Application of plant metabarcoding to identify diverse honeybee pollen forage along an urban-agricultural gradient.

Understanding animal foraging ecology requires large sample sizes spanning broad environmental and temporal gradients. For pollinators, this has been hampered by the laborious nature of morphologically identifying pollen. Identifying pollen from urban environments is particularly difficult due to the presence of diverse ornamental species associated with consumer horticulture. Metagenetic pollen analysis represents a potential solution to this issue. Building upon prior laboratory and bioinformatic methods, we applied quantitative multilocus metabarcoding to characterize the foraging ecology of honeybee colonies situated in urban, suburban, mixed suburban-agricultural and rural agricultural sites in central Ohio, USA. In cross-validating a subset of our metabarcoding results using microscopic palynology, we find strong concordance between the molecular and microscopic methods. Our results suggest that forage from the agricultural site exhibited decreased taxonomic diversity and temporal turnover relative to the urban and suburban sites, though the generalization of this observation will require replication across additional sites and cities. Our work demonstrates the power of honeybees as environmental samplers of floral community composition at large spatial scales, aiding in the distinction of taxa characteristically associated with urban or agricultural land use from those distributed ubiquitously across the sampled landscapes. Observed patterns of high forage diversity and compositional turnover in our more urban sites are likely reflective of the fine-grain heterogeneity and high beta diversity of urban floral landscapes at the scale of honeybee foraging. This provides guidance for future studies investigating how relationships between urbanization and measures of pollinator health are mediated by variation in floral resource dynamics across landscapes.

Risk and Protective Factors for COVID-19 Infection among Pregnant Women with Sickle Cell Trait.

Pregnant women and individuals with sickle cell trait (SCT) and underlying comorbidities are both independently more vulnerable to severe illness from coronavirus disease 2019 (COVID-19) compared to nonpregnant women and those without SCT. However, our understanding of the specific factors influencing susceptibility to COVID-19 infection among pregnant women with SCT is currently constrained by limited available data. This study aims to determine the risk and protective factors that influence the likelihood of COVID-19 infection in this population. A retrospective analysis was done among 151 women with SCT in the reproductive age group. Multivariable analysis was performed to determine the various factors affecting COVID-19 infection among pregnant women with SCT. The study found that COVID-19-vaccinated pregnant women with SCT had a 90% lower risk of contracting COVID-19 and were 9 times more likely to have a COVID-19 infection if they had a history of pulmonary conditions such as asthma or chronic obstructive pulmonary disease. The present study further emphasizes the importance of the COVID-19 vaccine in preventing infection and safeguarding the health of pregnant women with SCT, particularly those with underlying comorbidities.