Cyclic Workflow Research Articles

Increased Multiplexity in Optical Tissue Clearing-Based Three-Dimensional Immunofluorescence Microscopy of the Tumor Microenvironment by Light-Emitting Diode Photobleaching

Optical tissue clearing and three-dimensional (3D) immunofluorescence (IF) microscopy is transforming imaging of the complex tumor microenvironment (TME). However, current 3D IF microscopy has restricted multiplexity; only 3 or 4 cellular and noncellular TME components can be localized in cleared tumor tissue. Here we report a light-emitting diode (LED) photobleaching method and its application for 3D multiplexed optical mapping of the TME. We built a high-power LED light irradiation device and temperature-controlled chamber for completely bleaching fluorescent signals throughout optically cleared tumor tissues without compromise of tissue and protein antigen integrity. With newly developed tissue mounting and selected region-tracking methods, we established a cyclic workflow involving IF staining, tissue clearing, 3D confocal microscopy, and LED photobleaching. By registering microscope channel images generated through 3 work cycles, we produced 8-plex image data from individual 400 μm-thick tumor macrosections that visualize various vascular, immune, and cancer cells in the same TME at tissue-wide and cellular levels in 3D. Our method was also validated for quantitative 3D spatial analysis of cellular remodeling in the TME after immunotherapy. These results demonstrate that our LED photobleaching system and its workflow offer a novel approach to increase the multiplexing power of 3D IF microscopy for studying tumor heterogeneity and response to therapy.

Abstract 3771: 3D correlated multi-scale cellular and molecular architecture of solid tumors

Abstract A solid tumor presents heterogeneous 3D structures at tissue, cell, and molecule levels. To develop advanced cancer diagnostics and therapies, it is important to understand in-depth cellular and molecular architecture of a tumor at multiple scales. Here we introduce novel optical microscopy methodologies for in-depth 3D spatial analysis of tumor tissues: 1) LED photobleaching-mediated 3D multiplex immunofluorescence (IF) microscopy, 2) Correlated 3D multi-resolution optical microscopy, and 3) 3D tissue region-based cell type-selective multi-omics. We built a high-power LED light irradiator with a broad emission spectrum (490-700 nm) that bleaches a broad wavelength of fluorescence signals simultaneously throughout an optically cleared, 400 µm-thick tumor tissue. Cyclic workflow involving IF staining, optical tissue clearing, 3D confocal microscopy, and LED photobleaching enables visualization of multiple cell types in the same whole 400 µm-thick tumor tissue after computational 3D image registration. The constructed multiplex image offers comprehensive 3D cellular landscape of a tumor. We also developed a method for tracking regions of interest (ROIs) in the middle of a large tumor tissue using a UV-activated visible dye in light sheet microscopy. Light sheet microscopy allows imaging an optically cleared large-sized tumor tissue at a low spatial, tissue resolution. To mark the ROI positions on a tumor, the dye is infused into agarose gel surrounding the tumor tissue and be activated and present purple-colored lines where are exposed to UV light sheets in light sheet microscopy. The tumor tissue was physically sectioned at the marked ROI positions using a vibratome after reversing tissue clearing process. Sequential IF staining and high-resolution confocal microscopy permit for visualizing detailed cellular compositions of the ROIs in the tumor. The tissue and cellular-resolution 3D images from light sheet and confocal microscopy are correlatively integrated to display ‘Google Earth’-like multi-scale view of a tumor tissue. To further analyze the ROIs of a tumor at molecular level, we have developed optical microscope-mediated fluorescence lithography methods that allow fluorescently labeling of a selected cell type in ROIs of an optically cleared 3D tumor tissue. After wash free from clearing solution and dissociation of the tumor into cells, fluorescence-marked, intact cells from the ROIs are collected through flow cell sorting. Proteins and mRNAs are extracted from the collected cells and sent to LC-MS/MS analysis and RNA sequencing. The spatial multi-omics method provides in-depth molecular information of selected cells in the ROIs of a tumor. We believe all these 3D microscopy methods will provide powerful spatial analysis tools for better understanding cellular and molecular architecture of solid tumors. Citation Format: Steve Seung-Young Lee, Yi-Chien Wu, Jingtian Zheng, Elie Abi Khalil, Samuel Wang, Alexander Lippert, Joshua Plank. 3D correlated multi-scale cellular and molecular architecture of solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3771.

