A review of sample collection and analytical methods for detecting per- and polyfluoroalkyl substances in indoor and outdoor air.

Per- and polyfluoroalkyl substances (PFAS) are a unique class of chemicals synthesized to aid in industrial processes, fire-fighting products, and to benefit consumer products such as clothing, cosmetics, textiles, carpets, and coatings. The widespread use of PFAS and their strong carbon-fluorine bonds has led to their ubiquitous presence throughout the world. Airborne transport of PFAS throughout the atmosphere has also contributed to environmental pollution. Due to the potential environmental and human exposure concerns of some PFAS, research has extensively focused on water, soil, and organismal detection, but the presence of PFAS in the air has become an area of growing concern. Methods to measure polar PFAS in various matrices have been established, while the investigation of polar and nonpolar PFAS in air is still in its early development. This literature review aims to present the last two decades of research characterizing PFAS in outdoor and indoor air, focusing on active and passive air sampling and analytical methods. The PFAS classes targeted and detected in air samples include fluorotelomer alcohols (FTOHs), perfluoroalkane sulfonamides (FASAs), perfluoroalkane sulfonamido ethanols (FASEs), perfluorinated carboxylic acids (PFCAs), and perfluorinated sulfonic acids (PFSAs). Although the manufacturing of perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) has been largely phased out, these two PFAS are still often detected in air samples. Additionally, recent estimates indicate that there are thousands of PFAS that are likely present in the air that are not currently monitored in air methods. Advances in air sampling methods are needed to fully characterize the atmospheric transport of PFAS.

Molecular phylogeny and divergence time of Harpalyce (Leguminosae, Papilionoideae), a lineage with amphitropical diversification in seasonally dry forests and savannas.

Our knowledge of the systematics of the papilionoid legume tribe Brongniartieae has greatly benefitted from recent advances in molecular phylogenetics. The tribe was initially described to include species marked by a strongly bilabiate calyx and an embryo with a straight radicle, but recent research has placed taxa from the distantly related core Sophoreae and Millettieae within it. Despite these advances, the most species-rich genera within the Brongniartieae are still not well studied, and their morphological and biogeographical evolution remains poorly understood. Comprising 35 species, Harpalyce is one of these poorly studied genera. In this study, we present a comprehensive, multi-locus molecular phylogeny of the Brongniartieae, with an increased sampling of Harpalyce, to investigate morphological and biogeographical evolution within the group. Our results confirm the monophyly of Harpalyce and indicate that peltate glandular trichomes and a strongly bilabiate calyx with a carinal lip and three fused lobes are synapomorphies for the genus, which is internally divided into three distinct ecologically and geographically divergent lineages, corresponding to the previously recognized sections. Our biogeographical reconstructions demonstrate that Brongniartieae originated in South America during the Eocene, with subsequent pulses of diversification in South America, Mesoamerica, and Australia. Harpalyce also originated in South America during the Miocene at around 20 Ma, with almost synchronous later diversification in South America and Mexico/Mesoamerica beginning 10 Ma, but mostly during the Pliocene. Migration of Harpalyce from South to North America was accompanied by a biome and ecological shift from savanna to seasonally dry forest.

Accurate, automated taxonomic assignment of genebank accessions: a new method demonstrated using high-throughput marker data from 10,000 Capsicum spp. accessions.

KEY MESSAGE: We demonstrate how an algorithm that uses cheap genetic marker data can ensure the taxonomic assignments of genebank samples are complete, intuitive, and consistent-which enhances their value. To maximise the benefit of genebank resources, accurate and complete taxonomic assignments are imperative. The rise of genebank genomics allows genetic methods to be used to ensure this, but these need to be largely automated since the number of samples dealt with is too great for efficient manual recategorisation, however no clearly optimal method has yet arisen. A recent landmark genebank genomic study sequenced over 10,000 genebank accessions of peppers (Capsicum spp.), a species of great commercial, cultural, and scientific importance, which suffers from much taxonomic ambiguity. Similar datasets will, in coming decades, be produced for hundreds of plant taxa, affording a perfect opportunity to develop automated taxonomic correction methods in advance of the incipient genebank genomics explosion, alongside providing insights into pepper taxonomy in general. We present a marker-based taxonomic assignment approach that combines ideas from several standard classification algorithms, resulting in a highly flexible and customisable classifier suitable to impose intuitive assignments, even in highly reticulated species groups with complex population structures and evolutionary histories. Our classifier performs favourably compared with key alternative methods. Possible sensible alterations to pepper taxonomy based on the results are proposed for discussion by the relevant communities.

