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Ice nucleating particles (INPs) play a crucial role in initiating ice crystal formation in clouds, influencing the dynamics and optical properties of clouds and their impacts on precipitation and the climate system. Despite their importance, there is limited knowledge about the vertical distribution of INPs. This study focuses on aircraft measurements conducted during spring 2018 above the boreal forest of Hyytiälä, Finland. Similarities between INP concentrations, activated fractions, particle concentrations, and size distributions observed at ground level and in the boundary layer aloft indicate that surface particles and INPs are efficiently transported and mixed within the boundary layer. INP concentrations observed in the boundary layer are best predicted by a parameterization describing near-surface INP concentrations driven by the abundance of biogenic aerosol in the Finnish boreal forest, suggesting that biogenic INPs are dominant in the boundary layer above the same environment. Most of the INP concentrations and activated fractions observed in the free troposphere are notably lower than in the boundary layer, and the distinct particle size distributions suggest that different aerosol populations, likely resulting from long-range transport, are present in the free troposphere. However, we show one case where higher INP concentrations are observed in the free troposphere and where a homogeneous particle population exists from the surface to the free troposphere. This indicates that surface particles and INPs from the boreal forest can occasionally reach the free troposphere, which is particularly important as the INPs in the free troposphere can further travel horizontally and/or vertically and impact cloud formation.

Atmospheric aerosol particles have a considerable influence on climate via both aerosol–radiation and aerosol–cloud interactions. A major fraction of global aerosol particles, in terms of their number concentration, is due to atmospheric new particle formation (NPF) that involves both neutral and charged clusters and particles. NPF is the major source of atmospheric intermediate ions, i.e., charged particles with mobility diameters between approx. 2 and 7 nm. We investigate ion concentrations between 1.7 and 3.1 nm at the SMEAR II (Station for Measuring Forest Ecosystem–Atmosphere Relations II) measurement station in Hyytiälä, Finland. Both negative and positive ion number size distributions measured by a Neutral cluster and Air Ion Spectrometer (NAIS) are used. Our aim is to find the best diameter size range of ions for identifying and evaluating the intensity of local intermediate ion formation (LIIF). Intermediate ion formation (IIF) refers to the formation of intermediate ions through NPF, while local means that the growth of such ions from smaller clusters has occurred in close proximity (e.g., within 500 m to 1 km) to the measurement site, i.e., locally. We find that the ions in the mobility diameter size range of 2.0–2.3 nm are the best suited for detection of LIIF. The ion concentrations in this size range indicate the elevated rates of IIF, and the potential distances the growing ions have traveled are smaller than those for larger ions. In addition, in Hyytiälä, the negative ion concentrations are more sensitive to IIF than the positive ion concentrations due to the higher difference in concentrations between periods of IIF and the background. Therefore, we recommend the concentrations of ions with diameters 2.0–2.3 nm as the best choice for identifying and evaluating the intensity of LIIF.

Objective: American Indian and Alaska Native people in the United States experience high rates of stomach cancer. Helicobacter pylori infection is a significant risk factor for stomach cancer, and H. pylori strains that carry the cagA gene are linked to greater gastrointestinal disease severity. Yet, little is known about H. pylori and cagA infections in American Indian and Alaska Native people, particularly at the tribal level. We assessed the prevalence and risk factors of H. pylori infection and cagA gene carriage in tribal members from the Navajo Nation. Patients and Methods: We conducted a cross-sectional study with adults from the Navajo Nation. Stool samples collected from participants were analyzed with droplet digital PCR for H. pylori 16S ribosomal and cagA virulence genes. Self-administered health and food questionnaires were mailed to participants to collect information on sociodemographic, health, lifestyle, and environmental risk factors for H. pylori infection. Logistic regression assessed the association between risk factors and H. pylori infection and cagA gene carriage. Results: Among 99 adults, the median age was 45 (age range: 18 to 79 years), and 73.7% were female. About 56.6% (95% CI: 46.2-66.5) of participants were infected with H. pylori. Of H. pylori-infected participants, 78.6% (95% CI: 65.6-88.4) were cagA-gene positive. No significant associations of relevant risk factors with H. pylori and cagA-gene positive infections were noted. Conclusions: In a community-based study population, a substantial proportion of adult tribal members had H. pylori and cagA-gene positive infections. Given these high proportions, culturally appropriate prevention strategies and interventions addressing H. pylori infections present an avenue for additional research and stomach cancer prevention in the Navajo Nation.

Here we introduce a new method, termed “nanoparticle ranking analysis”, for characterizing new particle formation (NPF) from atmospheric observations. Using daily variations of the particle number concentration at sizes immediately above the continuous mode of molecular clusters, here in practice 2.5–5 nm (i.e. ΔN2.5−5), we can determine the occurrence probability and estimate the strength of atmospheric NPF events. After determining the value of ΔN2.5−5 for all the days during a period under consideration, the next step of the analysis is to rank the days based on this simple metric. The analysis is completed by grouping the days either into a number of percentile intervals based on their ranking or into a few modes in the distribution of log (ΔN2.5−5) values. Using 5 years (2018–2022) of data from the SMEAR II station in Hyytiälä, Finland, we found that the days with higher (lower) ranking values had, on average, both higher (lower) probability of NPF events and higher (lower) particle formation rates. The new method provides probabilistic information about the occurrence and intensity of NPF events and is expected to serve as a valuable tool to define the origin of newly formed particles at many types of environments that are affected by multiple sources of aerosol precursors.

Atmospheric cluster ions are important constituents in the atmosphere, and their concentrations and compositions govern their role in atmospheric chemistry. However, there is currently limited quantitative research on atmospheric ion compositions, sources, and sinks, especially in the urban atmosphere where pollution levels and human populations are intense. In this study, we measured the compositions of negative cluster ions and neutral molecules using an atmospheric pressure interface high-resolution time-of-flight mass spectrometer (APi-TOF) and a chemical ionization mass spectrometer in urban Beijing. Quantitative analysis of cluster ions was performed by their comparison with condensation sink (CS), reagent ions, and neutral molecules. We demonstrate the feasibility of quantifying cluster ions with different compositions using in situ-measured ion mobility distributions from a neutral cluster and air ion spectrometer (NAIS). The median concentration of negative cluster ions was 85 (61–112 for 25 %–75 %) cm−3 during the measurement period, which was negatively correlated with CS. The negative cluster ions mainly consisted of inorganic nitrogen-containing ions, inorganic sulfur-containing ions, and organic ions in the form of adducts with NO3- or HSO4-. The CHON-related organic ions accounted for over 70 % of the total organic ions. Although the molecules clustered with NO3- and HSO4- had similar compositions, we found that HSO4- clustered more efficiently with CHO and CHONnonNPs species (CHON excluding nitrated phenols), while NO3- clustered more efficiently with nitrated phenols (CHONNPs). Additionally, most organic ions were positively correlated with neutral molecules, resulting in similar diurnal cycles of organic ions and neutral molecules. However, an exception was found for CHONNPs, the concentration of which is also significantly influenced by the reagent ions NO3-. The charge fractions are generally higher for molecules with higher molecular weight and a higher oxidation state, and the opposite diurnal variations in charging fractions between H2SO4 and organic species indicate a charging competition between them. Finally, we choose HSO4- and C3H3O4- as representatives to calculate the contribution of different formation and loss pathways. We found their losses are condensational loss onto aerosol particles (73 %–75 %), ion–molecule reaction losses (19 %), and ion–ion recombination losses (6 %–8 %).

Optical resonators are used in spectroscopic measurements of atmospheric trace gases to establish long optical path lengths L with enhanced absorption in compact instruments. In cavity-enhanced broad-band methods, the exact knowledge of both the magnitude of L and its spectral dependency on the wavelength λ is fundamental for the correct retrieval of trace gas concentrations. L(λ) is connected to the spectral mirror reflectivity R(λ), which is often referred to instead. L(λ) is also influenced by other quantities like broad-band absorbers or alignment of the optical resonator. The established calibration techniques to determine L(λ), e.g. introducing gases with known optical properties or measuring the ring-down time, all have limitations: limited spectral resolution, insufficient absolute accuracy and precision, inconvenience for field deployment, or high cost of implementation. Here, we present two new methods that aim to overcome these limitations: (1) the narrow-band cavity ring-down (NB-CRD) method uses cavity ring-down spectroscopy and a tunable filter to retrieve spectrally resolved path lengths L(λ); (2) integrated calibration by means of optical modulation (ICOM) allows the determination of the optical path length at the spectrometer resolution with high accuracy in a relatively simple setup. In a prototype setup we demonstrate the high accuracy and precision of the new approaches. The methods facilitate and improve the determination of L(λ), thereby simplifying the use of cavity-enhanced absorption spectroscopy.

