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Abstract Objective This study aims to elucidate the long‐term benefit of newborn screening (NBS) for individuals with long‐chain 3‐hydroxy‐acyl‐CoA dehydrogenase (LCHAD) and mitochondrial trifunctional protein (MTP) deficiency, inherited metabolic diseases included in NBS programs worldwide. Methods German national multicenter study of individuals with confirmed LCHAD/MTP deficiency identified by NBS between 1999 and 2020 or selective metabolic screening. Analyses focused on NBS results, confirmatory diagnostics, and long‐term clinical outcomes. Results Sixty‐seven individuals with LCHAD/MTP deficiency were included in the study, thereof 54 identified by NBS. All screened individuals with LCHAD deficiency survived, but four with MTP deficiency (14.8%) died during the study period. Despite NBS and early treatment neonatal decompensations (28%), symptomatic disease course (94%), later metabolic decompensations (80%), cardiomyopathy (28%), myopathy (82%), hepatopathy (32%), retinopathy (17%), and/or neuropathy (22%) occurred. Hospitalization rates were high (up to a mean of 2.4 times/year). Disease courses in screened individuals with LCHAD and MTP deficiency were similar except for neuropathy, occurring earlier in individuals with MTP deficiency (median 3.9 vs. 11.4 years; p = 0.0447). Achievement of dietary goals decreased with age, from 75% in the first year of life to 12% at age 10, and consensus group recommendations on dietary management were often not achieved. Interpretation While NBS and early treatment result in improved (neonatal) survival, they cannot reliably prevent long‐term morbidity in screened individuals with LCHAD/MTP deficiency, highlighting the urgent need of better therapeutic strategies and the development of disease course‐altering treatment.

Abstract Efficient navigation is supported by a cognitive map of space. The hippocampus plays a key role for this map by linking multimodal sensory information with spatial memory representations. However, in human navigation studies, the full range of sensory information is often unavailable due to the stationarity of experimental setups. We investigated the contribution of multisensory information to memory-guided spatial navigation by presenting a virtual version of the Morris water maze on a screen and in an immersive mobile virtual reality setup. Patients with hippocampal lesions and matched controls navigated to memorized object locations in relation to surrounding landmarks. Our results show that availability of multisensory input improves memory-guided spatial navigation in both groups. It has distinct effects on navigational behaviour, with greater improvement in spatial memory performance in patients. We conclude that congruent multisensory information shifts computations to extrahippocampal areas that support spatial navigation and compensates for spatial navigation deficits.

The multi-scheme chemical ionisation inlet 1 (MION1) enables rapid switching between the measurement of atmospheric ions without chemical ionisation and neutral molecules using various atmospheric pressure chemical ionisation methods. In this study, we introduce the upgraded version, the multi-scheme chemical ionisation inlet 2 (MION2). The new design incorporates enhanced ion optics, resulting in increased reagent ion concentration, ensuring a robust operation, and enabling the use of multiple chemical ionisation methods with the same ionisation time. In order to simplify the regular calibration of MION2, we developed an open-source flow reactor chemistry model called MARFORCE. This model enables quantification of the chemical production of sulfuric acid (H2SO4), hypoiodous acid (HOI), and hydroperoxyl radical (HO2). MARFORCE simulates the convection–diffusion–reaction processes occurring within typical cylindrical flow reactors with uniform inner diameters. The model also includes options to simulate chemical processes in the following two scenarios: (1) when two flow reactors with different inner diameters are connected and (2) when two flows are merged into one using a Y-shaped tee, although with reduced accuracy. Furthermore, the chemical mechanism files in the model are compatible with the widely used Master Chemical Mechanism (MCM), allowing for future adaptation to simulate other chemical processes in flow reactors. Furthermore, we conducted a comprehensive characterisation of the bromide (Br−) and nitrate (NO3-) chemical ionisation methods with different ionisation times. We performed calibration experiments for H2SO4, HOI, and HO2 by combining gas kinetic experiments with the MARFORCE model. The evaluation of sulfur dioxide (SO2), water (H2O), and molecular iodine (I2) involved dilution experiments from a gas cylinder (SO2), dew point mirror measurements (H2O), and a derivatisation approach combined with a high-performance liquid chromatography quantification (I2), respectively. Our findings indicate that the detection limit is inversely correlated with the fragmentation enthalpy of the analyte–reagent ion (Br−) cluster. In other words, stronger binding (resulting in a larger fragmentation enthalpy) leads to a lower detection limit. Additionally, a moderately longer ionisation time enhances the detection sensitivity, thereby reducing the detection limit. For instance, when using the Br− chemical ionisation method with a 300 ms ionisation time, the estimated detection limit for H2SO4 is 2.9×104 molec. cm−3. Notably, this detection limit is even superior to that achieved by the widely used Eisele-type chemical ionisation inlet (7.6×104 molec. cm−3), as revealed by direct comparisons. While the NO3- chemical ionisation method remains stable in the presence of high humidity, we have observed that the Br− chemical ionisation method (Br−–MION2) is significantly affected by the air water content. Higher levels of air water lead to reduced sensitivity for HO2 and SO2 under the examined conditions. However, we have found that a sharp decline in sensitivity for H2SO4, HOI, and I2 occurs only when the dew point exceeds 0.5–10.5 ∘C (equivalent to 20 %–40 % RH; calculated at 25 ∘C throughout this paper). For future studies utilising the atmospheric pressure Br− chemical ionisation method, including Br−–MION2, it is crucial to carefully consider the molecular-level effects of humidity. By combining approaches such as the water-insensitive NO3-–MION2 with Br−–MION2, MION2 can offer more comprehensive insights into atmospheric composition than what can be achieved by either method alone. By employing instrument voltage scanning, chemical kinetic experiments, and quantum chemical calculations, we have conclusively established that the presence of iodine oxides does not interfere with the detection of HIO3. Our comprehensive analysis reveals that the ions IO3-, HIO3⚫NO3-, and HIO3⚫Br−, which are detected using the Br− and NO3- chemical ionisation methods, are primarily, if not exclusively, generated from gaseous HIO3 molecules within atmospherically relevant conditions.