Analysis of >3400 worldwide eggplant accessions reveals two independent domestication events and multiple migration-diversification routes.

Eggplant (Solanum melongena) is an important Solanaceous crop, widely cultivated and consumed in Asia, the Mediterranean basin, and Southeast Europe. Its domestication centers and migration and diversification routes are still a matter of debate. We report the largest georeferenced and genotyped collection to this date for eggplant and its wild relatives, consisting of 3499 accessions from seven worldwide genebanks, originating from 105 countries in five continents. The combination of genotypic and passport data points to the existence of at least two main centers of domestication, in Southeast Asia and the Indian subcontinent, with limited genetic exchange between them. The wild and weedy eggplant ancestor S. insanum shows admixture with domesticated S. melongena, similar to what was described for other fruit-bearing Solanaceous crops such as tomato and pepper and their wild ancestors. After domestication, migration and admixture of eggplant populations from different regions have been less conspicuous with respect to tomato and pepper, thus better preserving 'local' phenotypic characteristics. The data allowed the identification of misclassified and putatively duplicated accessions, facilitating genebank management. All the genetic, phenotypic, and passport data have been deposited in the Open Access G2P-SOL database, and constitute an invaluable resource for understanding the domestication, migration and diversification of this cosmopolitan vegetable.

Prolonged voluntary wheel running reveals unique adaptations in mdx mice treated with microdystrophin constructs ± the nNOS-binding site.

We tested the effects of prolonged voluntary wheel running on the muscle function of mdx mice treated with one of two different microdystrophin constructs. At 7 weeks of age mdx mice were injected with a single dose of AAV9-CK8-microdystrophin with (gene therapy 1, GT1) or without (gene therapy 2, GT2) the nNOS-binding domain and were assigned to one of four gene therapy treated groups: mdxRGT1 (run, GT1), mdxGT1 (no run, GT1), or mdxRGT2 (run,GT2), mdxGT2 (no run, GT2). There were two mdx untreated groups injected with excipient: mdxR (run, no gene therapy) and mdx (no run, no gene therapy). A third no treatment group, Wildtype (WT) received no injection and did not run. mdxRGT1, mdxRGT2 and mdxR performed voluntary wheel running for 52 weeks; WT and remaining mdx groups were cage active. Robust expression of microdystrophin occurred in diaphragm, quadriceps, and heart muscles of all treated mice. Dystrophic muscle pathology was high in diaphragms of non-treated mdx and mdxR mice and improved in all treated groups. Endurance capacity was rescued by both voluntary wheel running and gene therapy alone, but their combination was most beneficial. All treated groups increased in vivo plantarflexor torque over both mdx and mdxR mice. mdx and mdxR mice displayed ∼3-fold lower diaphragm force and power compared to WT values. Treated groups demonstrated partial improvements in diaphragm force and power, with mdxRGT2 mice experiencing the greatest improvement at ∼60% of WT values. Evaluation of oxidative red quadriceps fibers revealed the greatest improvements in mitochondrial respiration in mdxRGT1 mice, reaching WT levels. Interestingly, mdxGT2 mice displayed diaphragm mitochondrial respiration values similar to WT but mdxRGT2 animals showed relative decreases compared to the no run group. Collectively, these data demonstrate that either microdystrophin construct combined with voluntary wheel running increased in vivo maximal muscle strength, power, and endurance. However, these data also highlighted important differences between the two microdystrophin constructs. GT1, with the nNOS-binding site, improved more markers of exercise-driven adaptations in metabolic enzyme activity of limb muscles, while GT2, without the nNOS-binding site, demonstrated greater protection of diaphragm strength after chronic voluntary endurance exercise but decreased mitochondrial respiration in the context of running.