The concentration of atmospheric ions affects the total aerosol particle number concentrations in the atmosphere as well as atmospheric new particle formation via ion-induced nucleation, ion–ion recombination, and effects on condensational growth. In this study, we investigate the concentrations and long-term trends of atmospheric ions in a boreal forest environment using 16 years of cluster ion (0.8–2 nm) and intermediate ion (2–7 nm) measurements and characterize the most important factors that explain those trends. We found that the median concentration of cluster ions in a boreal forest was 710 cm−3, the median concentration of 2–4 intermediate ions was 14 cm−3, and the median concentration of 4–7 nm intermediate ions was 9 cm−3. The concentrations of both cluster and intermediate ions have been increasing over the 16-year measurement period, with cluster ion concentrations increasing by about 1 % yr−1 and intermediate ion concentrations increasing 1.7 %–3.9 % yr−1. The increase in cluster ion concentrations can be best explained by the decrease in the coagulation sink caused by larger aerosol particles. Meanwhile, the dependence of intermediate ion concentrations on meteorological conditions is evident, but ionization sources and the coagulation sink do not seem to explain the increasing trend. This is likely because the dynamics of intermediate ions are more complicated, so that ionization sources and the coagulation sink alone cannot directly explain the variation. Season-specific analysis of the ion concentrations suggests that while the coagulation sink is the limiting factor for the ion concentrations in spring and summer, the dynamics are different in autumn and winter. Based on our findings, we recommend that a more comprehensive analysis is needed to determine if the increase in ambient ion concentrations, increasing temperature, and changing abundance of condensable vapors makes ion-mediated and ion-induced nucleation pathways in the boreal forest more relevant in the future.

At SMEAR II research station in Hyytiälä, located in the Finnish boreal forest, the process of new particle formation and the role of ions has been investigated for almost 20 years near the ground and at canopy level. However, above SMEAR II, the vertical distribution and diurnal variation of these different atmospheric ions are poorly characterized. In this study, we assess the atmospheric ion composition in the stable boundary layer, residual layer, mixing layer, and free troposphere, and the evolution of these atmospheric ions due to photochemistry and turbulent mixing through the day. To measure the vertical profile of atmospheric ions, we developed a tailored set-up for online mass spectrometric measurements, capable of being deployed in a Cessna 172 with minimal modifications. Simultaneously, instruments dedicated to aerosol properties made measurements in a second Cessna. We conducted a total of 16 measurement flights in May 2017, during the spring, which is the most active new particle formation season. A flight day typically consisted of three distinct flights through the day (dawn, morning, and afternoon) to observe the diurnal variation and at different altitudes (from 100 to 3200 m above ground), to capture the boundary layer development from the stable boundary layer, residual layer to mixing layer, and the free troposphere. Our observations showed that the ion composition is distinctly different in each layer and depends on the air mass origin and time of the day. Before sunrise, the layers are separated from each other and have their own ion chemistry. We observed that the ions present within the stable layer are of the same composition as the ions measured at the canopy level. During daytime when the mixing layer evolved and the compounds are vertically mixed, we observed that highly oxidized organic molecules are distributed to the top of the boundary layer. The ion composition in the residual layer varies with each day, showing similarities with either the stable boundary layer or the free troposphere. Finally, within the free troposphere, we detected a variety of carboxylic acids and ions that are likely containing halogens, originating from the Arctic Sea.

