In Situ Monitoring of the Catalytic Activity of Cytochrome c Oxidase in a Biomimetic Architecture

AbstractCytochrome c oxidase (CcO) from Paracoccus denitrificans was immobilized in a strict orientation via a his-tag attached to subunit I on a gold film and reconstituted in situ into a protein-tethered bilayer lipid membrane. In this orientation, the cytochrome c (cyt c) binding site is directed away from the electrode pointing to the outer side of the protein-tethered bilayer lipid membrane architecture. The CcO can thus be activated by cyt c under aerobic conditions. Catalytic activity was monitored by impedance spectroscopy, as well as cyclic voltammetry. Cathodic and anodic currents of the CcO with cyt c added to the bulk solution were shown to increase under aerobic compared to anaerobic conditions. Catalytic activity was considered in terms of repeated electrochemical oxidation/reduction of the CcO/cyt c complex in the presence of oxygen. The communication of cyt c bound to the CcO with the electrode is discussed in terms of a hopping mechanism through the redox sites of the enzyme. Simulations supporting this hypothesis are included

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Molecular excitation in the Interstellar Medium: recent advances in collisional, radiative and chemical processes

We review the different excitation processes in the interstellar mediumComment: Accepted in Chem. Re

The 2020 UV emitter roadmap

Solid state UV emitters have many advantages over conventional UV sources. The (Al,In,Ga)N material system is best suited to produce LEDs and laser diodes from 400 nm down to 210 nm—due to its large and tuneable direct band gap, n- and p-doping capability up to the largest bandgap material AlN and a growth and fabrication technology compatible with the current visible InGaN-based LED production. However AlGaN based UV-emitters still suffer from numerous challenges compared to their visible counterparts that become most obvious by consideration of their light output power, operation voltage and long term stability. Most of these challenges are related to the large bandgap of the materials. However, the development since the first realization of UV electroluminescence in the 1970s shows that an improvement in understanding and technology allows the performance of UV emitters to be pushed far beyond the current state. One example is the very recent realization of edge emitting laser diodes emitting in the UVC at 271.8 nm and in the UVB spectral range at 298 nm. This roadmap summarizes the current state of the art for the most important aspects of UV emitters, their challenges and provides an outlook for future developments

Serum Potassium and Risk of Death or Kidney Replacement Therapy in Older People With CKD Stages 4-5: Eight-Year Follow-up

Rationale & Objective: Hypokalemia may accelerate kidney function decline. Both hypo- and hyperkalemia can cause sudden cardiac death. However, little is known about the relationship between serum potassium and death or the occurrence of kidney failure requiring replacement therapy (KRT). We investigated this relationship in older people with chronic kidney disease (CKD) stage 4-5. Study Design: Prospective observational cohort study. Setting & Participants: We followed 1,714 patients (≥65 years old) from the European Quality (EQUAL) study for 8 years from their first estimated glomerular filtration rate (eGFR) < 20 mL/min/1.73 m2 measurement. Exposure: Serum potassium was measured every 3 to 6 months and categorized as ≤3.5, >3.5-≤4.0, >4.0-≤4.5, >4.5-≤5.0 (reference), >5.0-≤5.5, >5.5-≤6.0, and >6.0 mmol/L. Outcome: The combined outcome death before KRT or start of KRT. Analytical Approach: The association between categorical and continuous time-varying potassium and death or KRT start was examined using Cox proportional hazards and restricted cubic spline analyses, adjusted for age, sex, diabetes, cardiovascular disease, renin-angiotensin-aldosterone system (RAAS) inhibition, eGFR, and subjective global assessment (SGA). Results: At baseline, 66% of participants were men, 42% had diabetes, 47% cardiovascular disease, and 54% used RAAS inhibitors. Their mean age was 76 ± 7 (SD) years, mean eGFR was 17 ± 5 (SD) mL/min/1.73 m2, and mean SGA was 6.0 ± 1.0 (SD). Over 8 years, 414 (24%) died before starting KRT, and 595 (35%) started KRT. Adjusted hazard ratios for death or KRT according to the potassium categories were 1.6 (95% CI, 1.1-2.3), 1.4 (95% CI, 1.1-1.7), 1.1 (95% CI, 1.0-1.4), 1 (reference), 1.1 (95% CI, 0.9-1.4), 1.8 (95% CI, 1.4-2.3), and 2.2 (95% CI, 1.5-3.3). Hazard ratios were lowest at a potassium of about 4.9 mmol/L. Limitations: Shorter intervals between potassium measurements would have allowed for more precise estimations. Conclusions: We observed a U-shaped relationship between serum potassium and death or KRT start among patients with incident CKD 4-5, with a nadir risk at a potassium level of 4.9 mmol/L. These findings underscore the potential importance of preventing both high and low potassium in patients with CKD 4-5. Plain-Language Summary: Abnormal potassium blood levels may increase the risk of death or kidney function decline, especially in older people with chronic kidney disease (CKD). We studied 1,714 patients aged ≥65 years with advanced CKD from the European Quality (EQUAL) study and followed them for 8 years. We found that both low and high levels of potassium were associated with an increased risk of death or start of kidney replacement therapy, with the lowest risk observed at a potassium level of 4.9 mmol/L. In patients with CKD, the focus is often on preventing high blood potassium. However, this relatively high optimum potassium level stresses the potential importance of also preventing low potassium levels in older patients with advanced CKD

Update of the fluid-rock geochemical modelling activity in storage research

Paper 37AKirste, D.; Schacht, U.; Higgs, K.; Underschultz, J

Evolution of formation water chemistry and geochemical modelling of the CO2CRC Otway Site residual gas saturation test

AbstractThe CO2CRC Otway Project Stage 2B field test was a residual CO2 saturation and dissolution experiment carried out on the Paaratte Formation in the Otway Basin of Australia. During the 87 day test a downhole U-tube sampling assembly was used to collect formation water samples at various time intervals. The waters were analysed for chemical composition, dissolved gas content and stable isotopic composition of H and O. Changes in the chemical and isotopic composition of the formation water were observed from the initial baseline samples collected through to the conclusion of the test. Systematic reoccurrences of relatively large linear changes in the alkalinity, Ca2+, Fe2+, Mg2+ and SiO2(aq) were observed during different test sequences. Similar behaviour occurred for the δ18O and δ2H values suggesting a complex system controlled by at least two processes. The chemical evolution was consistent with CO2-water-rock interactions, dominated by carbonate dissolution with some silicate dissolution. The mineral dissolution driven changes in water composition are overlain by what was clearly mixing of the injected and in situ formation water. The isotopic composition of the water was used to confirm the role of mixing and the calculated residual gas saturation values were broadly consistent with those derived by other methods. The extent of reaction in the relatively short time frame of the test was used to evaluate the capabilities of kinetics based reaction path models. The models were generated using published reaction rate data with commonly used assumptions regarding upscaling of reactive surface area. These assumptions consist of reducing the calculated geometric surface area that accounts for grain shape and roughness by factors of 100 to 1000 depending on the mineral habit. The numerical models provided a very good fit to the field data indicating that the rate data and the associated assumptions are relatively robust