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Previously, [1,3]dioxolo[4,5-f][1,3]benzodioxole (DBD)-based fluorophores used as highly sensitive fluorescence lifetime probes reporting on their microenvironmental polarity have been described. Now, a new generation of DBD dyes has been developed. Although they are still sensitive to polarity, in contrast to the former DBD dyes, they have extraordinary spectroscopic properties even in aqueous surroundings. They are characterized by long fluorescence lifetimes (10-20ns), large Stokes shifts (approximate to 100nm), high photostabilities, and high quantum yields (>0.56). Here, the spectroscopic properties and synthesis of functionalized derivatives for labeling biological targets are described. Furthermore, thio-reactive maleimido derivatives of both DBD generations show strong intramolecular fluorescence quenching. This mechanism has been investigated and is found to undergo a photoelectron transfer (PET) process. After reaction with a thiol group, this fluorescence quenching is prevented, indicating successful bonding. Being sensitive to their environmental polarity, these compounds have been used as powerful fluorescence lifetime probes for the investigation of conformational changes in the maltose ATP-binding cassette transporter through fluorescence lifetime spectroscopy. The differing tendencies of the fluorescence lifetime change for both DBD dye generations promote their combination as a powerful toolkit for studying microenvironments in proteins.
Kritische Mineralstoffe in der Schwangerschaft sowie im Säuglings- und Kleinkindalter : Calcium
(1995)
Kritische Mineralstoffe in der Schwangerschaft sowie im Säuglings- und Kleinkindalter : Eisen
(1995)
Kritische Mineralstoffe in der Schwangerschaft sowie im Säuglings- und Kleinkindalter : Fluoride
(1995)
Tile drains strongly influence the water cycle in agricultural catchment in terms of water quantity and quality. The connectivity of preferential flow to tile drains can create shortcuts for rapid transport of solutes into surface waters. The leaching of pesticides can be linked to a set of main factors including, rainfall characteristics, soil moisture, chemical properties of the pesticides, soil properties, and preferential flow paths. The connectivity of the macropore system to the tile drain is crucial for pesticide leaching. Concurring influences of the main factors, threshold responses and the role of flow paths are still poorly understood. The objective of this study is to investigate these influences by a replica series of three irrigation experiments on a tile drain field site using natural and artificial tracers together with applied pesticides. We found a clear threshold behavior in the initialization of pesticide transport that was different between the replica experiments. Pre-event soil water contributed significantly to the tile drain flow, and creates a flow path for stored pesticides from the soil matrix to the tile drain. This threshold is controlled by antecedent soil moisture and precipitation characteristics, and the interaction between the soil matrix and preferential flow system. Fast transport of pesticides without retardation and the remobilization could be attributed to this threshold and the interaction between the soil matrix and the preferential flow system. Thus, understanding of the detailed preferential flow processes clearly enhances the understanding of pesticide leaching on event and long term scale, and can further improve risk assessment and modeling approaches. (C) 2014 Elsevier B.V. All rights reserved.
Prokaryotic solute binding protein-dependent ATP-binding cassette import systems are divided into type land type II and mechanistic differences in the transport process going along with this classification are under intensive investigation. Little is known about the conformational dynamics during the catalytic cycle especially concerning the transmembrane domains. The type I transporter for positively charged amino acids from Salmonella enterica serovar Typhimurium (1A0-Hi5QMP2) was studied by limited proteolysis in detergent solution in the absence and presence of co-factors including ATP, ADP, LAO/arginine, and Mg2+ ions. Stable peptide fragments could be obtained and differentially susceptible cleavage sites were determined by mass spectrometry as Lys-258 in the nucleotide-binding subunit, HisP, and Arg-217/Arg-218 in the transmembrane subunit, HisQ In contrast, transmembrane subunit HisM was gradually degraded but no stable fragment could be detected. HisP and HisQ were equally resistant under pre- and post-hydrolysis conditions in the presence of arginine-loaded solute-binding protein LAO and ATP/ADP. Some protection was also observed with LAO/arginine alone, thus reflecting binding to the transporter in the apo-state and transmembrane signaling. Comparable digestion patterns were obtained with the transporter reconstituted into proteoliposomes and nanodiscs. Fluorescence lifetime spectroscopy confirmed the change of HisQ(R218) to a more apolar microenvironment upon ATP binding and hydrolysis. Limited proteolysis was subsequently used as a tool to study the consequences of mutations on the transport cycle. Together, our data suggest similar conformational changes during the transport cycle as described for the maltose ABC transporter of Escherichia coli, despite distinct structural differences between both systems.
Despite advances in machine learning-based clinical prediction models, only few of such models are actually deployed in clinical contexts. Among other reasons, this is due to a lack of validation studies. In this paper, we present and discuss the validation results of a machine learning model for the prediction of acute kidney injury in cardiac surgery patients initially developed on the MIMIC-III dataset when applied to an external cohort of an American research hospital. To help account for the performance differences observed, we utilized interpretability methods based on feature importance, which allowed experts to scrutinize model behavior both at the global and local level, making it possible to gain further insights into why it did not behave as expected on the validation cohort. The knowledge gleaned upon derivation can be potentially useful to assist model update during validation for more generalizable and simpler models. We argue that interpretability methods should be considered by practitioners as a further tool to help explain performance differences and inform model update in validation studies.