Possible involvement of a calmodulin regulated Ca2+-ATPase in exocytosis performance in Paramecium tetraurelia cells

AbstractSurface membrane fractions from Paramecium tetraurelia cells contain a calmodulin-stimulated Ca2+-ATPase responding to low levels of free Ca2+ and with features characteristic of a membrane-bound ATPase responding to low levels of free Ca2+ and with features characteristics of a membrane-bound ATPase. Among the different strains analyzed this enzyme was practically absent selectively from the ‘non-discharge” mutant nd9—28°C (from J. Beisson); if cultured at a permissive temperature (18°C), this strain showed identical values of calmodulin-stimulated Ca2+-ATPase activity as wild-type cells (7S) or strains with mutations which do not affect exocytosis performance. We conclude that this calmodulin-stimulated Ca2+-activated ATPase might be a prerequisite for membrane fusion in the course of exocytosis performance

Three-dimensional geoelectric modelling with optimal work/accuracy rate using an adaptive wavelet algorithm

Despite the ever-increasing power of modern computers, realistic modelling of complex 3-D earth models is still a challenging task and requires substantial computing resources. The overwhelming majority of current geophysical modelling approaches includes either finite difference or non-adaptive finite element algorithms and variants thereof. These numerical methods usually require the subsurface to be discretized with a fine mesh to accurately capture the behaviour of the physical fields. However, this may result in excessive memory consumption and computing times. A common feature of most of these algorithms is that the modelled data discretizations are independent of the model complexity, which may be wasteful when there are only minor to moderate spatial variations in the subsurface parameters. Recent developments in the theory of adaptive numerical solvers have the potential to overcome this problem. Here, we consider an adaptive wavelet-based approach that is applicable to a large range of problems, also including nonlinear problems. In comparison with earlier applications of adaptive solvers to geophysical problems we employ here a new adaptive scheme whose core ingredients arose from a rigorous analysis of the overall asymptotically optimal computational complexity, including in particular, an optimal work/accuracy rate. Our adaptive wavelet algorithm offers several attractive features: (i) for a given subsurface model, it allows the forward modelling domain to be discretized with a quasi minimal number of degrees of freedom, (ii) sparsity of the associated system matrices is guaranteed, which makes the algorithm memory efficient and (iii) the modelling accuracy scales linearly with computing time. We have implemented the adaptive wavelet algorithm for solving 3-D geoelectric problems. To test its performance, numerical experiments were conducted with a series of conductivity models exhibiting varying degrees of structural complexity. Results were compared with a non-adaptive finite element algorithm, which incorporates an unstructured mesh to best-fitting subsurface boundaries. Such algorithms represent the current state-of-the-art in geoelectric modelling. An analysis of the numerical accuracy as a function of the number of degrees of freedom revealed that the adaptive wavelet algorithm outperforms the finite element solver for simple and moderately complex models, whereas the results become comparable for models with high spatial variability of electrical conductivities. The linear dependence of the modelling error and the computing time proved to be model-independent. This feature will allow very efficient computations using large-scale models as soon as our experimental code is optimized in terms of its implementatio

3-D electrical resistivity tomography using adaptive wavelet parameter grids

We present a novel adaptive model parametrization strategy for the 3-D electrical resistivity tomography problem and demonstrate its capabilities with a series of numerical examples. In contrast to traditional parametrization schemes, which are based on fixed disjoint blocks, we discretize the subsurface in terms of Haar wavelets and adaptively adjust the parametrization as the iterative inversion proceeds. This results in a favourable balance of cell sizes and parameter reliability, that is, in regions where the data constrain the subsurface properties well, our parametrization strategy leads to a fine grid, whereas poorly resolved areas are represented only by a few large blocks. This is documented with eigenvalue analyses and by computing model resolution matrices. During the initial iteration steps, only a few model parameters are involved, which reduces the risk that the regularization dominates the inversion. The algorithm also automatically accounts for non-linear effects caused by pronounced conductivity contrasts. Inside conductive features a finer grid is generated than inside more resistive structures. The automated parameter adaptation is computationally efficient, because the coarsening and refinement subroutines have a nearly linear numerical complexity with respect to the number of model parameters. Because our approach is not tightly coupled to electrical resistivity tomography, it should be straightforward to adapt it to other data type

Verhaltenstherapeutische Behandlung eines Patienten mit beginnender Alzheimer-Demenz