Cyclic workflow to improve implementation of learning points from morbidity and mortality meetings

BackgroundMorbidity and mortality meetings (M&MMs) are organized in most hospital departments with an educational purpose to learn from adverse events (AEs) to improve patient care. M&MMs often lack effectiveness due to unsuccessful systematic follow-up of areas of improvement. This can have an effect on improving patient safety and care. Therefore, a new strategy that focuses on implementing areas of improvement into daily practice is necessary. The study aim is to see if we could improve the implementation of meeting outcomes from the M&MM by using a cyclic workflow, and which factors are important to achieve its implementation.MethodsThis prospective study took place at the department of gynecologic oncology of a university hospital. Research was conducted with a participatory action research (PAR) approach using 10 consecutive M&MMs in 2019 and 2020. The cyclical workflow consisted of an action list based on the PDCA-cycle, a check of the implementation of areas for improvement at the next M&MM and regular monitoring of tasks. Each M&MM was observed and each professional with an assigned task was interviewed and gave their informed consent. Thematic content analysis was performed with the program Atlas.ti 8.4.20.ResultsOut of the 39 tasks that resulted from 10 M&MMs, 37 (94.8%) followed all the steps in the PDCA-cycle and were implemented. In total, 16 interviews were conducted with consultants, nurses, registrars and residents. Five main factors were important to achieve follow-up of areas for improvement: organizational culture, motivation, commitment, communication to mobilize employees and skills. Repetition of the cyclic workflow at the M&MM and an external person who reminded professionals of their assigned task(s) was important to change habits and motivate professionals.ConclusionCyclical tools can support the implementation of areas for improvement to optimize the M&MM. A M&MM with an organizational culture where attendees can discuss openly and freely may motivate attendees to take on tasks successfully. A positive stimulant to reach commitment of professionals is team participation. Integrating new habits of reflection may lead to a deeper level of learning from the PDCA-cycle and of the M&MM. Creating a learning environment outside of the M&MM may support professionals to take on actions and engage in improvement practices. Future research may focus on including a comparative analysis to show a success rate of the implementation of learning points from the M&MM more clearly.

Exploring the Semi-Supervised Video Object Segmentation Problem from a Cyclic Perspective

Modern video object segmentation (VOS) algorithms have achieved remarkably high performance in a sequential processing order, while most of currently prevailing pipelines still show some obvious inadequacy like accumulative error, unknown robustness or lack of proper interpretation tools. In this paper, we place the semi-supervised video object segmentation problem into a cyclic workflow and find the defects above can be collectively addressed via the inherent cyclic property of semi-supervised VOS systems. Firstly, a cyclic mechanism incorporated to the standard sequential flow can produce more consistent representations for pixel-wise correspondance. Relying on the accurate reference mask in the starting frame, we show that the error propagation problem can be mitigated. Next, a simple gradient correction module, which naturally extends the offline cyclic pipeline to an online manner, can highlight the high-frequent and detailed part of results to further improve the segmentation quality while keeping feasible computation cost. Meanwhile such correction can protect the network from severe performance degration resulted from interference signals. Finally we develop cycle effective receptive field (cycle-ERF) based on gradient correction process to provide a new perspective into analyzing object-specific regions of interests. We conduct comprehensive comparison and detailed analysis on challenging benchmarks of DAVIS16, DAVIS17 and Youtube-VOS, demonstrating that the cyclic mechanism is helpful to enhance segmentation quality, improve the robustness of VOS systems, and further provide qualitative comparison and interpretation on how different VOS algorithms work. The code of this project can be found at https://github.com/lyxok1/STM-Training.

Development of an Automated Compressor Unit for Gas Compression at the Periodic Connection of an Ejector

The authors developed a new scientific approach for gas compression using ejector compressor units. A new patented technical solution opens up the prospect for the effective use of ejector compressor units when compressing various gases to pressures of 10…40 MPa. The goal of the research work is the development of automation systems using new scientific principles for gas compression. A new scientific approach is associated with the improvement of the ejector compressor unit, with the provision of conditions for the periodic connection of the ejector as part of the implementation of the cyclic low-frequency workflow. The results of scientific research can be used to create energy-efficient technologies for compressing and transferring various gases; it can be methane, associated petroleum gas, nitrogen, carbon dioxide, air, hydrogen or other gases. There is the prospect of using ejector compressors to create new internal combustion engines. Creating cheaper and more economical compressors will allow solving actual production problems in remote Arctic oil and gas fields.

Simulation-based Production Planning and Execution Control for Reconfigurable Assembly Cells

In order to meet the continuously changing market conditions and achieve economy of scale, a current trend in the automotive industry is the application of modular reconfigurable assembly systems. Although they offer efficient solution to meet the customers needs, the management of these systems is often a challenging issue, as the continuous advance in the assembly technology introduces new requirements in production planning and control activities. In the paper, a novel approach is introduced that enables the faster introduction of modular assembly cells in the daily production by offering a flexible platform for evaluating the system performance considering dynamic logistics and production environment. The method is aimed at evaluating different modular cell configurations with discrete-event simulation, applying automated model building and centralized simulation model control. Besides, the simulation is linked with the production and capacity planning model of the system in order to implement a cyclic workflow to plan the production and evaluate the system performance in a proactive way, before releasing the plan to the production. The method and the implemented workflow are evaluated within a real case study from the automotive industry.

