Availability of Heavy Metals in Soils and their Uptake by Vegetable Species

Head lettuce, bush beans and celery were grown in subsequent years in an experimental field on anthropogenously uncontaminated or heavy metal contaminated soils at a mean pH of 6.3 ± 0.1. The contaminated plots were made up by amending or replacing the upper 20 cm soil layer with heavy metal contaminated alluvial top soil. Contamination includes Cd, Zn, Pb and Cu. Phytoavailable fractions of these elements were extracted with 1 M ammonium nitrate. Cd, Zn, Pb and Cu were also determined in the leaves of all three species as well as in bean pods and celery bulbs. The results show that plant uptake of Cd and Zn increased with increasing soil contamination while the uptake of Pb was low. No dependence of Cu uptake on total soil Cu content could be seen within the given contamination range. The relationship between Cd, Zn, Pb and Cu in plants and ammonium nitrate soil extracts was determined by twofactorial linear regression where r was approximately 0.8 for Zn, 0.7 for Cd and 0.5 for Pb whereas no relationship was found for Cu. For the pot experiments carried out in a greenhouse two different soils (loamy sand, silt loam) were amended with 5 and 10 % metallurgical slag and adjusted to pH levels around 7 and 5 while controls did not contain slag. Phytoavailable heavy metal fractions were extracted from soil samples using ammonium nitrate or Calcium chloride + DTPA (CAT). Spinach was grown on these soils and the concentrations of Cd, Zn, Pb and Cu in the shoots correlated with their concentration in the soil extracts. The uptake of these elements by the plants increased with increasing slag amendment and decreasing pH. Strong depression of growth was observed at a pH around 5 in all treatments of the lighter and in the slag treatments of the heavier soil. In the slag treatments this was accompanied by increased endogenous Cd and Zn concentrations. The plant content of Cd, Zn and Pb correlated better with the ammonium nitrate extractable soil fraction of these elements than in the field experiments (r > 0.9). Correlations based on the CAT extractable fraction of Cd and Zn yielded values for r around 0.5 while it was only 0.1 for Pb. As in the field trials correlations for Cu were very poor with both extraction methods

A Large-scale Virtual Patient Cohort to Study ECG Features of Interatrial Conduction Block

Interatrial conduction block refers to a disturbance in the propagation of electrical impulses in the conduction pathways between the right and the left atrium. It is a risk factor for atrial fibrillation, stroke, and premature death. Clinical diagnostic criteria comprise an increased P wave duration and biphasic P waves in lead II, III and aVF due to retrograde activation of the left atrium. Machine learning algorithms could improve the diagnosis but require a large-scale, well-controlled and balanced dataset. In silico electrocardiogram (ECG) signals, optimally obtained from a statistical shape model to cover anatomical variability, carry the potential to produce an extensive database meeting the requirements for successful machine learning application. We generated the first in silico dataset including interatrial conduction block of 9,800 simulated ECG signals based on a bi-atrial statistical shape model. Automated feature analysis was performed to evaluate P wave morphology, duration and P wave terminal force in lead V1. Increased P wave duration and P wave terminal force in lead V1 were found for models with interatrial conduction block compared to healthy models. A wide variability of P wave morphology was detected for models with interatrial conduction block. Contrary to previous assumptions, our results suggest that a biphasic P wave morphology seems to be neither necessary nor sufficient for the diagnosis of interatrial conduction block. The presented dataset is ready for a classification with machine learning algorithms and can be easily extended

Pilot-study on the influence of carrier gas and plasma application (open resp. delimited) modifications on physical plasma and its antimicrobial effect against Pseudomonas aeruginosa and Staphylococcus aureus

Introduction: Physical plasma is a promising new technology regarding its antimicrobial effects. This is especially accounting for treatment of bacterial infection of chronic wounds. Plasma can be generated with different carrier gases causing various biological effects. Screening of different carrier gases and plasma generation setups is therefore needed to find suitable compositions for highly effective antimicrobial plasma treatments and other applications

Expression of a novel versican variant in dorsal root ganglia from spared nerve injury rats

The size and modular structure of versican and its gene suggest the existence of multiple splice variants. We have identified, cloned, and sequenced a previously unknown exon located within the noncoding gene sequence downstream of exon 8. This exon, which we have named exon 8β, specifies two stop-codons. mRNAs of the versican gene with exon 8β are predicted to be constitutively degraded by nonsense-mediated RNA decay. Here, we tested the hypothesis that these transcripts become expressed in a model of neuropathic pain