Understanding chemical processes leading to the formation of atmospheric aerosol particles is crucial to improve our capabilities in predicting the future climate. However, those mechanisms are still inadequately characterized, especially in polar regions. In this study, we report observations of neutral and charged aerosol precursor molecules and chemical cluster composition (qualitatively and quantitatively), as well as air ions and aerosol particle number concentrations and size distributions from the Marambio research station (64∘15′ S, 56∘38′ W), located north of the Antarctic Peninsula. We conducted measurements during the austral summer, between 15 January and 25 February 2018. The scope of this study is to characterize new particle formation (NPF) event parameters and connect our observations of gas-phase compounds with the formation of secondary aerosols to resolve the nucleation mechanisms at the molecular scale. NPF occurred on 40 % of measurement days. All NPF events were observed during days with high solar radiation, mostly with above-freezing temperatures and with low relative humidity. The averaged formation rate for 3 nm particles (J3) was 0.686 cm−3 s−1, and the average particle growth rate (GR3.8–12 nm) was 4.2 nm h−1. Analysis of neutral aerosol precursor molecules showed measurable concentrations of iodic acid (IA), sulfuric acid (SA), and methane sulfonic acid (MSA) throughout the entire measurement period with significant increase in MSA and SA concentrations during NPF events. We highlight SA as a key contributor to NPF processes, while IA and MSA likely only contribute to particle growth. Mechanistically, anion clusters containing ammonia and/or dimethylamine (DMA) and SA were identified, suggesting significant concentration of ammonia and DMA as well. Those species are likely contributing to NPF events since SA alone is not sufficient to explain observed nucleation rates. Here, we provide evidence of the marine origin of the measured chemical precursors and discuss their potential contribution to the aerosol phase.

Several studies have investigated new particle formation (NPF) events from various sites ranging from pristine locations, including forest sites, to urban areas. However, there is still a dearth of studies investigating NPF processes and subsequent aerosol growth in coastal yet semi-urban sites, where the tropospheric layer is a concoction of biogenic and anthropogenic gases and particles. The investigation of factors leading to NPF becomes extremely complex due to the highly dynamic meteorological conditions at the coastline especially when combined with both continental and oceanic weather conditions. Herein, we engage in a comprehensive study of particle number size distributions and aerosol-forming precursor vapors at the coastal semi-urban site in Helsinki, Finland. The measurement period, 25 June–18 August 2019, was timed with the recurring cyanobacterial summer bloom in the Baltic Sea region and coastal regions of Finland. Our study recorded several regional/local NPF and aerosol burst events during this period. Although the overall anthropogenic influence on sulfuric acid (SA) concentrations was low during the measurement period, we observed that the regional or local NPF events, characterized by SA concentrations on the order of 107 molec.cm-3, occurred mostly when the air mass traveled over the land areas. Interestingly, when the air mass traveled over the Baltic Sea, an area enriched with algae and cyanobacterial blooms, high iodic acid (IA) concentration coincided with an aerosol burst or a spike event at the measurement site. Further, SA-rich bursts were seen when the air mass traveled over the Gulf of Bothnia, enriched with cyanobacterial blooms. The two most important factors affecting aerosol precursor vapor concentrations, and thus the aerosol formation, were speculated to be (1) the type of phytoplankton species and intensity of bloom present in the coastal regions of Finland and the Baltic Sea and (2) the wind direction. During the events, most of the growth of sub-3 nm particles was probably due to SA, rather than IA or methane sulfonic acid (MSA); however much of the particle growth remained unexplained indicative of the strong role of organics in the growth of particles, especially in the 3–7 nm particle size range. Further studies are needed to explore the role of organics in NPF events and the potential influence of cyanobacterial blooms in coastal locations.

The formation of ice particles in Earth's atmosphere strongly influences the dynamics and optical properties of clouds and their impacts on the climate system. Ice formation in clouds is often triggered heterogeneously by ice-nucleating particles (INPs) that represent a very low number of particles in the atmosphere. To date, many sources of INPs, such as mineral and soil dust, have been investigated and identified in the low and mid latitudes. Although less is known about the sources of ice nucleation at high latitudes, efforts have been made to identify the sources of INPs in the Arctic and boreal environments. In this study, we investigate the INP emission potential from high-latitude boreal forests in the mixed-phase cloud regime. We introduce the HyICE-2018 measurement campaign conducted in the boreal forest of Hyytiälä, Finland, between February and June 2018. The campaign utilized the infrastructure of the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, with additional INP instruments, including the Portable Ice Nucleation Chamber I and II (PINC and PINCii), the SPectrometer for Ice Nuclei (SPIN), the Portable Ice Nucleation Experiment (PINE), the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT) and the Microlitre Nucleation by Immersed Particle Instrument (µL-NIPI), used to quantify the INP concentrations and sources in the boreal environment. In this contribution, we describe the measurement infrastructure and operating procedures during HyICE-2018, and we report results from specific time periods where INP instruments were run in parallel for inter-comparison purposes. Our results show that the suite of instruments deployed during HyICE-2018 reports consistent results and therefore lays the foundation for forthcoming results to be considered holistically. In addition, we compare measured INP concentrations to INP parameterizations, and we observe good agreement with the Tobo et al. (2013) parameterization developed from measurements conducted in a ponderosa pine forest ecosystem in Colorado, USA.