The exceptionally long and protracted aridity in the Atacama Desert (AD), Chile, provides an extreme, terrestrial ecosystem that is ideal for studying microbial community dynamics under hyperarid conditions. Our aim was to characterize the temporal response of hyperarid soil AD microbial communities to ex situ simulated rainfall (5% g water/g dry soil for 4 weeks) without nutrient amendment. We conducted replicated microcosm experiments with surface soils from two previously well-characterized AD hyperarid locations near Yungay at 1242 and 1609 masl (YUN1242 and YUN1609) with distinct microbial community compositions and average soil relative humidity levels of 21 and 17%, respectively. The bacterial and archaeal response to soil wetting was evaluated by 16S rRNA gene qPCR, and amplicon sequencing. Initial YUN1242 bacterial and archaeal 16S rRNA gene copy numbers were significantly higher than for YUN1609. Over the next 4 weeks, qPCR results showed significant increases in viable bacterial abundance, whereas archaeal abundance decreased. Both communities were dominated by 10 prokaryotic phyla (Actinobacteriota, Proteobacteria, Chloroflexota, Gemmatimonadota, Firmicutes, Bacteroidota, Planctomycetota, Nitrospirota, Cyanobacteriota, and Crenarchaeota) but there were significant site differences in the relative abundances of Gemmatimonadota and Chloroflexota, and specific actinobacterial orders. The response to simulated rainfall was distinct for the two communities. The actinobacterial taxa in the YUN1242 community showed rapid changes while the same taxa in the YUN1609 community remained relatively stable until day 30. Analysis of inferred function of the YUN1242 microbiome response implied an increase in the relative abundance of known spore-forming taxa with the capacity for mixotrophy at the expense of more oligotrophic taxa, whereas the YUN1609 community retained a stable profile of oligotrophic, facultative chemolithoautotrophic and mixotrophic taxa. These results indicate that bacterial communities in extreme hyperarid soils have the capacity for growth in response to simulated rainfall; however, historic variations in long-term hyperaridity exposure produce communities with distinct putative metabolic capacities.

Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics and in particular in studying the life cycle of weather systems. The three-dimensional (3-D) structure and temporal evolution of the associated PV features, however, are not yet fully understood. An automated technique to objectively identify 3-D PV features can help to shed light on 3-D atmospheric dynamics in specific case studies as well as facilitate statistical evaluations within climatological studies. Such a technique to identify PV features fully in 3-D, however, does not yet exist. This study presents a novel algorithm for the objective identification of PV anomalies along the dynamical tropopause in gridded data, as commonly output by numerical simulation models. The algorithm is inspired by morphological image processing techniques and can be applied to both two-dimensional (2-D) and 3-D fields on vertically isentropic levels. The method maps input data to a horizontally stereographic projection and relies on an efficient computation of horizontal distances within the projected field. Candidates for PV anomaly features are filtered according to heuristic criteria, and feature description vectors are obtained for further analysis. The generated feature descriptions are well suited for subsequent case studies of 3-D atmospheric dynamics as represented by the underlying numerical simulation. We evaluate our approach by comparison with an existing 2-D technique and demonstrate the full 3-D perspective by means of a case study of an extreme precipitation event that was dynamically linked to a prominent subtropical PV anomaly. The case study demonstrates variations in the 3-D structure of the detected PV anomalies that would not have been captured by a 2-D method. We discuss further advantages of using a 3-D approach, including elimination of temporal inconsistencies in the detected features due to 3-D structural variation and elimination of the need to manually select a specific isentropic level on which the anomalies are assumed to be best captured. These advantages, as well as the suitability of the implementation to process big data sets, also open applications for climatological analyses. The method is made available as open-source for straightforward use by the atmospheric community.

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

Abstract The aim of the study was a systematic evaluation of cognitive development in individuals with glutaric aciduria type 1 (GA1), a rare neurometabolic disorder, identified by newborn screening in Germany. This national, prospective, observational, multi-centre study includes 107 individuals with confirmed GA1 identified by newborn screening between 1999 and 2020 in Germany. Clinical status, development, and IQ were assessed using standardized tests. Impact of interventional and non-interventional parameters on cognitive outcome was evaluated. The majority of tested individuals (n = 72) showed stable IQ values with age (n = 56 with IQ test; median test age 11 years) but a significantly lower performance (median [IQR] IQ 87 [78–98]) than in general population, particularly in individuals with a biochemical high excreter phenotype (84 [75–96]) compared to the low excreter group (98 [92–105]; p = 0.0164). For all patients, IQ results were homogenous on subscale levels. Sex, clinical motor phenotype and quality of metabolic treatment had no impact on cognitive functions. Long-term neurologic outcome in GA1 involves both motor and cognitive functions. The biochemical high excreter phenotype is the major risk factor for cognitive impairment while cognitive functions do not appear to be impacted by current therapy and striatal damage. These findings implicate the necessity of new treatment concepts.

To pave the way for healthy aging in early treated phenylketonuria (ETPKU) patients, a better understanding of the neurological course in this population is needed, requiring easy accessible biomarkers to monitor neurological disease progression in large cohorts. The objective of this pilot study was to investigate the potential of glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) as blood biomarkers to indicate changes of the central nervous system in ETPKU. In this single-center cross-sectional study, GFAP and NfL concentrations in serum were quantified using the Simoa® multiplex technology in 56 ETPKU patients aged 6–36 years and 16 age matched healthy controls. Correlation analysis and hierarchical linear regression analysis were performed to investigate an association with disease-related biochemical parameters and retinal layers assessed by optical coherence tomography. ETPKU patients did not show significantly higher GFAP concentrations (mean 73 pg/ml) compared to healthy controls (mean 60 pg/ml, p = 0.140). However, individual pediatric and adult ETPKU patients had GFAP concentrations above the healthy control range. In addition, there was a significant association of GFAP concentrations with current plasma tyrosine concentrations (r = −0.482, p = 0.036), a biochemical marker in phenylketonuria, and the retinal inner nuclear layer volume (r = 0.451, p = 0.04). There was no evidence of NfL alterations in our ETPKU cohort. These pilot results encourage multicenter longitudinal studies to further investigate serum GFAP as a complementary tool to better understand and monitor neurological disease progression in ETPKU. Follow-up investigations on aging ETPKU patients are required to elucidate the potential of serum NfL as biomarker.

Abstract Background Cobalamin (cbl)-related remethylation disorders are a heterogeneous group of inherited disorders comprising the remethylation of homocysteine to methionine and affecting multiple organ systems, most prominently the nervous system and the bone marrow. To date, the parenteral, generally intramuscular, lifelong administration of hydroxycobalamin (OHCbl) is the mainstay of therapy in these disorders. The dosage and frequency of OHCbl is titrated in each patient to the minimum effective dose in order to account for the painful injections. This may result in undertreatment, a possible risk factor for disease progression and disease-related complications. Results We describe parenteral administration of OHCbl using a subcutaneous catheter together with a portable infusion pump in a home therapy setting in four pediatric patients with remethylation disorders, two patients with cblC, one patient with cblG, and one patient with cblE deficiency, in whom intramuscular injections were not or no longer feasible. The placement of the subcutaneous catheters and handling of the infusion pump were readily accomplished and well accepted by the patients and their families. No adverse events occurred. The use of a small, portable syringe driver pump allowed for a most flexible administration of OHCbl in everyday life. The concentrations of total homocysteine levels were determined at regular patient visits and remained within the therapeutic target range. This approach allowed for the continuation of OHCbl therapy or the adjustment of therapy required to improve metabolic control in our patients. Conclusions Subcutaneous infusion using a subcutaneous catheter system and a portable pump for OHCbl administration in combined and isolated remethylation disorders is safe, acceptable, and effective. It decreases disease burden in preventing frequent single injections and providing patient independence. Thus, it may promote long-term adherence to therapy in patients and parents.

