Inhibition of 26S proteasome activity by α-synuclein is mediated by the proteasomal chaperone Rpn14/PAAF1

\ua9 2024 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.Parkinson\u27s disease (PD) is characterized by aggregation of α-synuclein (α-syn) into protein inclusions in degenerating brains. Increasing amounts of aggregated α-syn species indicate significant perturbation of cellular proteostasis. Altered proteostasis depends on α-syn protein levels and the impact of α-syn on other components of the proteostasis network. Budding yeast Saccharomyces cerevisiae was used as eukaryotic reference organism to study the consequences of α-syn expression on protein dynamics. To address this, we investigated the impact of overexpression of α-syn and S129A variant on the abundance and stability of most yeast proteins using a genome-wide yeast library and a tandem fluorescent protein timer (tFT) reporter as a measure for protein stability. This revealed that the stability of in total 377 cellular proteins was altered by α-syn expression, and that the impact on protein stability was significantly enhanced by phosphorylation at Ser129 (pS129). The proteasome assembly chaperone Rpn14 was identified as one of the top candidates for increased protein stability by expression of pS129 α-syn. Elevated levels of Rpn14 enhanced the growth inhibition by α-syn and the accumulation of ubiquitin conjugates in the cell. We found that Rpn14 interacts physically with α-syn and stabilizes pS129 α-syn. The expression of α-syn along with elevated levels of Rpn14 or its human counterpart PAAF1 reduced the proteasome activity in yeast and in human cells, supporting that pS129 α-syn negatively affects the 26S proteasome through Rpn14. This comprehensive study into the alternations of protein homeostasis highlights the critical role of the Rpn14/PAAF1 in α-syn-mediated proteasome dysfunction

3G - Geophysical Methods Delivering Input to Geostatistical Methods for Geotechnical Site Characterization

Geophysical methods are able to contribute significantly to geotechnical site characterization. In-situ parameters are collected and gaps between boreholes or other direct tests are filled with information. However the limited resolution has to be considered and the indirect geophysical parameters have to be translated into something geotechnically useful. Moreover, the limitations have to be evaluated when including geophysical data into geostatistical models. If done properly, the use of geophysics will help in an efficient and effective site characterization. A comprehensive overview on existing geophysical (mostly seismic) methods is given as well as information on the calibration of geophysical against geotechnical parameters, pitfalls and limitations and some hints how to include these data into geostatistical/geotechnical models

Condition assessment of foundation piles and utility poles based on guided wave propagation using a network of tactile transducers and support vector machines

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%

Innovative Ultrasonic Techniques for Inspection and Monitoring of Large Concrete Structures

Ultrasonic echo and transmission techniques are used in civil engineering on a regular basis. New sensors and data processing techniques have lead to many new applications in the structural investigation as well as quality control. But concrete structures in the nuclear sector have special features and parameters, which pose problems for the methods and instrumentation currently available, e.g. extreme thickness, dense reinforcement, steel liners or special materials. Several innovative ultrasonic techniques have been developed to deal with these issues at least partly in lab experiments and pilot studies. Modern imaging techniques as multi-offset SAFT have been used e. g. to map delaminations. Thick concrete walls have successfully been inspected, partly through a steel liner. Embedded ultrasonic sensors have been designed which will be used in monitoring networks of large concrete structures above and below ground. In addition, sensitive mathematical methods as coda wave interferometry have been successfully evaluated to detect subtle changes in material properties. Examples of measurements and data evaluation are presented

Wavelet packet energy–based damage identification of wood utility poles using support vector machine multi-classifier and evidence theory

© The Author(s) 2018. This article presents a novel assessment framework to identify the health condition of wood utility poles. The innovative approach is based on the integration of data mining and machine learning methods and combines advanced signal processing, multi-sensor data fusion and decision ensembles to classify different damage condition types of wood poles. In the proposed framework, wavelet packet analysis is employed to transform captured multi-channel stress wave signals into energy information, which is consequently compressed by principal component analysis to extract a feature vector. Furthermore, support vector machine multi-classifier, optimized by genetic algorithm, is designed to identify the pole condition type. Finally, evidence theory is applied to fuse different assessment results from different sensors for a final decision. For validation of the proposed approach, the wood pole specimens with three common damage condition types are tested using a novel multi-sensor narrow-band frequency-excitation non-destructive testing system in the laboratory. The final experimental analysis results confirm that the proposed approach is capable of making full use of multi-sensor information and providing an effective and accurate identification on types of conditions in wood poles

A new non-destructive testing system based on narrow-band frequency excitation for the condition assessment of pole structures using frequency response functions and principle component analysis

This work proposes a new narrow-band frequency excitation-based non-destructive testing (NDT) system combined with advanced signal processing technique for damage identification of timber and concrete poles. Compared to traditional hammer impact testing with broad-band frequency wave excitation, this new system adopts tactile transducers to generate controllable stress waves with narrowband frequency, avoiding multi-mode wave excitation of traditional methods. In the proposed NDT method, frequency response functions (FRFs) and principle component analysis (PCA) are used to extract signal features in captured single-mode stress waves for condition assessment. To validate the performance of the proposed system and to assess the effectiveness of the advanced signal processing methods, four different timber poles and five concrete poles with various health states and damage types are employed for NDT testing and assessment. The results show that for the tested poles, the proposed method is able to achieve condition assessment accuracies of as high as 89% for timber poles and 93% for concrete poles. Keywords Non-destructive testing, timber and concrete pole, narrow-band frequency excitation, tactile transducer, frequency response functions, principle component analysis, advanced signal processin

Integrity Testing of Cast In Situ Concrete Piles Based on an Impulse Response Function Method Using Sine-Sweep Excitation by a Shaker

FP7 Programme (European Commission