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Traffic-related air pollution in marginalized neighborhoods: a community perspective
Khan, Rahanna N; Saporito, Antonio F; Zenon, Jania; Goodman, Lael; Zelikoff, Judith T
OBJECTIVES/UNASSIGNED:Marginalized communities are exposed to higher levels of traffic-related air pollution (TRAP) than the general population. TRAP exposure is linked to pulmonary toxicity, neurotoxicity, and cardiovascular toxicity often through mechanisms of inflammation and oxidative stress. Early life exposure to TRAP is also implicated in higher rates of asthma in these same communities. There is a critical need for additional epidemiological, in vivo, and in vitro studies to define the health risks of TRAP exposure affecting the most vulnerable groups to set strict, protective air pollution standards in these communities. MATERIALS AND METHODS/UNASSIGNED:A literature review was conducted to summarize recent findings (2010-2024) concerning TRAP exposure and toxic mechanisms that are relevant to the most affected underserved communities. CONCLUSIONS/UNASSIGNED:Guided by the perspectives of NYC community scientists, this contemporary review of toxicological and epidemiological studies considers how the exposome could lead to disproportionate exposures and health effects in underserved populations.
PMID: 38618680
ISSN: 1091-7691
CID: 5723322
A contemporary review of machine learning to predict adverse pregnancy outcomes from pharmaceuticals, including DDIs
Gardella, Julie; Abrahamsson, Dimitri; Zelikoff, Judith
Those undergoing pregnancy are often excluded from clinical drug trials due to the risk that participation would pose. However, they often require pharmaceuticals to manage health conditions that, if gone untreated, could harm themselves or the fetus. This can mean that such individuals take one or more pharmaceuticals during pregnancy, many of which have unknown reproductive effects. Machine learning models have been used to successfully predict a number of reproductive toxicological outcomes for pharmaceuticals, including transplacental transfer, US Food and Drug Administration safety rating, and drug interactions. Models use quantitative chemical and structural features of active compounds to make predictions concerning the outcome of interest using computational algorithms. Results from these models can be a potential source of valuable information for pregnant people and their medical providers when making decisions regarding therapeutic drug use. This review summarizes current machine learning applications to make predictions about risk and toxicity of medication use during pregnancy. Our review of the recent literature revealed that machine learning quantitative structure-activity relationship models can be used successfully to predict the transplacental transfer and the US Food and Drug Administration pregnancy safety category of pharmaceuticals; such models have also been employed to predict drug interactions, though not specifically during pregnancy. This latter topic is a potential area for future research. In this review, no single algorithm or descriptor-calculation software emerged as the most widely used, and their performances depend on a variety of factors, including outcome of interest and combination of such algorithms and software.
PMID: 39374154
ISSN: 1741-7899
CID: 5705912
An introduction to the adverse health impacts of inhaled toxicants in global marginalized communities [Editorial]
Saporito, Antonio F; Zelikoff, Judith T
PMID: 39033486
ISSN: 1091-7691
CID: 5699522
Reproductive effects associated with phthalate mixture exposure
Opoku, Florence; Flaws, Jodi A; Zelikoff, Judith T
PMID: 38423834
ISSN: 1878-7541
CID: 5691602
Soil health is human health
Romano, Isabella; Zelikoff, Judith T
PMID: 39241377
ISSN: 1878-7541
CID: 5688362
The effects of electronic cigarette inhalation on immune responses: Perspectives from animal model studies
Naranjo, Kelly; Awada, Christina; Zelikoff, Judith T
PMID: 38777725
ISSN: 1878-7541
CID: 5654772
Effects of E-cigarette Whole Body Aerosol Exposure on Lung Inflammation to an Acute Streptococcus Pneumoniae Challenge in Mice
Grunig, G.; Kothandaraman, C.; Ye, C.; Voynov, D.; Durmus, N.; Goriainova, V.; Raja, A.; Chalupa, D.; Weiser, J.; Kwon, S.; Nolan, A.; Elder, A.C.P.; Zelikoff, J.