Life evolved on this planet under the pull of gravity, shielded from radiation by the magnetosphere and shaped by circadian rhythms due to Earth’s rotation on its axis. Once living beings leave such a protective environment, adaptive responses are activated to grant survival. In view of long manned mission out of Earth’s orbit, it is relevant to understand how humans adapt to space and if the responses activated might reveal detrimental in the long run. Here we review present knowledge about the effects on the vessels of various extraterrestrial factors on humans as well as in vivo and in vitro experimental models. It emerges that the vasculature activates complex adaptive responses finalized to supply oxygen and nutrients to all the tissues and to remove metabolic waste and carbon dioxide. Most studies point to oxidative stress and mitochondrial dysfunction as mediators of vascular alterations in space. Unraveling the cellular and molecular mechanisms involved in these adaptive processes might offer hints to design proper and personalized countermeasures to predict a safe future in space.

Introduction A growing body of evidence suggests that hearing loss is a significant and potentially modifiable risk factor for cognitive impairment. Although the mechanisms underlying the associations between cognitive decline and hearing loss are unclear, listening effort has been posited as one of the mechanisms involved with cognitive decline in older age. To date, there has been a lack of research investigating this association, particularly among adults with mild cognitive impairment (MCI).Methods and analysis 15–25 cognitively healthy participants and 15–25 patients with MCI (age 40–85 years) will be recruited to participate in an exploratory study investigating the association between cognitive functioning and listening effort. Both behavioural and objective measures of listening effort will be investigated. The sentence-final word identification and recall (SWIR) test will be administered with single talker non-intelligible speech background noise while monitoring pupil dilation. Evaluation of cognitive function will be carried out in a clinical setting using a battery of neuropsychological tests. This study is considered exploratory and proof of concept, with information taken to help decide the validity of larger-scale trials.Ethics and dissemination Written approval exemption was obtained by the Scientific Ethics Committee in the central region of Denmark (De Videnskabsetiske Komiteer i Region Hovedstaden), reference 19042404, and the project is registered pre-results at clinicaltrials.gov, reference NCT04593290, Protocol ID 19042404. Study results will be disseminated in peer-reviewed journals and conferences.

BackgroundThe gold standard measurement for recording sleep is polysomnography performed in a hospital environment for 1 night. This requires individuals to sleep with a device and several sensors attached to their face, scalp, and body, which is both cumbersome and expensive. Self-trackers, such as wearable sensors (eg, smartwatch) and nearable sensors (eg, sleep mattress), can measure a broad range of physiological parameters related to free-living sleep conditions; however, the optimal duration of such a self-tracker measurement is not known. For such free-living sleep studies with actigraphy, 3 to 14 days of data collection are typically used. ObjectiveThe primary goal of this study is to investigate if 3 to 14 days of sleep data collection is sufficient while using self-trackers. The secondary goal is to investigate whether there is a relationship among sleep quality, physical activity, and heart rate. Specifically, we study whether individuals who exhibit similar activity can be clustered together and to what extent the sleep patterns of individuals in relation to seasonality vary. MethodsData on sleep, physical activity, and heart rate were collected over 6 months from 54 individuals aged 52 to 86 years. The Withings Aura sleep mattress (nearable; Withings Inc) and Withings Steel HR smartwatch (wearable; Withings Inc) were used. At the individual level, we investigated the consistency of various physical activities and sleep metrics over different time spans to illustrate how sensor data from self-trackers can be used to illuminate trends. We used exploratory data analysis and unsupervised machine learning at both the cohort and individual levels. ResultsSignificant variability in standard metrics of sleep quality was found between different periods throughout the study. We showed specifically that to obtain more robust individual assessments of sleep and physical activity patterns through self-trackers, an evaluation period of >3 to 14 days is necessary. In addition, we found seasonal patterns in sleep data related to the changing of the clock for daylight saving time. ConclusionsWe demonstrate that >2 months’ worth of self-tracking data are needed to provide a representative summary of daily activity and sleep patterns. By doing so, we challenge the current standard of 3 to 14 days for sleep quality assessment and call for the rethinking of standards when collecting data for research purposes. Seasonal patterns and daylight saving time clock change are also important aspects that need to be taken into consideration when choosing a period for collecting data and designing studies on sleep. Furthermore, we suggest using self-trackers (wearable and nearable ones) to support longer-term evaluations of sleep and physical activity for research purposes and, possibly, clinical purposes in the future.

BackgroundAnalyses of electronic medical databases often compare clinical practice to guideline recommendations. These analyses have a limited ability to simultaneously evaluate many interconnected medical decisions. We aimed to overcome this limitation with an alternative method and apply it to the diagnostic workup of HIV, where misuse can contribute to HIV transmission, delay care, and incur unnecessary costs.MethodsWe used graph theory to assess patterns of HIV diagnostic testing in a national healthcare system. We modeled the HIV diagnostic testing guidelines as a directed graph. Each node in the graph represented a test, and the edges pointed from one test to the next in chronological order. We then graphed each patient's HIV testing. This set of patient-level graphs was aggregated into a single graph. Finally, we compared the two graphs, the first representing the recommended approach to HIV diagnostic testing and the second representing the observed patterns of HIV testing, to assess for clinical practice deviations.ResultsThe HIV diagnostic testing of 1.643 million patients provided 8.790 million HIV diagnostic test results for analysis. Significant deviations from recommended practice were found including the use of HIV resistance tests (n = 3,007) and HIV nucleic acid tests (n = 16,567) instead of the recommended HIV screen.ConclusionsWe developed a method that modeled a complex medical scenario as a directed graph. When applied to HIV diagnostic testing, we identified deviations in clinical practice from guideline recommendations. The model enabled the identification of intervention targets and prompted systemwide policy changes to enhance HIV detection.

An amendment to this paper has been published and can be accessed via the original article.

