Cancer classification in the genomic era: five contemporary problems

Abstract Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., “lung cancer” designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification and the successful application of these concepts in precision medicine.http://deepblue.lib.umich.edu/bitstream/2027.42/134599/1/40246_2015_Article_49.pd

Experiment, simulation and analysis on coupling hydrodynamic forces under key parameters for a spherical underwater exploration robot

As a novel underwater exploration robot, BYSQ-2 spherical robot uses the heavy pendulum to change the attitudes with the characteristics of small steering resistance and high compressive strength. However, the greater water resistance in the process of moving forward obstructs the rapid movement, because the robot has a spherical shell and only one propeller. The maximum speed was obtained only 0.6 m/s according to experimental tests and theoretical calculations. In order to improve the movement speed, the robot’s virtual assembly model was built to study the coupling hydrodynamic forces between the spherical shell and the propeller by CFD method. The coupling hydrodynamic forces were analyzed and summarized under different key structural parameters that include the pipe diameter and the shell diameter. Furthermore, in the conditions of different rotational speed, propeller thrust and water resistance of robot were simulated and calculated. According to the simulation results of the model with the appropriate structural parameters, it was demonstrated that the speed of the robot was improved obviously in the process of moving forward

DocTrack: A Visually-Rich Document Dataset Really Aligned with Human Eye Movement for Machine Reading

The use of visually-rich documents (VRDs) in various fields has created a demand for Document AI models that can read and comprehend documents like humans, which requires the overcoming of technical, linguistic, and cognitive barriers. Unfortunately, the lack of appropriate datasets has significantly hindered advancements in the field. To address this issue, we introduce \textsc{DocTrack}, a VRD dataset really aligned with human eye-movement information using eye-tracking technology. This dataset can be used to investigate the challenges mentioned above. Additionally, we explore the impact of human reading order on document understanding tasks and examine what would happen if a machine reads in the same order as a human. Our results suggest that although Document AI models have made significant progress, they still have a long way to go before they can read VRDs as accurately, continuously, and flexibly as humans do. These findings have potential implications for future research and development of Document AI models. The data is available at \url{https://github.com/hint-lab/doctrack}.Comment: 14 pages, 8 figures, Accepted by Findings of EMNLP202

Characteristic analysis and fluctuation control for a underactuated spherical underwater robot

With robots used widely in many fields in recent years, the underwater robot with various characteristics has been thoroughly researched. As a new type of underwater spherical robot, BYSQ-2 uses the heavy pendulum to adjust the attitude, which is flexible and novel. However, it has been not fully understood that how the heavy pendulum would affect the underactuated robot’s regular movement. In this paper a fluctuation characteristic for the robot is shown, and then an adaptive control method is proposed to suppress the fluctuation. Based on the simplified structure of the robot, a swing phenomenon of the heavy pendulum is found. Moreover, the reason for the fluctuation is analyzed in the processes of the accelerating and pitching. A dynamic equation for this model is established to accurately calculate the characteristic, and the virtual simulation proves the validity of the theoretical calculation. The characteristics of this coupling fluctuation are summarized by changing motion parameters and structure parameters. The results prove that the pendulum’s length and the controlling process are closely related with the velocity fluctuation of the robot. Moreover, in order to suppress the fluctuations, a pitching controller is designed to prevent the heavy pendulum from swinging based on the method of neural network sliding mode. The RBF neural network is used to compensate the nonlinearity and disturbance uncertainties, and two sliding mode structures make the swing rapidly inhibited. At the same time, the pitch angle's error also got convergence. The stability of the control system is proof by Lyapunov and Barbalat theories. Finally, the simulation and experiment show that the control method is feasible and excellent, which can fulfill the suppressed control for the fluctuation of the robot

Finite time point-stabilization of underwater spherical roving robot

This paper addresses the point stabilization problem for the underwater spherical roving robot (BYSQ-3) in the horizontal plane. The finite-time stable control laws are adopted to steer the robot to the origin fast, accurately and reliably. Firstly, the inner structure and operational principle of the robot is described and the kinematic and dynamic equations are established. Secondly, the diffeomorphism transformation and change of inputs are introduced to decouple the multivariable coupling system into two subsystems. The second subsystem consists of two double integrator systems. The finite-time controller is introduced to ensure part states converge to zero in finite time. Then, the other states are steered to the origin using the same method. Thirdly, the design process has no virtual input and the stability analysis is simple, the controller designed is easy for engineering implementation. The simulation and experiment results are presented to validate the shorter convergence time and better stability character of the controller

