Extending Regulatory Biokinetic Lead Models towards Food Safety: Evaluation of Consumer Baby Food Contribution to Infant Blood Lead Levels and Variability.

The U.S. Food and Drug Administration released proposed lead (Pb) action levels for foods intended for babies and young children in January 2023 based on the agency's interim reference value of 2.2 µg/day for dietary Pb. Since the 1980s, biokinetic models have estimated blood lead levels (BLLs) associated with environmental contamination, but their use in food safety assessment has been limited. We compared three recent biokinetic models (IEUBK Model, ICRP Model Version 5, and AALM) to develop insights on contributors to variability in potential exposures to Pb in consumer baby food products. While modest variation was observed for babies, the predictions trended to convergence for children aged 3 and older, approaching the U.S. FDA dietary conversion factor of 0.16 µg Pb/dL blood per µg Pb intake/day. We applied the IEUBK model in a probabilistic exposure assessment framework characterizing the distribution of Pb in soil, dust, water, and food intake in the United States. Soil and dust were the primary contributors to variance in infant BLLs, while food and water contributed <15% combined. Thus, reductions in upper-bound soil and dust concentrations will be necessary before achieving appreciable reductions in the frequency of BLLs greater than the BLRV of 3.5 µg/dL.

Refinement of a microfurnace pyrolysis-GC-MS method for quantification of tire and road wear particles (TRWP) in sediment and solid matrices.

Tire and road wear particles (TRWP) are produced by abrasion at the interface of the pavement and tread surface and contain tread rubber with road mineral encrustations. Quantitative thermoanalytical methods capable of estimating TRWP concentrations are needed to assess the prevalence and environmental fate of these particles. However, the presence of complex organic constituents in sediment and other environmental samples presents a challenge to the reliable determination of TRWP concentrations using current pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) methodologies. We are unaware of a published study evaluating pretreatment and other method refinements for microfurnace Py-GC-MS analysis of the elastomeric polymers in TRWP including polymer-specific deuterated internal standards as specified in ISO Technical Specification (ISO/TS) 20593:2017 and ISO/TS 21396:2017. Thus, potential method refinements were evaluated for microfurnace Py-GC-MS, including chromatography parameter modification, chemical pretreatment, and thermal desorption for cryogenically-milled tire tread (CMTT) samples in an artificial sediment matrix and a sediment field sample. The tire tread dimer markers used for quantification were 4-vinylcyclohexene (4-VCH), a marker for styrene-butadiene rubber (SBR) and butadiene rubber (BR), 4-phenylcyclohexene (4-PCH), a marker for SBR, and dipentene (DP), a marker for natural rubber (NR) or isoprene. The resultant modifications included optimization of GC temperature and mass analyzer settings, along with sample pretreatment with potassium hydroxide (KOH) and thermal desorption. Peak resolution was improved while minimizing matrix interferences with overall accuracy and precision consistent with those typically observed in environmental sample analysis. The initial method detection limit for an artificial sediment matrix was approximately 180 mg/kg for a 10 mg sediment sample. A sediment and a retained suspended solids sample were also analyzed to illustrate the applicability of microfurnace Py-GC-MS towards complex environmental sample analysis. These refinements should help encourage the adoption of pyrolysis techniques for mass-based measurements of TRWP in environmental samples both near and distant from roadways.

Assessment of ethanol exposure from hand sanitizer use and potential for developmental toxicity in nursing infants.

Ingestion of ethanol during pregnancy is known to have detrimental effects on the fetus. Although the potential developmental effects of maternal ethanol intake during lactation are less well characterized, public health guidelines recommend avoidance of alcohol or, if alcohol is consumed, to allow for 1-2 h to pass before nursing. A proposal to classify ethanol as potentially harmful to breast-fed children warrants an investigation of the potential adverse neurodevelopmental effects of low-dose ethanol exposure during lactation. There currently are no studies that have examined neurodevelopmental outcomes from lactational exposure to ethanol from the use of topical products that contain ethanol, such as alcohol-based hand sanitizers (ABHS). Furthermore, the epidemiological literature of lactational ethanol exposures from maternal alcohol consumption is limited in design, provides equivocal evidence of neurological effects in infants, and is insufficient to characterize a dose-response relationship for developmental effects. Toxicological studies that observed neurodevelopmental effects in pups from ethanol via lactation did so at exceedingly high doses that also caused maternal toxicity. In this investigation, blood ethanol concentrations (BECs) of breastfeeding women following typical-to-intense ABHS use were computationally predicted and compared to health benchmarks to quantify the risk for developmental outcomes. Margins of 2.2 to 1000 exist between BECs associated with ABHS use compared to BECs associated with neurotoxicity adverse effect levels in the toxicology literature or oral ethanol intake per public health guidelines. Neurodevelopmental effects are not likely to occur in infants due to ABHS use by breastfeeding women, even when ABHSs are used at intense frequencies.

PBPK modeling characterization of potential acute impairment effects from inhalation of ethanol during e-cigarette use.

Objective: Ethanol is used as a solvent for flavoring chemicals in some electronic cigarette (e-cigarette) liquids (e-liquids). However, there are limited data available regarding the effects of inhalation of ethanol on blood alcohol concentration (BAC) during e-cigarette use. In this study, a modified physiologically based pharmacokinetic (PBPK) model for inhalation of ethanol was used to estimate the BAC time-profile of e-cigarette users who puffed an e-liquid containing 23.5% ethanol. Materials and Methods: A modified PBPK model for inhalation of ethanol was developed. Use characteristics were estimated based on first-generation and second-generation e-cigarette topography parameters. Three representative use-case puffing profiles were modeled: a user that took many, short puffs; a typical user with intermediate puff counts and puff durations; and a user that took fewer, long puffs. Results and Discussion: The estimated peak BACs for these three user profiles were 0.22, 0.22, and 0.30 mg/L for first-generation devices, respectively, and 0.85, 0.58, and 0.34 mg/L for second-generation devices, respectively. Additionally, peak BACs for individual first-generation users with directly measured puffing parameters were estimated to range from 0.06 to 0.67 mg/L. None of the scenarios modeled predicted a peak BAC result that approached toxicological or regulatory thresholds that would be associated with physiological impairment (roughly 0.01% or 100 mg/L). Conclusions: The approach used in this study, combining a validated PBPK model for a toxicant with peer-reviewed topographical parameters, can serve as a screening-level exposure assessment useful for evaluation of the safety of e-liquid formulations. Abbreviations: BAC: blood alcohol concentration; e-cigarette: electronic cigarette; e-liquid: e-cigarette liquid or propylene glycol and/or vegetable glycerin-based liquid; HS-GC-FID: headspace gas chromatography with flame-ionization detection; HS-GC-MS: headspace gas chromatography-mass spectrometry; PBPK: physiologically based pharmacokinetic; Cair: puff concentration expressed as ppm; Cair,mass: ethanol air concentration expressed on a mass basis; Cv: ethanol concentration in the venous blood; ρ: density; EC: ethanol concentration in the liquid; PLC: liquid consumption per puff; PAV: air volume of the puff; Cair,mass: puff concentration expressed as ppm; MW: molecular weight; P: pressure; T: temperature; PK: pharmacokinetic.