Towards accurate and efficient live cell imaging data analysis

Dynamische zelluläre Prozesse wie Zellzyklus, Signaltransduktion oder Transkription zu analysieren wird Live-cell-imaging mittels Zeitraffermikroskopie verwendet. Um nun aber Zellabstammungsbäume aus einem Zeitraffervideo zu extrahieren, müssen die Zellen segmentiert und verfolgt werden können. Besonders hier, wo lebende Zellen über einen langen Zeitraum betrachtet werden, sind Fehler in der Analyse fatal: Selbst eine extrem niedrige Fehlerrate kann sich amplifizieren, wenn viele Zeitpunkte aufgenommen werden, und damit den gesamten Datensatz unbrauchbar machen. In dieser Arbeit verwenden wir einen einfachen aber praktischen Ansatz, der die Vorzüge der manuellen und automatischen Ansätze kombiniert. Das von uns entwickelte Live-cell-Imaging Datenanalysetool ‘eDetect’ ergänzt die automatische Zellsegmentierung und -verfolgung durch Nachbearbeitung. Das Besondere an dieser Arbeit ist, dass sie mehrere interaktive Datenvisualisierungsmodule verwendet, um den Benutzer zu führen und zu unterstützen. Dies erlaubt den gesamten manuellen Eingriffsprozess zu rational und effizient zu gestalten. Insbesondere werden zwei Streudiagramme und eine Heatmap verwendet, um die Merkmale einzelner Zellen interaktiv zu visualisieren. Die Streudiagramme positionieren ähnliche Objekte in unmittelbarer Nähe. So kann eine große Gruppe ähnlicher Fehler mit wenigen Mausklicks erkannt und korrigiert werden, und damit die manuellen Eingriffe auf ein Minimum reduziert werden. Die Heatmap ist darauf ausgerichtet, alle übersehenen Fehler aufzudecken und den Benutzern dabei zu helfen, bei der Zellabstammungsrekonstruktion schrittweise die perfekte Genauigkeit zu erreichen. Die quantitative Auswertung zeigt, dass eDetect die Genauigkeit der Nachverfolgung innerhalb eines akzeptablen Zeitfensters erheblich verbessern kann. Beurteilt nach biologisch relevanten Metriken, übertrifft die Leistung von eDetect die derer Tools, die den Wettbewerb ‘Cell Tracking Challenge’ gewonnen haben.Live cell imaging based on time-lapse microscopy has been used to study dynamic cellular behaviors, such as cell cycle, cell signaling and transcription. Extracting cell lineage trees out of a time-lapse video requires cell segmentation and cell tracking. For long term live cell imaging, data analysis errors are particularly fatal. Even an extremely low error rate could potentially be amplified by the large number of sampled time points and render the entire video useless. In this work, we adopt a straightforward but practical design that combines the merits of manual and automatic approaches. We present a live cell imaging data analysis tool `eDetect', which uses post-editing to complement automatic segmentation and tracking. What makes this work special is that eDetect employs multiple interactive data visualization modules to guide and assist users, making the error detection and correction procedure rational and efficient. Specifically, two scatter plots and a heat map are used to interactively visualize single cells' visual features. The scatter plots position similar results in close vicinity, making it easy to spot and correct a large group of similar errors with a few mouse clicks, minimizing repetitive human interventions. The heat map is aimed at exposing all overlooked errors and helping users progressively approach perfect accuracy in cell lineage reconstruction. Quantitative evaluation proves that eDetect is able to largely improve accuracy within an acceptable time frame, and its performance surpasses the winners of most tasks in the `Cell Tracking Challenge', as measured by biologically relevant metrics

Open Innovation Web-Based Platform for Evaluation of Water Quality Based on Big Data Analysis

There are many models presented that assess water quality. However, the applications of the models are limited due to the difficulty of preparing input data and interpreting model output. In this paper, we developed a Web-based platform to assist researchers in analyzing water quality. The data from sensors can be automatically imported to the platform according to the configured information of data structures. The platform also provides conventional methods and big data methods for the users to analyze water quality. Moreover, the users can choose the water quality parameters according to the water usage. The presented platform can show the model output in a text format and a graphic format, which allows for the analysis to be better understood by the user. The platform integrates the input, analysis, and output together well and brings great convenience to the research on water quality

A method of attitude measurement and level assessment for skiers based on wearable inertial measurement

Quantitative analysis of sports is an important development direction of scientific skiing training, and the digital expression of human movement patterns during skiing is the basis for scientific quantitative analysis. A human motion capture and attitude reconstruction system based on a wearable BSBD inertial measurement unit was designed and built, combined with the human multi-rigid body motion model to realize the human body reconstruction during the skiing, and applied to the auxiliary training of slewing movements in alpine skiing. At the same time, for the indoor training scene based on the multi-degree-of-freedom simulated ski training platform, a digital evaluation method suitable for ski slalom is proposed. The method uses motion capture system and posture reconstruction system to extract five kinds of sliding characteristic data of skiers, and realizes the evaluation of skiers’ technical parameters through similarity measurement and linear fitting with high-level athletes’ motion parameters, so as to assist scientific training. Finally, experiments are carried out on the indoor Olymp simulated ski training bench to verify the effectiveness of the method

Magnetic Resonance Imaging of Bone Marrow Cell-Mediated Interleukin-10 Gene Therapy of Atherosclerosis

