Spin dynamics in semiconductors

This article reviews the current status of spin dynamics in semiconductors which has achieved a lot of progress in the past years due to the fast growing field of semiconductor spintronics. The primary focus is the theoretical and experimental developments of spin relaxation and dephasing in both spin precession in time domain and spin diffusion and transport in spacial domain. A fully microscopic many-body investigation on spin dynamics based on the kinetic spin Bloch equation approach is reviewed comprehensively.Comment: a review article with 193 pages and 1103 references. To be published in Physics Reports

Ungulate browsing shapes climate change impacts on forest biodiversity in Hungary

Climate change can result in a slow disappearance of forests dominated by less drought-tolerant native European beech (Fagus sylvatica) and oak species (Quercus spp.) and further area expansion of more drought-tolerant non-native black locust (Robinia pseudoacacia) against those species in Hungary. We assumed that the shift in plant species composition was modified by selective ungulate browsing. Thus, we investigated which woody species are selected by browsing game. We have collected data on the species composition of the understory and the browsing impact on it in five different Hungarian even-aged forests between 2003 and 2005. Based on these investigations the non-native Robinia pseudoacacialiving under more favourable climatic conditions was generally preferred (Jacobs’ selectivity index: D=0.04±0.77), while the nativeFagus sylvatica and Quercus spp. (Q. petraea, Q. robur), both more vulnerable to increasing aridity, were avoided (D=-0.37±0.11;-0.79±0.56;-0.9±0.16; respectively) among target tree species. However, economically less or not relevant species, e.g. elderberry (Sambucus spp.), blackberry (Rubus spp.) or common dogwood (Cornus sanguinea) were the most preferred species (D=0.01±0.71; -0.12±0.58; -0.2±0.78, respectively). Our results imply that biodiversity conservation, i.e. maintaining or establishing a multi-species understory layer, can be a good solution to reduce the additional negative game impact on native target tree species suffering from drought. Due to preference for Robinia pseudoacaciaselective browsing can decelerate the penetration of this species into native forest habitats. We have to consider the herbivorous pressure of ungulates and their feeding preferences in planning our future multifunctional forests in the light of climate change impacts

Glycan labeling strategies and their use in identification and quantification

Most methods for the analysis of oligosaccharides from biological sources require a glycan derivatization step: glycans may be derivatized to introduce a chromophore or fluorophore, facilitating detection after chromatographic or electrophoretic separation. Derivatization can also be applied to link charged or hydrophobic groups at the reducing end to enhance glycan separation and mass-spectrometric detection. Moreover, derivatization steps such as permethylation aim at stabilizing sialic acid residues, enhancing mass-spectrometric sensitivity, and supporting detailed structural characterization by (tandem) mass spectrometry. Finally, many glycan labels serve as a linker for oligosaccharide attachment to surfaces or carrier proteins, thereby allowing interaction studies with carbohydrate-binding proteins. In this review, various aspects of glycan labeling, separation, and detection strategies are discussed

Lake sedimentary dna research on past terrestrial and aquatic biodiversity: Overview and recommendations

The use of lake sedimentary DNA to track the long-term changes in both terrestrial and aquatic biota is a rapidly advancing field in paleoecological research. Although largely applied nowadays, knowledge gaps remain in this field and there is therefore still research to be conducted to ensure the reliability of the sedimentary DNA signal. Building on the most recent literature and seven original case studies, we synthesize the state-of-the-art analytical procedures for effective sampling, extraction, amplification, quantification and/or generation of DNA inventories from sedimentary ancient DNA (sedaDNA) via high-throughput sequencing technologies. We provide recommendations based on current knowledge and best practises.</jats:p

Mobility modeling of peptides in capillary electrophoresis

Recent rapid developments in proteomics require high-resolution separation of a large number of peptides for their downstream identification by mass spectrometry. Capillary electrophoresis (CE) is an electric-field-mediated bioanalytical technique capable of rapid, high-resolution separation of very complex sample mixtures. Development of CE methods for adequate separation of a large number of peptides is usually a time-consuming task. Application of model-based approaches to predict peptide mobilities in CE from known physicochemical properties can shorten tedious experimental optimization of separation. This endeavor requires specification of structural descriptors followed by selection of appropriate modeling methods. To date, numerous theoretical predictive models have been developed, mostly based on Stokes’ Law to relate peptide mobilities to structural properties (e.g., charge and size). However, these two-variable models could not successfully predict electrophoretic mobilities for all categories of peptides with a reasonable degree of accuracy. To address the shortcomings of the two-variable models, new strategies were recently introduced, including the usage of additional peptide descriptors or applying non-linear modeling (e.g., artificial neural networks), to attain more accurate, robust prediction. Effective application of machine-learning techniques to the development of predictive models has consolidated conjecture on non-linear relationships between peptide structural descriptors and their electrophoretic mobilities. In this article, we review recent advances in CE mobility modeling of peptides, particularly in respect to predicting optimal separation conditions for the analysis of highly complex peptide mixtures in proteomics applications