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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.

The Portable Ice Nucleation Chamber 2 (PINCii) is a newly developed continuous flow diffusion chamber (CFDC) for measuring ice nucleating particles (INPs). PINCii is a vertically oriented parallel-plate CFDC that has been engineered to improve upon the limitations of previous generations of CFDCs. This work presents a detailed description of the PINCii instrument and the upgrades that make it unique compared with other operational CFDCs. The PINCii design offers several possibilities for improved INP measurements. Notably, a specific icing procedure results in low background particle counts, which demonstrates the potential for PINCii to measure INPs at low concentrations ( L−1). High-spatial-resolution wall-temperature mapping enables the identification of temperature inhomogeneities on the chamber walls. This feature is used to introduce and discuss a new method for analyzing CFDC data based on the most extreme lamina conditions present within the chamber, which represent conditions most likely to trigger ice nucleation. A temperature gradient can be maintained throughout the evaporation section in addition to the main chamber, which enables PINCii to be used to study droplet activation processes or to extend ice crystal growth. A series of both liquid droplet activation and ice nucleation experiments were conducted at temperature and saturation conditions that span the spectrum of PINCii's operational conditions (-50≤ temperature ≤-15 ∘C and 100 ≤ relative humidity with respect to ice ≤160 %) to demonstrate the instrument's capabilities. In addition, typical sources of uncertainty in CFDCs, including particle background, particle loss, and variations in aerosol lamina temperature and relative humidity, are quantified and discussed for PINCii.

Sulfuric acid and dimethylamine vapours in the atmosphere can form molecular clusters, which participate in new particle formation events. In this work, we have produced, measured, and identified clusters of sulfuric acid and dimethylamine using an electrospray ionizer coupled with a planar-differential mobility analyser, connected to an atmospheric pressure interface time-of-flight mass spectrometer (ESI–DMA–APi-TOF MS). This set-up is suitable for evaluating the extent of fragmentation of the charged clusters inside the instrument. We evaluated the fragmentation of 11 negatively charged clusters both experimentally and using a statistical model based on quantum chemical data. The results allowed us to quantify the fragmentation of the studied clusters and to reconstruct the mass spectrum by removing the artifacts due to the fragmentation.

To quantify the contribution of new particle formation (NPF) to ultrafine particle number and cloud condensation nuclei (CCN) budgets, one has to understand the mechanisms that govern NPF in different environments and its temporal extent. Here, we study NPF in Cyprus, an Eastern Mediterranean country located at the crossroads of three continents and affected by diverse air masses originating from continental, maritime, and desert-dust source areas. We performed 1-year continuous measurements of aerosol particles down to ∼ 1 nm in diameter for the first time in the Eastern Mediterranean and Middle East (EMME) region. These measurements were complemented with trace gas data, meteorological variables, and retroplume analysis. We show that NPF is a very frequent phenomenon at this site and has higher frequencies of occurrence during spring and autumn. NPF events were both of local and regional origin, and the local events occurred frequently during the month with the lowest NPF frequency. Some NPF events exhibited multiple onsets, while others exhibited apparent particle shrinkage in size. Additionally, NPF events were observed during the nighttime and during episodes of high desert-dust loadings. Particle formation rates and growth rates were comparable to those in urban environments, although our site is a rural one. Meteorological variables and trace gases played a role in explaining the intra-monthly variability of NPF events, but they did not explain why summer months had the least NPF frequency. Similarly, pre-existing aerosol loading did not explain the observed seasonality. The months with the least NPF frequency were associated with higher H2SO4 concentrations but lower NO2 concentrations, which is an indicator of anthropogenic influence. Air masses arriving from the Middle East were not observed during these months, which could suggest that precursor vapors important for nucleation and growth are transported to our site from the Middle East. Further comprehensive measurements of precursor vapors are required to prove this hypothesis.

The knowledge of the dynamics of sub-3 nm particles in the atmosphere is crucial for our understanding of the first steps of atmospheric new particle formation. Therefore, accurate and stable long-term measurements of the smallest atmospheric particles are needed. In this study, we analyzed over 5 years of particle concentrations in size classes 1.1–1.7 and 1.7–2.5 nm obtained with the particle size magnifier (PSM) and 3 years of precursor vapor concentrations measured with the chemical ionization atmospheric pressure interface time-of-flight mass spectrometer (CI-APi-ToF) at the SMEAR II station in Hyytiälä, Finland. The results show that there are significant seasonal differences in median concentrations of sub-3 nm particles, but the two size classes behave partly differently. The 1.1–1.7 nm particle concentrations are highest in summer, while the 1.7–2.5 nm particle concentrations are highest in springtime. The 1.7–2.5 nm particles exhibit a daytime maximum in all seasons, while the 1.1–1.7 nm particles have an additional evening maximum during spring and summer. Aerosol precursor vapors have notable diurnal and seasonal differences as well. Sulfuric acid and highly oxygenated organic molecule (HOM) monomer concentrations have clear daytime maxima, while HOM dimers have their maxima during the night. HOM concentrations for both monomers and dimers are the highest during summer and the lowest during winter following the biogenic activity in the surrounding forest. Sulfuric acid concentrations are the highest during spring and summer, with autumn and winter concentrations being 2 to 3 times lower. A correlation analysis between the sub-3 nm concentrations and aerosol precursor vapor concentrations indicates that both HOMs (particularly their dimers) and sulfuric acid play a significant role in new particle formation in the boreal forest. Our analysis also suggests that there might be seasonal differences in new particle formation pathways that need to be investigated further.

We measured amines in boreal forest air in Finland both in gas and particle phases with 1 h time resolution using an online ion chromatograph (instrument for Measuring AeRosols and Gases in Ambient Air – MARGA) connected to an electrospray ionization quadrupole mass spectrometer (MS). The developed MARGA-MS method was able to separate and detect seven different amines: monomethylamine (MMA), dimethylamine (DMA), trimethylamine (TMA), ethylamine (EA), diethylamine (DEA), propylamine (PA), and butylamine (BA). The detection limits of the method for amines were low (0.2–3.1 ng m−3), the accuracy of IC-MS analysis was 11–37 %, and the precision 10–15 %. The proper measurements in the boreal forest covered about 8 weeks between March and December 2015. The amines were found to be an inhomogeneous group of compounds, showing different seasonal and diurnal variability. Total MMA (MMA(tot)) peaked together with the sum of ammonia and ammonium ions already in March. In March, monthly means for MMA were −3 in gas and aerosol phases, respectively, and for NH3 and NH4+ these were 52 ± 16 and 425 ± 371 ng m−3, respectively. Monthly medians in March for MMA(tot), NH3, and NH4+ were −3, respectively. DMA(tot) and TMA(tot) had summer maxima indicating biogenic sources. We observed diurnal variation for DMA(tot) but not for TMA(tot). The highest concentrations of these compounds were measured in July. Then, monthly means for DMA were −3 in gas and aerosol phases, respectively, and for TMA these were 0.4 ± 0.1 and 1.8 ± 0.5 ng m−3. Monthly medians in July for DMA were below the detection limit (DL) and 4.9 ng m−3 in gas and aerosol phases, respectively, and for TMA these were 0.4 and 1.4 ng m−3. When relative humidity of air was > 90 %, gas-phase DMA correlated well with 1.1–2 nm particle number concentration (R2 = 0.63) suggesting that it participates in atmospheric clustering. EA concentrations were low all the time. Its July means were −3 in gas and aerosol phases, respectively, but individual concentration data correlated well with monoterpene concentrations in July. Monthly means of PA and BA were below detection limits at all times.