Low temperature destruction of gas-phase per- and polyfluoroalkyl substances using an alumina-based catalyst.

Per- and polyfluoroalkyl substances (PFAS) pose a major health and environmental problem. Methods are needed to ensure that PFAS are not released into the environment during their use or disposal. Alumina-based catalysts have been used for the abatement of small perfluorocarbons, e.g. tetrafluoromethane and perfluoropropane, emitted during the silicon etching process. Here, an alumina-based catalyst was tested to determine if these catalysts may facilitate the destruction of gas-phase PFAS. The catalyst was challenged with two nonionic surfactants with eight fluorinated carbons, 8:2 fluorotelomer alcohol and N-Ethyl-N-(2-hydroxyethyl)perfluorooctylsulfonamide. The catalyst helped decrease the temperatures needed for the destruction of the parent PFAS relative to a thermal-only treatment. Temperatures of 200°C were sufficient to destroy the parent PFAS using the catalyst, although a significant number of fluorinated products of incomplete destruction (PIDs) were observed. The PIDs were no longer observed by about 500°C with catalyst treatment. Alumina-based catalysts are a promising PFAS pollution control technology that could eliminate both perfluorocarbons and longer chain PFAS from gas streams.Implications: The release of per- and polyfluoroalkyl substances (PFAS) into the atmosphere can cause problems for human health and the environment. It is critical to reduce and eliminate PFAS emissions from potential sources, such as manufacturers, destruction technologies, and fluoropolymer processing and application sites. Here, an alumina-based catalyst was used to eliminate the emissions of two gas-phase PFAS with eight fully fluorinated carbons. No PFAS were observed in the emissions when the catalyst was at 500°C, lowering the energy requirements for PFAS destruction. This shows that alumina-based catalysts are a promising area for research for PFAS pollution controls and the elimination of PFAS emissions into the atmosphere.

Characterization of PFAS air emissions from thermal application of fluoropolymer dispersions on fabrics.

During thermal processes utilized in affixing fluoropolymer coatings dispersion to fibers and fabrics, coating components are vaporized. It is suspected that per- and polyfluoroalkyl substances (PFAS) from the dispersions may undergo chemical transformations at the temperatures used, leading to additional emitted PFAS thermal byproducts. It is important to characterize these emissions to support evaluation of the resulting environmental and health impacts. In this study, a bench-scale system was built to simulate this industrial process via thermal application of dispersions to fiberglass utilizing relevant temperatures and residence times in sequential drying, baking, and sintering steps. Experiments were performed with two commercially available dispersions and a simple model mixture containing a single PFAS (6:2 fluorotelomer alcohol [6:2 FTOH]). Vapor-phase emissions were sampled and characterized by several off-line and real-time mass spectrometry techniques for targeted and nontargeted PFAS. Results indicate that multiple PFAS thermal transformation products and multiple nonhalogenated organic species were emitted from the exit of the high temperature third (sintering) furnace when 6:2 FTOH was the only PFAS present in the aqueous mixture. This finding supports the hypothesis that temperatures typical of these industrial furnaces may also induce chemical transformations within the fluorinated air emissions. Experiments using the two commercial fluoropolymer dispersions indicate air emissions of part-per-million by volume (ppmv) concentrations of heptafluoropropyl-1,2,2,2-tetrafluoroethyl ether (Fluoroether E1), as well as other PFAS at operationally relevant temperatures. We suspect that E1 is a direct thermal decomposition product (via decarboxylation) of 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)propanoic acid (commonly referred to as HFPO-DA) present in the dispersions. Other thermal decomposition products, including the monomer, tetrafluoroethene, may originate from the PFAS used to stabilize the dispersion or from the polymer particles in suspension. This study represents the first researcher-built coating application simulator to report nontargeted PFAS emission characterization, real-time analyses, and the quantification of 30 volatile target PFAS.Implications: Thermal processes used to affix fluoropolymers to fabrics are believed to be a source of PFAS air emissions. These coating operations are used by many large and small manufacturers and typically do not currently require any air emissions control. This research designed and constructed a bench-scale system that simulates these processes and used several off-line and advanced real-time mass spectroscopy techniques to characterize PFAS air emissions from two commercial fluoropolymer dispersions. Further, as the compositions of commercial dispersions are largely unknown, a model three-component solution containing a single PFAS was used to characterize emissions of multiple PFAS thermal transformation products at operationally relevant conditions. This research shows that fluoropolymer fabric coating facilities can be sources of complex mixtures of PFAS air emissions that include volatile and semivolatile PFAS present in the dispersions, as well as PFAS byproducts formed by the thermal transformation of fluorocarbon and hydrocarbon species present in these dispersions.