A characteristic feature of atherosclerosis is its diffuse involvement of arteries across the entire human body. Bone marrow cells (BMC) can be simultaneously transferred with therapeutic genes and magnetic resonance (MR) contrast agents prior to their transplantation. Via systemic transplantation, these dual-transferred BMCs can circulate through the entire body and thus function as vehicles to carry genes/contrast agents to multiple atherosclerosis. This study was to evaluate the feasibility of using in vivo MR imaging (MRI) to monitor BMC-mediated interleukin-10 (IL-10) gene therapy of atherosclerosis.For in vitro confirmation, donor mouse BMCs were transduced by IL-10/lentivirus, and then labeled with a T2-MR contrast agent (Feridex). For in vivo validation, atherosclerotic apoE(-/-) mice were intravenously transplanted with IL-10/Feridex-BMCs (Group I, n = 5) and Feridex-BMCs (Group II, n = 5), compared to controls without BMC transplantation (Group III, n = 5). The cell migration to aortic atherosclerotic lesions was monitored in vivo using 3.0T MRI with subsequent histology correlation. To evaluate the therapeutic effect of BMC-mediated IL-10 gene therapy, we statistically compared the normalized wall indexes (NWI) of ascending aortas amongst different mouse groups with various treatments.Of in vitro experiments, simultaneous IL-10 transduction and Feridex labeling of BMCs were successfully achieved, with high cell viability and cell labeling efficiency, as well as IL-10 expression efficiency (≥90%). Of in vivo experiments, MRI of animal groups I and II showed signal voids within the aortic walls due to Feridex-created artifacts from the migrated BMCs in the atherosclerotic plaques, which were confirmed by histology. Histological quantification showed that the mean NWI of group I was significantly lower than those of group II and group III (P<0.05).This study has confirmed the possibility of using MRI to track, in vivo, IL-10/Feridex-BMCs recruited to atherosclerotic lesions, where IL-10 genes function to prevent the progression of atherosclerosis

Direct Fusion of Geostationary Meteorological Satellite Visible and Infrared Images Based on Thermal Physical Properties

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion

eDetect: A Fast Error Detection and Correction Tool for Live Cell Imaging Data Analysis

Summary: Live cell imaging has been widely used to generate data for quantitative understanding of cellular dynamics. Various applications have been developed to perform automated imaging data analysis, which often requires tedious manual correction. It remains a challenge to develop an efficient curation method that can analyze massive imaging datasets with high accuracy. Here, we present eDetect, a fast error detection and correction tool that provides a powerful and convenient solution for the curation of live cell imaging analysis results. In eDetect, we propose a gating strategy to distinguish correct and incorrect image analysis results by visualizing image features based on principal component analysis. We demonstrate that this approach can substantially accelerate the data correction process and improve the accuracy of imaging data analysis. eDetect is well documented and designed to be user friendly for non-expert users. It is freely available at https://sites.google.com/view/edetect/ and https://github.com/Zi-Lab/eDetect. : Automation in Bioinformatics; Bioinformatics; Cell Biology Subject Areas: Automation in Bioinformatics, Bioinformatics, Cell Biolog

Analyzing the Driving Mechanism of Rural Transition from the Perspective of Rural–Urban Continuum: A Case Study of Suzhou, China

Rural transition has become a core topic in the study of the urban–rural relationship in China. Analyzing the transition process and sorting out the key driving factors in different periods is essential for providing critical references for the urban–rural integration and rural revitalization policy. This paper takes Suzhou, a rapidly urbanizing prefecture-level city that has experienced three obvious stages of rural transition since China’s reform and opening-up, as the case area to explore the driving mechanism from the perspective of rural–urban continuum. We first construct the index system for measuring rural transition from two dimensions of rurality and urbanity. Then, we identify the core influencing factors of different phases from 1990 to 2015, employing spatial regression models and then extract the main driving mechanism. The results revealed the following key findings. (1) Rural transition in Suzhou has both proximity effects and structural effects; the development patterns of rural areas are becoming more heterogeneous. (2) From the rurality dimension, the regression coefficient of index representing grain production changes from positive to negative during the research periods, reflecting the “non-grain” trend of agricultural production in rural areas. (3) From the urbanity dimension, the regression coefficient of index promoting by foreign direct investment increases from 0.372 in 1990 to 0.829 in 2015, indicating that the external driving force of rural transition has become stronger. (4) In 2015, the regression coefficient of index representing tertiary industry reaches 0.468, meaning the modern service industry has played an increasingly important role in rural development. Our study provides valuable insights into the dynamic change of driving mechanism of rural transition at the town level, argues that the general trend of viewing transition process as rurality weakens and urbanity enhances could be replaced by multifunctional pathways. This study supplements existing research to understand new phenomena during the transition process, the latter offer implications for policy-making, such as grain security, spatial spillovers, and rural tourism

Understanding ecological civilization in China: from political context to science

China's concept of "ecological civilization" can be understood as a new system of development and governance based on the perspective of political decision-making. Environmental management, ecological restoration, and green development are its primary principles-distinctly different from industrial and agricultural-oriented civilizations. In this paper, we evaluate the evolution of political connotations of the ecological civilization concept in China over the past 15 years through a textual analysis approach. Additionally, we systematically outline an ecological civilization indicator system and analyze its evolutionary process, applicable scales, and role in guiding the implementation of the ecological civilization concept. Eco-civilization demonstration sites and experiences are also discussed, followed by a review of academic research and policy-making responses. Finally, we propose different perspectives on the outlook for the future of ecological civilization development in China. [Abstract copyright: © 2023. The Author(s) under exclusive licence to Royal Swedish Academy of Sciences.