Potential Exposure and Risk Associated with Metal Contamination in Foods

Humans require several trace elements as components of the diet. Some of these elements are required in extremely small quantities (only micrograms per day). On the other hand, in higher concentrations, some elements may also have deleterious, even lethal, effects. Metals such as arsenic, chromium (Cr), lead (Pb), and mercury (Hg) are naturally occurring chemical compounds. The contamination of food with these metals occurs mainly through human activities, such as farming and industry, or from contamination during food processing and storage. People can be exposed to these metals by ingesting contaminated food or water, and their accumulation in the body can lead to harmful effects over time. The main objective of this chapter is to provide a literature review on the various types of foodborne poisoning caused by the contamination of food with arsenic, Cr, Pb, and Hg and on food safety issues associated with the presence of these metals in food. Research findings from various studies carried out to examine the relationship between metal exposure and the adverse health effects of metals are addressed

Why we shouldn’t blame women for gender disparity in academia : perspectives of women in zoology

The following letter, from a network of women zoologists, is a reply to the article of AlShebli et al. (2020), which suggests that female protégés reap more benefits when mentored by men and concludes that female mentors hinder the success of their female protégés and the quality of their impact. This contribution has two parts. First, we highlight the most relevant methodological flaws which, in our opinion, may have impacted the conclusions of AlShebli et al. (2020). Second, we discuss issues pertaining to women in science, bring a perspective of Women in Zoology and discuss how current diversity policies are positively changing our field

Prolonged maternal separation induces undernutrition and systemic inflammation with disrupted hippocampal development in mice

Objective: Prolonged maternal separation (PMS) in the first 2 wk of life has been associated with poor growth with lasting effects in brain structure and function. This study aimed to investigate whether PMS-induced undernutrition could cause systemic inflammation and changes in nutrition-related hormonal levels, affecting hippocampal structure and neurotransmission in C57BL/6J suckling mice. Methods: This study assessed mouse growth parameters coupled with insulin-like growth factor-1 (IGF-1) serum levels. In addition, leptin, adiponectin, and corticosterone serum levels were measured following PMS. Hippocampal stereology and the amino acid levels were also assessed. Furthermore, we measured myelin basic protein and synapthophysin (SYN) expression in the overall brain tissue and hippocampal SYN immunolabeling. For behavioral tests, we analyzed the ontogeny of selected neonatal reflexes. PMS was induced by separating half the pups in each litter from their lactating dams for defined periods each day (4 h on day 1, 8 h on day 2, and 12 h thereafter). A total of 67 suckling pups were used in this study. Results: PMS induced significant slowdown in weight gain and growth impairment. Significant reductions in serum leptin and IGF-1 levels were found following PMS. Total CA3 area and volume were reduced, specifically affecting the pyramidal layer in PMS mice. CA1 pyramidal layer area was also reduced. Overall hippocampal SYN immunolabeling was lower, especially in CA3 field and dentate gyrus. Furthermore, PMS reduced hippocampal aspartate, glutamate, and gammaaminobutyric acid levels, as compared with unseparated controls. Conclusion: These findings suggest that PMS causes significant growth deficits and alterations in hippocampal morphology and neurotransmission.This work was supported in part by National Institutes of Health (NIH) research grant 5R01HD053131, funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the NIH Office of Dietary Supplements, and Brazilian grants from CNPq and CAPES (Grant # RO1 HD053131). The authors would like to thank Dr. Patricia Foley for veterinarian technical support and Dr. Jose Paulo Andrade for the excellent comments and suggestions to improve this manuscript. N.S. contributed with the stereological studies. I.L.F. and R.B.O. contributed with the behavioral studies. I.L.F., R.B.O., and R.L.G. contributed with the study design, study analysis, and manuscript preparation. G.A.M. and P.B.F. contributed with neurochemical brain analyses. J.I.A.L. and G.M.A. contributed with hormonal and CRP serum analyses. D.G.C., K.M.C., and R.S.R. contributed with animal experimentation and data collection

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Estimating the global conservation status of more than 15,000 Amazonian tree species

Estimates of extinction risk for Amazonian plant and animal species are rare and not often incorporated into land-use policy and conservation planning. We overlay spatial distribution models with historical and projected deforestation to show that at least 36% and up to 57% of all Amazonian tree species are likely to qualify as globally threatened under International Union for Conservation of Nature (IUCN) Red List criteria. If confirmed, these results would increase the number of threatened plant species on Earth by 22%. We show that the trends observed in Amazonia apply to trees throughout the tropics, and we predict thatmost of the world’s >40,000 tropical tree species now qualify as globally threatened. A gap analysis suggests that existing Amazonian protected areas and indigenous territories will protect viable populations of most threatened species if these areas suffer no further degradation, highlighting the key roles that protected areas, indigenous peoples, and improved governance can play in preventing large-scale extinctions in the tropics in this century