Fish and chips: Using machine learning to estimate the effects of basal cortisol on fish foraging behavior.

Foraging is an essential behavior for animal survival and requires both learning and decision-making skills. However, despite its relevance and ubiquity, there is still no effective mathematical framework to adequately estimate foraging performance that also takes interindividual variability into account. In this work, foraging performance is evaluated in the context of multi-armed bandit (MAB) problems by means of a biological model and a machine learning algorithm. Siamese fighting fish (Betta splendens) were used as a biological model and their ability to forage was assessed in a four-arm cross-maze over 21 trials. It was observed that fish performance varies according to their basal cortisol levels, i.e., a reduced average reward is associated with low and high levels of basal cortisol, while the optimal level maximizes foraging performance. In addition, we suggest the adoption of the epsilon-greedy algorithm to deal with the exploration-exploitation tradeoff and simulate foraging decisions. The algorithm provided results closely related to the biological model and allowed the normalized basal cortisol levels to be correlated with a corresponding tuning parameter. The obtained results indicate that machine learning, by helping to shed light on the intrinsic relationships between physiological parameters and animal behavior, can be a powerful tool for studying animal cognition and behavioral sciences.

2nd and 3rd order spectral energy corrections with penumbral de-blurring methodology for opacity platform used on the National Ignition Facility.

The Opacity Spectrometer (OpSpec) used in the National Ignition Facility's opacity experiments measures x-ray spectra from 0.9 to 2.1 keV from the different experimental regions: the backlight source, emission source, and the absorption region with the transmission calculated from these regions. The OpSpec designs have gone through several iterations to help improve the signal-to-noise ratio, remove alternate crystal plane reflections, and improve spectral resolution, which helps to increase the validity of the opacity measurements. However, the source spans well outside the current working spectral range, and higher-order reflections are intrinsic to the crystal, which increases the overall signal seen in the data regions. The recorded data are the convolution of 1st order transmission, higher-order reflections, and the penumbra blurring. This work represents the details for deconvolving the 2nd and 3rd order spectral energy corrections with a penumbral de-blurring to correct the relative measurement of x-ray intensity of different spectral energies and further analysis of datasets relevant to the opacity experiments.

The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis.

BACKGROUND: Racial inequities in maternal mortality in the U.S. continue to be stark. METHODS: The 2015-2018, 4-year total population, county-level, pregnancy-related mortality ratio (PRM; deaths per 100,000 live births; National Center for Health Statistics (NCHS), restricted use mortality file) was linked with the Public Health Exposome (PHE). Using data reduction techniques, 1591 variables were extracted from over 62,000 variables for use in this analysis, providing information on the relationships between PRM and the social, health and health care, natural, and built environments. Graph theoretical algorithms and Bayesian analysis were applied to PHE/PRM linked data to identify latent networks. RESULTS: PHE variables most strongly correlated with total population PRM were years of potential life lost and overall life expectancy. Population-level indicators of PRM were overall poverty, smoking, lack of exercise, heat, and lack of adequate access to food. CONCLUSIONS: In this high-dimensional analysis, overall life expectancy, poverty indicators, and health behaviors were found to be the strongest predictors of pregnancy-related mortality. This provides strong evidence that maternal death is part of a broader constellation of both similar and unique health behaviors, social determinants and environmental exposures as other causes of death.

