Elemental signatures of Australopithecus africanus teeth reveal seasonal dietary stress.

Reconstructing the detailed dietary behaviour of extinct hominins is challenging1-particularly for a species such as Australopithecus africanus, which has a highly variable dental morphology that suggests a broad diet2,3. The dietary responses of extinct hominins to seasonal fluctuations in food availability are poorly understood, and nursing behaviours even less so; most of the direct information currently available has been obtained from high-resolution trace-element geochemical analysis of Homo sapiens (both modern and fossil), Homo neanderthalensis4 and living apes5. Here we apply high-resolution trace-element analysis to two A. africanus specimens from Sterkfontein Member 4 (South Africa), dated to 2.6-2.1 million years ago. Elemental signals indicate that A. africanus infants predominantly consumed breast milk for the first year after birth. A cyclical elemental pattern observed following the nursing sequence-comparable to the seasonal dietary signal that is seen in contemporary wild primates and other mammals-indicates irregular food availability. These results are supported by isotopic evidence for a geographical range that was dominated by nutritionally depauperate areas. Cyclical accumulation of lithium in A. africanus teeth also corroborates the idea that their range was characterized by fluctuating resources, and that they possessed physiological adaptations to this instability. This study provides insights into the dietary cycles and ecological behaviours of A. africanus in response to food availability, including the potential cyclical resurgence of milk intake during times of nutritional challenge (as observed in modern wild orangutans5). The geochemical findings for these teeth reinforce the unique place of A. africanus in the fossil record, and indicate dietary stress in specimens that date to shortly before the extinction of Australopithecus in South Africa about two million years ago.

Detection and Imaging of Exposure-Related Metabolites and Xenobiotics in Hard Tissues by Laser Sampling and Mass Spectrometry.

The utility of two novel laser-based methods, laser ablation electrospray ionization (LAESI) and laser desorption ionization (LDI) from silicon nanopost array (NAPA), is explored via local analysis and mass spectrometry imaging (MSI) of hard tissues (tooth and hair) for the detection and mapping of organic components. Complex mass spectra are recorded in local analysis mode from tooth dentin and scalp hair samples. Nicotine and its metabolites (cotinine, hydroxycotinine, norcotinine, and nicotine) are detected by LAESI-MS in the teeth of rats exposed to tobacco smoke. The intensities of the detected metabolite peaks are proportional to the degree of exposure. Incorporating ion mobility separation in the LAESI-MS analysis of scalp hair enables the detection of cotinine in smoker hair along with other common molecular species, including endogenous steroid hormones and some lipids. Single hair strands are imaged by MALDI-MSI and NAPA-LDI-MSI to explore longitudinal variations in the level of small molecules. Comparing spectra integrated from NAPA-LDI-MSI and MALDI-MSI images reveals that the two techniques provide complementary information. There were 105 and 82 sample-related peaks for MALDI and NAPA, respectively, with an overlap of only 16 peaks, indicating a high degree of complementarity. Enhanced molecular coverage and spatial resolution offered by LAESI-MS and NAPA-LDI-MSI can reveal the distributions of known and potential biomarkers in hard tissues, facilitating exposome research.

IMU-Assisted Manual 3D-Ultrasound Imaging Using Motion-Constrained Swept-Fan Scans.

Three-dimensional (3D) ultrasonic imaging can enable post-facto plane of interest selection. It can be performed with devices such as wobbler probes, matrix probes, and sensor-based probes. Ultrasound systems that support 3D-imaging are expensive with added hardware complexity compared to 2D-imaging systems. An inertial measurement unit (IMU) can potentially be used for 3D-imaging by using it to track the motion of a one-dimensional array probe and constraining its motion in one degree of freedom (1-DoF) rotation (swept-fan). This work demonstrates the feasibility of an affordable IMU-assisted manual 3D-ultrasound scanner (IAM3US). A consumer-grade IMU-assisted 3D scanner prototype is designed with two support structures for swept-fan. After proper IMU calibration, an appropriate KF-based algorithm estimates the probe orientation during the swept-fan. An improved scanline-based reconstruction method is used for volume reconstruction. The evaluation of the IAM3US system is done by imaging a tennis ball filled with water and the head region of a fetal phantom. From fetal phantom reconstructed volumes, suitable 2D planes are extracted for biparietal diameter (BPD) manual measurements. Later, in-vivo data is collected. The novel contributions of this paper are (1) the application of a recently proposed algorithm for orientation estimation of swept-fan for 3D imaging, chosen based on the noise characteristics of selected consumer grade IMU (2) assessment of the quality of the 1-DoF swept-fan scan with a deflection detector along with monitoring of maximum angular rate during the scan and (3) two probe holder designs to aid the operator in performing the 1-DoF rotational motion and (4) end-to-end 3D-imaging system-integration. Phantom studies and preliminary in-vivo obstetric scans performed on two patients illustrate the usability of the system for diagnosis purposes.