ORIGINAL:0017190
ISSN: 2325-6621
CID: 5651812
E-Cigarette Exposure Alters Neuroinflammation Gene and Protein Expression in a Murine Model: Insights from Perinatally Exposed Offspring and Post-Birth Mothers
Awada, Christina; Saporito, Antonio F; Zelikoff, Judith T; Klein, Catherine B
The use of E-cigarettes, often considered a safer alternative to traditional smoking, has been associated with high rates of cellular toxicity, genetic alterations, and inflammation. Neuroinflammatory impacts of cigarette smoking during pregnancy have been associated with increased risks of adverse childhood health outcomes; however, it is still relatively unknown if the same propensity is conferred on offspring by maternal vaping during gestation. Results from our previous mouse inhalation studies suggest such a connection. In this earlier study, pregnant C57BL/6 mice were exposed daily to inhaled E-cig aerosols (i.e., propylene glycol and vegetable glycerin, [PG/VG]), with or without nicotine (16 mg/mL) by whole-body inhalation throughout gestation (3 h/d; 5 d/week; total ~3-week) and continuing postnatally from post-natal day (PND) 4-21. As neuroinflammation is involved in the dysregulation of glucose homeostasis and weight gain, this study aimed to explore genes associated with these pathways in 1-mo.-old offspring (equivalent in humans to 12-18 years of age). Results in the offspring demonstrated a significant increase in glucose metabolism protein levels in both treatment groups compared to filtered air controls. Gene expression analysis in the hypothalamus of 1 mo. old offspring exposed perinatally to E-cig aerosols, with and without nicotine, revealed significantly increased gene expression changes in multiple genes associated with neuroinflammation. In a second proof-of-principal parallel study employing the same experimental design, we shifted our focus to the hippocampus of the postpartum mothers. We targeted the mRNA levels of several neurotrophic factors (NTFs) indicative of neuroinflammation. While there were suggestive changes in mRNA expression in this study, levels failed to reach statistical significance. These studies highlight the need for ongoing research on E-cig-induced alterations in neuroinflammatory pathways.
PMCID:10970539
PMID: 38540381
ISSN: 2073-4425
CID: 5645042
Fertility in indigenous communities: An environmental justice perspective
Gordon, Rachel; Zelikoff, Judith T
PMID: 38171982
ISSN: 1878-7541
CID: 5628352
In vivo exposure to electronic waste (e-waste) leachate and hydraulic fracturing fluid adversely impacts the male reproductive system
Raja, Amna; Costa, Patricia; Blum, Jason L; Doherty-Lyons, Shannon; Igbo, Juliet K; Meltzer, Gabriella; Orem, William; McCawley, Michael; Zelikoff, Judith T
Human health effects can arise from unregulated manual disassembly of electronic waste (e-waste) and/or hydraulic fracturing fluid spills. There is limited literature on the effects of e-waste and hydraulic fracturing wastewater exposure on the male reproductive system. Thus, this proof-of-concept study begins to address the question of how wastewater from two potentially hazardous environmental processes could affect sperm quality. Therefore, three groups of eight-week-old adult mice were exposed (5 d/wk for 6 wks) via a mealworm (Tenebrio molitor and Zophabas morio) feeding route to either: (1) e-waste leachate (50% dilution) from the Alaba Market (Lagos, Nigeria); (2) West Virginia hydraulic fracturing flowback (HFF) fluid (50% dilution); or, (3) deionized water (control). At 24-hours (hr), 3 weeks (wk), or 9-wk following the 6-wk exposure period, cohorts of mice were necropsied and adverse effects/persistence on the male reproductive system were examined. Ingestion of e-waste leachate or HFF fluid decreased number and concentration of sperm and increased both chromatin damage and numbers of morphological abnormalities in the sperm when compared to control mice. Levels of serum testosterone were reduced post-exposure (3- and 9-wk) in mice exposed to e-waste leachate and HFF when compared to time-matched controls, indicating the long-term persistence of adverse effects, well after the end of exposure. These data suggest that men living around or working in vicinity of either e-waste or hydraulic fracturing could face harmful effects to their reproductive health. From both a human health and economic standpoint, development of prevention and intervention strategies that are culturally relevant and economically sensitive are critically needed to reduce exposure to e-waste and HFF-associated toxic contaminants.
PMID: 38160783
ISSN: 1873-1708
CID: 5624052