It was recently shown by the CERN CLOUD experiment that biogenic highly oxygenated molecules (HOMs) form particles under atmospheric conditions in the absence of sulfuric acid, where ions enhance the nucleation rate by 1–2 orders of magnitude. The biogenic HOMs were produced from ozonolysis of α-pinene at 5 °C. Here we extend this study to compare the molecular composition of positive and negative HOM clusters measured with atmospheric pressure interface time-of-flight mass spectrometers (APi-TOFs), at three different temperatures (25, 5 and −25 °C). Most negative HOM clusters include a nitrate (NO3−) ion, and the spectra are similar to those seen in the nighttime boreal forest. On the other hand, most positive HOM clusters include an ammonium (NH4+) ion, and the spectra are characterized by mass bands that differ in their molecular weight by ∼ 20 C atoms, corresponding to HOM dimers. At lower temperatures the average oxygen to carbon (O : C) ratio of the HOM clusters decreases for both polarities, reflecting an overall reduction of HOM formation with decreasing temperature. This indicates a decrease in the rate of autoxidation with temperature due to a rather high activation energy as has previously been determined by quantum chemical calculations. Furthermore, at the lowest temperature (−25 °C), the presence of C30 clusters shows that HOM monomers start to contribute to the nucleation of positive clusters. These experimental findings are supported by quantum chemical calculations of the binding energies of representative neutral and charged clusters.

The measurement of sub-3 nm aerosol particles is technically challenging. Therefore, there is a lack of knowledge about the concentrations of atmospheric sub-3 nm particles and their variation in different environments. In this study, the concentrations of ∼ 1–3 nm particles measured with a particle size magnifier (PSM) were investigated at nine sites around the world. Sub-3 nm particle concentrations were highest at the sites with strong anthropogenic influence. In boreal forest, measured particle concentrations were clearly higher in summer than in winter, suggesting the importance of biogenic precursor vapors in this environment. At all sites, sub-3 nm particle concentrations had daytime maxima, which are likely linked to the photochemical production of precursor vapors and the emissions of precursor vapors or particles from different sources. When comparing ion concentrations to the total sub-3 nm particle concentrations, electrically neutral particles were observed to dominate in polluted environments and in boreal forest during spring and summer. Generally, the concentrations of sub-3 nm particles seem to be determined by the availability of precursor vapors rather than the level of the sink caused by preexisting aerosol particles. The results also indicate that the formation of the smallest particles and their subsequent growth to larger sizes are two separate processes, and therefore studying the concentration of sub-3 nm particles separately in different size ranges is essential.

Measuring sub-3 nm particles outside of controlled laboratory conditions is a challenging task, as many of the instruments are operated at their limits and are subject to changing ambient conditions. In this study, we advance the current understanding of the operation of the Airmodus A11 nano Condensation Nucleus Counter (nCNC), which consists of an A10 Particle Size Magnifier (PSM) and an A20 Condensation Particle Counter (CPC). The effect of the inlet line pressure on the measured particle concentration was measured, and two separate regions inside the A10, where supersaturation of working fluid can take place, were identified. The possibility of varying the lower cut-off diameter of the nCNC was investigated; by scanning the growth tube temperature, the range of the lower cut-off was extended from 1–2.5 to 1–6 nm. Here we present a new inlet system, which allows automated measurement of the background concentration of homogeneously nucleated droplets, minimizes the diffusion losses in the sampling line and is equipped with an electrostatic filter to remove ions smaller than approximately 4.5 nm. Finally, our view of the guidelines for the optimal use of the Airmodus nCNC is provided.

The bacterial and archaeal community composition and the possible carbon assimilation processes and energy sources of microbial communities in oligotrophic, deep, crystalline bedrock fractures is yet to be resolved. In this study, intrinsic microbial communities from groundwater of six fracture zones from 180 to 2300 m depths in Outokumpu bedrock were characterized using high-throughput amplicon sequencing and metagenomic prediction. Comamonadaceae-, Anaerobrancaceae- and Pseudomonadaceae-related operational taxonomic units (OTUs) form the core community in deep crystalline bedrock fractures in Outokumpu. Archaeal communities were mainly composed of Methanobacteriaceae-affiliating OTUs. The predicted bacterial metagenomes showed that pathways involved in fatty acid and amino sugar metabolism were common. In addition, relative abundance of genes coding the enzymes of autotrophic carbon fixation pathways in predicted metagenomes was low. This indicates that heterotrophic carbon assimilation is more important for microbial communities of the fracture zones. Network analysis based on co-occurrence of OTUs revealed possible “keystone” genera of the microbial communities belonging to Burkholderiales and Clostridiales. Bacterial communities in fractures resemble those found in oligotrophic, hydrogen-enriched environments. Serpentinization reactions of ophiolitic rocks in Outokumpu assemblage may provide a source of energy and organic carbon compounds for the microbial communities in the fractures. Sulfate reducers and methanogens form a minority of the total microbial communities, but OTUs forming these minor groups are similar to those found in other deep Precambrian terrestrial bedrock environments.

The International Continental Scientific Drilling Program (ICDP) has long espoused studies of deep subsurface life, and has targeted fundamental questions regarding subsurface life, including the following: "(1) What is the extent and diversity of deep microbial life and what are the factors limiting it? (2) What are the types of metabolism/carbon/energy sources and the rates of subsurface activity? (3) How is deep microbial life adapted to subsurface conditions? (4) How do subsurface microbial communities affect energy resources? And (5) how does the deep biosphere interact with the geosphere and atmosphere?" (Horsfield et al., 2014) Many ICDP-sponsored drilling projects have included a deep-life component; however, to date, not one project has been driven by deep-life goals, in part because geomicrobiologists have been slow to initiate deep biosphere-driven ICDP projects. Therefore, the Deep Carbon Observatory (DCO) recently partnered with the ICDP to sponsor a workshop with the specific aim of gathering potential proponents for deep-life-driven ICDP projects and ideas for candidate drilling sites. Twenty-two participants from nine countries proposed projects and sites that included compressional and extensional tectonic environments, evaporites, hydrocarbon-rich shales, flood basalts, Precambrian shield rocks, subglacial and subpermafrost environments, active volcano–tectonic systems, megafan deltas, and serpentinizing ultramafic environments. The criteria and requirements for successful ICDP applications were presented. Deep-life-specific technical requirements were discussed and it was concluded that, while these procedures require adequate planning, they are entirely compatible with the sampling needs of other disciplines. As a result of this workshop, one drilling workshop proposal on the Basin and Range Physiographic Province (BRPP) has been submitted to the ICDP, and several other drilling project proponents plan to submit proposals for ICDP-sponsored drilling workshops in 2016.