Quantitative fluoride imaging of teeth using CaF emission by laser induced breakdown spectroscopy.

In this work, we propose the use of molecular emission of calcium fluoride (CaF) by laser induced breakdown spectroscopy (LIBS) to obtain quantitative fluoride distribution images of teeth. LIBS has proved to be an efficient technique to detect low amounts of fluoride in solids, and human teeth have the advantage being a matrix rich in calcium. We used new calibration material from sintered hydroxyapatite pellets doped with fluoride to determine the optimized LIBS conditions of argon flow at 1 L min-1 and using the green emission bands of CaF in 530 nm, and obtained a calibration curve between 0 and 400 µg g-1, and LOD of 18 µg g-1. This methodology was applied within a rat model of fluoride exposure and showed increasing tooth-fluoride with increased exposure dose. To demonstrate applicability of this method in human teeth, we quantified fluoride distribution in teeth from three children from non-fluorinated and fluorinated water regions. Samples from children living in fluoridated water regions showed higher fluoride concentrations in dentine formed after birth, compared to a child from a non-fluoridated region. Teeth have been used as biomarkers for environmental exposure and this new method opens the opportunity in epidemiology research to study critical windows of early life exposure to fluoride as well.

Prenatal Lead Exposure Is Associated with Reduced Abundance of Beneficial Gut Microbial Cliques in Late Childhood: An Investigation Using Microbial Co-Occurrence Analysis (MiCA).

Many analytical methods used in gut microbiome research focus on either single bacterial taxa or the whole microbiome, ignoring multibacteria relationships (microbial cliques). We present a novel analytical approach to identify microbial cliques within the gut microbiome of children at 9-11 years associated with prenatal lead (Pb) exposure. Data came from a subset of participants (n = 123) in the Programming Research in Obesity, Growth, Environment and Social Stressors cohort. Pb concentrations were measured in maternal whole blood from the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the gut microbiome. Using a novel analytical approach, Microbial Co-occurrence Analysis (MiCA), we paired a machine learning algorithm with randomization-based inference to first identify microbial cliques that were predictive of prenatal Pb exposure and then estimate the association between prenatal Pb exposure and microbial clique abundance. With second-trimester Pb exposure, we identified a two-taxa microbial clique that included Bifidobacterium adolescentis and Ruminococcus callidus and a three-taxa clique that also included Prevotella clara. Increasing second-trimester Pb exposure was associated with significantly increased odds of having the two-taxa microbial clique below the median relative abundance (odds ratio (OR) = 1.03, 95% confidence interval (CI) [1.01-1.05]). Using a novel combination of machine learning and causal inference, MiCA identified a significant association between second-trimester Pb exposure and the reduced abundance of a probiotic microbial clique within the gut microbiome in late childhood.

Air pollution and cardiovascular disease: Can the Australian bushfires and global COVID-19 pandemic of 2020 convince us to change our ways?

Air pollution is a major global challenge for a multitude of reasons. As a specific concern, there is now compelling evidence demonstrating a causal relationship between exposure to airborne pollutants and the onset of cardiovascular disease (CVD). As such, reducing air pollution as a means to decrease cardiovascular morbidity and mortality should be a global health priority. This review provides an overview of the cardiovascular effects of air pollution and uses two major events of 2020-the Australian bushfires and COVID-19 pandemic lockdown-to illustrate the relationship between air pollution and CVD. The bushfires highlight the substantial human and economic costs associated with elevations in air pollution. Conversely, the COVID-19-related lockdowns demonstrated that stringent measures are effective at reducing airborne pollutants, which in turn resulted in a potential reduction in cardiovascular events. Perhaps one positive to come out of 2020 will be the recognition that tough measures are effective at reducing air pollution and that these measures have the potential to stop thousands of deaths from CVD.