1,2-Dehydro-pyrrolizidine alkaloids (PA), their corresponding N -oxides (PANO) and tropane alkaloids (TA), are toxic plant metabolites. If plant material, containing these toxins, is present in the feed of dairy cows these toxins can be transferred into milk. Here, milk was sampled directly from dairy farms in the German federal states of Bavaria and Schleswig-Holstein in 2020-2022 in order to investigate a possible contamination of milk at the production stage. In total, 228 milk samples were analysed for 54 PA/PANO and two TA by a sensitive LC-ESI-MS/MS method. In addition, a subset of milk samples ( n  = 85) was independently analysed for TA by a cooperating laboratory for verification. PA/PANO were found in 26 samples (11%) with a low median sum content of the contaminated samples of 0.024 µg/L. The highest level of contamination was 5.6 µg/L. Senecionine-, lycopsamine- and heliotrine-type PA/PANO were detected. In four samples (1.8%), atropine was determined up to 0.066 µg/L. The toxin levels in the milk samples hardly contributed to the total daily exposure. These data are first-time results on contamination rates and levels occurring in milk from individual dairy farms, based on a large sample number.

Tauopathies are characterized by the abnormal buildup of tau protein, with early oligomeric forms associated with neurodegeneration and the later neurofibrillary tangles possibly conferring neuroprotection. The molecular mechanisms governing the formation of these tau species are unclear. Lately, there has been an increased focus on examining the interactions between tau and other proteins, along with their influence on the aggregation of tau. Our previous work revealed EFhd2's association with pathological tau in animal models and tauopathy brains. Herein, we examined the impact of EFhd2 on monomeric and filamentous tau in vitro . The results demonstrated that EFhd2 incubation with monomeric full length human tau (hTau40) formed amorphous aggregates, where both EFhd2 and hTau40 colocalized. Moreover, EFhd2 is entangled with arachidonic acid (ARA)-induced filamentous hTau40. Furthermore, EFhd2-induced aggregation with monomeric and filamentous hTau40 is EFhd2 concentration dependent. Using sandwich ELISA assays, we assessed the reactivity of TOC1 and Alz50-two conformation-specific tau antibodies-to EFhd2-hTau40 aggregates (in absence and presence of ARA). No TOC1 signal was detected in EFhd2 aggregates with monomeric hTau40 whereas EFhd2 aggregates with hTau in the presence of ARA showed a higher signal compared to hTau40 filaments. In contrast, EFhd2 aggregates with both monomeric and filamentous hTau40 reduced Alz50 reactivity. Taken together, our results illustrate for the first time that EFhd2, a tau-associated protein, interacts with monomeric and filamentous hTau40 to form large aggregates that are starkly different from tau oligomers and filaments. Given these findings and previous research, we hypothesize that EFhd2 may play a role in the formation of tau aggregates. Nevertheless, further in vivo studies are imperative to test this hypothesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Soliman, Umstead, Lamp and Vega.)