ABSTRACTBispecific antibodies continue to represent a growth area for antibody therapeutics, with roughly a third of molecules in clinical development being T-cell engagers that use an anti-CD3 binding arm. CD3 antibodies possessing cross-reactivity with cynomolgus monkey typically recognize a highly electronegative linear epitope at the extreme N-terminus of CD3 epsilon (CD3ε). Such antibodies have high isoelectric points and display problematic polyreactivity (correlated with poor pharmacokinetics for monospecific antibodies). Using insights from the crystal structure of anti-Hu/Cy CD3 antibody ADI-26906 in complex with CD3ε and antibody engineering using a yeast-based platform, we have derived high-affinity CD3 antibody variants with very low polyreactivity and significantly improved biophysical developability. Comparison of these variants with CD3 antibodies in the clinic (as part of bi- or multi-specifics) shows that affinity for CD3 is correlated with polyreactivity. Our engineered CD3 antibodies break this correlation, forming a broad affinity range with no to low polyreactivity. Such antibodies will enable bispecifics with improved pharmacokinetic and safety profiles and suggest engineering solutions that will benefit the large and growing sector of T-cell engagers.

IntroductionLactococcus is a genus of lactic acid bacteria used in the dairy industry as a starter. Lactococci have been found to produce altogether more than 40 different bacteriocins, ribosomally synthesized antimicrobial proteins. All known Lactococcus spp. bacteriocins belong to classes I and II, which are mainly heat-resistant peptides. No class III bacteriocins, bigger heat-sensitive proteins, including phage tail-like bacteriocins, have been found from the Lactococcus spp. Unlike phage tail-like bacteriocins, prophage lysins have not been regarded as bacteriocins, possibly because phage lysins contribute to autolysis, degrading the host's own cell wall.MethodsWild-type Lactococcus lactis strain LAC460, isolated from spontaneously fermented idli batter, was examined for its antimicrobial activity. We sequenced the genome, searched phage lysins from the culture supernatant, and created knock-out mutants to find out the source of the antimicrobial activity.Results and discussionThe strain LAC460 was shown to kill other Lactococcus strains with protease- and heat-sensitive lytic activity. Three phage lysins were identified in the culture supernatant. The genes encoding the three lysins were localized in different prophage regions in the chromosome. By knock-out mutants, two of the lysins, namely LysL and LysP, were demonstrated to be responsible for the antimicrobial activity. The strain LAC460 was found to be resistant to the lytic action of its own culture supernatant, and as a consequence, the phage lysins could behave like bacteriocins targeting and killing other closely related bacteria. Hence, similar to phage tail-like bacteriocins, phage lysin-like bacteriocins could be regarded as a novel type of class III bacteriocins.

Weissella strains are often detected in spontaneously fermented foods. Because of their abilities to produce lactic acid and functional exopolysaccharides as well as their probiotic traits, Weissella spp. improve not only the sensorial properties but also nutritional values of the fermented food products. However, some Weissella species have been associated with human and animal diseases. In the era of vast genomic sequencing, new genomic/genome data are becoming available to the public on daily pace. Detailed genomic analyses are due to provide a full understanding of individual Weissella species. In this study, the genomes of six Weissella paramesenteroides strains were de novo sequenced. The genomes of 42 W. paramesenteroides strains were compared to discover their metabolic and functional potentials in food fermentation. Comparative genomics and metabolic pathway reconstructions revealed that W. paramesenteroides is a compact group of heterofermentative bacteria with good capacity of producing secondary metabolites and vitamin Bs. Since the strains rarely harbored plasmid DNA, they did not commonly possess the genes associated with bacteriocin production. All 42 strains were shown to bear vanT gene from the glycopeptide resistance gene cluster vanG. Yet none of the strains carried virulence genes.

Isolation of extracellular vesicles (EV) has been developing rapidly in parallel with the interest in EVs. However, commonly utilized protocols may not suit more challenging sample matrixes and could potentially yield suboptimal results. Knowing and assessing the pitfalls of isolation procedure to be used, should be involved to some extent for EV analytics. EVs in cow milk are of great interest due to their abundancy and large-scale availability as well as their cross-species bioavailability and possible use as drug carriers. However, the characteristics of milk EVs overlap with those of other milk components. This makes it difficult to isolate and study EVs individually. There exists also a lack of consensus for isolation methods. In this study, we demonstrated the differences between various differential centrifugation-based approaches for isolation of large quantities of EVs from cow milk. Samples were further purified with gradient centrifugation and size exclusion chromatography (SEC) and differences were analyzed. Quality measurements were conducted on multiple independent platforms. Particle analysis, electron microscopy and RNA analysis were used, to comprehensively characterize the isolated samples and to identify the limitations and possible sources of contamination in the EV isolation protocols. Vesicle concentration to protein ratio and RNA to protein ratios were observed to increase as samples were purified, suggesting co-isolation with major milk proteins in direct differential centrifugation protocols. We demonstrated a novel size assessment of vesicles using a particle mobility analyzer that matched the sizing using electron microscopy in contrast to commonly utilized nanoparticle tracking analysis. Based on the standards of the International Society for Extracellular Vesicles and the quick checklist of EV-Track.org for EV isolation, we emphasize the need for complete characterization and validation of the isolation protocol with all EV-related work to ensure the accuracy of results and allow further analytics and experiments., Competing Interests: The authors declare no conflicts of interest., (© 2024 The Authors. Journal of Extracellular Biology published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles.)

Pure biogenic new particle formation (NPF) induced by highly oxygenated organic molecules (HOMs) could be an important mechanism for pre-industrial aerosol formation. However, it has not been unambiguously confirmed in the ambient due to the scarcity of truly pristine continental locations in the present-day atmosphere or the lack of chemical characterization of NPF precursors. Here, we report ambient observations of pure biogenic HOM-driven NPF over a peatland in southern Finland. Meteorological decoupling processes formed an "air pocket" (i.e., a very shallow surface layer) at night and favored NPF initiated entirely by biogenic HOM from this peatland, whose atmospheric environment closely resembles that of the pre-industrial era. Our study sheds light on pre-industrial aerosol formation, which represents the baseline for estimating the impact of present and future aerosol on climate, as well as on future NPF, the features of which may revert toward pre-industrial-like conditions due to air pollution mitigation.

