Exposure to DDT and DDE and functional neuroimaging in adolescents from the CHAMACOS cohort

Ethnic and Sex Differences in the Association Between Organochlorine Exposure and Cognitive Function in Late Life

BACKGROUND

Organochlorine pesticides persist in the environment and body for extended periods. However, little is known about their long-term impact on cognition in older adults and if their influence differs by race/ethnicity (hereinafter ethnicity) and sex.

METHODS

We evaluated cognitive function and organochlorine levels by ethnicity and sex in 979 adults, age 60+ from the National Health and Nutrition Examination Surveys (2011-2014). We utilized weighted linear generalized estimating equations to measure differences between 7 log-transformed lipid-adjusted organochlorines (ng/g) and cognitive function. A composite cognitive function score was created using the mean of the z-scores from immediate and delayed of a word-list memory test, verbal fluency, and digit substitution test. Covariates included age, education, marital status, sex, and ethnicity. Exploratory sensitivity analyses included body mass index, ratio of income-to-poverty, and occupation, which were added to the models individually. Weighted sample included: 55.4% females; 79.8% NH-White; 9.2% NH-Black; 3.4% Mexican-American; 4.0% Other-Hispanic; 3.5% NH-Asian.

RESULTS

We found significant differences in cognitive outcomes and organochlorine levels across ethnic and sex groups. The variability in cognitive performance and organochlorine exposure both within and between these groups, suggests that organochlorines may play a role in cognitive disparities, despite limited significant interaction effects. Sensitivity analyses adjusting for body mass index, ratio of income-to-poverty, and longest occupation held indicated that most specific-organochlorine associations remained significant.

CONCLUSIONS

Our findings emphasize the importance of examining both the distributions of organochlorines and cognition by ethnicity and sex and their interactions to understand how each may contribute to cognitive health disparities in older adults.

NiReject: toward automated bad channel detection in functional near-infrared spectroscopy

Significance

The increasing sample sizes and channel densities in functional near-infrared spectroscopy (fNIRS) necessitate precise and scalable identification of signals that do not permit reliable analysis to exclude them. Despite the relevance of detecting these "bad channels," little is known about the behavior of fNIRS detection methods, and the potential of unsupervised and semi-supervised machine learning remains unexplored.

Aim

We developed three novel machine learning-based detectors, unsupervised, semi-supervised, and hybrid NiReject, and compared them with existing approaches.

Approach

We conducted a systematic literature search and demonstrated the influence of bad channel detection. Based on 29,924 signals from two independently rated datasets and a simulated scenario space of diverse phenomena, we evaluated the NiReject models, six of the most established detection methods in fNIRS, and 11 prominent methods from other domains.

Results

Although the results indicated that a lack of proper detection can strongly bias findings, detection methods were reported in only 32% of the included studies. Semi-supervised models, specifically semi-supervised NiReject, outperformed both established thresholding-based and unsupervised detectors. Hybrid NiReject, utilizing a human feedback loop, addressed the practical challenges of semi-supervised methods while maintaining precise detection and low rating effort.

Conclusions

This work contributes toward more automated and reliable fNIRS signal quality control by comprehensively evaluating existing and introducing novel machine learning-based techniques and outlining practical considerations for bad channel detection.

Exposure to Endocrine Disruptors in Early life and Neuroimaging Findings in Childhood and Adolescence: a Scoping Review

PURPOSE OF REVIEW: Evidence suggests neurotoxicity of endocrine disrupting chemicals (EDCs) during sensitive periods of development. We present an overview of pediatric population neuroimaging studies that examined brain influences of EDC exposure during prenatal period and childhood. RECENT FINDINGS: We found 46 studies that used magnetic resonance imaging (MRI) to examine brain influences of EDCs. These studies showed associations of prenatal exposure to phthalates, organophosphate pesticides (OPs), polyaromatic hydrocarbons and persistent organic pollutants with global and regional brain structural alterations. Few studies suggested alteration in functional MRI associated with prenatal OP exposure. However, studies on other groups of EDCs, such as bisphenols, and those that examined childhood exposure were less conclusive. These findings underscore the potential profound and lasting effects of prenatal EDC exposure on brain development, emphasizing the need for better regulation and strategies to reduce exposure and mitigate impacts. More studies are needed to examine the influence of postnatal exposure to EDC on brain imaging.

Developmental dyslexia genes are selectively targeted by diverse environmental pollutants

BACKGROUND

Developmental dyslexia, a complex neurodevelopmental disorder, not only affects children's academic performance but is also associated with increased healthcare costs, lower employment rates, and reduced productivity. The pathogenesis of dyslexia remains unclear and it is generally considered to be caused by the overlap of genetic and environmental factors. Systematically exploring the close relationship between exposure to environmental compounds and susceptibility genes in the development of dyslexia is currently lacking but high necessary.

METHODS

In this study, we systematically compiled 131 publicly reported susceptibility genes for dyslexia sourced from DisGeNET, OMIM, and GeneCards databases. Comparative Toxicogenomics Database database was used to explore the overlap between susceptibility genes and 95 environmental compounds, including metals, persistent organic pollutants, polycyclic aromatic hydrocarbons, and pesticides. Chemical bias towards the dyslexia risk genes was taken into account in the observation/expectation ratios > 1 and the corresponding P value obtained by hypergeometric probability test.

RESULTS

Our study found that the number of dyslexia risk genes targeted by each chemical varied from 1 to 109. A total of 35 chemicals were involved in chemical reactions with dyslexia-associated genes, with significant enrichment values (observed/expected dyslexia risk genes) ranging from 1.147 (Atrazine) to 66.901 (Dibenzo(a, h)pyrene).

