Receptor-Mediated Attachment and Uptake of Hyaluronan Conjugates by Breast Cancer Cells.

Chemotherapy, a mainstay modality for cancer, is often hindered by systemic toxicity and side effects. With the emergence of nanomedicine, the development of drug therapy has shifted toward targeted therapy. Hyaluronan (HA) is an ideal molecule as a targeted delivery system because many carcinomas overexpress HA receptors. We have conjugated resveratrol, a natural polyphenol, and 3-(5-methoxy, 2-methyl-1H-indol-3-yl)-1-(4-pyridinyl)-2-propen-1-one (MOMIPP), a chalcone, to HA with the goal of enhancing drug bioavailability and targeting triple negative breast cancers. We demonstrate the ability of HA conjugates to accumulate in the tumor interstitium within 6 h after tail vein injections. In vitro, these conjugates interact with their target receptors, which are overexpressed by triple negative breast cancer cells under static and physiological flow. These interactions result in enhanced uptake and efficacy of the therapeutic, as demonstrated by a reduced IC50 over that of nonconjugated drugs. Thus, HA offers a platform to solubilize, target, and enhance the efficacy of chemotherapeutics.

Characterization of Transition to Turbulence for Blood in a Straight Pipe Under Steady Flow Conditions.

Blood is a complex fluid that, among other things, has been established to behave as a shear thinning, non-Newtonian fluid when exposed to low shear rates (SR). Many hemodynamic investigations use a Newtonian fluid to represent blood when the flow field of study has relatively high SR (>200 s-1). Shear thinning fluids have been shown to exhibit differences in transition to turbulence (TT) compared to that of Newtonian fluids. Incorrect prediction of the transition point in a simulation could result in erroneous hemodynamic force predictions. The goal of the present study was to compare velocity profiles near TT of whole blood and Newtonian blood analogs in a straight rigid pipe with a diameter 6.35 mm under steady flow conditions. Rheology was measured for six samples of whole porcine blood and three samples of a Newtonian fluid, and the results show blood acts as a shear thinning non-Newtonian fluid. Measurements also revealed that blood viscosity at SR = 200 s-1 is significantly larger than at SR = 1000 s-1 (13.8%, p < 0.001). Doppler ultrasound (DUS) was used to measure velocity profiles for blood and Newtonian samples at different flow rates to produce Reynolds numbers (Re) ranging from 1000 to 3300 (based on viscosity at SR = 1000 s-1). Two mathematically defined methods, based on the velocity profile shape change and turbulent kinetic energy (TKE), were used to detect TT. Results show similar parabolic velocity profiles for both blood and the Newtonian fluid for Re < 2200. However, differences were observed between blood and Newtonian fluid velocity profiles for larger Re. The Newtonian fluid had blunt-like velocity profiles starting at Re = 2403 ± 8 which indicated transition. In contrast, blood did not show this velocity profile change until Re = 2871 ± 104. The Newtonian fluid had large velocity fluctuations (root mean square (RMS) > 20%) with a maximum TKE near the pipe center at Re = 2316 ± 34 which indicated transition. In contrast, blood results showed the maximum TKE at Re = 2806 ± 109. Overall, the critical Re was delayed by ∼20% (p < 0.001) for blood compared to the Newtonian fluid. Thus, a Newtonian assumption for blood at flow conditions near transition could lead to large errors in velocity prediction for steady flow in a straight pipe. However, these results are specific to this pipe diameter and not generalizable since SR is highly dependent on pipe diameter. Further research is necessary to understand this relation in different pipe sizes, more complex geometries, and under pulsatile flow conditions.

Osteoactivin induces transdifferentiation of C2C12 myoblasts into osteoblasts.