Objective: Black youth are disproportionately exposed to school exclusionary discipline. We examined the impact of race on age at the onset of school disciplinary actions and police contact, and the rate of receiving increasingly severe disciplinary actions., Method: Youth (N = 2,156) and their caregivers participating in the Adolescent Brain Cognitive Development Social Development (ABCD-SD) study reported on the occurrence and timing of disciplinary events and youths' demographics, delinquency, and neighborhood conditions. Experiences of exclusionary discipline were analyzed using logistic regression and Cox proportional hazards models., Results: Black youth reported significantly higher rates of almost all disciplinary events compared to White youth. In logistic regression and Cox models, Black youth experienced higher risk for exclusionary discipline and police contact (odds ratios from 2.47 [detention] to 5.16 [sent home]; hazard ratios from 1.36 [detention] to 4.71 [expelled]), even after adjusting for sex, delinquency, neighborhood conditions, and the interaction between race and sex. Black youth who received detention and suspension were at higher risk for additional, more severe school discipline than were White youth., Conclusion: Consistent with a racial bias in exclusionary discipline practices and policing, Black youth, particularly Black male youth, were at a higher risk for experiencing almost all disciplinary outcomes and at younger ages than White youth, after controlling for delinquency, sex, and neighborhood factors. Compared to White students, school detention and suspension status predicted an accelerated cascade of school discipline outcomes for Black students, suggesting racial disparities in how the severity of school discipline escalates over time., Diversity & Inclusion Statement: We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list. While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list., (Copyright © 2024. Published by Elsevier Inc.)

Youth self-reports are a mainstay of delinquency assessment; however, making valid inferences about delinquency using these assessments requires equivalent measurement across groups of theoretical interest. We examined whether a brief 10-item delinquency measure exhibited measurement invariance across non-Hispanic White ( n = 6,064) and Black ( n = 1,666) youth (ages 10-11 years old) in the Adolescent Brain Cognitive Development sm Study (ABCD Study®). We detected differential item functioning (DIF) in two items. Black youth were more likely to report being arrested or picked up by police than White youth with the same score on the latent delinquency trait. Although multiple covariates (income, urgency, and callous-unemotional traits) reduced mean-level difference in overall delinquency, they were generally unrelated to the DIF in the Arrest item. However, the DIF in the Arrest item was reduced in size and no longer significant after adjusting for neighborhood safety. Results illustrate the importance of considering measurement invariance when using self-reported delinquency scores to draw inferences about group differences, and the utility of measurement invariance analyses for helping to identify mechanisms that contribute to group differences generally., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Biogenic vapors form new particles in the atmosphere, affecting global climate. The contributions of monoterpenes and isoprene to new particle formation (NPF) have been extensively studied. However, sesquiterpenes have received little attention despite a potentially important role due to their high molecular weight. Via chamber experiments performed under atmospheric conditions, we report biogenic NPF resulting from the oxidation of pure mixtures of β-caryophyllene, α-pinene, and isoprene, which produces oxygenated compounds over a wide range of volatilities. We find that a class of vapors termed ultralow-volatility organic compounds (ULVOCs) are highly efficient nucleators and quantitatively determine NPF efficiency. When compared with a mixture of isoprene and monoterpene alone, adding only 2% sesquiterpene increases the ULVOC yield and doubles the formation rate. Thus, sesquiterpene emissions need to be included in assessments of global aerosol concentrations in pristine climates where biogenic NPF is expected to be a major source of cloud condensation nuclei.

Mass spectrometry is uniquely suited to identify and quantify environmentally relevant molecules and molecular clusters. Mass spectrometry alone is, however, not able to distinguish between isomers. In this study, we demonstrate the use of both an experimental set-up using a differential mobility analyser, and computational ion mobility calculations for identification of isomers. In the experimental set-up, we combined electrospray ionisation with a differential mobility analyser time-of-flight mass spectrometer to separate environmentally relevant constitutional isomers, such as catechol, resorcinol and hydroquinone, and configurational isomers, such as cyclohexanediols and fatty acids (i.e., oleic and elaidic acids). Computational ion mobility predictions were obtained using the Ion Mobility Software (IMoS) program. We find that isomer separation can be achieved with the differential mobility analyser, while for catechol, resorcinol and hydroquinone, the computational predictions can reproduce the experimental order of the ion mobilities between the isomers, confirming the isomer identification. Our experimental set-up allows analysis both in the gas and liquid phase. The differential mobility analyser can, moreover, be combined with any mass spectrometry set-up, making it a versatile tool for the separation of isomers., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Diabetic cardiovascular autonomic neuropathy (CAN) is associated with increased mortality and morbidity. To explore metabolic mechanisms associated with CAN we investigated associations between serum metabolites and CAN in persons with type 1 diabetes (T1D)., Materials and Methods: Cardiovascular reflex tests (CARTs) (heart rate response to: deep breathing; lying-to-standing test; and the Valsalva maneuver) were used to diagnose CAN in 302 persons with T1D. More than one pathological CARTs defined the CAN diagnosis. Serum metabolomics and lipidomic profiles were analyzed with two complementary non-targeted mass-spectrometry methods. Cross-sectional associations between metabolites and CAN were assessed by linear regression models adjusted for relevant confounders., Results: Participants were median (IQR) aged 55(49, 63) years, 48% males with diabetes duration 39(32, 47) years, HbA 1c 63(55,69) mmol/mol and 34% had CAN. A total of 75 metabolites and 106 lipids were analyzed. In crude models, the CAN diagnosis was associated with higher levels of hydroxy fatty acids (2,4- and 3,4-dihydroxybutanoic acids, 4-deoxytetronic acid), creatinine, sugar derivates (ribitol, ribonic acid, myo-inositol), citric acid, glycerol, phenols, phosphatidylcholines and lower levels of free fatty acids and the amino acid methionine (p<0.05). Upon adjustment, positive associations with the CAN diagnoses were retained for hydroxy fatty acids, tricarboxylic acid (TCA) cycle-based sugar derivates, citric acid, and phenols (P<0.05)., Conclusion: Metabolic pathways, including the TCA cycle, hydroxy fatty acids, phosphatidylcholines and sugar derivatives are associated with the CAN diagnosis in T1D. These pathway may be part of the pathogeneses leading to CAN and may be modifiable risk factors for the complication., 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., (Copyright © 2022 Hansen, Suvitaival, Theilade, Mattila, Lajer, Trošt, Ahonen, Hansen, Legido-Quigley, Rossing and Ahluwalia.)

The formation and growth of atmospheric particles involving sulfuric acid and organic vapors is estimated to have significant climate effects. To accurately represent this process in large-scale models, the correct interpretation of the observations on particle growth, especially below 10 nm, is essential. Here, we disentangle the factors governing the growth of sub-10 nm particles in the presence of sulfuric acid and organic vapors, using molecular-resolution cluster population simulations and chamber experiments. We find that observed particle growth rates are determined by the combined effects of (1) the concentrations and evaporation rates of the condensing vapors, (2) particle population dynamics, and (3) stochastic fluctuations, characteristic to initial nucleation. This leads to a different size-dependency of growth rate in the presence of sulfuric acid and/or organic vapors at different concentrations. Specifically, the activation type behavior, resulting in growth rate increasing with the particle size, is observed only at certain vapor concentrations. In our model simulations, cluster-cluster collisions enhance growth rate at high vapor concentrations and their importance is dictated by the cluster evaporation rates, which demonstrates the need for accurate evaporation rate data. Finally, we show that at sizes below ∼2.5-3.5 nm, stochastic effects can importantly contribute to particle population growth. Overall, our results suggest that interpreting particle growth observations with approaches neglecting population dynamics and stochastics, such as with single particle growth models, can lead to the wrong conclusions on the properties of condensing vapors and particle growth mechanisms., Competing Interests: There are no conflicts of interest to declare., (This journal is © The Royal Society of Chemistry.)

