Utility of Gene Expression Profiling in Skin Cancer: A Comprehensive Review.

Understanding the metastatic potential of a skin cancer is essential to effective management. Gene expression profiling (GEP) is an innovative technology that has allowed for a better understanding of tumor biology in various skin cancers. Current methods focus on identifying and quantifying ribonucleic acid (RNA) transcripts in tissue samples. Using reverse transcriptase-polymerase chain reaction, specific RNA transcripts are reverted into deoxyribonucleic acid (DNA) for quantification. The addition of RNA-seq has further enhanced our knowledge of genomes not only by measuring known sequences, but also by identifying novel genes in various skin cancers. GEP requires only a small amount of RNA and has a high level of reproducibility. Using this technology, several GEPs for skin cancers have been developed to augment diagnosis and prognosis of skin cancer. This article reviews the process of gene expression profiling and the current GEPs that are available or under investigation for skin cancer. J Drugs Dermatol. 2023;22(5): doi:10.36849/JDD.7017.

Trigeminal trophic syndrome in a pediatric patient with diffuse intrinsic pontine glioma.

A 13-year-old girl with a history of diffuse intrinsic pontine glioma (DIPG) suffered from progressively worsening facial ulcerations secondary to paresthesia-induced self-excoriation. She was diagnosed with trigeminal trophic syndrome (TTS) induced by DIPG and struggled to heal her lesions in the background of this excoriation disorder. A multidisciplinary approach that included mood disorder management with sertraline and amitriptyline helped diminish paresthesia, improve her quality of life, and promote healing of the ulcers despite the progression of her DIPG. This case highlights the multifactorial complexity of TTS in pediatric patients and the need for successful management strategies.

A novel method for quantifying arm motion similarity.

This paper proposes a novel task-independent method for quantifying arm motion similarity that can be applied to any kinematic/dynamic variable of interest. Given two arm motions for the same task, not necessarily with the same completion time, it plots the time-normalized curves against one another and generates four real-valued features. To validate these features we apply them to quantify the relationship between healthy and paretic arm motions of chronic stroke patients. Studying both unimanual and bimanual arm motions of eight chronic stroke patients, we find that inter-arm coupling that tends to synchronize the motions of both arms in bimanual motions, has a stronger effect at task-relevant joints than at task-irrelevant joints. It also revealed that the paretic arm suppresses the shoulder flexion of the non-paretic arm, while the latter encourages the shoulder rotation of the former.

Task-relevance of grasping-related degrees of freedom in reach-to-grasp movements.

The kinematic redundancy of the human arm enables the rotation of the arm plane about the shoulder-wrist axis, represented by a swivel angle, which is affected by hand orientation when grasping. The coordination of grasping-related degrees of freedom (GR-DOFs), including swivel angle, forearm supination, wrist flexion and radial deviation, depends on their task-relevance, which can be quantified by the ratio of a joint's active motion range to its total motion range (R-AMR). The R-AMR values are computed across the target position and orientation to compare the task-relevance of the GR-DOFs. Statistical analysis of R-AMR values at the end of reach-to-grasp movements shows that among the GR-DOFs, radial deviation is most sensitive to changes in target position, while forearm supination is most sensitive to changes in target orientation. The forearm supination and swivel angle coordinate for energy-efficiency such that the swivel angle, which adjusts the posture of the whole arm, is largely unused until the forearm supination approaches its joint limit. The results further the understanding of the human motor control system in arm motion control and may benefit the design of the control algorithm for the upper limb exoskeleton.

The rotational axis approach for resolving the kinematic redundancy of the human arm in reaching movements.

The human arm is kinematically redundant with respect to reaching tasks in a 3 dimensional (3D) workspace. Research on reaching movements of the healthy human arm reveals the control strategy of the human motor system, which can be further applied to the upper limb exoskeletons used for stroke rehabilitation. Experiments performed on ten healthy subjects have shown that when reaching from one point to another, the human arm rotates around an axis going through the shoulder. The proposed redundancy resolution based on the direction of the axis can predict the arm posture with a higher accuracy comparing to a redundancy resolution that maximizes the motion efficiency. It is also shown that for reaching movements in the comfortable arm motion range, the directions of the axis are constrained by a linear model.

Admittance control of an upper limb exoskeleton--reduction of energy exchange.

The synergy of human arms and wearable robot systems (e.g. exoskeletons) is enabled by a control algorithm that maximizes the transparency between the two subsystems. The transparency can be improved by integrating the admittance control along with an arm redundancy resolution algorithm. Recent research effort resulted in a new criterion for the human arm redundancy resolution for unconstrained arm motions estimating the swivel angle with prediction errors of less than 5°. The proposed criterion for the arm redundancy resolution defines the mouth as the primary target of the the human hand during unconstrained arm motions in free space. It was postulated based on experimental data analysis that this criterion is based on a neural mechanism directing the hand towards the head for self-feeding. In conjunction with the proposed redundancy resolution criteria a task space admittance control algorithm is introduced based on multiple force sensor inputs obtained at the interface between the human arm and the exoskeleton system. The system performance was evaluated by five healthy subjects performing a peg-in-hole task for three different target locations. The velocities and interaction forces at the upper arm, lower arm, handle and tip were recorded and further used to power exchange between the subject and the device. Results indicated that the proposed control scheme outperforms the purely reactive task space admittance control with energy exchange reduced to 11.22%. Improving the quality of the human control of a wearable robot system may allow the robot to be a natural and transparent extension of the operator's body.

Viscoelastic model for redundancy resolution of the human arm via the swivel angle: applications for upper limb exoskeleton control.

One of the key research efforts associated with a redundant seven degree of freedom (7-DOF) upper limb exoskeleton robot that is mechanically coupled to the human body is to develop high and low level control algorithms that enable the system to become a natural extension of the human body. Improving the synergistic relationship between the exoskeleton and the operator is manifested in part by decreasing the force exchange between the two entities. Such a reduction is accomplished in part by developing criteria for resolving the human arm redundancy. The redundancy may be represented by a swivel angle which is defined as the angular rotation of the elbow around an axis that passes through the shoulder and wrist joints. The proposed criteria for defining the swivel angle takes into account the dynamics of the human arm along with a viscoelastic muscle-like model with variable damping. The swivel angle is estimated using the pseudo-inverse of the Jacobian with a secondary objective function that estimates the desired joint angles during human arm movement. The result is then fed to the muscle model to create a more realistic human motion. The estimated swivel angle is then compared with the actual swivel angle measured experimentally by a motion capture system. Results indicate that the average error between the estimated and measured swivel joint angle is 4.4 degrees (in the range [3.7-6] degrees), which are lower than the kinematically based redundant resolution criterion.