In phenylalanine hydroxylase (PAH) deficiency, an easily feasible method to access the progression of neurodegeneration is warranted to contribute to current discussions on treatment indications and targets. The objective of the present study was to investigate whether optical coherence tomography (OCT) measures as markers of neurodegeneration differ between patients with PAH deficiency and healthy controls (HCs) according to phenotype and metabolic control. In this single-center cross-sectional study, 92 patients with different phenotypes of PAH deficiency [PAH deficiency not requiring treatment, early treated phenylketonuria (ETPKU), and late-diagnosed phenylketonuria (PKU)] compared with 76 HCs were examined using spectral-domain OCT. Indices of phenylalanine elevation and variability were correlated with OCT parameters. Late-diagnosed PKU patients showed reduced peripapillary retinal nerve fiber layer (pRNFL) thickness and combined ganglion cell and inner plexiform layer (GCIPL) volume. Adult ETPKU patients were found to have lower GCIPL volume (p = 0.016), which correlated with the indices of phenylalanine control. In pediatric ETPKU patients with poor metabolic control, pRNFL was significantly reduced (p = 0.004). Patients with PAH deficiency not requiring treatment did not exhibit retinal degeneration. Inner nuclear layer (INL) was significantly increased in the pediatric ETPKU patients, driven by those with current poor metabolic control (p = 0.006). Our data provide evidence of retinal neuroaxonal degeneration and INL swelling, depending on the phenotype, current age, and metabolic control. These findings suggest that OCT is suitable to investigate neurodegeneration in PKU and we propose OCT as a sensitive, reliable, safe, low-burden, and low-cost examination for future multicenter studies.

Microbial communities in incipient soil systems serve as the only biotic force shaping landscape evolution. However, the underlying ecological forces shaping microbial community structure and function are inadequately understood. We used amplicon sequencing to determine microbial taxonomic assembly and metagenome sequencing to evaluate microbial functional assembly in incipient basaltic soil subjected to precipitation. Community composition was stratified with soil depth in the pre-precipitation samples, with surficial communities maintaining their distinct structure and diversity after precipitation, while the deeper soil samples appeared to become more uniform. The structural community assembly remained deterministic in pre- and post-precipitation periods, with homogenous selection being dominant. Metagenome analysis revealed that carbon and nitrogen functional potential was assembled stochastically. Sub-populations putatively involved in the nitrogen cycle and carbon fixation experienced counteracting assembly pressures at the deepest depths, suggesting the communities may functionally assemble to respond to short-term environmental fluctuations and impact the landscape-scale response to perturbations. We propose that contrasting assembly forces impact microbial structure and potential function in an incipient landscape; in situ landscape characteristics (here homogenous parent material) drive community structure assembly, while short-term environmental fluctuations (here precipitation) shape environmental variations that are random in the soil depth profile and drive stochastic sub-population functional dynamics.

Carnitine transporter defect (CTD) is a potentially life-threatening disorder causing acute metabolic decompensation, cardiac arrhythmia, and cardiac and skeletal myopathies. CTD is included in many newborn screening (NBS) programs. The screening parameter free carnitine, however, is influenced by maternal conditions due to placental transfer. This study reviewed the NBS results for CTD as part of a pilot study in Bavaria, Germany, and the long-term follow-up of the identified patients treated in our center between January 1999 and June 2018. Among 1,816,000 Bavarian NBS samples, six newborns were diagnosed with CTD (incidence of 1:302,667; positive predictive value (PPV) of 1.63% from 2008 to 2018). In the 24 newborns presented to our center for confirmatory testing, we detected four newborns and six mothers with CTD, one newborn and three mothers in whom CTD was presumed but not genetically confirmed, and one mother with glutaric aciduria type I. In 11 newborns, no indication for an inborn error of metabolism was found. The newborns and mothers with CTD had no serious cardiac adverse events or relevant muscular symptoms at diagnosis and during treatment for up to 14 years. Three mothers were lost to follow-up. Revealing a lower incidence than expected, our data confirm that NBS for CTD most likely misses newborns with CTD. It rather produces high numbers of false-positives and a low PPV picking up asymptomatic mothers with a diagnosis of uncertain clinical significance. Our data add to the growing evidence that argues against an implementation of CTD in NBS programs.

Mechanical cues contribute to the maintenance of a healthy endothelium, which is essential for vascular integrity. Indeed endothelial cells are mechanosensors that integrate the forces in the form of biochemical signals. The cytoskeleton is fundamental in sensing mechanical stimuli and activating specific signaling pathways. Because the cytoskeleton is very rapidly remodeled in endothelial cells exposed to microgravity, we investigated whether the disruption of actin polymerization by cytochalasin D in 1g condition triggers and orchestrates responses similar to those occurring in micro- and macro-vascular endothelial cells upon gravitational unloading. We focused our attention on the effect of simulated microgravity on stress proteins and transient receptor potential melastatin 7 (TRPM7), a cation channel that acts as a mechanosensor and modulates endothelial cell proliferation and stress response. Simulated microgravity downregulates TRPM7 in both cell types. However, 24 h of treatment with cytochalasin D decreases the amounts of TRPM7 only in macrovascular endothelial cells, suggesting that the regulation and the role of TRPM7 in microvascular cells are more complex than expected. The 24 h culture in the presence of cytochalasin D mimics the effect of simulated microgravity in modulating stress response in micro- and macro-vascular endothelial cells. We conclude that cytoskeletal disruption might mediate some effects of microgravity in endothelial cells.

Common methods for measuring soil denitrification in situ include monitoring the accumulation of 15N-labelled N2 and N2O evolved from 15N-labelled soil nitrate pool in closed chambers that are placed on the soil surface. Gas diffusion is considered to be the main transport process in the soil. Because accumulation of gases within the chamber decreases concentration gradients between soil and the chamber over time, the surface efflux of gases decreases as well, and gas production rates are underestimated if calculated from chamber concentrations without consideration of this mechanism. Moreover, concentration gradients to the non-labelled subsoil exist, inevitably causing downward diffusion of 15N-labelled denitrification products. A numerical 3-D model for simulating gas diffusion in soil was used in order to determine the significance of this source of error. Results show that subsoil diffusion of 15N-labelled N2 and N2O – and thus potential underestimation of denitrification derived from chamber fluxes – increases with chamber deployment time as well as with increasing soil gas diffusivity. Simulations based on the range of typical soil gas diffusivities of unsaturated soils showed that the fraction of N2 and N2O evolved from 15N-labelled NO3- that is not emitted at the soil surface during 1 h chamber closing is always significant, with values up to >50 % of total production. This is due to accumulation in the pore space of the 15N-labelled soil and diffusive flux to the unlabelled subsoil. Empirical coefficients to calculate denitrification from surface fluxes were derived by modelling multiple scenarios with varying soil water content. Modelling several theoretical experimental set-ups showed that the fraction of produced gases that are retained in soil can be lowered by lowering the depth of 15N labelling and/or increasing the length of the confining cylinder. Field experiments with arable silt loam soil for measuring denitrification with the 15N gas flux method were conducted to obtain direct evidence for the incomplete surface emission of gaseous denitrification products. We compared surface fluxes of 15N2 and 15N2O from 15N-labelled micro-plots confined by cylinders using the closed-chamber method with cylinders open or closed at the bottom, finding 37 % higher surface fluxes with the bottom closed. Modelling fluxes of this experiment confirmed this effect, however with a higher increase in surface flux of 89 %. From our model and experimental results we conclude that field surface fluxes of 15N-labelled N2 and N2O severely underestimate denitrification rates if calculated from chamber accumulation only. The extent of this underestimation increases with closure time. Underestimation also occurs during laboratory incubations in closed systems due to pore space accumulation of 15N-labelled N2 and N2O. Due to this bias in past denitrification measurements, denitrification in soils might be more relevant than assumed to date. Corrected denitrification rates can be obtained by estimating subsurface flux and storage with our model. The observed deviation between experimental and modelled subsurface flux revealed the need for refined model evaluation, which must include assessment of the spatial variability in diffusivity and production and the spatial dimension of the chamber.