Using primary teeth and archived dried spots for exposomic studies in children: Exploring new paths in the environmental epidemiology of pediatric cancer.

It is estimated that 300,000 children 0-14 years of age are diagnosed with cancer worldwide each year. While the absolute risk of cancer in children is low, it is the leading cause of death due to disease in children in high-income countries. In spite of this, the etiologies of pediatric cancer are largely unknown. Environmental exposures have long been thought to play an etiologic role. However, to date, there are few well-established environmental risk factors for pediatric malignancies, likely due to technical barriers in collecting biological samples prospectively in pediatric populations for direct measurements. In this review, we propose the use of novel or underutilized biospecimens (dried blood spots and teeth) and molecular approaches for exposure assessment (epigenetics, metabolomics, and somatic mutational profiles). Future epidemiologic studies of pediatric cancer should incorporate novel exposure assessment methodologies, data on molecular features of tumors, and a more complete assessment of gene-environment interactions.

Prenatal air pollution influences neurodevelopment and behavior in autism spectrum disorder by modulating mitochondrial physiology.

We investigate the role of the mitochondrion, an organelle highly sensitive to environmental agents, in the influence of prenatal air pollution exposure on neurodevelopment and behavior in 96 children with autism spectrum disorder (ASD) [45 with neurodevelopmental regression (NDR); 76% Male; mean (SD) age 10 y 9 m (3 y 9 m)]. Mitochondrial function was assessed using the Seahorse XFe96 in fresh peripheral blood mononuclear cells. Second and third trimester average and maximal daily exposure to fine air particulate matter of diameter ≤2.5 µm (PM2.5) was obtained from the Environmental Protection Agency's Air Quality System. Neurodevelopment was measured using the Vineland Adaptive Behavior Scale 2nd edition and behavior was assessed using the Aberrant Behavior Checklist and Social Responsiveness Scale. Prenatal PM2.5 exposure influenced mitochondrial respiration during childhood, but this relationship was different for those with (r = 0.25-0.40) and without (r = -0.07 to -0.19) NDR. Mediation analysis found that mitochondrial respiration linked to energy production accounted for 25% (SD = 2%) and 10% (SD = 2%) of the effect of average prenatal PM2.5 exposure on neurodevelopment and behavioral symptoms, respectively. Structural equation models estimated that PM2.5 and mitochondrial respiration accounted for 34% (SD = 4%) and 36% (SD = 3%) of the effect on neurodevelopment, respectively, and that behavior was indirectly influenced by mitochondrial respiration through neurodevelopment but directly influenced by prenatal PM2.5. Our results suggest that prenatal exposure to PM2.5 disrupts neurodevelopment and behavior through complex mechanisms, including long-term changes in mitochondrial respiration and that patterns of early development need to be considered when studying the influence of environmental agents on neurodevelopmental outcomes.

Validated single urinary assay designed for exposomic multi-class biomarkers of common environmental exposures.