Trajectory Optimization for Velocity Jumps Reduction considering the Unexpectedness Characteristics of Space Manipulator Joint-Locked Failure

Aiming at reducing joint velocity jumps caused by an unexpected joint-locked failure during space manipulator on-orbit operations without shutting down manipulator, trajectory optimization strategy considering the unexpectedness characteristics of joint-locked failure is proposed in the paper, which can achieve velocity jumps reduction in both operation space and joint space simultaneously. In the strategy, velocity in operation space concerning task completion directly is treated as equality constraints, and velocity in joint space concerning motion performance is treated as objective function. Global compensation vector which consists of coefficient, gradient of manipulability, and orthogonal matrix of null space is constructed to minimize the objective function. For each particular failure time, unique optimal coefficient can be obtained when the objective function is minimal. As a basis, a method for optimal coefficient function fitting is proposed based on a priori failure information (possible failure time and the corresponding optimal coefficient) to guarantee the unexpectedness characteristics of joint-locked failure. Simulations are implemented to validate the efficiency of trajectory optimization strategy in reducing velocity jumps in both joint space and operation space. And the feasibility of coefficient function is also verified in reducing velocity jump no matter when joint-locked failure occurs

Positive correlation between the expression of hEag1 and HIF-1α in breast cancers: An observational study

Objectives: To explore the expression patterns of Eag1 (ether á go-go 1) and HIF-1α (hypoxia-inducible factor 1α) in a cohort of patients with breast cancer. Setting: Department of general surgery in an upper first-class hospital in Xi\u27an, China. Participants: A total of 112 female Han Chinese patients with a diagnosis of invasive ductal carcinoma were included. Patients with main internal diseases, such as cardiovascular, endocrine, gastroenterological, haematological, infectious diseases, etc, were excluded. Primary and secondary outcome measures: Expression profiles of Eag1 and HIF-1α. Results: Eag1 and HIF-1α were overexpressed in the tumour tissues compared with the pair-matched control tissues, p=0.002 and \u3c0.001, respectively. The expression of Eag1 and HIF-1α was negatively correlated with tumour size, p=0.032 and p=0.025, respectively, and lymph node status (p=0.040, p=0.032, respectively). The coexpression of Eag1 and HIF-1α was correlated with tumour size ( p=0.012), lymph node status (p=0.027) and tumour stage (p=0.036). HIF-1α has a strong correlation with hEag1 expression (κ=0.731, p\u3c0.001). Conclusions: HIF-1á expression has a strong correlation with hEag1 expression. We are the first to attempt to explore the correlation at the population level

Extracellular Matrix Elasticity Regulates Osteocyte Gap Junction Elongation: Involvement of Paxillin in Intracellular Signal Transduction

Background/Aims: Osteocytes can sense and respond to extracellular stimuli, including biochemical factors throughout the cell body, dendritic processes, and cilia bending. However, further exploration is required of osteocyte function in response to substrate stiffness, an important passive mechanical cue at the interface between osteocytes and the extracellular matrix, and the deep bio-mechanism in osteocytes involving mechanosensing of cell behavior. Methods: We fabricated silicon-based elastomer polydimethylsiloxane substrates with different stiffnesses but with the same surface topologies. We then seeded osteocytes onto the substrates to examine their responses. Methodologies used included scanning electron microscopy (SEM) for cell morphology, confocal laser scanning microscopy (CLSM) for protein distribution, western blot for protein levels, co-immunoprecipitation for protein interactions, and quantitative real-time polymerase chain reaction for gene expression. Results: SEM images revealed that substrate stiffness induced a change in osteocyte morphology, and CLSM of F-actin staining revealed that substrate stiffness can alter the cytoskeleton. These results were accompanied by changes in focal adhesion capacity in osteocytes, determined via characterization of vinculin expression and distribution. Furthermore, on the exterior of the cell membrane, fibronectin was altered by substrate stiffness. The fibronectin then induced a change in paxillin on the inner membrane of the cell via protein–protein interaction through transmembrane processing. Paxillin led to changes in connexin 43 via protein–protein binding, thereby influencing osteocyte gap junction elongation. Conclusion: This process -from mechanosensing and mechanotransduction to cell function - not only indicates that the effects of mechanical factors on osteocytes can be directly sensed from the cell body, but also indicates the involvement of paxillin transduction