Water is a key component of life, the natural environment and human health. For monitoring the conditions of a water body, the chlorophyll a concentration can serve as a proxy for nutrients and oxygen supply. In situ measurements of water quality parameters are often time-consuming, expensive and limited in areal validity. Therefore, we apply remote sensing techniques. During field campaigns, we collected hyperspectral data with a spectrometer and in situ measured chlorophyll a concentrations of 13 inland water bodies with different spectral characteristics. One objective of this study is to estimate chlorophyll a concentrations of these inland waters by applying three machine learning regression models: Random Forest, Support Vector Machine and an Artificial Neural Network. Additionally, we simulate four different hyperspectral resolutions of the spectrometer data to investigate the effects on the estimation performance. Furthermore, the application of first order derivatives of the spectra is evaluated in turn to the regression performance. This study reveals the potential of combining machine learning approaches and remote sensing data for inland waters. Each machine learning model achieves an R2-score between 80% to 90% for the regression on chlorophyll a concentrations. The random forest model benefits clearly from the applied derivatives of the spectra. In further studies, we will focus on the application of machine learning models on spectral satellite data to enhance the area-wide estimation of chlorophyll a concentration for inland waters.

At radioactive ion beam (RIB) facilities, ions of short-lived radionuclides are cooled and bunched in buffer-gas-filled Paul traps to improve the ion-beam quality for subsequent experiments. To deliver even colder ions, beneficial to RIB experiments' sensitivity or accuracy, we employ Doppler and sympathetic cooling in a Paul trap cooler-buncher. The improved emittance of Mg^{+}, K^{+}, and O_{2}^{+} ion beams is demonstrated by a reduced time-of-flight spread of the extracted ion bunches with respect to room-temperature buffer-gas cooling. Cooling externally-produced hot ions with energies of at least 7 eV down to a few Kelvin is achieved in a timescale of O(100 ms) by combining a low-pressure helium background gas with laser cooling. This is sufficiently short to cool short-lived radioactive ions. As an example of this technique's use for RIB research, the mass-resolving power in a multireflection time-of-flight mass spectrometer is shown to increase by up to a factor of 4.6 with respect to buffer-gas cooling. Simulations show good agreement with the experimental results and guide further improvements and applications. These results open a path to a significant emittance improvement and, thus, unprecedented ion-beam qualities at RIB facilities, achievable with standard equipment readily available. The same method provides opportunities for future high-precision experiments with radioactive cold trapped ions.

Environmental contamination is a fundamental determinant of health and well-being, and when the environment is compromised, vulnerabilities are generated. The complex challenges associated with environmental health and food security are influenced by current and emerging political, social, economic, and environmental contexts. To solve these “wicked” dilemmas, disparate public health surveillance efforts are conducted by local, state, and federal agencies. More recently, citizen/community science (CS) monitoring efforts are providing site-specific data. One of the biggest challenges in using these government datasets, let alone incorporating CS data, for a holistic assessment of environmental exposure is data management and interoperability. To facilitate a more holistic perspective and approach to solution generation, we have developed a method to provide a common data model that will allow environmental health researchers working at different scales and research domains to exchange data and ask new questions. We anticipate that this method will help to address environmental health disparities, which are unjust and avoidable, while ensuring CS datasets are ethically integrated to achieve environmental justice. Specifically, we used a transdisciplinary research framework to develop a methodology to integrate CS data with existing governmental environmental monitoring and social attribute data (vulnerability and resilience variables) that span across 10 different federal and state agencies. A key challenge in integrating such different datasets is the lack of widely adopted ontologies for vulnerability and resiliency factors. In addition to following the best practice of submitting new term requests to existing ontologies to fill gaps, we have also created an application ontology, the Superfund Research Project Data Interface Ontology (SRPDIO).

The automated analysis of large areas with respect to land-cover and land-use is nowadays typically performed based on the use of hyperspectral or multispectral data acquired from airborne or spaceborne platforms. While hyperspectral data offer a more detailed description of the spectral properties of the Earth’s surface and thus a great potential for a variety of applications, multispectral data are less expensive and available in shorter time intervals which allows for time series analyses. Particularly with the recent availability of multispectral Sentinel-2 data, it seems desirable to have a comparative assessment of the potential of both types of data for land-cover and land-use classification. In this paper, we focus on such a comparison and therefore involve both types of data. On the one hand, we focus on the potential of hyperspectral data and the commonly applied techniques for data-driven dimensionality reduction or feature selection based on these hyperspectral data. On the other hand, we aim to reason about the potential of Sentinel-2 data and therefore transform the acquired hyperspectral data to Sentinel-2-like data. For performance evaluation, we provide classification results achieved with the different types of data for two standard benchmark datasets representing an urban area and an agricultural area, respectively.

In this paper, we investigate the potential of estimating the soil-moisture content based on VNIR hyperspectral data combined with LWIR data. Measurements from a multi-sensor field campaign represent the benchmark dataset which contains measured hyperspectral, LWIR, and soil-moisture data conducted on grassland site. We introduce a regression framework with three steps consisting of feature selection, preprocessing, and well-chosen regression models. The latter are mainly supervised machine learning models. An exception are the self-organizing maps which combine unsupervised and supervised learning. We analyze the impact of the distinct preprocessing methods on the regression results. Of all regression models, the extremely randomized trees model without preprocessing provides the best estimation performance. Our results reveal the potential of the respective regression framework combined with the VNIR hyperspectral data to estimate soil moisture measured under real-world conditions. In conclusion, the results of this paper provide a basis for further improvements in different research directions.