Sub-keV design for the National Ignition Facility's soft x-ray Opacity Spectrometer (OpSpec) and expansion plans for time-resolved measurements.

When compared with the National Ignition Facility's (NIF) original soft x-ray opacity spectrometer, which used a convex cylindrical design, an elliptically shaped design has helped to increase the signal-to-noise ratio and eliminated nearly all reflections from alternate crystal planes. The success of the elliptical geometry in the opacity experiments has driven a new elliptical geometry crystal with a spectral range covering 520-1100 eV. When coupled with the primary elliptical geometry, which spans 1000-2100 eV, the new sub-keV elliptical geometry helps to cover the full iron L-shell and major oxygen transitions important to solar opacity experimentation. The new design has been built and tested by using a Henke x-ray source and shows the desired spectral coverage. Additional plans are underway to expand these opacity measurements into a mode of time-resolved detection, ∼1 ns gated, but considerations for the detector size and photometrics mean a crystal geometry redesign. The new low-energy geometry, including preliminary results from the NIF opacity experiments, is presented along with the expansion plans into a time-resolved platform.

Blood-Based Biomarkers of Repetitive, Subconcussive Blast Overpressure Exposure in the Training Environment: A Pilot Study.

Because of their unknown long-term effects, repeated mild traumatic brain injuries (TBIs), including the low, subconcussive ones, represent a specific challenge to healthcare systems. It has been hypothesized that they can have a cumulative effect, and they may cause molecular changes that can lead to chronic degenerative processes. Military personnel are especially vulnerable to consequences of subconcussive TBIs because their training involves repeated exposures to mild explosive blasts. In this pilot study, we collected blood samples at baseline, 6 h, 24 h, 72 h, 2 weeks, and 3 months after heavy weapons training from students and instructors who were exposed to repeated subconcussive blasts. Samples were analyzed using the reverse and forward phase protein microarray platforms. We detected elevated serum levels of glial fibrillary acidic protein, ubiquitin C-terminal hydrolase L1 (UCH-L1), nicotinic alpha 7 subunit (CHRNA7), occludin (OCLN), claudin-5 (CLDN5), matrix metalloprotease 9 (MMP9), and intereukin-6 (IL-6). Importantly, serum levels of most of the tested protein biomarkers were the highest at 3 months after exposures. We also detected elevated autoantibody titers of proteins related to vascular and neuroglia-specific proteins at 3 months after exposures as compared to baseline levels. These findings suggest that repeated exposures to subconcussive blasts can induce molecular changes indicating not only neuron and glia damage, but also vascular changes and inflammation that are detectable for at least 3 months after exposures whereas elevated titers of autoantibodies against vascular and neuroglia-specific proteins can indicate an autoimmune process.

Neural Transformers for Intraductal Papillary Mucosal Neoplasms (IPMN) Classification in MRI images.

Early detection of precancerous cysts or neoplasms, i.e., Intraductal Papillary Mucosal Neoplasms (IPMN), in pancreas is a challenging and complex task, and it may lead to a more favourable outcome. Once detected, grading IPMNs accurately is also necessary, since low-risk IPMNs can be under surveillance program, while high-risk IPMNs have to be surgically resected before they turn into cancer. Current standards (Fukuoka and others) for IPMN classification show significant intra- and inter-operator variability, beside being error-prone, making a proper diagnosis unreliable. The established progress in artificial intelligence, through the deep learning paradigm, may provide a key tool for an effective support to medical decision for pancreatic cancer. In this work, we follow this trend, by proposing a novel AI-based IPMN classifier that leverages the recent success of transformer networks in generalizing across a wide variety of tasks, including vision ones. We specifically show that our transformer-based model exploits pre-training better than standard convolutional neural networks, thus supporting the sought architectural universalism of transformers in vision, including the medical image domain and it allows for a better interpretation of the obtained results.