Epidemiological studies often call for analytical methods that use a small biospecimen volume to quantify trace level exposures to environmental chemical mixtures. Currently, as many as 150 polar metabolites of environmental chemicals have been found in urine. Therefore, we developed a multi-class method for quantitation of biomarkers in urine. A single sample preparation followed by three LC injections was optimized in a proof-of-approach for a multi-class method. The assay was validated to quantify 50 biomarkers of exposure in urine, belonging to 7 chemical classes and 16 sub-classes. The classes represent metabolites of 12 personal care and consumer product chemicals (PCPs), 5 polycyclic aromatic hydrocarbons (PAHs), 5 organophosphate flame retardants (OPFRs), 18 pesticides, 5 volatile organic compounds (VOCs), 4 tobacco alkaloids, and 1 drug of abuse. Human urine (0.2 mL) was spiked with isotope-labeled internal standards, enzymatically deconjugated, extracted by solid-phase extraction, and analyzed using high-performance liquid chromatography-tandem mass spectrometry. The methanol eluate from the cleanup was split in half and the first half analyzed for PCPs, PAH, and OPFR on a Betasil C18 column; and pesticides and VOC on a Hypersil Gold AQ column. The second half was analyzed for tobacco smoke metabolites and a drug of abuse on a Synergi Polar RP column. Limits of detection ranged from 0.01 to 1.0 ng/mL of urine, with the majority ≤0.5 ng/mL (42/50). Analytical precision, estimated as relative standard deviation of intra- and inter-batch uncertainty, variabilities, was <20%. Extraction recoveries ranged from 83 to 109%. Results from the optimized multi-class method were qualified in formal international proficiency testing programs. Further method customization options were explored and method expansion was demonstrated by inclusion of up to 101 analytes of endo- and exogenous chemicals. This exposome-scale assay is being used for population studies with savings of assay costs and biospecimens, providing both quantitative results and the discovery of unexpected exposures.

Biodynamic Interfaces Are Essential for Human-Environment Interactions.

The environment impacts human health in profound ways, yet few theories define the form of the relationship between human physiology and the environment. It is conjectured that such complex systems cannot interact directly, but rather their interaction requires the formation of an intermediary "interface." This position contrasts with current epidemiological constructs of causation, which implicitly assume that two complex systems transfer information directly while remaining separate entities. Further, it is contended that dynamic, process-based interfaces incorporate components from all the interacting systems but exhibit operational independence. This property has many consequences, the foremost being that characteristics of the interface cannot be fully resolved by only studying the systems involved in the interaction. The interface itself must be the subject of inquiry. Without refocusing the attention on biodynamic interfaces, how the environment impacts health cannot be discerned. Also see the video abstract here https://youtu.be/XeyjeZeyo4o.

A brief review of the current knowledge on environmental toxicants and risk of pediatric cancers.

The incidence of pediatric cancers has steadily increased since 1975, which could suggest that other exogenous factors are accounting for an increasing proportion of cases. There has been growing concern over environmental exposures (i.e., toxicants) the on development of pediatric cancers. However, identifying environmental exposures on childhood cancer risk has been challenging because these outcomes are infrequent compared to cancer in adults, and it is difficult to estimate exposure during specific critical periods of development (e.g., pre-conception, in utero, early childhood) that are likely more important for childhood cancer development. Here, we summarize the International Agency for Research on Cancer (IARC) Group 1 agents (toxicants known to be carcinogenic to humans), their routes of exposure, current methods for risk mitigation, and what is known of their associations with pediatric cancer risk. Our review suggests that environmental toxicants are important and potentially modifiable risk factors that need to be more fully explored in children and adolescents.

Dysregulated biodynamics in metabolic attractor systems precede the emergence of amyotrophic lateral sclerosis.

Evolutionarily conserved mechanisms maintain homeostasis of essential elements, and are believed to be highly time-variant. However, current approaches measure elemental biomarkers at a few discrete time-points, ignoring complex higher-order dynamical features. To study dynamical properties of elemental homeostasis, we apply laser ablation inductively-coupled plasma mass spectrometry (LA-ICP-MS) to tooth samples to generate 500 temporally sequential measurements of elemental concentrations from birth to 10 years. We applied dynamical system and Information Theory-based analyses to reveal the longest-known attractor system in mammalian biology underlying the metabolism of nutrient elements, and identify distinct and consistent transitions between stable and unstable states throughout development. Extending these dynamical features to disease prediction, we find that attractor topography of nutrient metabolism is altered in amyotrophic lateral sclerosis (ALS), as early as childhood, suggesting these pathways are involved in disease risk. Mechanistic analysis was undertaken in a transgenic mouse model of ALS, where we find similar marked disruptions in elemental attractor systems as in humans. Our results demonstrate the application of a phenomological analysis of dynamical systems underlying elemental metabolism, and emphasize the utility of these measures in characterizing risk of disease.