Background: Although previous risk models exist for advanced heart failure with reduced ejection fraction (HFrEF), few integrate invasive hemodynamics or support missing data. This study developed and validated a heart failure (HF) hemodynamic risk and phenotyping score for HFrEF, using Machine Learning (ML)., Methods: Prior to modeling, patients in training and validation HF cohorts were assigned to 1 of 5 risk categories based on the composite endpoint of death, left ventricular assist device (LVAD) implantation or transplantation (DeLvTx), and rehospitalization in 6 months of follow-up using unsupervised clustering. The goal of our novel interpretable ML modeling approach, which is robust to missing data, was to predict this risk category (1, 2, 3, 4, or 5) using either invasive hemodynamics alone or a rich and inclusive feature set that included noninvasive hemodynamics (all features). The models were trained using the ESCAPE trial and validated using 4 advanced HF patient cohorts collected from previous trials, then compared with traditional ML models. Prediction accuracy for each of these 5 categories was determined separately for each risk category to generate 5 areas under the curve (AUCs, or C-statistics) for belonging to risk category 1, 2, 3, 4, or 5, respectively., Results: Across all outcomes, our models performed well for predicting the risk category for each patient. Accuracies of 5 separate models predicting a patient's risk category ranged from 0.896 +/- 0.074 to 0.969 +/- 0.081 for the invasive hemodynamics feature set and 0.858 +/- 0.067 to 0.997 +/- 0.070 for the all features feature set., Conclusion: Novel interpretable ML models predicted risk categories with a high degree of accuracy. This approach offers a new paradigm for risk stratification that differs from prediction of a binary outcome. Prospective clinical evaluation of this approach is indicated to determine utility for selecting the best treatment approach for patients based on risk and prognosis., Competing Interests: Disclosure None, (Copyright © 2024 Elsevier Inc. All rights reserved.)

A great need currently exists for rapid, inexpensive, and accurate methods for microbial analysis in the medical, food, industrial, and water quality fields. Here, a novel capillary isotachophoresis (CITP) method is presented for the focusing, sorting, and quantitation of intact cells in mixed samples based on their electrophoretic mobility ranges. Using a series of ion spacers dissolved in the sample, this technique results in several efficient cell peaks in the electropherogram corresponding to specific cell electrophoretic mobility ranges. The concentrations of different species in mixed-cell samples are determined from the cell peak areas and the known peak response factors for the cell species using a series of linear equations. Method design and optimization are discussed, including the choice of running buffer, pH, and ion spacers. Mixed-cell samples of up to four different species were focused and quantified as a proof-of-principle of the method. When sample cell concentrations were toward the middle of the linear response range, accuracies between 1% and 11% and relative standard deviations of 1%-14% were obtained, depending on the number of cell species in the mixture. This work provides a useful basis for future studies of cell quantitation using CITP, which could be potentially applied to a variety of fields including cell growth studies, microbial contamination testing, and sterility testing., (© 2023 Wiley-VCH GmbH.)

Polychlorinated dibenzo- para -dioxins (PCDDs) and dibenzofurans (PCDFs) (collectively and colloquially referred to as 'dioxins') as well as polychlorinated biphenyls (PCBs) are persistent and ubiquitous environmental contaminants that may unintentionally enter and accumulate along the food chain. Owing to their chronic toxic effects in humans and bioaccumulative properties, their presence in feed and food requires particular attention. One important exposure pathway for consumers is consumption of milk and dairy products. Their transfer from feed to milk has been studied for the past 50 years to quantify the uptake and elimination kinetics. We extracted transfer parameters (transfer rate, transfer factor, biotransfer factor and elimination half-lives) in a machine-readable format from seventy-six primary and twenty-nine secondary literature items. Kinetic data for some toxicologically relevant dioxin congeners and the elimination half-lives of dioxin-like PCBs are still not available. A well-defined selection of transfer parameters from literature was statistically analysed and shown to display high variability. To understand this variability, we discuss the data with an emphasis on influencing factors, such as experimental conditions, cow performance parameters and metabolic state. While no universal interpretation could be derived, a tendency for increased transfer into milk is apparently connected to an increase in milk yield and milk fat yield as well as during times of body fat mobilisation, for example during the negative energy balance after calving. Over the past decades, milk yield has increased to over 40 kg/d during high lactation, so more research is needed on how this impacts feed to food transfer for PCDD/Fs and PCBs.

Understanding the transfer of polychlorinated dibenzo- p -dioxins (PCDDs) and dibenzofurans (PCDFs) as well as polychlorinated biphenyls (PCBs) from oral exposure into cow's milk is not purely an experimental endeavour, as it has produced a large corpus of theoretical work. This work consists of a variety of predictive toxicokinetic models in the realms of health and environmental risk assessment and risk management. Their purpose is to provide mathematical predictive tools to organise and integrate knowledge on the absorption, distribution, metabolism and excretion processes. Toxicokinetic models are based on more than 50 years of transfer studies summarised in part I of this review series. Here in part II, several of these models are described and systematically classified with a focus on their applicability to risk analysis as well as their limitations. This part of the review highlights the opportunities and challenges along the way towards accurate, congener-specific predictive models applicable to changing animal breeds and husbandry conditions.

