A Data-Mining Interpretation Method of Pavement Dynamic Response Signal by Combining DBSCAN and Findpeaks Function.

During a heavy traffic flow featuring a substantial number of vehicles, the data reflecting the strain response of asphalt pavement under the vehicle load exhibit notable fluctuations with abnormal values, which can be attributed to the complex operating environment. Thus, there is a need to create a real-time anomalous-data diagnosis system which could effectively extract dynamic strain features, such as peak values and peak separation from the large amount of data. This paper presents a dynamic response signal data analysis method that utilizes the DBSCAN clustering algorithm and the findpeaks function. This method is designed to analyze data collected by sensors installed within the pavement. The first step involves denoising the data using low-pass filters and other techniques. Subsequently, the DBSCAN algorithm, which has been improved using the K-Dist method, is used to diagnose abnormal data after denoising. The refined findpeaks function is further implemented to carry out the adaptive feature extraction of the denoised data which is free from anomalies. The enhanced DBSCAN algorithm is tested via simulation and illustrates its effectiveness while detecting abnormal data in the road dynamic response signal. The findpeaks function enables the relatively accurate identification of peak values, thus leading to the identification of strain signal peaks of complex multi-axle lorries. This study is valuable for efficient data processing and effective information utilization in pavement monitoring.

Positron Emission Tomography Imaging of Synaptic Dysfunction in Parkinson's Disease.

Parkinson's disease (PD) is one of the most common neurodegenerative diseases with a complex pathogenesis. Aggregations formed by abnormal deposition of alpha-synuclein (αSyn) lead to synapse dysfunction of the dopamine and non-dopamine systems. The loss of dopaminergic neurons and concomitant alterations in non-dopaminergic function in PD constitute its primary pathological manifestation. Positron emission tomography (PET), as a representative molecular imaging technique, enables the non-invasive visualization, characterization, and quantification of biological processes at cellular and molecular levels. Imaging synaptic function with PET would provide insights into the mechanisms underlying PD and facilitate the optimization of clinical management. In this review, we focus on the synaptic dysfunction associated with the αSyn pathology of PD, summarize various related targets and radiopharmaceuticals, and discuss applications and perspectives of PET imaging of synaptic dysfunction in PD.

Cellular senescence imaging and senolysis monitoring in cancer therapy based on a ß-galactosidase-activated aggregation-induced emission luminogen.

Cellular senescence is a permanent state of cell cycle arrest characterized by increased activity of senescence associated ß-galactosidase (SA-ß-gal). Notably, cancer cells have been also observed to exhibit the senescence response and are being considered for sequential treatment with pro-senescence therapy followed by senolytic therapy. However, there is currently no effective agent targeting ß-galactosidase (ß-Gal) for imaging cellular senescence and monitoring senolysis in cancer therapy. Aggregation-induced emission luminogen (AIEgen) demonstrates strong fluorescence, good photostability, and biocompatibility, making it a potential candidate for imaging cellular senescence and monitoring senolysis in cancer therapy when endowed with ß-Gal-responsive capabilities. In this study, we introduced a ß-Gal-activated AIEgen named QM-ß-gal for cellular senescence imaging and senolysis monitoring in cancer therapy. QM-ß-gal exhibited good amphiphilic properties and formed aggregates that emitted a fluorescence signal upon ß-Gal activation. It showed high specificity towards the activity of ß-Gal in lysosomes and successfully visualized DOX-induced senescent cancer cells with intense fluorescence both in vitro and in vivo. Encouragingly, QM-ß-gal could image senescent cancer cells in vivo for over 14 days with excellent biocompatibility. Moreover, it allowed for the monitoring of senescent cancer cell clearance during senolytic therapy with ABT263. This investigation indicated the potential of the ß-Gal-activated AIEgen, QM-ß-gal, as an in vivo approach for imaging cellular senescence and monitoring senolysis in cancer therapy via highly specific and long-term fluorescence imaging. STATEMENT OF SIGNIFICANCE: This work reported a ß-galactosidase-activated AIEgen called QM-ß-gal, which effectively imaged DOX-induced senescent cancer cells both in vitro and in vivo. QM-ß-gal specifically targeted the increased expression and activity of ß-galactosidase in senescent cancer cells, localized within lysosomes. It was cleared rapidly before activation but maintained stability after activation in the DOX-induced senescent tumor. The AIEgen exhibited a remarkable long-term imaging capability for senescent cancer cells, lasting over 14 days and enabled monitoring of senescent cancer cell clearance through ABT263-induced apoptosis. This approach held promise for researchers seeking to achieve prolonged imaging of senescent cells in vivo.