Network Dynamics in Elemental Assimilation and Metabolism.

Metabolism and physiology frequently follow non-linear rhythmic patterns which are reflected in concepts of homeostasis and circadian rhythms, yet few biomarkers are studied as dynamical systems. For instance, healthy human development depends on the assimilation and metabolism of essential elements, often accompanied by exposures to non-essential elements which may be toxic. In this study, we applied laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to reconstruct longitudinal exposure profiles of essential and non-essential elements throughout prenatal and early post-natal development. We applied cross-recurrence quantification analysis (CRQA) to characterize dynamics involved in elemental integration, and to construct a graph-theory based analysis of elemental metabolism. Our findings show how exposure to lead, a well-characterized toxicant, perturbs the metabolism of essential elements. In particular, our findings indicate that high levels of lead exposure dysregulate global aspects of metabolic network connectivity. For example, the magnitude of each element's degree was increased in children exposed to high lead levels. Similarly, high lead exposure yielded discrete effects on specific essential elements, particularly zinc and magnesium, which showed reduced network metrics compared to other elements. In sum, this approach presents a new, systems-based perspective on the dynamics involved in elemental metabolism during critical periods of human development.

Biological clocks and incremental growth line formation in dentine.

Dentine- and enamel-forming cells secrete matrix in consistent rhythmic phases, resulting in the formation of successive microscopic growth lines inside tooth crowns and roots. Experimental studies of various mammals have proven that these lines are laid down in subdaily, daily (circadian), and multidaily rhythms, but it is less clear how these rhythms are initiated and maintained. In 2001, researchers reported that lesioning the so-called master biological clock, the suprachiasmatic nucleus (SCN), halted daily line formation in rat dentine, whereas subdaily lines persisted. More recently, a key clock gene (Bmal1) expressed in the SCN in a circadian manner was also found to be active in dentine- and enamel- secretory cells. To probe these potential neurological and local mechanisms for the production of rhythmic lines in teeth, we reexamined the role of the SCN in growth line formation in Wistar rats and investigated the presence of daily lines in Bmal1 knockout mice (Bmal1-/- ). In contrast to the results of the 2001 study, we found that both daily and subdaily growth lines persisted in rat dentine after complete or partial SCN lesion in the majority of individuals. In mice, after transfer into constant darkness, daily rhythms continued to manifest as incremental lines in the dentine of each Bmal1 genotype (wild-type, Bmal+/- , and Bmal1-/- ). These results affirm that the manifestation of biological rhythms in teeth is a robust phenomenon, imply a more autonomous role of local biological clocks in tooth growth than previously suggested, and underscore the need further to elucidate tissue-specific circadian biology and its role in incremental line formation. Investigations of this nature will strengthen an invaluable system for determining growth rates and calendar ages from mammalian hard tissues, as well as documenting the early lives of fossil hominins and other primates.

Exposure to environmental chemical mixtures is associated with nasal colonization by Staphylococcus aureus: NHANES 2001-2004.

BACKGROUND: Understanding the health effects of exposure to chemical mixtures is critically important given the broad range of concurrent exposures throughout the life-course. While investigations of environmental chemicals and components of the human microbiome are becoming more common, few have examined associations with chemical mixtures. This study assesses the association between exposure to mixtures of 66 different environmental chemicals and nasal colonization of Staphylococcus aureus (SA) and methicillin resistant SA (MRSA). METHODS: Data came from the National Health and Nutrition Examination Survey (NHANES) 2001-2004. The analytical sample consists of 10,312 participants, age 6 years and older, subdivided into 8 groups with different chemical exposure mixtures. Within each of 6 chemical classes (metals, phthalates, polycyclic aromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), polyfluorochemicals (PFCs), and phenols), weighted quantile sum (WQS) regression was used to analyze the joint association of the component compounds and nasal SA colonization. WQS was also used to assess the joint association of 3 chemical mixtures (metals, metal and PAHs, and metal and triclosan) and nasal MRSA colonization. All regression models were adjusted for confounders. RESULTS: The analytical sample was between ages 6-85, slightly more female, and predominantly non-smokers. Prevalence of SA carriage was 29.2%, and MRSA colonization prevalence was 1.2%. Within each chemical class, odds of SA colonization increased statistically significantly with exposure to mixtures of metals (OR = 1.11, 95% CI = 1.02-1.20), phthalates (OR = 1.09, 95% CI = 1.04-1.14), and phenols (OR = 1.08, 95% CI = 1.01-1.15). Exposure to a mixture of metals combined with PAHs was also associated with increased odds of MRSA carriage (OR = 1.38, 95% CI = 1.02-1.86). CONCLUSION: Results indicate an association between multiple environmental chemical mixtures and SA colonization, including MRSA. These findings support the need for further analysis of associations between chemical mixtures and SA colonization, as well as other components of the human microbiome.