Long‐term indoor gunshot exposure of special police forces induces bronchitic reactions and elevated blood lead levels—The Berlin shooting range study

Background Gunshot emissions contain toxic elements that can harm those frequently exposed, such as police officers. Several years ago, police indoor firing ranges were closed by the Berlin municipality in response to police officer health complaints, and an investigation was launched into the possible respiratory health risks of frequent gunshot emission exposure. We, therefore, conducted an exploratory cross-sectional study to investigate clinical and functional parameters of respiratory health as well as the burden of trace elements in policemen with long-term high exposure to indoor gunshot emissions, compared to low-exposure and control groups. Methods We conducted lung function tests and collected blood and urine samples from Berlin police officers and government employees who were divided into three subject groups based on exposure to gunshot emissions: high exposure (n = 53), low exposure (n = 94) and no exposure (n = 76). Lung function was examined using body plethysmography. Blood and urine samples were tested via inductively coupled plasma mass spectrometry for the presence of common gunshot powder elements (antimony, lead and manganese). Exposure and symptoms were assessed using records as well as questionnaires. Results Higher exposure was associated with more respiratory symptoms during gun shooting practice (64% vs. 21%, P < 0.001) compared to the low-exposure group. Headache, cough, discoloured mucous and shortness of breath were also more common as were some other symptoms. The cough symptomatology of the high-exposure group also persisted significantly longer (median: 0.67 vs. 0.01 days, range: 0 to 5 days, P = 0.029) compared to the low-exposure group. They also showed a lower forced expiratory volume in 1 s/forced vital capacity quotient (Tiffeneau index), P = 0.018 between the three groups and P = 0.005 for the high-exposure group, a possible marker of early, subclinical bronchial obstruction. We observed increased blood lead concentrations depending on subject's age (+1.2% per year, 95% confidence interval: 0.5–1.9%, P < 0.001) and cumulative gunshot exposure (+0.34% per 100 000 shots, 0.02–0.66%, P = 0.037). Conclusions These first results suggest that long-term exposure to indoor gunshot emissions induces bronchitic reactions due to repeated irritation of the airways. Higher levels of exposure lead to more negatively impacted lung function and higher blood lead levels with the possible reason that more frequent exposure may mean shorter regeneration phases for the respiratory mucous membrane. We recommend a reduction of exposure to gunshot emissions in order to decrease symptoms and avoid any—even small—deterioration in spirometry

Delineation of Two Clinically and Molecularly Distinct Subgroups of Posterior Fossa Ependymoma

Despite the histological similarity of ependymomas from throughout the neuroaxis, the disease likely comprises multiple independent entities, each with a distinct molecular pathogenesis. Transcriptional profiling of two large independent cohorts of ependymoma reveals the existence of two demographically, transcriptionally, genetically, and clinically distinct groups of posterior fossa (PF) ependymomas. Group A patients are younger, have laterally located tumors with a balanced genome, and are much more likely to exhibit recurrence, metastasis at recurrence, and death compared with Group B patients. Identification and optimization of immunohistochemical (IHC) markers for PF ependymoma subgroups allowed validation of our findings on a third independent cohort, using a human ependymoma tissue microarray, and provides a tool for prospective prognostication and stratification of PF ependymoma patients

Genome Sequencing of SHH Medulloblastoma Predicts Genotype-Related Response to Smoothened Inhibition

SummarySmoothened (SMO) inhibitors recently entered clinical trials for sonic-hedgehog-driven medulloblastoma (SHH-MB). Clinical response is highly variable. To understand the mechanism(s) of primary resistance and identify pathways cooperating with aberrant SHH signaling, we sequenced and profiled a large cohort of SHH-MBs (n = 133). SHH pathway mutations involved PTCH1 (across all age groups), SUFU (infants, including germline), and SMO (adults). Children >3 years old harbored an excess of downstream MYCN and GLI2 amplifications and frequent TP53 mutations, often in the germline, all of which were rare in infants and adults. Functional assays in different SHH-MB xenograft models demonstrated that SHH-MBs harboring a PTCH1 mutation were responsive to SMO inhibition, whereas tumors harboring an SUFU mutation or MYCN amplification were primarily resistant

Functional Brain Networks Develop from a “Local to Distributed” Organization

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements