We found no overall adverse association between prenatal MeHg exposure and neurodevelopmental outcomes. However, maternal PUFA status as a putative marker of the inflammatory milieu appeared to modify the associations of prenatal MeHg exposure with the PDI. Increasing DHA status was positively associated with language development yet negatively associated with the MDI. These findings may indicate the existence of an optimal DHA balance with respect to arachidonic acid for different aspects of neurodevelopment.

Cranial irradiation is the main therapeutic treatment for primary and metastatic malignancies in the brain. However, cranial radiation therapy produces long-term impairment in memory, information processing, and attention that contribute to a decline in quality of life. The hippocampal neural network is fundamental for proper storage and retrieval of episodic and spatial memories, suggesting that hippocampal signaling dysfunction could be responsible for the progressive memory deficits observed following irradiation. Previous rodent studies demonstrated that irradiation induces significant loss in dendritic spine number, alters spine morphology, and is associated with behavioral task deficits. Additionally, the literature suggests a common mechanism in which synaptic elimination via microglial-mediated phagocytosis is complement dependent and associated with cognitive impairment in aging as well as disease. We demonstrate sexual dimorphisms in irradiation-mediated alterations of microglia activation markers and dendritic spine density. Further, we find that the significant dendritic spine loss observed in male mice following irradiation is microglia complement receptor 3 (CR3)-dependent. By identifying sex-dependent cellular and molecular factors underlying irradiation-mediated spine loss, therapies can be developed to counteract irradiation-induced cognitive decline and improve patient quality of life.

Objective Considerable inaccuracy in estimates of human immunodeficiency virus (HIV) incidence has been a serious obstacle to the development of efficient HIV/AIDS prevention and interventions. Accurately distinguishing recent or incident infections from chronic infections enables one to monitor epidemics and evaluate the impact of HIV prevention/intervention trials. However, serological testing has not been able to realize these promises due to a number of critical limitations. Our study is to design a novel scheme of identifying incident infections in a highly accurate manner, based on the characteristics of HIV gene diversification within an infected individual. Methods We perform a comprehensive meta-analysis on 5596 full envelope HIV genes generated by single genome amplification-direct sequencing from 182 incident and 43 chronic cases. We devise a binary classification test based on the tail characteristics of the Hamming distance distribution of sequences. Results We identify a clear signature of incident infectiones, the presence of closely related strains in the sampled HIV envelope gene sequences in each HIV infected patient, in both single-variant and multi-variant transmissions. The sequence similarity used as a biomarker is found to have high specificity and sensitivity, greater than 95%, and is robust to viral and host specific factors such as the clade of the viral strain, viral load, and the length and location of sequences in the HIV envelope gene. Conclusions Because of rapid and continuing improvements in sequencing technology and cost, sequence based incidence assays hold great promise as a means of quantifying HIV incidence from a single blood test.

While the Food Safety Modernization Act established standards for the use of surface water for produce production, water quality is known to vary over space and time. Targeted approaches for identifying hazards in water that account for this variation may improve growers' ability to address pre-harvest food safety risks. Models that utilize publicly-available data (e.g., land-use, real-time weather) may be useful for developing these approaches. The objective of this study was to use pre-existing datasets collected in 2017 (N = 181 samples) and 2018 (N = 191 samples) to train and test models that predict the likelihood of detecting Salmonella and pathogenic E. coli markers (eaeA, stx) in agricultural water. Four types of features were used to train the models: microbial, physicochemical, spatial and weather. "Full models" were built using all four features types, while "nested models" were built using between one and three types. Twenty learners were used to develop separate full models for each pathogen. Separately, to assess information gain associated with using different feature types, six learners were randomly selected and used to develop nine, nested models each. Performance measures for each model were then calculated and compared against baseline models where E. coli concentration was the sole covariate. In the methods, we outline the advantages and disadvantages of each learner. Overall, full models built using ensemble (e.g., Node Harvest) and "blackbox" (e.g., SVMs) learners out-performed full models built using more interpretable learners (e.g., tree-and rule-based learners) for both outcomes. However, nested eaeAstx models built using interpretable learners and microbial data performed almost as well as these full models. While none of the nested Salmonella models performed as well as the full models, nested models built using spatial data consistently outperformed models that excluded spatial data. These findings demonstrate that machine learning approaches can be used to predict when and where pathogens are likely to be present in agricultural water. This study serves as a proof-of-concept that can be built upon once larger datasets become available and provides guidance on Weller et al. Predicting Foodborne Pathogen Presence in Water the learner-data combinations that should be the foci of future efforts (e.g., tree-based microbial models for pathogenic E. coli).

