Solubility and diffusional uptake of hydrogen in quartz at high water pressures: Implications for hydrolytic weakening

Attempts to introduce molecular water into dry, natural quartz crystals by diffusive transport and thus weaken them hydrolytically at T = 700°–900°C and PH_2O = 400–1550 MPa have failed. Infrared spectroscopy of hydrothermally annealed single crystals of natural quartz reveals the diffusive uptake of interstitial hydrogen (resulting in hydroxyl groups) at rates similar to those previously proposed for intracrystalline water at high water pressures. The solubility of interstitial hydrogen at these conditions is independent of temperature and pressure; instead, it depends upon the initial aluminum concentration by the local charge neutrality condition [H_i·] = [Al_(Si)′]. The rate of interstitial hydrogen diffusion parallel to c is given by an Arrhenius relation with D_0 = 1.4 × 10^(−1) m^2/s and Q = 200 ± 20 kJ/mol, in close agreement with H diffusivities reported for much lower pressures (PH_2O = 2.5 MPa). Deformation experiments following hydrothermal annealing show no mechanical weakening, and the lack of any detectable broadband absorption associated with molecular water shows that the diffusion rates of structural water are much lower than those of hydrogen. These results are consistent with the available oxygen diffusion data for quartz and with the failure to observe weakening in previous studies of quartz deformation at pressures of 300–500 MPa; they call into question the rapid rates of diffusion originally suggested for the hydrolytic weakening defect. It is suggested that the observed weakening in many previous experiments was complicated by microcracking processes in response to nonhydrostatic stresses and low effective confining pressures. Extensive microcracking may provide a mechanism for molecular water to enter quartz and allow local plastic deformation to occur. It does not appear that molecular water can diffuse far enough into uncracked quartz to allow hydrolytic weakening over annealing times that are feasible in the laboratory

Increased brain-derived neurotrophic factor (BDNF) protein concentrations in mice lacking brain serotonin

The interplay between BDNF signaling and the serotonergic system remains incompletely understood. Using a highly sensitive enzyme-linked immunosorbent assay, we studied BDNF concentrations in hippocampus and cortex of two mouse models of altered serotonin signaling: tryptophan hydroxylase (Tph)2-deficient (Tph2 (-/-)) mice lacking brain serotonin and serotonin transporter (SERT)-deficient (SERT(-/-)) mice lacking serotonin re-uptake. Surprisingly, hippocampal BDNF was significantly elevated in Tph2 (-/-) mice, whereas no significant changes were observed in SERT(-/-) mice. Furthermore, BDNF levels were increased in the prefrontal cortex of Tph2 (-/-) but not of SERT(-/-) mice. Our results emphasize the interaction between serotonin signaling and BDNF. Complete lack of brain serotonin induces BDNF expression

Conceptual modeling for adaptive environmental assessment and management in the Barycz Valley, Lower Silesia, Poland

The complexity of interactions in socio-ecological systems makes it very difficult to plan and implement policies successfully. Traditional environmental management and assessment techniques produce unsatisfactory results because they often ignore facets of system structure that underlie complexity: delays, feedbacks, and non-linearities. Assuming that causes are linked in a linear chain, they concentrate on technological developments (“hard path”) as the only solutions to environmental problems. Adaptive Management is recognized as a promising alternative approach directly addressing links between social and ecological systems and involving stakeholders in the analysis and decision process. This “soft path” requires special tools to facilitate collaboration between “experts” and stakeholders in analyzing complex situations and prioritizing policies and actions. We have applied conceptual modeling to increase communication, understanding and commitment in the project of seven NGOs “Sustainable Regional Development in the Odra Catchment”. The main goal was to help our NGO partners to facilitate their efforts related to developing sustainable policies and practices to respond to large-scale challenges (EU accession, global changes in climate and economy) to their natural, economic and socio-cultural heritages. Among the variety of sustainability issues explored by these NGOs, two (extensive agricultural practices and “green” local products) were examined by using Adaptive Management (AM) as a framework that would link analysis, discussion, research, actions and monitoring. Within the AM framework the project coordinators used tools of systems analysis (Mental Model Mapping) to facilitate discussions in which NGO professionals and local stakeholders could graphically diagram and study their understanding of what factors interacted and how they affect the region’s sustainability. These discussions produced larger-scale Regional Sustainability Models as well as more detailed sub-models of particular factors, processes, and feedback loops that appear critical to a sustainable future. The Regional Sustainability Model was used to identify a subset of key interacting factors (variables). For each variable, several sustainability indicators were suggested. The growing understanding and acceptance of the AM framework and systems analysis created a momentum both locally and within the region, which makes continued successful use of these indicators quite likely. In contrast to expert-driven projects that inject outside knowledge into a local context, this project established a broad basis for stakeholder-driven discussion that is articulated into goals, objectives, conceptual models, and indicators. The ability to learn and adapt in the AM framework increases the capacity to innovate and find policies and practices that enhance resilience and sustainability in a world in transition