Abstract Background Mitochondrial trifunctional protein (MTP) and long-chain 3-hydroxyacyl-CoA dehydrogenase (LCHAD) deficiency are long-chain fatty acid oxidation disorders with particularly high morbidity and mortality. Outcome can be favorable if diagnosed in time, prompting the implementation in newborn screening programs. Sporadic cases missed by the initial screening sample have been reported. However, little is known on pitfalls during confirmatory testing resulting in fatal misconception of the diagnosis. Results We report a series of three patients with MTP and LCHAD deficiency, in whom diagnosis was missed by newborn screening, resulting in life-threatening metabolic decompensations within the first half year of life. Two of the patients showed elevated concentrations of primary markers C16-OH and C18:1-OH but were missed by confirmatory testing performed by the maternity clinic. A metabolic center was not consulted. Confirmatory testing consisted of analyses of acylcarnitines in blood and organic acids in urine, the finding of normal excretion of organic acids led to rejection and underestimation of the diagnosis, respectively. The third patient, a preterm infant, was not identified in the initial screening sample due to only moderate elevations of C16-OH and C18:1-OH and normal secondary markers and analyte ratios. Conclusion Our observations highlight limitations of newborn screening for MTP/LCHAD deficiency. They confirm that analyses of acylcarnitines in blood and organic acids in urine alone are not suitable for confirmatory testing and molecular or functional analysis is crucial in diagnosing MTP/LCHAD deficiency. Mild elevations of primary biomarkers in premature infants need to trigger confirmatory testing. Our report underscores the essential role of specialized centers in confirming or ruling out diagnoses in suspicious screening results.

Genetic prediction of complex traits so far has limited accuracy because of insufficient understanding of the genetic risk. Here, Maier et al. develop an improved method for trait prediction that makes use of genetic correlations between traits and apply it to summary statistics of psychiatric diseases.

Vitamin D (VitD) exerts protective effects on the endothelium, which is fundamental for vascular integrity, partly by inhibiting free radical formation. We found that VitD prevents high glucose-induced Thioredoxin Interacting Protein (TXNIP) upregulation. Increased amounts of TXNIP are responsible for the accumulation of reactive oxygen species and, as a consequence, of lipid droplets. This is associated with increased amounts of triglycerides as the result of increased lipogenesis and reduced fatty acid oxidation. Remarkably, VitD rebalances the redox equilibrium, restores normal lipid content, and prevents the accumulation of lipid droplets. Our results highlight TXNIP as one of the targets of VitD in high glucose-cultured endothelial cells and shed some light on the protective effect of VitD on the endothelium.

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Based on a contrastive approach that compares the argumentative genre of editorial with the narrative genre of personal narrative across two production modes, single-authored data and data elicited in an editing-based task, this paper examines the impact of genre on the realizations of discourse relations, paying particular attention to the argumentative genre and its preferential realizations of Contrast, Continuation, Elaboration and Explanation/Result. Discourse relations are conceived of as sociocognitive constructs that are encoded in coherence strands and may additionally be signalled overtly with discourse connectives, metacomments and/or pragmatic word order. Quantitative analyses of single-authored and co-constructed data reveal systematic differences in the variation of degrees of overtness between editorials and personal narratives. In the argumentative genre, Explanation, Continuation and Comment tend to be realized with a lower degree of overtness, Elaboration with a higher degree of overtness. Contrast is realized overtly throughout the data, irrespective of genre.

Understanding water management is a crucial aspect in the development of improved polymer electrolyte fuel cells (PEFCs). Separating the performance degradation due to dehydration, water flooding and reactant starvation in PEFCs is a major challenge. In this study, acoustic emission (AE) analysis, a non-invasive and non-destructive diagnostic tool, is utilised to probe water formation and removal inside an operating fuel cell. In the acoustic emission as a function of polarisation (AEfP) method, AE activity from the PEFC is measured in terms of cumulative absolute AE energy (CAEE) hits during operation at discrete points on the polarisation curve. AEfP can identify the presence of liquid water in flow channels and correlate its formation and removal with the level of cell polarisation, and consequent internal temperature. Correlation between acoustic activity and water generation, supply and removal is achieved by varying current (polarisation), cathode air feed relative humidity (RH) and cell temperature, respectively. Features such as initial membrane hydration, liquid water formation, ‘flushing’ and the transition from ‘wet-channel’ to ‘dry-channel’ operation are identified using AE analysis, thereby providing a powerful and easy to implement diagnostic for PEFCs. Keywords: Acoustic emission, Flushing, Start-up, In-operando, Flooding, Water management

Challenges to the reclamation of pyritic mine tailings arise from in situ acid generation that severely constrains the growth of natural revegetation. While acid mine drainage (AMD) microbial communities are well-studied under highly acidic conditions, fewer studies document the dynamics of microbial communities that generate acid from pyritic material under less acidic conditions that can allow establishment and support of plant growth. This research characterizes the taxonomic composition dynamics of microbial communities present during a 6-year compost-assisted phytostabilization field study in extremely acidic pyritic mine tailings. A complementary microcosm experiment was performed to identify successional community populations that enable the acidification process across a pH gradient. Taxonomic profiles of the microbial populations in both the field study and microcosms reveal shifts in microbial communities that play pivotal roles in facilitating acidification during the transition between moderately and highly acidic conditions. The potential co-occurrence of organoheterotrophic and lithoautotrophic energy metabolisms during acid generation suggests the importance of both groups in facilitating acidification. Taken together, this research suggests that key microbial populations associated with pH transitions could be used as bioindicators for either sustained future plant growth or for acid generation conditions that inhibit further plant growth.

