Cross-species coherence in effects and modes of action in support of causality determinations in the U.S. Environmental Protection Agency's Integrated Science Assessment for Lead

Lead Nitrate Induces Inflammation and Apoptosis in Rat Lungs Through the Activation of NF-κB and AhR Signaling Pathways

Lead (Pb) is one of the most frequent hazardous air contaminants, where the lungs are particularly vulnerable to its toxicity. However, the Pb distribution and its impact on lung inflammation/apoptosis and particularly the involvement of nuclear factor kappa B (NF-κB) and aryl hydrocarbon receptor (AhR) signaling pathways in Pb-induced lung toxicity have not yet been fully investigated. Adult male Wistar albino rats were exposed to Pb nitrate 25, 50, and 100 mg/kg b.w. orally for 3 days. The histopathological changes of several rat organs were analyzed using hematoxylin and eosin staining. The concentrations of Pb ion in different organ tissues were quantified using inductive coupled plasma mass spectrometry, while gas chromatography-mass spectrometry was used to identify organic compounds. The changes in the mRNA and protein expression levels of inflammatory and apoptotic genes in response to Pb exposure were quantified by using RT-PCR and Western blot analyses, respectively. Treatment of rats with Pb for three consecutive days significantly increased the accumulation of Pb in lung tissues causing severe interstitial inflammation. Pb treatment also increased the percentage of lung apoptotic cells and modulated apoptotic genes (Bc2, p53, and TGF-α), inflammatory markers (IL-4, IL-10, TNF-α), and oxidative stress biomarkers (iNOS, CYP1A1, EphX) in rat lung tissues. These effects were associated with a significant increase in organic compounds, such as 3-nitrotyrosine and myeloperoxidase, and some inorganic elements, such as selenium. Importantly, the Pb-induced lung inflammation and apoptosis were associated with a proportional increase in the expression of NF-κB and AhR mRNAs and proteins. These findings clearly show that Pb induces severe inflammation and apoptosis in rat lungs and suggest that NF-κB and AhR may play a role in Pb-induced lung toxicity.

A toxicity pathway-based approach for modeling the mode of action framework of lead-induced neurotoxicity

BACKGROUND

The underlying mechanisms of lead (Pb) toxicity are not fully understood, which makes challenges to the traditional risk assessment. There is growing use of the mode of action (MOA) for risk assessment by integration of experimental data and system biology. The current study aims to develop a new pathway-based MOA for assessing Pb-induced neurotoxicity.

METHODS

The available Comparative Toxicogenomic Database (CTD) was used to search genes associated with Pb-induced neurotoxicity followed by developing toxicity pathways using Ingenuity Pathway Analysis (IPA). The spatiotemporal sequence of disturbing toxicity pathways and key events (KEs) were identified by upstream regulator analysis. The MOA framework was constructed by KEs in biological and chronological order.

RESULTS

There were a total of 71 references showing the relationship between lead exposure and neurotoxicity, which contained 2331 genes. IPA analysis showed that the neuroinflammation signaling pathway was the core toxicity pathway in the enriched pathways relevant to Pb-induced neurotoxicity. The upstream regulator analysis demonstrated that the aryl hydrocarbon receptor (AHR) signaling pathway was the upstream regulator of the neuroinflammation signaling pathway (11.76% overlap with upstream regulators, |Z-score|=1.451). Therefore, AHR activation was recognized as the first key event (KE1) in the MOA framework. The following downstream molecular and cellular key events were also identified. The pathway-based MOA framework of Pb-induced neurotoxicity was built starting with AHR activation, followed by an inflammatory response and neuron apoptosis.

CONCLUSION

Our toxicity pathway-based approach not only advances the development of risk assessment for Pb-induced neurotoxicity but also brings new insights into constructing MOA frameworks of risk assessment for new chemicals.