Background and Aim: Genetic markers are established as predictive of type 1 diabetes, but unknown early life environment is believed to be involved. Umbilical cord blood may reflect perinatal metabolism and exposures. We studied whether selected polar metabolites in cord blood contribute to prediction of type 1 diabetes., Methods: Using a targeted UHPLC-QQQ-MS platform, we quantified 27 low-molecular-weight metabolites (including amino acids, small organic acids, and bile acids) in 166 children, who later developed type 1 diabetes, and 177 random control children in the Norwegian Mother, Father, and Child cohort. We analyzed the data using logistic regression (estimating odds ratios per SD [adjusted odds ratio (aOR)]), area under the receiver operating characteristic curve (AUC), and k-means clustering. Metabolites were compared to a genetic risk score based on 51 established non-HLA single-nucleotide polymorphisms, and a 4-category HLA risk group., Results: The strongest associations for metabolites were aminoadipic acid (aOR = 1.23; 95% CI, 0.97-1.55), indoxyl sulfate (aOR = 1.15; 95% CI, 0.87-1.51), and tryptophan (aOR = 0.84; 95% CI, 0.65-1.10), with other aORs close to 1.0, and none significantly associated with type 1 diabetes. K-means clustering identified 6 clusters, none of which were associated with type 1 diabetes. Cross-validated AUC showed no predictive value of metabolites (AUC 0.49), whereas the non-HLA genetic risk score AUC was 0.56 and the HLA risk group AUC was 0.78., Conclusions: In this large study, we found no support of a predictive role of cord blood concentrations of selected bile acids and other small polar metabolites in the development of type 1 diabetes., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society.)

The Adolescent Brain Cognitive Development (ABCD) Study ® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Aims/hypothesis: Abnormal gut microbiota and blood metabolome profiles have been reported both in children and adults with uncomplicated type 1 diabetes as well as in adults with type 1 diabetes and advanced stages of diabetic nephropathy. In this study we aimed to investigate the gut microbiota and a panel of targeted plasma metabolites in individuals with type 1 diabetes of long duration without and with different levels of albuminuria., Methods: In a cross-sectional study we included 161 individuals with type 1 diabetes and 50 healthy control individuals. Individuals with type 1 diabetes were categorised into three groups according to historically measured albuminuria: (1) normoalbuminuria (<3.39 mg/mmol); (2) microalbuminuria (3.39-33.79 mg/mmol); and (3) macroalbuminuria (≥33.90 mg/mmol). From faecal samples, the gut microbiota composition at genus level was characterised by 16S rRNA gene amplicon sequencing and in plasma a targeted profile of 31 metabolites was analysed with ultra HPLC coupled to MS/MS., Results: Study participants were aged 60 ± 11 years (mean ± SD) and 42% were women. The individuals with type 1 diabetes had had diabetes for a mean of 42 ± 15 years and had an eGFR of 75 ± 25 ml min -1 (1.73 m) -2 . Measures of the gut microbial beta diversity differed significantly between healthy controls and individuals with type 1 diabetes, either with micro- or macroalbuminuria. Taxonomic analyses showed that 79 of 324 genera differed in relative abundance between individuals with type 1 diabetes and healthy controls and ten genera differed significantly among the three albuminuria groups with type 1 diabetes. For the measured plasma metabolites, 11 of 31 metabolites differed significantly between individuals with type 1 diabetes and healthy controls. When individuals with type 1 diabetes were stratified by the level of albuminuria, individuals with macroalbuminuria had higher plasma concentrations of indoxyl sulphate and L-citrulline than those with normo- or microalbuminuria and higher plasma levels of homocitrulline and L-kynurenine compared with individuals with normoalbuminuria. Whereas plasma concentrations of tryptophan were lower in individuals with macroalbuminuria compared with those with normoalbuminuria., Conclusions/interpretation: We demonstrate that individuals with type 1 diabetes of long duration are characterised by aberrant profiles of gut microbiota and plasma metabolites. Moreover, individuals with type 1 diabetes with initial stages of diabetic nephropathy show different gut microbiota and plasma metabolite profiles depending on the level of albuminuria. Graphical abstract.

Omics-based methods may provide new markers associated to diabetic retinopathy (DR). We investigated a wide omics panel of metabolites and lipids related to DR in type 1 diabetes. Metabolomic analyses were performed using two-dimensional gas chromatography with time-of-flight mass spectrometry and lipidomic analyses using an ultra-high-performance liquid chromatography quadruple time-of-flight mass spectrometry method in 648 individuals with type 1 diabetes. Subjects were subdivided into no DR, mild nonproliferative DR (NPDR), moderate NPDR, proliferative DR, and proliferative DR with fibrosis. End points were any progression of DR, onset of DR, and progression from mild to severe DR tracked from standard ambulatory care and investigated using Cox models. The cohort consisted of 648 participants aged a mean of 54.4 ± 12.8 years, 55.5% were men, and follow-up was 5.1-5.5 years. Cross-sectionally, 2,4-dihydroxybutyric acid (DHBA), 3,4-DHBA, ribonic acid, ribitol, and the triglycerides 50:1 and 50:2 significantly correlated ( P < 0.042) to DR stage. Longitudinally, higher 3,4-DHBA was a risk marker for progression of DR ( n = 133) after adjustment ( P = 0.033). We demonstrated multiple metabolites being positively correlated to a higher grade of DR in type 1 diabetes and several triglycerides being negatively correlated. Furthermore, higher 3,4-DHBA was an independent risk marker for progression of DR; however, confirmation is required., (© 2020 by the American Diabetes Association.)

Criminal career duration has not been well investigated. There are very few longitudinal data sets that last long enough and enough subjects to investigate criminal career duration, and especially the characteristics and risk profiles of especially life course persistent offenders. The aim of the study was to describe the predictability of criminal career duration based on both official records and self-reports of offending, and to put the results in the context of the Moffitt theory of "adolescent limited" and "life course persistent" offenders. The Pittsburgh Youth Study (n = 1517) is a seminal longitudinal study based on a community sample of high-risk boys from the city of Pittsburgh. Data was used from the oldest sample of boys in the PYS (N = 506). The participants were first assessed on average at age 12, and data was used up until age 36 for self-reported offending, and age 40 for police charges. The analyses were conducted on moderate and serious violence and moderate and serious theft. Career duration was based on self-reports and official charges in combination. The results show the extent to which commonly accepted and well validated risk factors predict criminal career duration with a special focus on individuals showing high rate/persistent offending in adolescence. Results show more pathways of delinquent development than have previously been described by Moffitt, (Psychological Review, 1993, 100(4), 674-701). Results also show that there is limited predictability of delinquency and offending over time. In addition, results show that only a small number of risk factors distinguish high and low rate adolescent offenders who become continuous offenders. Examples are peer factors. Implications for policy making and intervention science are discussed., (© 2020 John Wiley & Sons Ltd.)

