Features and prognostic impact of distant metastases in 45 dogs with de novo stage IV cutaneous mast cell tumours: A prospective study

BACKGROUND: Distant metastases in dogs with cutaneous mast cell tumors (cMCT) are rare and incurable. The aims of this prospective study were to clarify the clinico-pathological features of stage IV cMCTs and to identify possible prognostic factors for progression-free interval (PFI) and survival time (ST). MATERIAL AND METHODS: Dogs were eligible for recruitment if they had a previously untreated, histologically confirmed cMCT and if they underwent complete staging demonstrating stage IV disease. Dogs were uniformly followed-up, whereas treatment was not standardized and included no therapy, surgery, radiation therapy, chemotherapy, tyrosine-kinase inhibitors or a combination of these. RESULTS: 45 dogs with stage IV cMCT were enrolled. All dogs had distant metastatic disease, and 41 (91.1%) dogs had also metastasis in the regional lymph node. Histopathological grade and mutational status greatly varied among dogs. Median ST was 110 days. Notably, PFI and ST were independent of well-known prognostic factors, including anatomic site, histological grade, and mutational status. Conversely, tumor diameter >3\u2009cm, more than 2 metastatic sites, bone marrow infiltration, and lack of tumor control at the primary site were confirmed to be negative prognostic factors by multivariate analysis. CONCLUSION: Currently, there is no satisfactory treatment for stage IV cMCT. Asymptomatic dogs with tumor diameter <3\u2009cm and a low tumor burden, without bone marrow infiltration may be candidates for multimodal treatment. Stage IV dogs without lymph node metastasis may enjoy a surprisingly prolonged survival. The achievement of local tumor control seems to predict a better outcome in dogs with stage IV cMCT

Conformity and controversies in the diagnosis, staging and follow-up evaluation of canine nodal lymphoma: a systematic review of the last 15 years of published literature

Diagnostic methods used in the initial and post-treatment evaluation of canine lymphoma are heterogeneous and can vary within countries and institutions. Accurate reporting of clinical stage and response assessment is crucial in determining the treatment efficacy and predicting prognosis. This study comprises a systematic review of all available canine multicentric lymphoma studies published over 15 years. Data concerning diagnosis, clinical stage evaluation and response assessment procedures were extracted and compared. Sixty-three studies met the eligibility criteria. Fifty-five (87.3%) studies were non-randomized prospective or retrospective studies. The survey results also expose variations in diagnostic criteria and treatment response assessment in canine multicentric lymphoma. Variations in staging procedures performed and recorded led to an unquantifiable heterogeneity among patients in and between studies, making it difficult to compare treatment efficacies. Awareness of this inconsistency of procedure and reporting may help in the design of future clinical trials

A practical algorithmic approach to mature aggressive B cell lymphoma diagnosis in the double/triple hit era. Selecting cases, matching clinical benefit. A position paper from the Italian Group of Haematopathology (G.I.E.)

An accurate diagnosis of clinically distinct subgroups of aggressive mature B cell lymphomas is crucial for the choice of proper treatment. Presently, precise recognition of these disorders relies on the combination of morphological, immunophenotypical, and cytogenetic/molecular features. The diagnostic workup in such situations implies the application of costly and time-consuming analyses, which are not always required, since an intensified treatment option is reasonably reserved to fit patients. The Italian Group of Haematopathology proposes herein a practical algorithm for the diagnosis of aggressive mature B cell lymphomas based on a stepwise approach, aimed to select cases deserving molecular analysis, in order to optimize time and resources still assuring the optimal management for any patient

Distributed Control of a Limited Angular Field-of-View Multi-Robot System in Communication-Denied Scenarios: A Probabilistic Approach

Multi-robot systems are gaining popularity over single-agent systems for their advantages. Although they have been studied in agriculture, search and rescue, surveillance, and environmental exploration, real-world implementation is limited due to agent coordination complexities caused by communication and sensor limitations. In this work, we propose a probabilistic approach to allow coordination among robots in communication-denied scenarios, where agents can only rely on visual information from a camera with a limited angular field-of-view. Our solution utilizes a particle filter to analyze uncertainty in the location of neighbors, together with Control Barrier Functions to address the exploration-exploitation dilemma that arises when robots must balance the mission goal with seeking information on undetected neighbors. This technique was tested with virtual robots required to complete a coverage mission, analyzing how the number of deployed robots affects performances and making a comparison with the ideal case of isotropic sensors and communication. Despite an increase in the amount of time required to fulfill the task, results have shown to be comparable to the ideal scenario in terms of final configuration achieved by the system

Blastic plasmacytoid dendritic cell neoplasm: Genomics mark epigenetic dysregulation as a primary therapeutic target