Long-chain n-6 and n-3 PUFA (LC-PUFA), arachidonic acid (AA) (20:4n-6) and DHA (22:6n-3), are critical for optimal brain development. These fatty acids can be consumed directly from the diet, or synthesized endogenously from precursor PUFA by Δ-5 (encoded by FADS1) and Δ-6 desaturases (encoded by FADS2). The aim of this study was to determine the potential importance of maternal genetic variability in FADS1 and FADS2 genes to maternal LC-PUFA status and infant neurodevelopment in populations with high fish intakes. The Nutrition Cohorts 1 (NC1) and 2 (NC2) are longitudinal observational mother-child cohorts in the Republic of Seychelles. Maternal serum LC-PUFA was measured at 28 weeks gestation and genotyping for rs174537 (FADS1), rs174561 (FADS1), rs3834458 (FADS1-FADS2) and rs174575 (FADS2) was performed in both cohorts. The children completed the Bayley Scales of Infant Development II (BSID-II) at 30 months in NC1 and at 20 months in NC2. Complete data were available for 221 and 1310 mothers from NC1 and NC2 respectively. With increasing number of rs3834458 minor alleles, maternal concentrations of AA were significantly decreased (NC1 p=0.004; NC2 p<0.001) and precursor:product ratios for linoleic acid (LA) (18:2n-6)-to-AA (NC1 p<0.001; NC2 p<0.001) and α-linolenic acid (ALA) (18:3n-3)-to-DHA were increased (NC2 p=0.028). There were no significant associations between maternal FADS genotype and BSID-II scores in either cohort. A trend for improved PDI was found among infants born to mothers with the minor rs3834458 allele. In these high fish-eating cohorts, genetic variability in FADS genes was associated with maternal AA status measured in serum and a subtle association of the FADS genotype was found with neurodevelopment.

Methylmercury (MeHg) exposure via fish in the diet remains a priority public health concern. Individual variation in response to a given MeHg exposure and the biotransformation of MeHg that follows complicate our understanding of this issue. MeHg elimination from the human body occurs slowly (elimination rate (kel) approximately 0.01 day(-1) or approximately 70 days half-life [t1/2]) and is a major determinant of the Hg body burden resulting from fish consumption. The underlying mechanisms that control MeHg elimination from the human body remain poorly understood. We describe here improved methods to obtain a MeHg elimination rate via longitudinal Hg analysis in hair using laser ablation-inductively coupled plasma-mass spectrometry. We measured MeHg elimination rates in eight individuals following the consumption of 3 fish meals in two 75-day trials separated by a 4-month washout period. In addition, since MeHg biotransformation to inorganic Hg (I-Hg) is associated with Hg excretion, we speciated Hg in feces samples to estimate individual MeHg de-methylation status. We observed a wide range of MeHg elimination rates between individuals and within individuals over time (kel = 0.0163-0.0054 day(-1); estimated t1/2 = 42.5-128.3 days). The ratio of MeHg and I-Hg in feces also varied widely among individuals. While the %I-Hg in feces was likely influenced by dental amalgams, findings with subjects who lacked amalgams suggest that faster MeHg elimination is associated with a higher %I-Hg in feces indicating more complete de-methylation. We anticipate these methods will contribute to future investigations of genetic and dietary factors that influence MeHg disposition in people.

The Seychelles Child Development Study (SCDS) examines the effects of prenatal exposure to methylmercury on the functioning of the central nervous system. The SCDS data include 20 outcomes measured on 9-year old children that can be classified broadly in four outcome classes or “domains”: cognition, memory, motor, and social behavior. Previous analyses and scientific theory suggest that these outcomes may belong to more than one of these domains, rather than only a single domain as is frequently assumed for modeling. We present a framework for examining the effects of exposure and other covariates when the outcomes may each belong to more than one domain and where we also want to learn about the assignment of outcomes to domains. Each domain is defined by a sentinel outcome which is preassigned to that domain only. All other outcomes can belong to multiple domains and are not preassigned. Our model allows exposure and covariate effects to differ across domains and across outcomes within domains, and includes random subject-specific effects which model correlations between outcomes within and across domains. We take a Bayesian MCMC approach. Results from the Seychelles study and from extensive simulations show that our model can effectively determine sparse domain assignment, and at the same time give increased power to detect overall, domain-specific and outcome-specific exposure and covariate effects relative to separate models for each endpoint. When fit to the Seychelles data, several outcomes were classified as partly belonging to domains other than their originally assigned domains. In retrospect, the new partial domain assignments are reasonable and, as we discuss, suggest important scientific insights about the nature of the outcomes. Checks of model misspecification were improved relative to a model that assumes each outcome is in a single domain.

Background All fish contain methyl mercury (MeHg), a known neurotoxicant at adequate dosage. There is still substantial scientific uncertainty about the consequences, if any, of mothers consuming fish with naturally-acquired levels of MeHg contamination. In 1989-1990, we recruited the Main Cohort of the Seychelles Child Development Study to assess the potential developmental effects of prenatal MeHg exposure. We report here on associations with neurodevelopmental outcomes obtained at 22 and 24 years of age. Methods Neurodevelopmental tests at 22 years included the Boston Naming Test, Cambridge Neuropsychological Test Automated Battery (CANTAB), and the Profile of Mood States. At 24 years, we administered the Stroop Word-Color Test, the Barkley Adult ADHD Rating Scale, the Test of Variables of Attention, and the Finger Tapping test. We also administered a healthy behaviors survey at both ages. Primary analyses examined covariate-adjusted associations in multiple linear regression models with prenatal MeHg exposure. In secondary analyses we also examined associations with recent postnatal MeHg exposure. Results We did not observe adverse associations between prenatal MeHg exposure and any of the measured endpoints. Some measures of attention, executive function, and delayed recall showed improved performance with increasing exposure. Secondary analysis did not show consistent patterns of association with postnatal exposure. Conclusions Our cohort has been examined at ten different ages over 24 years of follow-up. Findings suggest that prenatal and recent postnatal MeHg exposure from ocean fish consumption is not adversely associated with neurobehavioral development at levels that are about ten times higher than typical U.S. exposures.