Phytostabilized highly acidic, pyritic mine tailings are susceptible to re-acidification over time despite initial addition of neutralizing amendments. Studies examining plant-associated microbial dynamics during re-acidification of phytostabilized regions are sparse. To address this, we characterized the rhizosphere and bulk bacterial communities of buffalo grass used in the phytostabilization of metalliferous, pyritic mine tailings undergoing re-acidification at the Iron King Mine and Humboldt Smelter Superfund Site in Dewey-Humboldt, AZ. Plant-associated substrates representing a broad pH range (2.35–7.76) were sampled to (1) compare the microbial diversity and community composition of rhizosphere and bulk compartments across a pH gradient, and (2) characterize how re-acidification affects the abundance and activity of the most abundant plant growth-promoting bacteria (PGPB; including N2-fixing) versus acid-generating bacteria (AGB; including Fe-cycling/S-oxidizing). Results indicated that a shift in microbial diversity and community composition occurred at around pH 4. At higher pH (>4) the species richness and community composition of the rhizosphere and bulk compartments were similar, and PGPB, such as Pseudomonas, Arthrobacter, Devosia, Phyllobacterium, Sinorhizobium, and Hyphomicrobium, were present and active in both compartments with minimal presence of AGB. In comparison, at lower pH (

Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population stratification. More generally, our results imply that typical constructions of polygenic scores are sensitive to population stratification and that population-level differences should be interpreted with caution.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Glutaric aciduria type I (GA-1) is a rare autosomal-recessive disorder of the degradation of the amino acids lysine and tryptophan caused by mutations of the GCDH gene encoding glutaryl-CoA-dehydrogenase. Newborn screening (NBS) for this condition is based on elevated levels of glutarylcarnitine (C5DC) in dried blood spots (DBS). Here we report four cases from three families in whom a correctly performed NBS did not detect the condition. Glutarylcarnitine concentrations were either normal (slightly below) or slightly above the cut-off. Ratios to other acylcarnitines were also not persistently elevated. Therefore, three cases were defined as screen negative, and one case was defined as normal, after a normal control DBS sample. One patient was diagnosed after an acute encephalopathic crisis, and the other three patients had an insidious onset of the disease. GA-1 was genetically confirmed in all cases. Despite extensive efforts to increase sensitivity and specificity of NBS for GA-1, by adjusting cut-offs and introducing various ratios, the biological diversity still leads to false-negative NBS results for GA-1.

Information about the chlorophyll a concentration of inland water bodies is essential for water monitoring. This study focuses on estimating chlorophyll a with remote sensing data, and machine learning (ML) approaches on the real-world SpecWa dataset. We adapt and apply a one-dimensional convolutional neural network (1D CNN) as a deep learning architecture for the first time to address this estimation. Since such a DL approach requires a large amount of data for its training, we rely on simulation data generated by the Water Color Simulator (WASI). This simulation is prepared accordingly and includes a knowledge-based water composition with two origins of the chlorophyll a concentration. Therefore, the training data is independent of the real-world SpecWa dataset, which is challenging for any ML approach. We define two spectral downsampling approaches as a pre-processing step, representing the hyperspectral EnMAP satellite mission (SR-EnMAP) and the multispectral Sentinel-2 mission (SR-Sentinel). Subsequently, we train a Random Forest, an artificial neural network, a band-ratio approach, and the 1D CNN on the WASI-generated simulation training dataset. Finally, all ML models are evaluated on the real SpecWa dataset. For both downsampled data, the 1D CNN outperforms the other ML models. On the finer resolved SR-EnMAP data it achieves an R2=81.9%, RMSE=12.4 μg L−1, and MAE=6.7 μg L−1. Besides, the 1D CNN’s performance decreases on the SR-Sentinel data to R2=62.4%. When focusing on the individual water bodies of the SpecWa dataset, the most significant differences exist between natural and artificial water bodies. We discover that the applied models estimate the chlorophyll a concentration of most natural water bodies satisfyingly. In sum, the newly DL approach can estimate the chlorophyll a values of unknown inland water bodies successfully, although it is trained on an entire simulation dataset.

This contribution covers the major historic milestones of the evolution of gas chromatography (GC) from its beginnings to its current status as one of the most powerful analytical separation techniques, and demonstrates simultaneously how this technique has enabled and continuously improved the analysis of organic binding media in objects of cultural heritage. After an introduction into the basics of chromatography, the development of GC is traced from its emergence in the late 1800s as a mere preparative technique through a period of relative stagnation into the mid of the 20th century. Then, the 1950s are covered by highlighting the major advances in theory and technology within this decade, all of which contributed to firmly consolidate the status of GC as a modern analytical separation technique. From there the maturing of GC is followed through the 1960s up to the present days, a period being marked by the transition from packed to capillary columns; the essential adaptation of injection and detection devices; the replacement of glass by fused silica as column material; major progresses in stationary phase chemistry; and, finally, the advent of the hyphenation of GC with mass spectrometric detection devices. Throughout this survey, examples of applications of contemporary GC techniques to binding media analysis are discussed to provide an illustrative historic record of the continuous improvements achieved. The account will be closed with critical reflections on GC’s current relevance to and future role in the analysis of binding media in objects of cultural heritage.

The concept of bacterial growth and substrate utilization is foundational in the field of microbiology, yet the teaching of this concept is often limited to a graph displaying a single ideal growth curve. As a result, the underlying mathematics are often ignored, and when they are introduced, the equations are generally splashed across the screen with little expectation for student retention or comprehension. We have designed a web-based, interactive learning program called Environmental Science Studios (ESStudios: http://esstudios.arizona.edu/) to model microbial growth to promote active, hands-on, problem-solving that fosters a deep understanding of the mathematics of growth phenomena. The ESStudios Microbial Growth and Dynamics Modeling Program was used as a supplement to traditional lecture in an environmental microbiology course. Using the program, students were able to easily conduct a large number of virtual experiments, make direct on-screen comparisons across experiments, and develop a strong understanding of the effect of growth parameters on microbial growth curves. Student feedback on the activity was positive, and during the activity, we noted they asked questions indicative of higher level understanding. This activity demonstrates ESStudio’s potential to shift the pedagogy from teaching microbial growth using generalizations and dry oration to teaching the concept with visuals, case-studies, and interactions that allow direct relation of the underlying mathematics with the physical manifestations of microbial growth.

With the implementation of tandem mass spectrometry (MS/MS), neonatal screening for medium-chain acyl-CoA dehydrogenase (MCADD) has been introduced in many screening programs worldwide. Together with phenylketonuria, MCADD is the disorder most frequently diagnosed. Despite undeniable beneficial effects on morbidity and mortality, neonatal screening for MCADD effectively exemplifies the unexpected challenges of increased diagnosis by screening programs. MS/MS-based screening revealed an at least 2-fold higher incidence than expected with a considerable share of individuals showing mild biochemical alterations and/or novel mutations with unknown clinical significance. Whether these individuals are at lower risk to experience metabolic decompensations is a matter of ongoing debate. Defining patients, stratifying them according to their clinical risk, and adopting treatment protocols is an as yet unmet challenge in neonatal screening for MCADD.