Lagged WQS regression for mixtures with many components.

The developmental timing of exposures to toxic chemicals or combinations of chemicals may be as important as the dosage itself. This concept is called "critical windows of exposure." The time boundaries of such windows can be detected if exposure data are collected repeatedly in short time intervals. The development of tooth-matrix biomarkers which provide prenatal and postnatal exposure measures in repeated intervals can provide such data. Using teeth, we use reverse distributed lagged models (DLMs) to incorporate weekly prenatal and postnatal measures of exposures to estimate time-varying associations with developmental effects. The analysis of such data using lagged weighted quantile sum (WQS) regression as an extension to reverse DLMs for complex mixtures was first proposed by Bello et al. This prior algorithm was not operationally generalizable to large numbers of components (say, more than five or six). We propose a revised algorithm that may be useful for larger mixtures by combining time-specific WQS(t) indices in a reverse DLM. We demonstrate the new algorithm using tooth data in association with a neurodevelopmental score and in simulated data from 3 cases wherein different components of a mixture have time varying associations and in the case where none have associations. The new algorithm correctly detects the simulated associations when the number of samples within the time-specific analyses is moderate to large.

Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures.

The impact of neurotoxic chemical mixtures on children's health is a critical public health concern. It is well known that during early life, toxic exposures may impact cognitive function during critical time intervals of increased vulnerability, known as windows of susceptibility. Knowledge on time windows of susceptibility can help inform treatment and prevention strategies, as chemical mixtures may affect a developmental process that is operating at a specific life phase. There are several statistical challenges in estimating the health effects of time-varying exposures to multi-pollutant mixtures, such as: multi-collinearity among the exposures both within time points and across time points, and complex exposure-response relationships. To address these concerns, we develop a flexible statistical method, called lagged kernel machine regression (LKMR). LKMR identifies critical exposure windows of chemical mixtures, and accounts for complex non-linear and non-additive effects of the mixture at any given exposure window. Specifically, LKMR estimates how the effects of a mixture of exposures change with the exposure time window using a Bayesian formulation of a grouped, fused lasso penalty within a kernel machine regression (KMR) framework. A simulation study demonstrates the performance of LKMR under realistic exposure-response scenarios, and demonstrates large gains over approaches that consider each time window separately, particularly when serial correlation among the time-varying exposures is high. Furthermore, LKMR demonstrates gains over another approach that inputs all time-specific chemical concentrations together into a single KMR. We apply LKMR to estimate associations between neurodevelopment and metal mixtures in Early Life Exposures in Mexico and Neurotoxicology, a prospective cohort study of child health in Mexico City.

Mass defect filtering for suspect screening of halogenated environmental chemicals: A case study of chlorinated organophosphate flame retardants.

