Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

<p>Abstract</p> <p>Background</p> <p>Three-dimensional <it>in vitro </it>culture of cancer cells are used to predict the effects of prospective anti-cancer drugs <it>in vivo</it>. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images.</p> <p>Methods</p> <p>Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using <it>k</it>-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system.</p> <p>Results</p> <p>Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images.</p> <p>Conclusion</p> <p>Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development.</p

Understanding Large-Language Model (LLM)-powered Human-Robot Interaction

Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the potential to transform human-robot interaction, very little is known about the distinctive design requirements for utilizing LLMs in robots, which may differ from text and voice interaction and vary by task and context. To better understand these requirements, we conducted a user study (n = 32) comparing an LLM-powered social robot against text- and voice-based agents, analyzing task-based requirements in conversational tasks, including choose, generate, execute, and negotiate. Our findings show that LLM-powered robots elevate expectations for sophisticated non-verbal cues and excel in connection-building and deliberation, but fall short in logical communication and may induce anxiety. We provide design implications both for robots integrating LLMs and for fine-tuning LLMs for use with robots.Comment: 10 pages, 4 figures. Callie Y. Kim and Christine P. Lee contributed equally to the work. To be published in Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI '24), March 11--14, 2024, Boulder, CO, US

Gravitational Collapse of Inhomogeneous Dust in (2+1) Dimensions

We examine the gravitational collapse of spherically symmetric inhomogeneous dust in (2+1) dimensions, with cosmological constant. We obtain the analytical expressions for the interior metric. We match the solution to a vacuum exterior. We discuss the nature of the singularity formed by analyzing the outgoing radial null geodesics. We examine the formation of trapped surfaces during the collapse.Comment: Accepted for publication in CQ

Journey to the Center of the Cookie Ecosystem: Unraveling Actors' Roles and Relationships

Web pages have been steadily increasing in complexity over time, including code snippets from several distinct origins and organizations. While this may be a known phenomenon, its implications on the panorama of cookie tracking received little attention until now. Our study focuses on filling this gap, through the analysis of crawl results that are both large-scale and fine-grained, encompassing the whole set of events that lead to the creation and sharing of around 138 million cookies from crawling more than 6 million webpages. Our analysis lets us paint a highly detailed picture of the cookie ecosystem, discovering an intricate network of connections between players that reciprocally exchange information and include each other's content in web pages whose owners may not even be aware. We discover that, in most webpages, tracking cookies are set and shared by organizations at the end of complex chains that involve several middlemen. We also study the impact of cookie ghostwriting, i.e., a common practice where an entity creates cookies in the name of another party, or the webpage. We attribute and define a set of roles in the cookie ecosystem, related to cookie creation and sharing. We see that organizations can and do follow different patterns, including behaviors that previous studies could not uncover: for example, many cookie ghostwriters send cookies they create to themselves, which makes them able to perform cross-site tracking even for users that deleted third-party cookies in their browsers. While some organizations concentrate the flow of information on themselves, others behave as dispatchers, allowing other organizations to perform tracking on the pages that include their content

A CASE STUDY: MATERIAL FLOW SIMULATION BASED ANALYSIS FOR MAINTENANCE NETWORK IMPROVEMENT

The competitiveness of enterprises operating in complex environments depends on how well their value creation factors can adapt to disruptions caused by unanticipated events. Building this resilience requires the ability to identify uncertainties and to model their impact on operations, which is difficult to achieve. Thus, increasing adaptability in maintenance and repair networks calls for an adequate approach to address uncertainties. It is necessary to consider the maintenance activities within and outside the company as well as those affecting all equipment supplier partners. Enhancement in simulation technique has opened the opportunity to analyse this complex system. This paper presents a comprehensive analysis introducing a potential approach using material flow simulation that models and simulates the impact of existing maintenance and repair activities to identify the uncertainties to increase the flexibility of the network while ensuring profitability and continuity

The collision and snapping of cosmic strings generating spherical impulsive gravitational waves

The Penrose method for constructing spherical impulsive gravitational waves is investigated in detail, including alternative spatial sections and an arbitrary cosmological constant. The resulting waves include those that are generated by a snapping cosmic string. The method is used to construct an explicit exact solution of Einstein's equations describing the collision of two nonaligned cosmic strings in a Minkowski background which snap at their point of collision.Comment: 10 pages, 6 figures, To appear in Class. Quantum Gra

Analytical Solution of a Stochastic Content Based Network Model

We define and completely solve a content-based directed network whose nodes consist of random words and an adjacency rule involving perfect or approximate matches, for an alphabet with an arbitrary number of letters. The analytic expression for the out-degree distribution shows a crossover from a leading power law behavior to a log-periodic regime bounded by a different power law decay. The leading exponents in the two regions have a weak dependence on the mean word length, and an even weaker dependence on the alphabet size. The in-degree distribution, on the other hand, is much narrower and does not show scaling behavior. The results might be of interest for understanding the emergence of genomic interaction networks, which rely, to a large extent, on mechanisms based on sequence matching, and exhibit similar global features to those found here.Comment: 13 pages, 5 figures. Rewrote conclusions regarding the relevance to gene regulation networks, fixed minor errors and replaced fig. 4. Main body of paper (model and calculations) remains unchanged. Submitted for publicatio

Can a Unruh Detector Feel a Cosmic String?

Unruh's detector calculation is used to study the effect of the defect angle $\beta$ in a space-time with a cosmic string for both the excitation and deexcitation cases. It is found that a rotating detector results in a non-zero effect for both finite (small) and infinite (large) time