Stepwise structural verification of cyclic workflow models with acyclic decomposition and reduction of loops

Existence of cycles (or loops) is one of the main sources that make the analysis of workflow models difficult. Several approaches of structural verification exist in the literature, but how to verify cyclic workflow models efficiently in a comprehensible form remains an open research question. Thus, a novel structural verification approach for cyclic workflow models by means of acyclic decomposition and reduction of loops is introduced in this paper with the following contributions. First, acyclic decomposition of natural loops, further enhanced by reduction of nested loops, enables existing verification techniques, normally dealing with acyclic models, to handle workflow models with natural loops. Second, instantiation of an irreducible loop into natural loops, altogether with reduction of concurrent loop entries, enables the proposed approach to handle workflow models with irreducible loops. Last, diagnostic information, provided by the proposed approach, helps stakeholders correct and improve their workflow models. Two examples are provided to show that the proposed approach is systematic and practical. In addition, a prototype of the proposed approach is developed. Its execution result shows that, while providing diagnostic information, the proposed approach can handle workflow models with arbitrary cycles effectively.

Regulatory interactions for iron homeostasis in Aspergillus fumigatus inferred by a Systems Biology approach

BackgroundIn System Biology, iterations of wet-lab experiments followed by modelling approaches and model-inspired experiments describe a cyclic workflow. This approach is especially useful for the inference of gene regulatory networks based on high-throughput gene expression data. Experiments can verify or falsify the predicted interactions allowing further refinement of the network model. Aspergillus fumigatus is a major human fungal pathogen. One important virulence trait is its ability to gain sufficient amounts of iron during infection process. Even though some regulatory interactions are known, we are still far from a complete understanding of the way iron homeostasis is regulated.ResultsIn this study, we make use of a reverse engineering strategy to infer a regulatory network controlling iron homeostasis in A. fumigatus. The inference approach utilizes the temporal change in expression data after a change from iron depleted to iron replete conditions. The modelling strategy is based on a set of linear differential equations and offers the possibility to integrate known regulatory interactions as prior knowledge. Moreover, it makes use of important selection criteria, such as sparseness and robustness. By compiling a list of known regulatory interactions for iron homeostasis in A. fumigatus and softly integrating them during network inference, we are able to predict new interactions between transcription factors and target genes. The proposed activation of the gene expression of hapX by the transcriptional regulator SrbA constitutes a so far unknown way of regulating iron homeostasis based on the amount of metabolically available iron. This interaction has been verified by Northern blots in a recent experimental study. In order to improve the reliability of the predicted network, the results of this experimental study have been added to the set of prior knowledge. The final network includes three SrbA target genes. Based on motif searching within the regulatory regions of these genes, we identify potential DNA-binding sites for SrbA. Our wet-lab experiments demonstrate high-affinity binding capacity of SrbA to the promoters of hapX, hemA and srbA.ConclusionsThis study presents an application of the typical Systems Biology circle and is based on cooperation between wet-lab experimentalists and in silico modellers. The results underline that using prior knowledge during network inference helps to predict biologically important interactions. Together with the experimental results, we indicate a novel iron homeostasis regulating system sensing the amount of metabolically available iron and identify the binding site of iron-related SrbA target genes. It will be of high interest to study whether these regulatory interactions are also important for close relatives of A. fumigatus and other pathogenic fungi, such as Candida albicans.

Graphical and Logical Formalisms for Business Process Modeling and Verification

Process models are an essential component of business process management and are found in various information systems such as workflow management systems, enterprise resource planning systems, and supply chain management systems. Process modeling and analysis are key steps in business process management. However, most existing activity-based process modeling paradigms found in process management tools lack a mathematical formalism, have limited expressive power, or have little analytical capability. Consequently, process modeling and analysis in the industry remain an art rather than a science.In this dissertation, we first propose a logic-based workflow verification approach by applying propositional logic with constraints to verifying the correctness of both acyclic and cyclic workflow models. We demonstrate that this approach is capable of detecting process anomalies in workflow models.We then propose process graphs as a graphical and mathematical tool for business process modeling and analysis. We formally define the syntax and semantics of process graphs and their constructs. We show that process graphs can not only model all types of execution order of activities, but also support multi-level abstraction, modular modeling, and analysis of the correctness of process models. We apply process graphs to defining and classifying process anomalies, and demonstrate that the proper use of process graphs can prevent certain process anomalies.We also propose process logic as a logical formalism and mathematical method to represent process models for the purpose of process verification. We formally define the syntax and semantics of process logic to reflect the characteristics of process structures in a more precise way. We establish a formal relationship between process logic and graphical representations of process models, and transform the problem of verifying the correctness of process models into the problem of determining the validity of process argument forms in process logic. We demonstrate that process logic can be used to verify completely the correctness of activity-based process models.Process graphs and process logic provide a theoretical foundation for the modeling, analysis, and verification of activity-based process models that are most widely used in the applications of business process management.