Dioxin-like polychlorinated biphenyls (dl-PCBs) as well as polychlorinated dibenzo- p -dioxins (PCDDs) and dibenzofurans (PCDFs) are a major concern for food safety, especially in fat-containing foods of animal origin, such as milk. Due to the lipophilic character of PCDD/Fs and PCBs, it is of special interest to explore whether the metabolic state of high-yielding cows influences the transfer rates into milk. Five German Holstein cows were orally exposed to a mixture of 17 PCDD/Fs, 12 dl-PCBs, and 6 non-dioxin-like PCBs (ndl-PCBs) for two dosing periods of 28 days each. The first period covered the negative energy balance (NEB) after calving, while the second period addressed the positive energy balance (PEB) in late lactation. Each dosing period was followed by a depuration period of around 100 days. During the NEB phase, the transfer rates of 14 PCDD/Fs and 7 dl-PCBs quantified were significantly ( p ≤ 0.1) higher compared to the PEB phase, indicating an influence of the metabolic state on the transfer. Furthermore, the congener-specific transfer rates (0.3-39%) were in the range of the results from former studies. This indicates that the milk yield of the exposed cows is not the only determining factor for the transfer of these congeners into milk.

Hypoglycin A (HGA) and its homologue methylenecyclopropylglycine (MCPrG) are present in ackee and lychee as well as seeds, leaves, and seedlings of some maple (Acer) species. They are toxic to some animal species and humans. The determination of HGA, MCPrG, and their glycine and carnitine metabolites in blood and urine is a useful tool for screening for potential exposure to these toxins. In addition, HGA, MCPrG, and/or their metabolites have been detected in milk. In this work, simple and sensitive ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) methods without derivatization were developed and validated for the quantification of HGA, MCPrG, and their metabolites in cow's milk and urine. An extraction procedure from milk samples has been developed, whereas a dilute-and-shoot approach was implemented for urine samples. For quantification, the MS/MS analysis was performed in multiple reaction monitoring mode. The methods were validated according to the European Union guidelines using blank raw milk and urine as matrices. The limit of quantification presented here for HGA in milk (1.12 µg/L) is noticeably lower than the lowest published limit of detection (9 µg/L). Acceptable values for recovery (89-106% and 85-104% in milk and urine, respectively) and precision (≤ 20%) were obtained for all the quality control levels. The stability of HGA and MCPrG in frozen milk over a period of 40 weeks has been demonstrated. The method was applied to 68 milk samples from 35 commercial dairy farms and showed the absence of any quantifiable amounts of HGA, MCPrG, and their metabolites., (© 2023. The Author(s).)

Study Objective: To identify Change in Systemic Arterial Pulsatitlity index (ΔSAPi) as a novel hemodynamic marker associated with outcomes in heart failure (HF)., Design: The ESCAPE trial was a randomized controlled trial., Setting: The ESCAPE trial was conducted at 26 sites., Participants: 134 patients were analyzed (mean age 56.8 ± 13.4 years, 29% female)., Interventions: We evaluated the change in SAPi, ([systemic pulse pressure/pulmonary artery wedge pressure) obtained at baseline and at the final hemodynamic measurement in the ESCAPE trial., Main Outcome Measures: Change in SAPi, (ΔSAPi), was analyzed for the primary outcomes of death, heart transplant, left ventricular assist device (DTxLVAD) or hospitalization, (DTxLVADHF) and secondary outcome of DTxLVAD using Cox proportional hazards regression., Results: Median change in SAPi was 0.81 (IQR 0.20-1.68). ΔSAPi in uppermost quartile was associated with reductions in DTxLVADHF (HR 0.55 [95% CI 0.32, 0.93]). ΔSAPi in the uppermost and lowermost quartiles combined was similarly associated with significant reductions in DTxLVADHF (HR 0.62 [95% CI 0.41, 0.94]). ΔSAPi higher than 1.17 was associated with improved DTxLVADHF. ΔSAPi was also associated with troponin levels at discharge (regression coefficient p = 0.001) and trended with 6-minute walk at discharge (Spearman correlation r = 0.179, p = 0.058)., Conclusion: ΔSAPi was strongly associated with improved HF clinical profile and adverse outcomes. These findings support further exploration of Δ SAPi in the risk stratification of HF., Competing Interests: Disclosure Statement: The authors declare that there is no conflict of interest.

Ventriculo-arterial (VA) coupling has been shown to have physiologic importance in heart failure (HF). We hypothesized that the systemic arterial pulsatility index (SAPi), a measure that integrates pulse pressure and a proxy for left ventricular end-diastolic pressure, would be associated with adverse outcomes in advanced HF. We evaluated the SAPi ([systemic systolic blood pressure-systemic diastolic blood pressure]/pulmonary artery wedge pressure) obtained from the final hemodynamic measurement in patients randomized to therapy guided by a pulmonary arterial catheter (PAC) and with complete data in the Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE) trial. Cox proportional hazards regression was performed for the outcomes of (a) death, transplant, left ventricular assist device (DTxLVAD) or hospitalization, (DTxLVADHF) and (b) DTxLVAD. Among 142 patients (mean age 56.8 ± 13.3 years, 30.3% female), the median SAPi was 2.57 (IQR 1.63-3.45). Increasing SAPi was associated with significant reductions in DTxLVAD (HR 0.60 per unit increase in SAPi, 95% CI 0.44-0.84) and DTxLVADHF (HR 0.81 per unit increase, 95% CI 0.70-0.95). Patients with a SAPi ≤ 2.57 had a marked increase in both outcomes, including more than twice the risk of DTxLVAD (HR 2.19, 95% CI 1.11-4.30) over 6 months. Among advanced heart failure patients with invasive hemodynamic monitoring in the ESCAPE trial, SAPi was strongly associated with adverse clinical outcomes. These findings support further investigation of the SAPi to guide treatment and prognosis in HF undergoing invasive hemodynamic monitoring., (© 2022. Springer Japan KK, part of Springer Nature.)

Ornithine decarboxylase (ODC) is a rate-limiting enzyme for the synthesis of polyamines (PAs). PAs are required for proliferation, and increased ODC activity is associated with cancer and neural over-proliferation. ODC levels and activity are therefore tightly regulated, including through the ODC-specific inhibitor, antizyme AZ1. Recently, ODC G84R has been reported as a partial loss-of-function variant that is associated with intellectual disability and seizures. However, G84 is distant from both the catalytic center and the ODC homodimerization interface. To understand how G84R modulates ODC activity, we have determined the crystal structure of ODC G84R in both the presence and the absence of the cofactor pyridoxal 5-phosphate. The structures show that the replacement of G84 by arginine leads to hydrogen bond formation of R84 with F420, the last residue of the ODC C-terminal helix, a structural element that is involved in the AZ1-mediated proteasomal degradation of ODC. In contrast, the catalytic center is essentially indistinguishable from that of wildtype ODC. We therefore reanalyzed the catalytic activity of ODC G84R and found that it is rescued when the protein is purified in the presence of a reducing agent to mimic the reducing environment of the cytoplasm. This suggests that R84 may exert its neurological effects not through reducing ODC catalytic activity but through misregulation of its AZ1-mediated proteasomal degradation., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

β2-adrenoreceptor (β2AR) agonists have been associated with a decreased risk of developing Parkinson's disease (PD) and are hypothesized to decrease expression of both alpha-synuclein mRNA (Snca) and protein (α-syn). Effects of β2AR agonist clenbuterol on the levels of Snca mRNA and α-syn protein were evaluated in vivo (rats and mice) and in rat primary cortical neurons by two independent laboratories. A modest decrease in Snca mRNA in the substantia nigra was observed after a single acute dose of clenbuterol in rats, however, this decrease was not maintained after multiple doses. In contrast, α-syn protein levels remained unchanged in both single and multiple dosing paradigms. Furthermore, clenbuterol did not decrease Snca in cultured rat primary cortical neurons, or decrease Snca or α-syn in mice. Additionally, compared to the single-dose paradigm, repeat dosing resulted in substantially lower levels of clenbuterol in plasma and brain tissue in rodents. Based on our observations of a transient decrease in Snca and no effect on α-syn protein in this preclinical study, these data support the conclusion that clenbuterol is not likely a viable disease-modifying strategy for PD., (© 2022. The Author(s).)