Accurate measures of changes in regional lung air volumes from chest x-rays of small animals.

Objective. To develop a robust technique for calculating regional volume changes within the lung from x-ray radiograph sequences captured during ventilation, without the use of computed tomography (CT).Approach. This technique is based on the change in transmitted x-ray intensity that occurs for each lung region as air displaces the attenuating lung tissue.Main results. Lung air volumes calculated from x-ray intensity changes showed a strong correlation (R2= 0.98) against the true volumes, measured from high-resolution CT. This correlation enables us to accurately convert projected intensity data into relative changes in lung air volume. We have applied this technique to measure changes in regional lung volumes from x-ray image sequences of mechanically ventilated, recently-deceased newborn rabbits, without the use of CT.Significance. This method is suitable for biomedical research studies,enabling quantitative regional measurement of relative lung air volumes at high temporal resolution, and shows great potential for future clinical application.

Soil bacterial assemblage responses to wildfire in low elevation southern California habitats.

Understanding how wildfires and modification in plant assemblages interact to influence soil bacteria assemblages is a crucial step in understanding how these disturbances may influence ecosystem structure and function. Here, we resampled soil from three study sites previously surveyed in spring 2016 and 2017 and compared soil bacterial assemblages prior to and six months after (spring 2019) the 2018 Woolsey Fire in the Santa Monica Mountain National Recreation Area using Illumina sequencing of the 16S rRNA gene. All sites harbored both native California sage scrub and a non-native (grassland or forbland) habitat, allowing us to examine how fire influenced bacterial assemblages in common southern California habitats. Most results contrasted with our a-priori hypotheses: (1) richness and diversity increased following the fire, (2) heat/drought resistant and sensitive bacteria did not show consistent and differing patterns by increasing and decreasing, respectively, in relative abundance after the fire, and (3) bacterial assemblage structure was only minimally impacted by fire, with no differences being found between 2017 (pre-fire) and 2019 (post-fire) in three of the six habitats sampled. As sage scrub and non-native grasslands consistently harbored unique bacterial assemblages both before and following the fire, modifications in plant compositions will likely have legacy effects on these soils that persist even after a fire. Combined, our results demonstrate that bacterial assemblages in southern California habitats are minimally affected by fire. Because direct impacts of fire are limited, but indirect impacts, e.g., modifications in plant compositions, are significant, plant restoration efforts following a fire should strive to revegetate sage scrub areas to prevent legacy changes in bacterial composition.

Economics of timed artificial insemination with unsorted or sexed semen in a high-producing, pasture-based dairy production system.

This study used a stochastic simulation model to estimate the potential economic benefit of using timed artificial insemination (TAI) in combination with conventional unsorted (TCONV) and sexed (TSEX) semen in heifers only (TCONV-H, TSEX-H) and in both heifers and lactating cows (TCONV-HC, TSEX-HC) in a high-producing, pasture-based production system. The scenarios were compared with a conventional reproductive policy (CONV) in which heifers and cows were inseminated with conventional unsorted semen after estrus detection. Sensitivity analysis was also used to estimate the effect of hormone costs from TAI use on the profitability of each program relative to CONV. The mean annual (± standard deviation) profit advantage (ΔPROF) over CONV for TCONV-H, TCONV-HC, TSEX-H, and TSEX-HC scenarios were €3.90/cow ± 4.65, €34.11/cow ± 25.69, €13.96/cow ± 6.83, and €41.52/cow ± 42.86, respectively. Combined application of both technologies was shown to return a greater annual ΔPROF on average compared with that achievable from TAI alone. However, the risk of not returning a positive annual ΔPROF varied across the scenarios with higher risk in TCONV-H and TSEX-HC. Specifically, TCONV-H and TSEX-HC had a 24 and 18% chance, respectively, of not returning a positive annual ΔPROF. Sensitivity analysis showed that when hormone costs increased by €10/cow TCONV-H and TSEX-HC had a 38 and 23% chance, respectively, of not returning a positive annual ΔPROF. The range in ΔPROF for TCONV policies was most sensitive to the TAI pregnancy rate and TSEX policies were most sensitive to the relative fertility achieved with sexed compared with unsorted semen. This study has shown TAI and sexed semen are complementary technologies that can increase genetic gain and profitability in a pasture-based, dairy production system.

