Neurodevelopmental exposure to chlorpyrifos (CPF) could increase risks for neurological disorders, such as autism spectrum disorder, cognitive impairment, or attention deficit hyperactivity disorder. The potential involvement of microglia reactive to inflammatory stimuli in these neurological disorders has been generally reported. However, the concrete effects and potential mechanisms of microglia dysfunction triggered by developmental CPF exposure remain unclear. Therefore, we established mouse and human embryonic microglial cells (HMC3 cell) models of developmental CPF exposure to evaluate the effects of developmental CPF exposure on neuroinflammation and underlying mechanisms. The results showed that developmental exposure to CPF enhanced the expression of Iba1 in hippocampus. CPF treatment increased inflammatory cytokines levels and TSPO expression in hippocampus and HMC3 cells. The levels of necroptosis and necroptosis-related signaling RIPK/MLKL were increased in hippocampus and HMC3 cells following CPF exposure. Furthermore, the expression of TLR4/TRIF signaling was increased in hippocampus and HMC3 cells subjected to CPF exposure. Notably, the increased levels of TLR4/TRIF signaling, RIPK/MLKL signaling, necroptosis and pro-inflammatory cytokines induced by CPF treatment were remarkably inhibited by TAK-242 (a specific TLR4 inhibitor). Additionally, the necroptosis and pro-inflammatory cytokines production induced by CPF treatment were significantly relieved by Nec-1 (a specific RIPK1 inhibitor). In general, the above results suggested that activated microglia in hippocampus subjected to developmental CPF exposure underwent RIPK1/MLKL-mediated necroptosis regulated by TLR4/TRIF signaling.

In this study, we aimed to identify the toxic effects of chlorpyrifos exposure on the tissues of common carp. For this purpose, we evaluated histopathological changes in the brain, gills, liver, kidney, testis, and ovaries after 21 days of chlorpyrifos exposure. Activation of 8-OHdG, cleaved caspase-3, and iNOS were assesed by immunofluorescence assay in chlorpyrifos-exposed brain and liver tissue. Additionally, we measured the expression levels of caspase-3, caspase-8, iNOS, MT1, CYP1A, and CYP3A genes in chlorpyrifos-exposed brain tissue, as well as the expression levels of FSH and LH genes in chlorpyrifos-exposed ovaries, using qRT-PCR. We observed severe histopathological lesions, including inflammation, degeneration, necrosis, and hemorrhage, in the evaluated tissues of common carp after both high and low levels of exposure to chlorpyrifos. We detected strong and diffuse signs of immunofluorescence reaction for 8-OHdG, iNOS, and cleaved caspase-3 in the chlorpyrifos-exposed brain and liver tissues. Furthermore, we found that chlorpyrifos exposure significantly upregulated the expressions of caspase-3, caspase-8, iNOS, and MT1, and also moderately upregulated CYP1A and CYP3A in the brain tissue of exposed carp. We also noted downregulation of FSH and LH gene expressions in chlorpyrifos-exposed ovary tissues. Based on our results, chlorpyrifos toxication caused crucial histopathological lesions in vital organs, induced oxidative stress, inflammation, and apoptosis in liver and brain tissues, and triggered reproductive sterility in common carp. Therefore, we can propose that chlorpyrifos toxication is highly dangerous to the health of common carp. Moreover, chlorpyrifos pollution in the water could threaten the common carp population. Use of chlorpyrifos should be restricted, and aquatic systems should be monitored for chlorpyrifos pollution.

We tested antioxidant responses of the green microalga Pseudokirchneriella subcapitata exposed to different concentrations of the three antibiotics erythromycin (ETM), ciprofloxacin (CPF) and sulfamethoxazole (SMZ). Measurements included the level of lipid peroxidation, the total antioxidative capacity and three major antioxidant mechanisms: the ascorbate–glutathione cycle, the xanthophyll cycle and the enzyme activities of catalase (CAT), superoxide dismutase (SOD), guaiacol glutathione peroxidase (GPX) and glutathione-S-transferase (GST). Three antibiotics significantly affect the antioxidant system of P. subcapitata, but in different ways the alga was more tolerant to CPF and SMZ exposures than to ETM exposure. ETM caused reductions in AsA and GSH biosynthesis, ascorbate–glutathione cycle, xanthophylls cycle and antioxidant enzyme activities. The toxicity of CPF seems to be mainly overcome via induction of the ascorbate–glutathione cycle and CAT, SOD and GPX activities, while the toxicity of SMZ on the photosynthetic apparatus is predominantly reduced by the xanthophyll cycle and GST activity.

To determine the chemical compositions and source identification of PM2.5 and PM2.5–10 fractions, airborne particulate matter (PM) samples were collected from May, 2011 through April, 2012 at three sites: up and downwind and within a scrap iron and steel smelting industry, Ife–Ibadan highway, south western Nigeria. Samples of PM2.5 (fine) and PM2.5–10 (coarse) were collected on Nuclepore polycarbonate filters using a low volume GENT sampler equipped with a stacked filter unit (SFU). A total of 200 samples were collected (100 of each fraction). The mass concentration of the sampled fine and coarse PM fraction ranged between 14.4–986.5μg/m3 and 11.2–3 250μg/m3, respectively. These values exceed the permissible daily limit (NAAQS) of 35μg/m3 for PM2.5 and 150μg/m3 for PM10. The samples were analyzed for black carbon (BC) using an optical transmissometer and for elemental concentrations using X–Ray Fluorescence (XRF). The size–resolved data sets were analyzed using Positive Matrix Factorization (PMF) to identify possible sources and estimate the contribution of these sources to the fine and coarse PM mass concentrations. Four source categories, providing stable profiles, were identified for both fine and coarse fractions. The identified sources and their contributions for the fine fraction are coking coal (83%), soil (10%), metallurgical industry (6%), and electronic waste processing (1%). For the coarse fraction, the identified sources are metallurgical production plus electronic waste (53%), suspended input materials (28%), soil (18%), and galvanized steel scrap with cadmium (1%). Conditional probability function (CPF) identified the local sources for both the fine and coarse PM samples. This work presents the first known major use of PMF in Nigeria for source identification in particulate matter (PM) studies.