Environmental distribution of <i>Echinococcus</i> and <i>Taenia spp-</i>contaminated dog faeces in Kyrgyzstan

Recently, there have been epidemics of human cystic echinococcosis (CE) and alveolar echinococcosis (AE) in Kyrgyzstan. This study investigated 2 districts for the presence of Echinococcus granulosus s.l. and Echinococcus multilocularis eggs; species identity was confirmed by polymerase chain reaction in dog feces and the level of environmental contamination with parasite eggs in 2017–2018 was also investigated. In the Alay district 5 villages with a high reported annual incidence of AE of 162 cases per 100 000 and 5 villages in the Kochkor district which had a much lower incidence of 21 cases per 100 000 were investigated. However, the proportion of dog feces containing E. granulosus s.l. eggs was ~4.2 and ~3.5% in Alay and Kochkor respectively. For E. multilocularis, the corresponding proportions were 2.8 and 3.2%. Environmental contamination of Echinococcus spp. eggs was estimated using the McMaster technique for fecal egg counts, weight and density of canine feces. The level of environmental contamination with E. multilocularis eggs was similar at 4.4 and 5.0 eggs per m2 in Alay and Kochkor respectively. The corresponding values for E. granulosus s.l. were 8.3 and 7.5 eggs per m2. There was no association between village or district level incidence of human AE or CE and the proportion of dog feces containing eggs of Echinococcus spp. or the level of environmental contamination. Increased contamination of taeniid eggs occured in the autumn, after the return of farmers with dogs from summer mountain pastures

Discovery and genotyping of structural variation from long-read haploid genome sequence data

In an effort to more fully understand the full spectrum of human genetic variation, we generated deep single-molecule, real-time (SMRT) sequencing data from two haploid human genomes. By using an assembly-based approach (SMRT-SV), we systematically assessed each genome independently for structural variants (SVs) and indels resolving the sequence structure of 461,553 genetic variants from 2 bp to 28 kbp in length. We find that &gt;89% of these variants have been missed as part of analysis of the 1000 Genomes Project even after adjusting for more common variants (MAF &gt; 1%). We estimate that this theoretical human diploid differs by as much as ∼16 Mbp with respect to the human reference, with long-read sequencing data providing a fivefold increase in sensitivity for genetic variants ranging in size from 7 bp to 1 kbp compared with short-read sequence data. Although a large fraction of genetic variants were not detected by short-read approaches, once the alternate allele is sequence-resolved, we show that 61% of SVs can be genotyped in short-read sequence data sets with high accuracy. Uncoupling discovery from genotyping thus allows for the majority of this missed common variation to be genotyped in the human population. Interestingly, when we repeat SV detection on a pseudodiploid genome constructed in silico by merging the two haploids, we find that ∼59% of the heterozygous SVs are no longer detected by SMRT-SV. These results indicate that haploid resolution of long-read sequencing data will significantly increase sensitivity of SV detection.</jats:p

Estimating antibiotic coverage from linked microbiological and clinical data from the Swiss Paediatric Sepsis Study to support empiric antibiotic regimen selection.

In light of rising antibiotic resistance, better methods for selection of empiric antibiotic treatment based on clinical and microbiological data are needed. Most guidelines target specific clinical infections, and variably adjust empiric antibiotic selection by certain patient characteristics. Coverage estimates reflect the probability that an antibiotic regimen will be active against the causative pathogen once confirmed and can provide an objective basis for empiric regimen selection. Coverage can be estimated for specific infections using a weighted incidence syndromic combination antibiograms (WISCAs) framework. However, no comprehensive data combining clinical and microbiological data for specific clinical syndromes are available in Switzerland. We therefore describe estimating coverage from semi-deterministically linked routine microbiological and cohort data of hospitalised children with sepsis. Coverage estimates were generated for each hospital and separately pooling data across ten contributing hospitals for five pre-defined patient risk groups. Data from 1,082 patients collected during the Swiss Paediatric Sepsis Study (SPSS) 2011-2015 were included. Preterm neonates were the most commonly represented group, and half of infants and children had a comorbidity. 67% of neonatal sepsis cases were hospital-acquired late-onset whereas in children 76% of infections were community-acquired. Escherichia coli, Coagulase-negative staphylococci (CoNS) and Staphylococcus aureus were the most common pathogens. At all hospitals, ceftazidime plus amikacin regimen had the lowest coverage, and coverage of amoxicillin plus gentamicin and meropenem were generally comparable. Coverage was improved when vancomycin was included in the regimen, reflecting uncertainty about the empirically targeted pathogen spectrum. Children with community-acquired infections had high coverage overall. It is feasible to estimate coverage of common empiric antibiotic regimens from linked data. Pooling data by patient risk groups with similar expected pathogen and susceptibility profiles may improve coverage estimate precision, supporting better differentiation of coverage between regimens. Identification of data sources, selection of regimens and consideration of pathogens to target for improved empiric coverage is important