RATIONALE: Organophosphate flame retardants (OPFRs) are a class of flame retardants widely found in environmental and biological matrices that have been extensively studied due to their adverse health effects in humans. OPFRs are loosely bound chemicals that can detach from treated products and be released into indoor and outdoor environments, where they have the potential to further undergo transformation and degradation processes, in particular the chlorinated OPFRs (Cl-PFRs). Their detection remains a moving target for analysts, and traditional targeted mass spectrometry methods are suitable only for those compounds with authentic standards. METHODS: Mass defect filter (MDF) is a strategy to filter molecular features using thresholds applied to the mass defect value of a target ion or molecular feature of interest. We have developed an MDF strategy for the detection and tentative identification of twelve potential Cl-PFR transformation products in a study mixture of six known Cl-PFRs using MS/MS data acquired on a high-resolution mass spectrometer. Most compounds in the Cl-PFRs family share a ClO4 P group as a core structure, of which modification results in a significant shift in the exact masses of the resulting compounds but show only a minimal shift in their mass defects. Subsequently, the MDF strategy was employed to tentatively identify Cl-PFRs retrospectively in six human urine samples that had previously been analyzed. RESULTS: MDF in combination with product ion filtering for the characteristic [H2 O3 P]+ and [H4 O4 P]+ ions and neutral loss filtering for the characteristic Cn H2n-x Clx group resulted in revealing suspects and homologues in the Cl-PFRs family. Furthermore, the MDF of the product ions detected additional Cl-PFR-related compounds that differed significantly in the exact masses of both precursor and product ions but had minimal shift in the mass defects of product ions. The mass defect of one or more common product ions helped to detect a few Cl-PFR analogs that had not been identified by MDF of the core structure precursor ion. CONCLUSIONS: MDF helped to detect some Cl-PFRs present in lower concentrations, which went undetected without data filters. MDF also helped to detect chromatographic peaks for Cl-PFR homologues that are likely structural analogs that resulted from impurities and/or derivatives and transformation products. The methodology was applied to demonstrate and tentatively detect known and suspect Cl-PFRs in human urine samples retrospectively.

Lead and Arsenic in Shed Deciduous Teeth of Children Living Near a Lead-Acid Battery Smelter.

Lead (Pb) is a potent neurotoxicant with no safe level of exposure. Elevated levels of Pb and arsenic (As) are found in the air and soil near facilities that recycle lead-acid batteries in the United States. In urban Los Angeles County, California, a facility processed ∼11 million batteries per year and operated for decades without proper environmental review. Measuring Pb and As in shed deciduous teeth is a promising technique to assess prenatal and early life exposure. In this pilot study coined the "Truth Fairy" Project, 50 shed deciduous teeth from 43 children living their entire lives within 2 miles of the smelter were analyzed to understand retrospective exposure to toxic metals using a community-driven research approach. Concentrations of Pb and As in teeth were assessed using laser-ablation-inductively coupled plasma-mass spectrometry. Soil Pb concentrations were determined using spatial kriging of surface soil measurements. The mean prenatal calcium normalized Pb levels in teeth samples (reported as a ratio 208Pb:43Ca) was 4.104 × 10-4 (SD 4.123 × 10-4), and the mean postnatal 208Pb:43Ca level was 4.109 × 10-4 (SD 3.369 × 10-4). Adjusted for maternal education and batch, we observe positive significant relationship between prenatal teeth Pb per 100 ppm increase in soil Pb (ß = 3.48, 95% CI 1.11, 5.86). The Truth Fairy study suggests prenatal and early life exposure to toxic metals is associated with legacy soil contamination in an urban community near a smelter.

Barium distributions in teeth reveal early-life dietary transitions in primates.

Early-life dietary transitions reflect fundamental aspects of primate evolution and are important determinants of health in contemporary human populations. Weaning is critical to developmental and reproductive rates; early weaning can have detrimental health effects but enables shorter inter-birth intervals, which influences population growth. Uncovering early-life dietary history in fossils is hampered by the absence of prospectively validated biomarkers that are not modified during fossilization. Here we show that large dietary shifts in early life manifest as compositional variations in dental tissues. Teeth from human children and captive macaques, with prospectively recorded diet histories, demonstrate that barium (Ba) distributions accurately reflect dietary transitions from the introduction of mother's milk through the weaning process. We also document dietary transitions in a Middle Palaeolithic juvenile Neanderthal, which shows a pattern of exclusive breastfeeding for seven months, followed by seven months of supplementation. After this point, Ba levels in enamel returned to baseline prenatal levels, indicating an abrupt cessation of breastfeeding at 1.2 years of age. Integration of Ba spatial distributions and histological mapping of tooth formation enables novel studies of the evolution of human life history, dietary ontogeny in wild primates, and human health investigations through accurate reconstructions of breastfeeding history.