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive hematologic malignancy for which there is still no effective B therapy. In order to identify genetic alterations useful for a new treatment design, we used whole-exome sequencing to analyze 14 BPDCN patients and the patient-derived CAL-1 cell line. The functional enrichment analysis of mutational data reported the epigenetic regulatory program to be the most significantly undermined (P&lt;0.0001). In particular, twenty-five epigenetic modifiers were found mutated (e.g. ASXL1, TET2, SUZ12, ARID1A, PHF2, CHD8); ASXL1 was the most frequently affected (28.6% of cases). To evaluate the impact of the identified epigenetic mutations at the gene-expression and Histone H3 lysine 27 trimethylation/acetylation levels, we performed additional RNA and pathology tissue-chromatin immunoprecipitation sequencing experiments. The patients displayed enrichment in gene signatures regulated by methylation and modifiable by decitabine administration, shared common H3K27-acetylated regions, and had a set of cell-cycle genes aberrantly up-regulated and marked by promoter acetylation. Collectively, the integration of sequencing data showed the potential of a therapy based on epigenetic agents. Through the adoption of a preclinical BPDCN mouse model, established by CAL-1 cell line xenografting, we demonstrated the efficacy of the combination of the epigenetic drugs 5’-azacytidine and decitabine in controlling disease progression in vivo

Communication Through Motion: Legibility of Multi-Robot Systems

The interaction between a user and a multi-robot system in a shared environment is a relatively uncharted topic. But, as these types of systems will increase in the future years, an efficient way of communication is necessary. To this aim, it is interesting to discover if a multi-robot system can communicate its intentions exploiting only some motion-variables, which are characteristics of the motion of the robots. This study is about the legibility of a multi-robot system: In particular, we focus on the influence of these motion-variables on the legibility of more than one group of robots that move in a shared environment with the user. These motion-variables are: Trajectory, dispersion and stiffness. They are generally used to define the motion of a group of mobile robots. Trajectory and dispersion were found relevant for the correctness of the communication between the user and the multi-robot system, while stiffness was found relevant for the rapidity of communication. The analysis of the influence of the motion-variables was carried out with an ANOVA (analysis of variance) based on a series of data coming from an experimental campaign conducted in a virtual reality set-up

On Coverage Control for Limited Range Multi-Robot Systems

This paper presents a coverage based control algorithm to coordinate a group of autonomous robots. Most of the solutions presented in the literature rely on an exact Voronoi partitioning, whose computation requires complete knowledge of the environment to be covered. This can be achieved only by robots with unlimited sensing capabilities, or through communication among robots in a limited sensing scenario. To overcome these limitations, we present a distributed control strategy to cover an unknown environment with a group of robots with limited sensing capabilities and in the absence of reliable communication. The control law is based on a limited Voronoi partitioning of the sensing area, and we demonstrate that the group of robots can optimally cover the environment using only information that is locally detected (without communication). The proposed method is validated by means of simulations and experiments carried out on a group of mobile robots

Towards the Legibility of Multi-robot Systems

Communication is crucial for human-robot collaborative tasks. In this context, legibility studies movement as the means of implicit communication between robotic systems and a human observer. This concept has been explored mostly for manipulators and humanoid robots. In contrast, little information is available in the literature about legibility of multi-robot systems or swarms, where simplicity and non-anthropomorphism of robots, along with the complexity of their interactions and aggregated behavior impose different challenges that are not encountered in single-robot scenarios. This article investigates legibility of multi-robot systems. Hence, we extend the definition of legibility, incorporating information about high-level goals in terms of the coordination objective of the group of robots, to previous results that focused solely on the legibility of spatial goals. A set of standard multi-robot algorithms corresponding to different coordination objectives are implemented and their legibility is evaluated in a user study, where participants observe the behavior of the multi-robot system in a virtual reality setup and are asked to identify the system's spatial goal and coordination objective. The results of the study confirmed that coordination objectives are discernible by the users, hence multi-robot systems can be controlled to be legible, in terms of spatial goal and coordination objective

A Digital Twin Driven Human-Centric Ecosystem for Industry 5.0

Industry 5.0 embodies the vision for the future of factories, emphasizing the importance of sustainable industrialization and the role of industry in society, through the key concept of placing the well-being of workers at the center of the production process. Building upon this vision, we propose a new paradigm to design human-centric industrial applications. To this end, we exploit Digital Twin (DT) technology to build a digital replica for each entity on the shop floor and support and augment interaction among workers and machines. While so far DTs in automation have been proposed for machine digitalization, the core element of the proposed approach is the Operator Digital Twin (ODT). In this scenario, biometrics allows to build a reliable model of those operator’s characteristics that are relevant in working contexts. Biometric traits are measured and processed to detect physical, emotional, and mental conditions, which are used to define the operator’s state. Perspectively, this allows to manage and monitor production and processes in an operator-in-the-loop manner, where not only is the operator aware of the state of the plant, but also any technological agent in the plant acts and reacts according to the operator’s needs and conditions. In this paper, we define the modeling of the envisioned ecosystem, present the designed DT’s blue-print architecture, discuss its implementation in relevant application scenarios, and report an example of implementation in a collaborative robotics scenario. Note to Practitioners—This paper was motivated by the problem of designing human-cyber-physical systems, where production processes are managed by concurrently taking into account operators, machines and plant status. This answers the needs of the novel Industry 5.0 paradigm, which aims to enhance social sustainability of modern factories. To this end, we propose an architecture based on digital twins that allows to develop a digital layer, detached from the physical one, where the plant can be monitored and managed. This allows the creation of a digital ecosystem where machines, operators, and the interactions among them are represented, augmented, and managed. We discuss how the proposed architecture can be applied to three relevant scenarios: remote training and maintenance, line operation and line supervision. Moreover, the implementation in a collaborative robotics scenario is presented, to provide an example of the proposed architecture can be implemented in industrial scenarios