CONCLUSION

The results indicated that dyslexia-associated genes were implicated in certain chemical reactions. However, these findings are exploratory, and further research involving animal or cellular experiments is needed.

Expression levels and network analysis of inflammamiRs in peripheral blood mononuclear cells exposed to DDE "in vitro"

Recent studies have demonstrated that dichlorodiphenyldichloroethylene (DDE) induced a pro-inflammatory condition in peripheral blood mononuclear cells (PBMC). However, the molecular mechanisms implicated in this condition are poorly understood. Therefore, this study aimed to evaluate miR-155, miR-126, and miR-21 expression levels in PBMC exposed "in vitro" to DDE. PBMC were dosed with increasing concentrations of DDE (10-80 µg mL^-1) at different treatment times (0-24 h). The results showed an up-regulation in the expression levels of assessed miRNAs (miR-155, miR-146, and miR-21) after PBMCs were exposed to DDE. Besides, bioinformatic analysis was performed to understand the biological roles of assessed miRNAs. The bioinformatic analysis shows that assessed miRNAs are associated with regulating signaling pathways involved in cancer, apoptosis, cell cycle, inflammation, metabolism, etc. These findings offer new insights into the molecular mechanisms related to the inflammatory processes and their regulation induced by DDE in PBMC exposed "in vitro".

Current opinions on the present and future use of functional near-infrared spectroscopy in psychiatry

Functional near-infrared spectroscopy (fNIRS) is an optical imaging technique for assessing human brain activity by noninvasively measuring the fluctuation of cerebral oxygenated- and deoxygenated-hemoglobin concentrations associated with neuronal activity. Owing to its superior mobility, low cost, and good tolerance for motion, the past few decades have witnessed a rapid increase in the research and clinical use of fNIRS in a variety of psychiatric disorders. In this perspective article, we first briefly summarize the state-of-the-art concerning fNIRS research in psychiatry. In particular, we highlight the diverse applications of fNIRS in psychiatric research, the advanced development of fNIRS instruments, and novel fNIRS study designs for exploring brain activity associated with psychiatric disorders. We then discuss some of the open challenges and share our perspectives on the future of fNIRS in psychiatric research and clinical practice. We conclude that fNIRS holds promise for becoming a useful tool in clinical psychiatric settings with respect to developing closed-loop systems and improving individualized treatments and diagnostics.

Pesticide exposure and cortical brain activation among farmworkers in Costa Rica

BACKGROUND

Previous epidemiological studies have reported associations of pesticide exposure with poor cognitive function and behavioral problems. However, these findings have relied primarily on neuropsychological assessments. Questions remain about the neurobiological effects of pesticide exposure, specifically where in the brain pesticides exert their effects and whether compensatory mechanisms in the brain may have masked pesticide-related associations in studies that relied purely on neuropsychological measures.

METHODS

We conducted a functional neuroimaging study in 48 farmworkers from Zarcero County, Costa Rica, in 2016. We measured concentrations of 13 insecticide, fungicide, or herbicide metabolites or parent compounds in urine samples collected during two study visits (approximately 3-5 weeks apart). We assessed cortical brain activation in the prefrontal cortex during tasks of working memory, attention, and cognitive flexibility using functional near-infrared spectroscopy (fNIRS). We estimated associations of pesticide exposure with cortical brain activation using multivariable linear regression models adjusted for age and education level.

RESULTS

We found that higher concentrations of insecticide metabolites were associated with reduced activation in the prefrontal cortex during a working memory task. For example, 3,5,6-trichloro-2-pyridinol (TCPy; a metabolite of the organophosphate chlorpyrifos) was associated with reduced activation in the left dorsolateral prefrontal cortex (β = -2.3; 95% CI: -3.9, -0.7 per two-fold increase in TCPy). Similarly, 3-phenoxybenzoic acid (3-PBA; a metabolite of pyrethroid insecticides) was associated with bilateral reduced activation in the dorsolateral prefrontal cortices (β = -3.1; 95% CI: -5.0, -1.2 and -2.3; 95% CI: -4.5, -0.2 per two-fold increase in 3-PBA for left and right cortices, respectively). These associations were similar, though weaker, for the attention and cognitive flexibility tasks. We observed null associations of fungicide and herbicide biomarker concentrations with cortical brain activation during the three tasks that were administered.

CONCLUSION

Our findings suggest that organophosphate and pyrethroid insecticides may impact cortical brain activation in the prefrontal cortex - neural dynamics that could potentially underlie previously reported associations with cognitive and behavioral function. Furthermore, our study demonstrates the feasibility and utility of fNIRS in epidemiological field studies.

Electrochemical oxidation of fipronil pesticide is effective under environmental relevant concentrations

Pesticide overuse has posed a threat to agricultural community as well as for the environment. In order to treat this pollution at its source, decentralized and selective technologies such as electrochemical processes appear especially relevant to avoid the possible generation of toxic degradation products. Electrochemical oxidation (ECO) is a promising electrochemically-driven process, but most studies evaluate performance under pollutant concentrations that are orders of magnitude higher than environmental relevant conditions. This work explores ECO treatment of fipronil using boron-doped diamond (BDD) as anode and titanium plate as cathode at small concentrations found in agricultural run-off. The effect of applied current density and initial contaminant concentrations were also studied. For a current density of 20 mA cm^-2 the decrease of COD and fipronil were about 97% and 100% after 360 min of electrolysis, respectively. Engineering figures of merit were evaluated to assess competitiveness of ECO decentralized propositions. Results suggest effective and feasible treatment of fipronil by ECO.