Background and Aims: Adipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas., Materials and Methods: Adipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The sample preparation optimization included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps., Results: Lipidomic analysis on human adipose biopsies lead to the identification of 186lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5%, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific., Conclusion: The method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations., Competing Interests: Trine Foged Henriksen is an employee of Capio CFR, which is a private hospital. Linda Ahonen is currently an employee of Biosyntia ApS, which is a company operating in the field of bioprocess technology. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Atmospheric new-particle formation (NPF) affects climate by contributing to a large fraction of the cloud condensation nuclei (CCN). Highly oxygenated organic molecules (HOMs) drive the early particle growth and therefore substantially influence the survival of newly formed particles to CCN. Nitrogen oxide (NO x ) is known to suppress the NPF driven by HOMs, but the underlying mechanism remains largely unclear. Here, we examine the response of particle growth to the changes of HOM formation caused by NO x . We show that NO x suppresses particle growth in general, but the suppression is rather nonuniform and size dependent, which can be quantitatively explained by the shifted HOM volatility after adding NO x . By illustrating how NO x affects the early growth of new particles, a critical step of CCN formation, our results help provide a refined assessment of the potential climatic effects caused by the diverse changes of NO x level in forest regions around the globe., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Atmospheric new particle formation (NPF), which is observed in many environments globally, is an important source of boundary-layer aerosol particles and cloud condensation nuclei, which affect both the climate and human health. To better understand the mechanisms behind NPF, chamber experiments can be used to simulate this phenomenon under well-controlled conditions. Recent advancements in instrumentation have made it possible to directly detect the first steps of NPF of molecular clusters (~1-2 nm in diameter) and to calculate quantities such as the formation and growth rates of these clusters. Whereas previous studies reported particle formation rates as the flux of particles across a specified particle diameter or calculated them from measurements of larger particle sizes, this protocol outlines methods to directly quantify particle dynamics for cluster sizes. Here, we describe the instrumentation and analysis methods needed to quantify particle dynamics during NPF of sub-3-nm aerosol particles in chamber experiments. The methods described in this protocol can be used to make results from different chamber experiments comparable. The experimental setup, collection and post-processing of the data, and thus completion of this protocol, take from months up to years, depending on the chamber facility, experimental plan and level of expertise. Use of this protocol requires engineering capabilities and expertise in data analysis.

The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography and time of flight mass spectrometry. Lipids were detected using ultra high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry. 2326 metabolic features were detected. Out of a total of 298 metabolites that were annotated we report here 185 that showed a technical variation of x < 30%. These metabolites included amino acids, fatty acid derivatives, carboxylic acids and phenolic compounds. Lipids predominantly belonged to the groups of diacylglycerols, triacylglycerols and ceramides. Metabolites varied between sampling areas, some were broadly homogeneous, others varied 80%. A LASSO-computed network using metabolites present in all areas showed two main clusters describing the system, DAG lipids and phenyllactic acid. In feces from healthy participants, the main groups detected were phenolic compounds, ceramides, diacylglycerols and triacylglycerols.

Molecular studies of the proteome and metabolome in readily available body fluids such as urine and blood performed in a comprehensive qualitative and quantitative way are a valuable source of information for kidney disease research. They provide potential biomarkers of disease progression, markers of efficacy of interventions, as well as information on the underlying pathophysiology. Identified proteins and metabolites may point to dysregulated biological pathways and this knowledge may be useful in the identification of new treatment targets.Many studies, focusing on chronic kidney disease as well as diabetic nephropathy, demonstrate that peptidome and metabolome analysis can substantially contribute to early detection and prediction of disease progression, but also stratification of kidney disease in clinical practice. An innovative, well-explored application of urinary peptidome analysis is the back-translation of results obtained in humans to animals, for animal model validation and improvement of the preclinical readouts. In this chapter, we provide an overview of urinary proteomic analysis with the CE-MS analytical platform, a strategy that has been successfully employed in several studies for the identification and validation of biomarkers in kidney diseases. We describe how to obtain the orthology between the animal model and humans. We also deliver an overview of the analysis of the metabolome with the GC×GC-TOF-MS and UHPLC-Q-TOF-MS analytical platforms for blood and serum as new methods being applied in kidney disease.It is expected that a systems medicine approach to kidney disease including multiple omics methods will provide us with the best way to understand and treat diabetic kidney disease in the future.

The media, the general public, and politicians often emphasize that mental illness is a precursor and a cause of violence, particularly emphasizing an assumed relationship between mental illness, including psychopathy and psychosis, and the use of guns to commit violence. We report which individuals with serious mental health problems have an increased risk to commit violence (including gun violence). Second, we answer the question to what extent serious mental health problems explain most violence and especially gun-related violence. And what is the opinion of experts on these questions? Third, we review which effective screening instrument can help to identify individuals with mental health problems who are at risk to carry a gun and commit violence. For policy makers and legislators, this article points out that most psychiatric disorders are not related to violence, with some exceptions such as schizophrenia and bipolar disorder, and often only in conjunction with substance use. We show that the attributable risk of mental illness to explain violence in general is low. We also emphasize that conduct disorder in late childhood or adolescence is a better predictor of violence than is mental illness at a later age. Empirically based screening methods to identify individuals with mental health problems who are prone to violence appear to have limited utility. Implications are discussed for clinicians and practitioners working in the justice system, researchers, and policy makers.

There is an urgent need for a better molecular understanding of the pathophysiology underlying development and progression of diabetic nephropathy. The aim of the current study was to identify novel associations between serum lipidomics and diabetic nephropathy. Non-targeted serum lipidomic analyses were performed with mass spectrometry in 669 individuals with type 1 diabetes. Cross-sectional associations of lipid species with estimated glomerular filtration rate (eGFR) and urinary albumin excretion were assessed. Moreover, associations with register-based longitudinal follow-up for progression to a combined renal endpoint including ≥30% decline in eGFR, ESRD and all-cause mortality were evaluated. Median follow-up time was 5.0-6.4 years. Adjustments included traditional risk factors and multiple testing correction. In total, 106 lipid species were identified. Primarily, alkyl-acyl phosphatidylcholines, triglycerides and sphingomyelins demonstrated cross-sectional associations with eGFR and macroalbuminuria. In longitudinal analyses, thirteen lipid species were associated with the slope of eGFR or albuminuria. Of these lipids, phosphatidylcholine and sphingomyelin species, PC(O-34:2), PC(O-34:3), SM(d18:1/24:0), SM(d40:1) and SM(d41:1), were associated with lower risk of the combined renal endpoint. PC(O-34:3), SM(d40:1) and SM(d41:1) were associated with lower risk of all-cause mortality while an SM(d18:1/24:0) was associated with lower risk of albuminuria group progression. We report distinct associations between lipid species and risk of renal outcomes in type 1 diabetes, independent of traditional markers of kidney function.

