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Blick in die Zukunft
(2019)
Vielfalt in der Uckermark
(2019)
Experimental and kinetic modelling studies are presented to investigate the mechanism of 3,3 ',5,5 '-tetramethylbenzidine (TMB) oxidation by hydrogen peroxide (H2O2) catalyzed by peroxidase-like Pt nanoparticles immobilized in spherical polyelectrolyte brushes (SPB-Pt). Due to the high stability of SPB-Pt colloidal, this reaction can be monitored precisely in situ by UV/VIS spectroscopy. The time-dependent concentration of the blue-colored oxidation product of TMB expressed by different kinetic models was used to simulate the experimental data by a genetic fitting algorithm. After falsifying the models with abundant experimental data, it is found that both H2O2 and TMB adsorb on the surface of Pt nanoparticles to react, indicating that the reaction follows the Langmuir-Hinshelwood mechanism. A true rate constant k, characterizing the rate-determining step of the reaction and which is independent on the amount of catalysts used, is obtained for the first time. Furthermore, it is found that the product adsorbes strongly on the surface of nanoparticles, thus inhibiting the reaction. The entire analysis provides a new perspective to study the catalytic mechanism and evaluate the catalytic activity of the peroxidase-like nanoparticles.
Purpose
After therapy of cancer of the esophagus or the esophagogastric junction, patients often suffer from anxiety and depression. Some risk factors for elevated anxiety and depression are reported, but the influence of steatorrhea, the frequency of which has only recently been reported, has not yet been investigated.
Method
Using the Hospital Anxiety and Depression Scale (HADS), we analyzed the correlation of anxiety and depression with steatorrhea, appetite, and weight loss in 72 patients with cancer of the esophagus or of the esophagogastric junction, who were treated at our rehabilitation clinic between January 2011 and December 2014. In addition, effectiveness of psychological interviews was analyzed.
Results
We have evaluable anxiety questionnaires from 51 patients showing a median anxiety value of 5 (range 0-13). As for the depression, results from evaluable questionnaires of 54 patients also showed a median value of 5 (range 0-15). Increased anxiety and depression values (> 7) were observed in 25.4% and 37.0% of the patients respectively. Patients who were admitted with steatorrhea for rehabilitation showed a statistically higher anxiety value (median 6.3 vs. 4.7, p < 0.05), reduced appetite, and a weight loss above 15 kg depicting a correlation to anxiety and depression. Psychological conversations helped lowering the depression but had no influence on anxiety.
Conclusions
Impairments after cancer treatment, such as steatorrhea, appetite loss, and weight loss, should be interpreted as an alarm signal and should necessitate screening for increased anxiety and depression. Psychological therapy can help improving the extent of the depression.
Polyhydroxyalkanoates (PHAs) have attracted attention as degradable (co)polyesters which can be produced by microorganisms with variations in the side chain. This structural variation influences not only the thermomechanical properties of the material but also its degradation behavior. Here, we used Langmuir monolayers at the air-water (A-W) interface as suitable models for evaluating the abiotic degradation of two PHAs with different side-chain lengths and crystallinity. By controlling the polymer state (semi crystalline, amorphous), the packing density, the pH, and the degradation mechanism, we could draw several significant conclusions. (i) The maximum degree of crystallinity for a PHA film to be efficiently degraded up to pH = 12.3 is 40%. (ii) PHA made of repeating units with shorter side-chain length are more easily hydrolyzed under alkaline conditions. The efficiency of alkaline hydrolysis decreased by about 65% when the polymer was 40% crystalline. (iii) In PHA films with a relatively high initial crystallinity, abiotic degradation initiated a chemicrystallization phenomenon, detected as an increase in the storage modulus (E'). This could translate into an increase in brittleness and reduction in the material degradability. Finally, we demonstrate the stability of the measurement system for long-term experiments, which allows degradation conditions for polymers that could closely simulate real-time degradation.
Geysers are hot springs whose frequency of water eruptions remain poorly understood. We set up a local broadband seismic network for 1 year at Strokkur geyser, Iceland, and developed an unprecedented catalog of 73,466 eruptions. We detected 50,135 single eruptions but find that the geyser is also characterized by sets of up to six eruptions in quick succession. The number of single to sextuple eruptions exponentially decreased, while the mean waiting time after an eruption linearly increased (3.7 to 16.4 min). While secondary eruptions within double to sextuple eruptions have a smaller mean seismic amplitude, the amplitude of the first eruption is comparable for all eruption types. We statistically model the eruption frequency assuming discharges proportional to the eruption multiplicity and a constant probability for subsequent events within a multituple eruption. The waiting time after an eruption is predictable but not the type or amplitude of the next one. <br /> Plain Language Summary Geysers are springs that often erupt in hot water fountains. They erupt more often than volcanoes but are quite similar. Nevertheless, it is poorly understood how often volcanoes and also geysers erupt. We created a list of 73,466 eruption times of Strokkur geyser, Iceland, from 1 year of seismic data. The geyser erupted one to six times in quick succession. We found 50,135 single eruptions but only 1 sextuple eruption, while the mean waiting time increased from 3.7 min after single eruptions to 16.4 min after sextuple eruptions. Mean amplitudes of each eruption type were higher for single eruptions, but all first eruptions in a succession were similar in height. Assuming a constant heat inflow at depth, we can predict the waiting time after an eruption but not the type or amplitude of the next one.