397), and 0.117 ± 0.047 African (0.051–0.352) (Figure 1A). These proportions differed significantly among the cities where participants were enrolled (ANOVA for European: F4,431 = 2.84, p = .02; Native American: F4,431 = 7.46, p < .0001; African: F4,431 = 5.64, p = .0002): the European component was highest in Medellin (Northwestern Andes) and lowest in Barranquilla (Northern Caribbean); the Native American component highest in Bogota (Central Andes) and lowest in Medellin; and the African component highest in Barranquilla and lowest in Bogota (Figure 1B-D). In agreement with this, we found evidence of limited but significant genetic structure (mean Fst ± SE = 0.004 ± 0.001, 95% CI = 0.002–0.006). However, there was no evidence of isolation by distance, according to a Mantel test considering genetic (Fst/(1-Fst)) and (log-transformed) geographic distance matrices (r = −0.43, 95% CI = −0.80–0.14, two-tailed p = .44). Furthermore, we did not find significant differences in the ancestral genetic composition by other factors controlled by design (p > .10 in all ANOVAs for BMI, sex, and age range).