Lead and cadmium blood levels and transfer to milk in cattle reared in a mining area

The presence of heavy metals in milk is a public health problem that negatively effects human health, especially infant health. This study evaluated the concentration levels of lead (Pb) and cadmium (Cd) in blood and its transfer to the milk of 20 cows in production in a rural community near the La Oroya Metallurgical Complex in Peru, which has emitted fine particulate matter for more than 90 years. Validated protocols were used for sample collection. The samples were analyzed by atomic absorption spectrophotometry. The results of the analysis indicated that the levels, in mg/kg, of Pb in blood and milk were 0.38 ± 0.041 and 0.58 ± 0.018, respectively; Pb in milk was 54% higher than that in blood (P < 0.01). Cd levels, in mg/kg, in blood and milk were 0.016 ± 0.002 and 0.02 ± 0.007, respectively; milk had 28% more Cd than did blood (P < 0.05). The results for Pb in milk were compared with the Codex Alimentarius standard (0.002 mg/kg); the mean concentration of Pb in milk was 29 times higher than the acceptable limit, and the mean concentration of Cd was 2 times higher than the acceptable limit of the Romanian standard (0.01 mg/kg). The result could be attributed to the impact of environmental pollution by mining waste. In Peru, there are no norms for maximum Pb and Cd values, and the establishment of maximum value norms for these metals in milk is suggested.

A weight of evidence framework for environmental assessments: Inferring quantities

The US Environmental Protection Agency (USEPA) has developed a generally applicable framework for a weight-of-evidence (WoE) process for deriving quantitative values from multiple estimates. These guidelines are intended for environmental assessments that require the generation of quantitative parameters such as degradation rates or that develop quantitative products such as criterion values or magnitudes of effects. The basic steps are to weigh evidence for the environmental quality to be quantified, generate the value by merging estimates or by identifying the best estimate, and weight the results to determine confidence in the numerical value. When multiple data sets or outputs of multiple models are available, it may be appropriate to weigh the evidence. Use of the framework to weigh multiple estimates may increase the accuracy of quantitative results compared to a single estimate from a default method. Its use can provide greater transparency compared to ad hoc weighing of evidence. Integr Environ Assess Manag 2017;13:1045-1051. Published 2017. This article is a US Government work and is in the public domain in the USA.

Food, health, and complexity: towards a conceptual understanding to guide collaborative public health action

BACKGROUND

What we eat simultaneously impacts our exposure to pathogens, allergens, and contaminants, our nutritional status and body composition, our risks for and the progression of chronic diseases, and other outcomes. Furthermore, what we eat is influenced by a complex web of drivers, including culture, politics, economics, and our built and natural environments. To date, public health initiatives aimed at improving food-related population health outcomes have primarily been developed within 'practice silos', and the potential for complex interactions among such initiatives is not well understood. Therefore, our objective was to develop a conceptual model depicting how infectious foodborne illness, food insecurity, dietary contaminants, obesity, and food allergy can be linked via shared drivers, to illustrate potential complex interactions and support future collaboration across public health practice silos.

METHODS

We developed the conceptual model by first conducting a systematic literature search to identify review articles containing schematics that depicted relationships between drivers and the issues of interest. Next, we synthesized drivers into a common model using a modified thematic synthesis approach that combined an inductive thematic analysis and mapping to synthesize findings.

RESULTS

The literature search yielded 83 relevant references containing 101 schematics. The conceptual model contained 49 shared drivers and 227 interconnections. Each of the five issues was connected to all others. Obesity and food insecurity shared the most drivers (n = 28). Obesity shared several drivers with food allergy (n = 11), infectious foodborne illness (n = 7), and dietary contamination (n = 6). Food insecurity shared several drivers with infectious foodborne illness (n = 9) and dietary contamination (n = 9). Infectious foodborne illness shared drivers with dietary contamination (n = 8). Fewer drivers were shared between food allergy and: food insecurity (n = 4); infectious foodborne illness (n = 2); and dietary contamination (n = 1).

CONCLUSIONS

Our model explicates potential interrelationships between five population health issues for which public health interventions have historically been siloed, suggesting that interventions targeted towards these issues have the potential to interact and produce unexpected consequences. Public health practitioners working in infectious foodborne illness, food insecurity, dietary contaminants, obesity, and food allergy should actively consider how their seemingly targeted public health actions may produce unintended positive or negative population health impacts.