The following case report shows a behavioral treatment of a 53-year-old Patient with Alzheimer's Disease (AD), The treatment includes procedures described in the Behavioral Competency Training (VKT) for patients with early-stage AD developed by Ehrhardt and associates. The program consists of about 20 weekly treatment sessions in which the patient's resources are activated and patient's coping is supported. The therapy and the intervention are debated in the light of the ongoing discussion about a state-of-the-art therapy for AD

Making SPIFFI SPIFFIER: Upgrade of the SPIFFI instrument for use in ERIS and performance analysis from re-commissioning

SPIFFI is an AO-fed integral field spectrograph operating as part of SINFONI on the VLT, which will be upgraded and reused as SPIFFIER in the new VLT instrument ERIS. In January 2016, we used new technology developments to perform an early upgrade to optical subsystems in the SPIFFI instrument so ongoing scientific programs can make use of enhanced performance before ERIS arrives in 2020. We report on the upgraded components and the performance of SPIFFI after the upgrade, including gains in throughput and spatial and spectral resolution. We show results from re-commissioning, highlighting the potential for scientific programs to use the capabilities of the upgraded SPIFFI. Finally, we discuss the additional upgrades for SPIFFIER which will be implemented before it is integrated into ERIS.Comment: 20 pages, 12 figures. Proceedings from SPIE Astronomical Telescopes and Instrumentation 201

FUM1—A Gene Required for Fumonisin Biosynthesis But Not for Maize Ear Rot and Ear Infection by Gibberella moniliformis in Field Tests

We have analyzed the role of fumonisins in infection of maize (Zea mays) by Gibberella moniliformis (anamorph Fusarium verticillioides) in field tests in Illinois and Iowa, United States. Fumonisin-nonproducing mutants were obtained by disrupting FUM1 (previouslyFUM5), the gene encoding a polyketide synthase required for fumonisin biosynthesis. Maize ear rot, ear infection, and fumonisin contamination were assessed by silk-channel injection in 1999 and 2000 and also by spray application onto maize silks, injection into maize stalks, and application with maize seeds at planting in 1999. Ear rot was evaluated by visual assessment of whole ears and by calculating percentage of symptomatic kernels by weight. Fumonisin levels in kernels were determined by high-performance liquid chromatography. The presence of applied strains in kernels was determined by analysis of recovered isolates for genetic markers and fumonisin production. Two independent fumonisin-nonproducing (fum1-3 and fum1-4) mutants were similar to their respective fumonisin-producing (FUM1-1) progenitor strains in ability to cause ear rot following silk-channel injection and also were similar in ability to infect maize ears following application by all four methods tested. This evidence confirms that fumonisins are not required for G. moniliformis to cause maize ear rot and ear infection

Mortality in Recreational Mountain-Biking in the Austrian Alps: A Retrospective Study over 16 Years.

Despite recreational mountain-biking's growing popularity worldwide, the literature on mortality in this leisure sporting activity is scarce. Therefore, the aim of the present study was to investigate the characteristics of fatal accidents as well as resulting dead victims during recreational mountain-biking in the Austrian Alps over the past 16 years. For this purpose, a retrospective study based on Austrian institutional documentation from 2006 to 2021 was conducted. In total, 97 fatalities (1 woman) with a mean age of 55.6 ± 13.9 years were recorded by the Austrian Alpine Police. Of those, 54.6% died due to a non-traumatic (mostly cardio-vascular) and 41.2% due to a traumatic event. Mountain-bikers fatally accidented for non-traumatic reasons frequently belonged to older age classes (p = 0.05) and mostly (73.6%) died during the ascent, whereas traumatic events mainly (70.0%) happened during the descent (p < 0.001). Throughout the examined period, the absolute number of fatalities slightly increased, whereas the mortality index (proportion of deaths/accidented victims) did not (mean value: 1.34 ± 0.56%). Factors such as male sex in general, above average age and uphill riding for non-traumatic accidents, as well as downhill riding for traumatic events, seem to be associated with fatalities during recreational mountain-biking in the Austrian Alps. These results should be considered for future preventive strategies in recreational mountain-biking

An Infinite Swapping Approach to the Rare-Event Sampling Problem

We describe a new approach to the rare-event Monte Carlo sampling problem. This technique utilizes a symmetrization strategy to create probability distributions that are more highly connected and thus more easily sampled than their original, potentially sparse counterparts. After discussing the formal outline of the approach and devising techniques for its practical implementation, we illustrate the utility of the technique with a series of numerical applications to Lennard-Jones clusters of varying complexity and rare-event character.Comment: 24 pages, 16 figure