Osteoactivin (OA) is a novel osteogenic factor important for osteoblast differentiation and function. Previous studies showed that OA stimulates matrix mineralization and transcription of osteoblast specific genes required for differentiation. OA plays a role in wound healing and its expression was shown to increase in post fracture calluses. OA expression was reported in muscle as OA is upregulated in cases of denervation and unloading stress. The regulatory mechanisms of OA in muscle and bone have not yet been determined. In this study, we examined whether OA plays a role in transdifferentiation of C2C12 myoblast into osteoblasts. Infected C2C12 with a retroviral vector overexpressing OA under the CMV promoter were able to transdifferentiate from myoblasts into osteoblasts. Immunofluorescence analysis showed that skeletal muscle marker MF-20 was severely downregulated in cells overexpressing OA and contained significantly less myotubes compared to uninfected control. C2C12 myoblasts overexpressing OA showed an increase in expression of bone specific markers such as alkaline phosphatase and alizarin red staining, and also showed an increase in Runx2 protein expression. We also detected increased levels of phosphorylated focal adhesion kinase (FAK) in C2C12 myoblasts overexpressing OA compared to control. Taken together, our results suggest that OA is able to induce transdifferentiation of myoblasts into osteoblasts through increasing levels of phosphorylated FAK.

The Impact of Hill-Type Actuator Components on the Performance of Reinforcement Learning Controllers to Reverse Upper-Limb Paralysis.

Functional electrical stimulation (FES) may allow people who are paralyzed due to spinal cord injuries (SCIs) to regain the ability to move. Deep neural networks (DNNs) trained with reinforcement learning (RL) have been recently explored as a promising methodology to control FES systems to restore upper-limb movements. However, previous studies suggested that large asymmetries in antagonistic upper-limb muscle strengths could impair RL controller performance. In this work, we investigated the underlying causes of asymmetry-associated decreases in controller performance by comparing different Hill-type models of muscle atrophy, and by characterizing RL controller sensitivity to passive mechanical properties of the arm. Simulations indicated that RL controller performance is relatively insensitive to moderate (up to 50%) changes in tendon stiffness and in flexor muscle stiffness. However, the viable workspace for RL control was substantially affected by flexor muscle weakness and by extensor muscle stiffness. Furthermore, we uncovered that RL controller performance issues previously attributed to asymmetrical antagonistic muscle strength resulted from flexor muscle active forces that were insufficient to counteract extensor muscle passive resistance. The simulations supported the adoption of rehabilitation protocols for reaching tasks that prioritize decreasing muscle passive resistance, and counteracting passive resistance with increased antagonistic muscle strength.

Improving the Learning Rate, Accuracy, and Workspace of Reinforcement Learning Controllers for a Musculoskeletal Model of the Human Arm.

Cervical spinal cord injuries frequently cause paralysis of all four limbs - a medical condition known as tetraplegia. Functional electrical stimulation (FES), when combined with an appropriate controller, can be used to restore motor function by electrically stimulating the neuromuscular system. Previous works have demonstrated that reinforcement learning can be used to successfully train FES controllers. Here, we demonstrate that transfer learning and curriculum learning can be used to improve the learning rates, accuracies, and workspaces of FES controllers that are trained using reinforcement learning.

Deep Reinforcement Learning for Control of Time-Varying Musculoskeletal Systems With High Fatigability: A Feasibility Study.

Functional electrical stimulation (FES) can be used to restore motor function to people with paralysis caused by spinal cord injuries (SCIs). However, chronically-paralyzed FES-stimulated muscles can fatigue quickly, which may decrease FES controller performance. In this work, we explored the feasibility of using deep neural network (DNN) controllers trained with reinforcement learning (RL) to control FES of upper-limb muscles after SCI. We developed upper-limb biomechanical models that exhibited increased muscle fatigability, decreased muscle recovery, and decreased muscle strength, as observed in people with chronic SCIs. Simulations confirmed that controller training time and controller performance are impaired to varying degrees by muscle fatigability. Also, the simulations showed that large muscle strength asymmetries between opposing muscles can substantially impair controller performance. However, the results of this study suggest that controller performance for highly-fatigable musculoskeletal systems can be preserved by allowing for rest between movements. Overall, the results suggest that RL can be used to successfully train FES controllers, even for highly-fatigable musculoskeletal systems.

Hindsight Experience Replay Improves Reinforcement Learning for Control of a MIMO Musculoskeletal Model of the Human Arm.