ABSTRACT Global deserts occupy one-third of the Earth’s surface and contribute significantly to organic carbon storage, a process at risk in dryland ecosystems that are highly vulnerable to climate-driven ecosystem degradation. The forces controlling desert ecosystem degradation rates are poorly understood, particularly with respect to the relevance of the arid-soil microbiome. Here we document correlations between increasing aridity and soil bacterial and archaeal microbiome composition along arid to hyperarid transects traversing the Atacama Desert, Chile. A meta-analysis reveals that Atacama soil microbiomes exhibit a gradient in composition, are distinct from a broad cross-section of nondesert soils, and yet are similar to three deserts from different continents. Community richness and diversity were significantly positively correlated with soil relative humidity (SoilRH). Phylogenetic composition was strongly correlated with SoilRH, temperature, and electrical conductivity. The strongest and most significant correlations between SoilRH and phylum relative abundance were observed for Acidobacteria, Proteobacteria, Planctomycetes, Verrucomicrobia, and Euryarchaeota (Spearman’s rank correlation [rs] = >0.81; false-discovery rate [q] = ≤0.005), characterized by 10- to 300-fold decreases in the relative abundance of each taxon. In addition, network analysis revealed a deterioration in the density of significant associations between taxa along the arid to hyperarid gradient, a pattern that may compromise the resilience of hyperarid communities because they lack properties associated with communities that are more integrated. In summary, results suggest that arid-soil microbiome stability is sensitive to aridity as demonstrated by decreased community connectivity associated with the transition from the arid class to the hyperarid class and the significant correlations observed between soilRH and both diversity and the relative abundances of key microbial phyla typically dominant in global soils. IMPORTANCE We identify key environmental and geochemical factors that shape the arid soil microbiome along aridity and vegetation gradients spanning over 300 km of the Atacama Desert, Chile. Decreasing average soil relative humidity and increasing temperature explain significant reductions in the diversity and connectivity of these desert soil microbial communities and lead to significant reductions in the abundance of key taxa typically associated with fertile soils. This finding is important because it suggests that predicted climate change-driven increases in aridity may compromise the capacity of the arid-soil microbiome to sustain necessary nutrient cycling and carbon sequestration functions as well as vegetative cover in desert ecosystems, which comprise one-third of the terrestrial biomes on Earth.

Phytostabilization is a remediation technology that uses plants for in-situ stabilization of contamination in soils and mine tailings. The objective of this study was to identify native plant species with potential for phytostabilization of the abandoned mine tailings in Nacozari, Sonora in northern Mexico. A flora of 42 species in 16 families of angiosperms was recorded on the tailings site and the abundance of the most common perennial species was estimated. Four of the five abundant perennial species showed evidence of regeneration: the ability to reproduce and establish new seedlings. A comparison of selected physicochemical properties of the tailings in vegetated patches with adjacent barren areas suggests that pH, electrical conductivity, texture, and concentration of potentially toxic elements do not limit plant distribution. For the most abundant species, the accumulation factor for most metals was

Small air pressure fluctuations in the atmosphere are responsible for the pressure pumping effect, which leads to an enhancement of soil gas transport. To investigate the spatial variability of these air pressure fluctuations, several high-precision differential pressure sensors were installed at the floor of a Scots pine forest. The alignment of the pressure sensors allowed for the determination of the propagation direction and speed of the observed air pressure fluctuations. Below-canopy and above-canopy airflow characteristics were monitored to find possible links between the air pressure fluctuations and the airflow. Results show that the propagation direction of the air pressure fluctuations observed at the forest floor correspond to the above-canopy and not to the below-canopy wind direction. Moreover, propagation speed of the air pressure fluctuations is higher than the below-canopy wind speed and corresponds to above-canopy wind speed. These findings indicate a connection between below-canopy air pressure fluctuations and above-canopy airflow. The air pressure fluctuations were found to be well correlated up to a distance of 15 m. With increasing distance, the correlation strongly decreases. However, the calculated pressure pumping coefficient, which quantifies the strength of the pressure pumping effect, yields similar values up to a distance of 90 m. This allowed specifying the range of influence of the air pressure fluctuations.

Water scarcity is a global issue that is expected to continue increasing in importance in the coming decades. Reclaimed water is one important source available to meet future needs. The reclamation process for wastewaters, particularly from industrial sources, involves the need to remove low-level contaminants. Here we report the efficacy of an ion flotation process that uses the biosurfactant monorhamnolipid as a metal collector to recover Cs+, Cd2+, and La3+ from water. These elements were tested at collector-to-colligend ratios of 2, 5, and 10. The collector-to-colligend ratio and metal valence play a large role in determining flotation success with removal efficiencies varying widely. The maximum removal efficiency for the metals when floated individually were 46.2, 99.8, and 98.6% for Cs+, Cd2+, and La3+, respectively. When mixed together at near equimolar concentrations removal efficiencies were 39.4, 98.4, and 88.1%, respectively. Removal efficiency for Cs+, Cd2+, and La3+ were up to 49.9, 99.5, and 51.5% when mixed at a ratio of 200:10:1, whereas conditional stability constants predict a removal order of La3+ > Cd2+> Cs+. Future research should examine parameters, including pH and ionic strength, that may affect the flotation process as well as actual metal-contaminated waste streams to evaluate the usefulness of this technology.

The essential processes and mechanisms of the transport of contaminants from a river to a well field via a flood water retention area are presented. The transport is conceptualized as a succession of three phases: (1) contaminant entry into the retention area, (2) passage through the soil zone and (3) transport with the groundwater flow. Depending on the conditions of a given location and on the properties of the contaminants of interest, processes within each transport phase may reduce the concentration of the contaminants at the well field. For the Kastenwoert-Rappenwoert study area, the results of the described processes are shown by chemical and ecotoxicological analyses as well as by numerical modelling. Based on the results of the analyses, it is predicted that some contaminants in the study area will be completely detained along the transport path, while others will be transported as far as the well field, although in significantly reduced concentrations.

The serine–threonine kinase Akt is a cell survival signaling pathway that inactivates the proapoptotic BCL-2 family protein Bad and promotes cell survival in cerebral ischemia. Involvement of the Akt/Bad signaling pathway after spinal cord injury (SCI) is, however, uncertain. Our results showed that phospho-Akt (serine-473) and phospho-Bad (serine-136) were significantly upregulated at 1 day after SCI. In addition, phospho-Akt and phospho-Bad were colocalized in motor neurons that survived SCI and inhibition of PI3-K reduced expression of phospho-Akt and phospho-Bad. Dimerization of Bad with 14-3-3 in the cytosol was increased whereas Bad/Bcl-XL binding in the mitochondria was decreased after SCI. We further found that reduced oxidative stress by SOD1 overexpression in rats enhanced the expression of phospho-Akt, phospho-Bad, Bad/14-3-3 binding and reduced Bad/Bcl-XL binding after SCI, as compared to wild-type rats. We conclude that oxidative stress may play a role in modulating Akt/Bad signaling and subsequent motor neuron survival after SCI.