Refine
Has Fulltext
- no (3)
Document Type
- Article (3)
Language
- English (3)
Is part of the Bibliography
- yes (3)
Keywords
- Body perception (1)
- Body size (1)
- Competitive growth strategies (1)
- Growth adjustment (1)
- Social group (1)
- Social network (1)
- amyloid precursor protein (1)
- amyloid precursor-like protein (1)
- animal movement (1)
- kernel density estimation (1)
Institute
- Institut für Biochemie und Biologie (3) (remove)
The amyloid precursor protein (APP) and its paralogs, amyloid precursor-like protein 1 (APLP1) and APLP2, are metalloproteins with a putative role both in synaptogenesis and in maintaining synapse structure. Here, we studied the effect of zinc on membrane localization, adhesion, and secretase cleavage of APP, APLP1, and APLP2 in cell culture and rat neurons. For this, we employed live-cell microscopy techniques, a microcontact printing adhesion assay and ELISA for protein detection in cell culture supernatants. We report that zinc induces the multimerization of proteins of the amyloid precursor protein family and enriches them at cellular adhesion sites. Thus, zinc facilitates the formation of de novo APP and APLP1 containing adhesion complexes, whereas it does not have such influence on APLP2. Furthermore, zinc-binding prevented cleavage of APP and APLPs by extracellular secretases. In conclusion, the complexation of zinc modulates neuronal functions of APP and APLPs by (i) regulating formation of adhesion complexes, most prominently for APLP1, and (ii) by reducing the concentrations of neurotrophic soluble APP/APLP ectodomains.
Meeting Reports
(2019)
Thirty-one scientists met at Aschauhof, Germany to discuss the role of beliefs and self-perception on body size. In view of apparent growth stimulatory effects of dominance within the social group that is observed in social mammals, they discussed various aspects of competitive growth strategies and growth adjustments. Presentations included new data from Indonesia, a cohort-based prospective study from Merida, Yucatan, and evidence from recent meta-analyses and patterns of growth in the socially deprived. The effects of stress experienced during pregnancy and adverse childhood events were discussed, as well as obesity in school children, with emphasis on problems when using z-scores in extremely obese children. Aspects were presented on body image in African-American women, and body perception and the disappointments of menopause in view of feelings of attractiveness in different populations. Secular trends in height were presented, including short views on so called 'racial types' vs bio-plasticity, and historic data on early-life nutritional status and later-life socioeconomic outcomes during the Dutch potato famine. New tools for describing body proportions in patients with variable degrees of phocomelia were presented along with electronic growth charts. Bio-statisticians discussed the influence of randomness, community and network structures, and presented novel tools and methods for analyzing social network data.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.