Several small molecule biomarkers have been reported in the literature for prediction and diagnosis of (pre)diabetes, its co-morbidities, and complications. Here, we report the development and validation of a novel, quantitative method for the determination of a selected panel of 34 metabolite biomarkers from human plasma. We selected a panel of metabolites indicative of various clinically-relevant pathogenic stages of diabetes. We combined these candidate biomarkers into a single ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method and optimized it, prioritizing simplicity of sample preparation and time needed for analysis, enabling high-throughput analysis in clinical laboratory settings. We validated the method in terms of limits of detection (LOD) and quantitation (LOQ), linearity ( R 2 ), and intra- and inter-day repeatability of each metabolite. The method's performance was demonstrated in the analysis of selected samples from a diabetes cohort study. Metabolite levels were associated with clinical measurements and kidney complications in type 1 diabetes (T1D) patients. Specifically, both amino acids and amino acid-related analytes, as well as specific bile acids, were associated with macro-albuminuria. Additionally, specific bile acids were associated with glycemic control, anti-hypertensive medication, statin medication, and clinical lipid measurements. The developed analytical method is suitable for robust determination of selected plasma metabolites in the diabetes clinic., Competing Interests: The authors declare no conflict of interest.

Background: The identification of early biomarkers of psychotic experiences (PEs) is of interest because early diagnosis and treatment of those at risk of future disorder is associated with improved outcomes. The current study investigated early lipidomic and coagulation pathway protein signatures of later PEs in subjects from the Avon Longitudinal Study of Parents and Children cohort., Methods: Plasma of 115 children (12 years of age) who were first identified as experiencing PEs at 18 years of age (48 cases and 67 controls) were assessed through integrated and targeted lipidomics and semitargeted proteomics approaches. We assessed the lipids, lysophosphatidylcholines (n = 11) and phosphatidylcholines (n = 61), and the protein members of the coagulation pathway (n = 22) and integrated these data with complement pathway protein data already available on these subjects., Results: Twelve phosphatidylcholines, four lysophosphatidylcholines, and the coagulation protein plasminogen were altered between the control and PEs groups after correction for multiple comparisons. Lipidomic and proteomic datasets were integrated into a multivariate network displaying a strong relationship between most lipids that were significantly associated with PEs and plasminogen. Finally, an unsupervised clustering approach identified four different clusters, with one of the clusters presenting the highest case-control ratio (p < .01) and associated with a higher concentration of smaller low-density lipoprotein cholesterol particles., Conclusions: Our findings indicate that the lipidome and proteome of subjects who report PEs at 18 years of age are already altered at 12 years of age, indicating that metabolic dysregulation may contribute to an early vulnerability to PEs and suggesting crosstalk between these lysophosphatidylcholines, phosphatidylcholines, and coagulation and complement proteins., (Copyright © 2019 Society of Biological Psychiatry. All rights reserved.)

Nanometer-scale clusters form from vapor-phase precursors and can subsequently grow into nanoparticles during atmospheric nucleation events. A particularly interesting set of clusters relevant to nucleation is hybrid iodine pentoxide-iodic acid clusters of the form (I 2 O 5 ) x (HIO 3 ) y as these clusters have been observed in coastal region nucleation events in anomalously high concentrations. To better understand their properties, we utilized ion mobility-mass spectrometry to probe the structures of cluster anions of the form (I 2 O 5 ) x (HIO 3 ) y (IO α ) - ( x = 0-7, y = 0-1, α = 1-3), similar to those observed in coastal nucleation events. We show that (I 2 O 5 ) x (HIO 3 ) y (IO α ) - clusters are relatively stable against dissociation during mass spectrometric measurement, as compared to other clusters observed in nucleation events over continental sites, and that at atmospherically relevant relative humidity levels (65% and less) clusters can become sufficiently hydrated to facilitate complete conversion of iodine pentoxide to iodic acid but that water sorption beyond this level is limited, indicating that the clusters do not persist as nanometer-scale droplets in the ambient.

Previous studies suggest that children who progress to type 1 diabetes (T1D) later in life already have an altered serum lipid molecular profile at birth. Here, we compared cord blood lipidome across the three study groups: children who progressed to T1D (PT1D; n = 30), children who developed at least one islet autoantibody but did not progress to T1D during the follow-up (P1Ab; n = 33), and their age-matched controls (CTR; n = 38). We found that phospholipids, specifically sphingomyelins, were lower in T1D progressors when compared to P1Ab and the CTR. Cholesterol esters remained higher in PT1D when compared to other groups. A signature comprising five lipids was predictive of the risk of progression to T1D, with an area under the receiver operating characteristic curve (AUROC) of 0.83. Our findings provide further evidence that the lipidomic profiles of newborn infants who progress to T1D later in life are different from lipidomic profiles in P1Ab and CTR., Competing Interests: There are no conflicts to declare.

Dyslexia is characterized by poor reading skills, yet often also difficulties in second-language learning. The differences between native- and second-language speech processing and the establishment of new brain representations for spoken second language in dyslexia are not, however, well understood. We used recordings of the mismatch negativity component of event-related potential to determine possible differences between the activation of long-term memory representations for spoken native- and second-language word forms in Finnish-speaking 9-11-year-old children with or without dyslexia, studying English as their second language in school. In addition, we sought to investigate whether the bottleneck of dyslexic readers' second-language learning lies at the level of word representations or smaller units and whether the amplitude of mismatch negativity is correlated with native-language literacy and related skills. We found that the activation of brain representations for familiar second-language words, but not for second-language speech sounds or native-language words, was weaker in children with dyslexia than in typical readers. Source localization revealed that dyslexia was associated with weak activation of the right temporal cortex, which has been previously linked with word-form learning. Importantly, the amplitude of the mismatch negativity for familiar second-language words correlated with native-language literacy and rapid naming scores, suggesting a close link between second-language processing and these skills., (Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Supplementation of formula with bovine milk fat globule membranes has been shown to narrow the gap in immunological and cognitive development between breast-fed and formula-fed infants., Method: In a double-blinded randomized controlled trial 160 formula-fed infants received an experimental formula (EF), supplemented with bovine milk fat globule membranes, or standard formula until 6 months of age. A breast-fed reference group was recruited. Lipidomic analyses were performed on plasma and erythrocyte membranes at 6 months and on serum at 4 and 12 months of age., Results: At 6 months of age, we observed a significant separation in the plasma lipidome between the two formula groups, mostly due to differences in concentrations of sphingomyelins (SM), phosphatidylcholines (PC), and ceramides, and in the erythrocyte membrane lipidome, mostly due to SMs, PEs and PCs. Already at 4 months, a separation in the serum lipidome was evident where SMs and PCs contributed. The separation was not detected at 12 months., Conclusions: The effect of MFGM supplementation on the lipidome is likely part of the mechanisms behind the positive cognitive and immunological effects of feeding the EF previously reported in the same study population.

