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Item Sources, effects and present perspectives of heavy metals contamination: Soil, plants and human food chain(Elsevier BV, 2024-04) Bishnu Agnon, Prodipto; Shafiul Islam, M.D.; KC, Shreejana; Das, Arpan; Anjum, Nafisa; Poudel, Amrit; Akter Suchi, ShahariaHeavy metal (HM) poisoning of agricultural soils poses a serious risk to plant life, human health, and global food supply. When HM levels in agricultural soils get to dangerous levels, it harms crop health and yield. Chromium (Cr), arsenic (As), nickel (Ni), cadmium (Cd), lead (Pb), mercury (Hg), zinc (Zn), and copper (Cu) are the main heavy metals. The environment contains these metals in varying degrees, such as in soil, food, water, and even the air. These substances damage plants and alter soil characteristics, which lowers crop yield. Crop types, growing circumstances, elemental toxicity, developmental stage, soil physical and chemical properties, and the presence and bioavailability of heavy metals (HMs) in the soil solution are some of the factors affecting the amount of HM toxicity in crops. By interfering with the normal structure and function of cellular components, HMs can impede various metabolic and developmental processes. Humans are exposed to numerous serious diseases by consuming these affected plant products. Exposure to certain metals can harm the kidneys, brain, intestines, lungs, liver, and other organs of the human body. This review assesses (1) contamination of heavy metals in soils through different sources, like anthropogenic and natural; (2) the effect on microorganisms and the chemical and physical properties of soil; (3) the effect on plants as well as crop production; and (4) entering the food chain and associated hazards to human health. Lastly, we identified certain research gaps and suggested further study. If people want to feel safe in their surroundings, there needs to be stringent regulation of the release of heavy metals into the environment.Item Community sharing: Contextualizing Western research notions of contamination within an Indigenous research paradigm(Wiley, 2022-03) Allen, Sarah; Held, Suzanne; Milne‐Price, Shauna; McCormick, Alma; Feng, Du; Inouye, Jillian; Schure, Mark B.; Castille, Dottie; Howe, Rae B.; Pitts, Mikayla; Keene, Shannen; Belone, Lorenda; Wallerstein, NinaBáa nnilah is a chronic illness self-management program designed by and for the Apsáalooke (Crow) community. Arising from a collaboration between an Indigenous non-profit organization and a university-based research team, Báa nnilah’s development, implementation and evaluation have been influenced by both Indigenous and Western research paradigms. Báa nnilah was evaluated using a randomized wait-list control group design. In a Western Research Paradigm (WRP), contamination, or intervention information shared by the intervention group with the control group, is actively discouraged as it makes ascertaining causality difficult, if not impossible. This approach is not consonant with Apsáalooke cultural values that include the encouragement of sharing helpful information with others, supporting an Indigenous Research Paradigm’s (IRP) goal of benefiting the community. The purpose of this paper is to address contamination and sharing as an area of tension between WRP and IRP. We describe how the concepts of contamination and sharing within Báa nnilah’s implementation and evaluation are interpreted differently when viewed from these contrasting paradigms, and set forth a call for greater exploration of Indigenous research approaches for developing, implementing and evaluating intervention programs in Indigenous communities. (Improving Chronic Illness Management with the Apsáalooke Nation: The Báa nnilah Project.:NCT03036189) ClinicalTrials.gov:NCT03036189)Item Using social contact data to improve the overall effect estimate of a cluster‐randomized influenza vaccination program in Senegal(Wiley, 2021-09) Potter, Gail E.; Carnegie, Nicole Bohme; Sugimoto, Jonathan D.; Diallo, Aldiouma; Victor, John C.; Neuzil, Kathleen M.; Halloran, M. Elizabethhis study estimates the overall effect of two influenza vaccination programs consecutively administered in a cluster-randomized trial in western Senegal over the course of two influenza seasons from 2009-2011. We apply cutting-edge methodology combining social contact data with infection data to reduce bias in estimation arising from contamination between clusters. Our time-varying estimates reveal a reduction in seasonal influenza from the intervention and a nonsignificant increase in H1N1 pandemic influenza. We estimate an additive change in overall cumulative incidence (which was 6.13% in the control arm) of -0.68 percentage points during Year 1 of the study (95% CI: -2.53, 1.18). When H1N1 pandemic infections were excluded from analysis, the estimated change was -1.45 percentage points and was significant (95% CI, -2.81, -0.08). Because cross cluster contamination was low (0-3% of contacts for most villages), an estimator assuming no contamination was only slightly attenuated (-0.65 percentage points). These findings are encouraging for studies carefully designed to minimize spillover. Further work is needed to estimate contamination – and its effect on estimation – in a variety of settings.