Cortical cell stiffness is independent of substrate mechanics

Cortical stiffness is an important cellular property that changes during migration, adhesion and growth. Previous atomic force microscopy (AFM) indentation measurements of cells cultured on deformable substrates have suggested that cells adapt their stiffness to that of their surroundings. Here we show that the force applied by AFM to a cell results in a significant deformation of the underlying substrate if this substrate is softer than the cell. This ‘soft substrate effect’ leads to an underestimation of a cell’s elastic modulus when analysing data using a standard Hertz model, as confirmed by finite element modelling and AFM measurements of calibrated polyacrylamide beads, microglial cells and fibroblasts. To account for this substrate deformation, we developed a ‘composite cell–substrate model’. Correcting for the substrate indentation revealed that cortical cell stiffness is largely independent of substrate mechanics, which has major implications for our interpretation of many physiological and pathological processes

Phosphatidylinositol 3-Akt-kinase-dependent phosphorylation of p21(Waf1/Cip1) as a novel mechanism of neuroprotection by glucocorticoids

The role of glucocorticoids in the regulation of apoptosis remains incongruous. Here, we demonstrate that corticosterone protects neurons from apoptosis by a mechanism involving the cyclin-dependent kinase inhibitor p21(Waf1/Cip1). In primary cortical neurons, corticosterone leads to a dose- and Akt-kinase-dependent upregulation with enhanced phosphorylation and cytoplasmic appearance of p21(Waf1/Cip1) at Thr 145. Exposure of neurons to the neurotoxin ethylcholine aziridinium (AF64A) results in activation of caspase-3 and a dramatic loss of p21(Waf1/Cip1) preceding apoptosis in neurons. These effects of AF64A are reversed by pretreatment with corticosterone. Corticosterone-mediated upregulation of p21(Waf1/Cip1) and neuroprotection are completely abolished by glucocorticoid and mineralocorticoid receptor antagonists as well as inhibitors of PI3- and Akt-kinase. Both germline and somatically induced p21(Waf1/Cip1) deficiency abrogate the neuroprotection by corticosterone, whereas overexpression of p21(Waf1/Cip1) suffices to protect neurons from apoptosis. We identify p21(Waf1/Cip1) as a novel antiapoptotic factor for postmitotic neurons and implicate p21(Waf1/Cip1) as the molecular target of neuroprotection by high-dose glucocorticoids

Estimating antibiotic coverage from linked microbiological and clinical data from the Swiss Paediatric Sepsis Study to support empiric antibiotic regimen selection

In light of rising antibiotic resistance, better methods for selection of empiric antibiotic treatment based on clinical and microbiological data are needed. Most guidelines target specific clinical infections, and variably adjust empiric antibiotic selection by certain patient characteristics. Coverage estimates reflect the probability that an antibiotic regimen will be active against the causative pathogen once confirmed and can provide an objective basis for empiric regimen selection. Coverage can be estimated for specific infections using a weighted incidence syndromic combination antibiograms (WISCAs) framework. However, no comprehensive data combining clinical and microbiological data for specific clinical syndromes are available in Switzerland. We therefore describe estimating coverage from semi-deterministically linked routine microbiological and cohort data of hospitalised children with sepsis. Coverage estimates were generated for each hospital and separately pooling data across ten contributing hospitals for five pre-defined patient risk groups. Data from 1,082 patients collected during the Swiss Paediatric Sepsis Study (SPSS) 2011-2015 were included. Preterm neonates were the most commonly represented group, and half of infants and children had a comorbidity. 67% of neonatal sepsis cases were hospital-acquired late-onset whereas in children 76% of infections were community-acquired. Escherichia coli, Coagulase-negative staphylococci (CoNS) and Staphylococcus aureus were the most common pathogens. At all hospitals, ceftazidime plus amikacin regimen had the lowest coverage, and coverage of amoxicillin plus gentamicin and meropenem were generally comparable. Coverage was improved when vancomycin was included in the regimen, reflecting uncertainty about the empirically targeted pathogen spectrum. Children with community-acquired infections had high coverage overall. It is feasible to estimate coverage of common empiric antibiotic regimens from linked data. Pooling data by patient risk groups with similar expected pathogen and susceptibility profiles may improve coverage estimate precision, supporting better differentiation of coverage between regimens. Identification of data sources, selection of regimens and consideration of pathogens to target for improved empiric coverage is important