To guide recruitment, the ABCD Study requires a method for identifying children at high risk for early-onset substance use that may be utilized during the recruitment process. This study was undertaken to inform the development of a brief screen for identifying youths' risk of early-onset substance use and other adverse outcomes. To be acceptable by participants in this context, consideration of potential items was limited to child characteristics previously determined to be potentially pertinent and parental cigarette smoking. To focus the analyses on a single target substance use outcome pertinent to the stated goals of the ABCD Study, early-onset marijuana use was selected. Utilizing data collected prior to the initiation of the ABCD Study, four longitudinal data sets were used in nine secondary data analyses to test, replicate and validate a brief screening assessment for boys and girls to identify those at risk for early-onset marijuana use by ages 14-15. The combination of child externalizing problems reported by the parent (4 items: destroys things belonging to his/her family or others; disobedience at school; lying or cheating; steals outside the home) and parent smoking (1 item) proved to be the optimal screen. This was largely replicated across the four data sets. Indicators of predictive efficiency were modest in magnitude and statistically significant in 8 out of the 9 analyses. The results informed the screen's optimal threshold for identifying children at risk for early-onset marijuana use. The addition of child internalizing problems did not improve these predictions. Further analyses showed the predictive utility of the screen for several other substance use outcomes at ages 15 to 18, including alcohol and nicotine use. The results support the use of a short screening assessment to identify youth at risk for early-onset substance use in the ABCD Study and other research., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objective: Nonalcoholic fatty liver disease (i.e., increased intrahepatic triglyceride [IHTG] content), predisposes to type 2 diabetes and cardiovascular disease. Adipose tissue lipolysis and hepatic de novo lipogenesis (DNL) are the main pathways contributing to IHTG. We hypothesized that dietary macronutrient composition influences the pathways, mediators, and magnitude of weight gain-induced changes in IHTG., Research Design and Methods: We overfed 38 overweight subjects (age 48 ± 2 years, BMI 31 ± 1 kg/m 2 , liver fat 4.7 ± 0.9%) 1,000 extra kcal/day of saturated (SAT) or unsaturated (UNSAT) fat or simple sugars (CARB) for 3 weeks. We measured IHTG ( 1 H-MRS), pathways contributing to IHTG (lipolysis ([ 2 H 5 ]glycerol) and DNL ( 2 H 2 O) basally and during euglycemic hyperinsulinemia), insulin resistance, endotoxemia, plasma ceramides, and adipose tissue gene expression at 0 and 3 weeks., Results: Overfeeding SAT increased IHTG more (+55%) than UNSAT (+15%, P < 0.05). CARB increased IHTG (+33%) by stimulating DNL (+98%). SAT significantly increased while UNSAT decreased lipolysis. SAT induced insulin resistance and endotoxemia and significantly increased multiple plasma ceramides. The diets had distinct effects on adipose tissue gene expression., Conclusions: Macronutrient composition of excess energy influences pathways of IHTG: CARB increases DNL, while SAT increases and UNSAT decreases lipolysis. SAT induced the greatest increase in IHTG, insulin resistance, and harmful ceramides. Decreased intakes of SAT could be beneficial in reducing IHTG and the associated risk of diabetes., (© 2018 by the American Diabetes Association.)

Type 1 diabetes (T1D) is one of the most prevalent autoimmune diseases among children in Western countries. Earlier metabolomics studies suggest that T1D is preceded by dysregulation of lipid metabolism. Here we used a lipidomics approach to analyze molecular lipids in a prospective series of 428 plasma samples from 40 children who progressed to T1D (PT1D), 40 children who developed at least a single islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and 40 matched controls (CTR). Sphingomyelins were found to be persistently downregulated in PT1D when compared to the P1Ab and CTR groups. Triacylglycerols and phosphatidylcholines were mainly downregulated in PT1D as compared to P1Ab at the age of 3 months. Our study suggests that distinct lipidomic signatures characterize children who progressed to islet autoimmunity or overt T1D, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement., (Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.)

Microbial communities in deep subsurface environments comprise a large portion of Earth's biomass, but the metabolic activities in these habitats are largely unknown. Here the effect of CO 2 and carbonate on the microbial community of an isolated groundwater fracture zone at 180 m depth of the Outokumpu Deep Scientific Drill Hole (Finland) was tested. Outokumpu groundwater at 180 m depth contains approximately 0.45 L L -1 dissolved gas of which methane contributes 76%. CO 2 , on the other hand, is scarce. The number of microbial cells with intracellular activity in the groundwater was low when examined with redox staining. Fluorescence Assisted Cell Sorting (FACS) analyses indicated that only 1% of the microbial community stained active with the redox sensing dye in the untreated groundwater after 4 weeks of starvation. However, carbon substrate and sulfate addition increased the abundance of fluorescent cells up to 7%. CO 2 and CO 2 + sulfate activated the greatest number of microbes, especially increasing the abundance of Pseudomonas sp., which otherwise was present at only low abundance in Outokumpu. Over longer exposure time (2 months) up to 50% of the bacterial cells in the groundwater were shown to incorporate inorganic carbon from carbonate into biomass. Carbon recapture is an important feature in this ecosystem since it may decrease the rate of carbon loss in form of CO 2 released from cellular processes., Competing Interests: Conflict of Interest: There are no conflicts of interest among the authors concerning this work.

The identification of an early biomarker of psychotic disorder is important as early treatment is associated with improved patient outcome. Metabolomic and lipidomic approaches in combination with multivariate statistical analysis were applied to identify plasma alterations in children (age 11) (38 cases vs 67 controls) and adolescents (age 18) (36 cases vs 117 controls) preceeding or coincident with the development of psychotic disorder (PD) at age 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC). Overall, 179 lipids were identified at age 11, with 32 found to be significantly altered between the control and PD groups. Following correction for multiple comparisons, 8 of these lipids remained significant (lysophosphatidlycholines (LPCs) LPC(18:1), LPC(18:2), LPC(20:3); phosphatidlycholines (PCs) PC(32:2; PC(34:2), PC(36:4), PC(0-34-3) and sphingomyelin (SM) SM(d18:1/24:0)), all of which were elevated in the PD group. At age 18, 23 lipids were significantly different between the control and PD groups, although none remained significant following correction for multiple comparisons. In conclusion, the findings indicate that the lipidome is altered in the blood during childhood, long before the development of psychotic disorder. LPCs in particular are elevated in those who develop PD, indicating inflammatory abnormalities and altered phospholipid metabolism. These findings were not found at age 18, suggesting there may be ongoing alterations in the pathophysiological processes from prodrome to onset of PD.