First genome-wide association study investigating blood pressure and renal traits in domestic cats.

Hypertension (HTN) and chronic kidney disease (CKD) are common in ageing cats. In humans, blood pressure (BP) and renal function are complex heritable traits. We performed the first feline genome-wide association study (GWAS) of quantitative traits systolic BP and creatinine and binary outcomes HTN and CKD, testing 1022 domestic cats with a discovery, replication and meta-analysis design. No variants reached experimental significance level in the discovery stage for any phenotype. Follow up of the top 9 variants for creatinine and 5 for systolic BP, one SNP reached experimental-wide significance for association with creatinine in the combined meta-analysis (chrD1.10258177; P = 1.34 × 10-6). Exploratory genetic risk score (GRS) analyses were performed. Within the discovery sample, GRS of top SNPs from the BP and creatinine GWAS show strong association with HTN and CKD but did not validate in independent replication samples. A GRS including SNPs corresponding to human CKD genes was not significant in an independent subset of cats. Gene-set enrichment and pathway-based analysis (GSEA) was performed for both quantitative phenotypes, with 30 enriched pathways with creatinine. Our results support the utility of GWASs and GSEA for genetic discovery of complex traits in cats, with the caveat of our findings requiring validation.

Quantifying Distances Between Non-Elliptical Clusters to Enhance the Identification of Meaningful Emotional Reactivity Subtypes.

Coordinated emotional responses across psychophysiological and subjective indices is a cornerstone of adaptive emotional functioning. Using clustering to identify cross-diagnostic subgroups with similar emotion response profiles may suggest novel underlying mechanisms and treatments.However, many psychophysiological measures are non-normal even in homogenous samples, and over-reliance on traditional elliptical clustering approaches may inhibit the identification of meaningful subgroups. Finite mixture models that allow for non-elliptical cluster distributions is an emerging methodological field that may overcome this hurdle. Furthermore, succinctly quantifying pairwise cluster separation could enhance the clinical utility of the clustering solutions. However, a comprehensive examination of distance measures in the context of elliptical and non-elliptical model-based clustering is needed to provide practical guidance on the computation, benefits, and disadvantages of existing measures. We summarize several measures that can quantify the multivariate distance between two clusters and suggest practical computational tools. Through a simulation study, we evaluate the measures across three scenarios that allow for clusters to differ in location, scale, skewness, and rotation. We then demonstrate our approaches using psychophysiological and subjective responses to emotional imagery captured through the Transdiagnostic Anxiety Study. Finally, we synthesize findings to provide guidance on how to use distance measures in clustering applications.

Low Temperature Thermal Treatment of Gas-Phase Fluorotelomer Alcohols by Calcium Oxide.

Given the extent to which per- and polyfluoroalkyl substances (PFAS) are used in commercial and industrial applications, the need to evaluate treatment options that reduce environmental emissions and human and ecological exposures of PFAS is becoming more necessary. One specific chemical class of PFAS, fluorotelomer alcohols (FTOHs), have vapor pressures such that a significant fraction is expected to be present in the gas-phase even at ambient temperatures. FTOHs are used in a variety of PFAS applications, including synthesis and material coatings. Using two complementary mass spectrometric methods, the use of calcium oxide (CaO) was examined as a low temperature and potentially low-cost thermal treatment media for removal and destruction of four gas-phase FTOHs of varying molecular weights. This was accomplished by assessing the removal/destruction efficiency of the FTOHs and the formation of fluorinated byproducts as a function of treatment temperature (200 - 800 °C) in the presence of CaO compared to thermal-only destruction. During the treatment process, there is evidence that other PFAS compounds are produced at low temperatures (200 - 600 °C) as the primary FTOH partially degrades. At temperatures above 600 °C, thermal treatment with CaO prevented the formation or removed nearly all these secondary products.