High-level spinal cord injuries often result in paralysis of all four limbs, leading to decreased patient independence and quality of life. Coordinated functional electrical stimulation (FES) of paralyzed muscles can be used to restore some motor function in the upper extremity. To coordinate functional movements, FES controllers should be developed to exploit the complex characteristics of human movement and produce the intended movement kinematics and/or kinetics. Here, we demonstrate the ability of a controller trained using reinforcement learning to generate desired movements of a horizontal planar musculoskeletal model of the human arm with 2 degrees of freedom and 6 actuators. The controller is given information about the kinematics of the arm, but not the internal state of the actuators. In particular, we demonstrate that a technique called "hindsight experience replay" can improve controller performance while also decreasing controller training time.

The Neural Representation of Force across Grasp Types in Motor Cortex of Humans with Tetraplegia.

Intracortical brain-computer interfaces (iBCIs) have the potential to restore hand grasping and object interaction to individuals with tetraplegia. Optimal grasping and object interaction require simultaneous production of both force and grasp outputs. However, since overlapping neural populations are modulated by both parameters, grasp type could affect how well forces are decoded from motor cortex in a closed-loop force iBCI. Therefore, this work quantified the neural representation and offline decoding performance of discrete hand grasps and force levels in two human participants with tetraplegia. Participants attempted to produce three discrete forces (light, medium, hard) using up to five hand grasp configurations. A two-way Welch ANOVA was implemented on multiunit neural features to assess their modulation to force and grasp Demixed principal component analysis (dPCA) was used to assess for population-level tuning to force and grasp and to predict these parameters from neural activity. Three major findings emerged from this work: (1) force information was neurally represented and could be decoded across multiple hand grasps (and, in one participant, across attempted elbow extension as well); (2) grasp type affected force representation within multiunit neural features and offline force classification accuracy; and (3) grasp was classified more accurately and had greater population-level representation than force. These findings suggest that force and grasp have both independent and interacting representations within cortex, and that incorporating force control into real-time iBCI systems is feasible across multiple hand grasps if the decoder also accounts for grasp type.

Neural Representation of Observed, Imagined, and Attempted Grasping Force in Motor Cortex of Individuals with Chronic Tetraplegia.

Hybrid kinetic and kinematic intracortical brain-computer interfaces (iBCIs) have the potential to restore functional grasping and object interaction capabilities in individuals with tetraplegia. This requires an understanding of how kinetic information is represented in neural activity, and how this representation is affected by non-motor parameters such as volitional state (VoS), namely, whether one observes, imagines, or attempts an action. To this end, this work investigates how motor cortical neural activity changes when three human participants with tetraplegia observe, imagine, and attempt to produce three discrete hand grasping forces with the dominant hand. We show that force representation follows the same VoS-related trends as previously shown for directional arm movements; namely, that attempted force production recruits more neural activity compared to observed or imagined force production. Additionally, VoS-modulated neural activity to a greater extent than grasping force. Neural representation of forces was lower than expected, possibly due to compromised somatosensory pathways in individuals with tetraplegia, which have been shown to influence motor cortical activity. Nevertheless, attempted forces (but not always observed or imagined forces) could be decoded significantly above chance, thereby potentially providing relevant information towards the development of a hybrid kinetic and kinematic iBCI.

Microstereolithography and characterization of poly(propylene fumarate)-based drug-loaded microneedle arrays.

Drug-loaded microneedle arrays for transdermal delivery of a chemotherapeutic drug were fabricated using multi-material microstereolithography (µSL). These arrays consisted of twenty-five poly(propylene fumarate) (PPF) microneedles, which were precisely orientated on the same polymeric substrate. To control the viscosity and improve the mechanical properties of the PPF, diethyl fumarate (DEF) was mixed with the polymer. Dacarbazine, which is widely used for skin cancer, was uniformly blended into the PPF/DEF solution prior to crosslinking. Each microneedle has a cylindrical base with a height of 700 µm and a conical tip with a height of 300 µm. Compression test results and characterization of the elastic moduli of the PPF/DEF (50:50) and PPF/drug mixtures indicated that the failure force was much larger than the theoretical skin insertion force. The release kinetics showed that dacarbazine can be released at a controlled rate for five weeks. The results demonstrated that the PPF-based drug-loaded microneedles are a potential method to treat skin carcinomas. In addition, µSL is an attractive manufacturing technique for biomedical applications, especially for micron-scale manufacturing.