An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction

A Closed-Loop Falls Monitoring and Prevention App for Multiple Sclerosis Clinical Practice: Human-Centered Design of the Multiple Sclerosis Falls InsightTrack

BACKGROUND

Falls are common in people with multiple sclerosis (MS), causing injuries, fear of falling, and loss of independence. Although targeted interventions (physical therapy) can help, patients underreport and clinicians undertreat this issue. Patient-generated data, combined with clinical data, can support the prediction of falls and lead to timely intervention (including referral to specialized physical therapy). To be actionable, such data must be efficiently delivered to clinicians, with care customized to the patient's specific context.

OBJECTIVE

This study aims to describe the iterative process of the design and development of Multiple Sclerosis Falls InsightTrack (MS-FIT), identifying the clinical and technological features of this closed-loop app designed to support streamlined falls reporting, timely falls evaluation, and comprehensive and sustained falls prevention efforts.

METHODS

Stakeholders were engaged in a double diamond process of human-centered design to ensure that technological features aligned with users' needs. Patient and clinician interviews were designed to elicit insight around ability blockers and boosters using the capability, opportunity, motivation, and behavior (COM-B) framework to facilitate subsequent mapping to the Behavior Change Wheel. To support generalizability, patients and experts from other clinical conditions associated with falls (geriatrics, orthopedics, and Parkinson disease) were also engaged. Designs were iterated based on each round of feedback, and final mock-ups were tested during routine clinical visits.

RESULTS

A sample of 30 patients and 14 clinicians provided at least 1 round of feedback. To support falls reporting, patients favored a simple biweekly survey built using REDCap (Research Electronic Data Capture; Vanderbilt University) to support bring-your-own-device accessibility-with optional additional context (the severity and location of falls). To support the evaluation and prevention of falls, clinicians favored a clinical dashboard featuring several key visualization widgets: a longitudinal falls display coded by the time of data capture, severity, and context; a comprehensive, multidisciplinary, and evidence-based checklist of actions intended to evaluate and prevent falls; and MS resources local to a patient's community. In-basket messaging alerts clinicians of severe falls. The tool scored highly for usability, likability, usefulness, and perceived effectiveness (based on the Health IT Usability Evaluation Model scoring).

CONCLUSIONS

To our knowledge, this is the first falls app designed using human-centered design to prioritize behavior change and, while being accessible at home for patients, to deliver actionable data to clinicians at the point of care. MS-FIT streamlines data delivery to clinicians via an electronic health record-embedded window, aligning with the 5 rights approach. Leveraging MS-FIT for data processing and algorithms minimizes clinician load while boosting care quality. Our innovation seamlessly integrates real-world patient-generated data as well as clinical and community-level factors, empowering self-care and addressing the impact of falls in people with MS. Preliminary findings indicate wider relevance, extending to other neurological conditions associated with falls and their consequences.

The Relationships Among Metal Homeostasis, Mitochondria, and Locus Coeruleus in Psychiatric and Neurodegenerative Disorders: Potential Pathogenetic Mechanism and Therapeutic Implications

While alterations in the locus coeruleus-noradrenergic system are present during early stages of neuropsychiatric disorders, it is unclear what causes these changes and how they contribute to other pathologies in these conditions. Data suggest that the onset of major depressive disorder and schizophrenia is associated with metal dyshomeostasis that causes glial cell mitochondrial dysfunction and hyperactivation in the locus coeruleus. The effect of the overactive locus coeruleus on the hippocampus, amygdala, thalamus, and prefrontal cortex can be responsible for some of the psychiatric symptoms. Although locus coeruleus overactivation may diminish over time, neuroinflammation-induced alterations are presumably ongoing due to continued metal dyshomeostasis and mitochondrial dysfunction. In early Alzheimer's and Parkinson's diseases, metal dyshomeostasis and mitochondrial dysfunction likely induce locus coeruleus hyperactivation, pathological tau or α-synuclein formation, and neurodegeneration, while reduction of glymphatic and cerebrospinal fluid flow might be responsible for β-amyloid aggregation in the olfactory regions before the onset of dementia. It is possible that the overactive noradrenergic system stimulates the apoptosis signaling pathway and pathogenic protein formation, leading to further pathological changes which can occur in the presence or absence of locus coeruleus hypoactivation. Data are presented in this review indicating that although locus coeruleus hyperactivation is involved in pathological changes at prodromal and early stages of these neuropsychiatric disorders, metal dyshomeostasis and mitochondrial dysfunction are critical factors in maintaining ongoing neuropathology throughout the course of these conditions. The proposed mechanistic model includes multiple pharmacological sites that may be targeted for the treatment of neuropsychiatric disorders commonly.

Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine

Many current clinical therapies for chronic diseases involve administration of drugs using dosage and bioavailability parameters estimated for a generalized population. This standard approach carries the risk of under dosing, which may result in ineffective treatment, or overdosing, which may cause undesirable side effects. Consequently, maintaining a drug concentration in the therapeutic window often requires frequent monitoring, adversely affecting the patient’s quality of life. In contrast, endogenous biosystems have evolved finely tuned feedback control loops that govern the physiological functions of the body based on multiple input parameters. To provide personalized treatment for chronic diseases, therefore, we require synthetic systems that can similarly generate a calibrated therapeutic response. Such engineered autonomous closed-loop devices should incorporate a sensor that actively tracks and evaluates the disease severity based on one or more biomarkers, as well as components that utilize these molecular inputs to bio compute and deliver the appropriate level of therapeutic output. Here, we review recent advances in applications of the closed-loop design principle in biomedical implants for treating severe and chronic diseases, highlighting translational studies of cellular therapies. We describe the engineering principles and components of closed-loop therapeutic devices, and discuss their potential to become a key pillar of personalized medicine.

A fully implantable wireless bidirectional neuromodulation system for mice

Novel research in the field of bioelectronic medicine requires neuromodulation systems that pair high-performance neurostimulation and bio-signal acquisition hardware with advanced signal processing and control algorithms. Although mice are the most commonly used animal in medical research, the size, weight, and power requirements of such bioelectronic systems either preclude use in mice or impose significant constraints on experimental design. Here, a fully-implantable recording and stimulation neuromodulation system suitable for use in mice is presented, measuring 2.2 cm3 and weighing 2.8 g. The bidirectional wireless interface allows simultaneous readout of multiple physiological signals and complete control over stimulation parameters, and a wirelessly rechargeable battery provides a lifetime of up to 5 days on a single charge. The device was implanted to deliver vagus nerve stimulation (n = 12 animals) and a functional neural interface (capable of inducing acute bradycardia) was demonstrated with lifetimes exceeding three weeks. The design utilizes only commercially-available electrical components and 3D-printed packaging, with the goal of facilitating widespread adoption and accelerating discovery and translation of future bioelectronic therapeutics.

An FSCV Deep Neural Network: Development, Pruning, and Acceleration on an FPGA

Fast-scan cyclic voltammetry (FSCV) is an electrochemical technique for measuring rapid changes in the extracellular concentration of neurotransmitters within the brain. Due to its fast scan rate and large output-data size, the current analysis of the FSCV data is often conducted on a computer external to the FSCV device. Moreover, the analysis is semi-automated and requires a good understanding of the characteristics of the underlying chemistry to interpret, making it unsuitable for real-time implementation on low-resource FSCV devices. This paper presents a hardware-software co-design approach for the analysis of FSCV data. Firstly, a deep neural network (DNN) is developed to predict the concentration of a dopamine solution and identify the data recording electrode. Secondly, the DNN is pruned to decrease its computation complexity, and a custom overlay is developed to implement the pruned DNN on a low-resource FPGA-based platform. The pruned DNN attains a recognition accuracy of 97.2% with a compression ratio of 3.18. When the DNN overlay is implemented on a PYNQ-Z2 platform, it achieves the execution time of 13 ms and power consumption of 1.479 W on the entire PYNQ-Z2 board. This study demonstrates the possibility of operating the DNN for FSCV data analysis on portable FPGA-based platforms.

A novel hypothesis on metal dyshomeostasis and mitochondrial dysfunction in amyotrophic lateral sclerosis: Potential pathogenetic mechanism and therapeutic implications

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by motor dysfunctions resulting from the loss of upper (UMNs) and lower (LMNs) motor neurons. While ALS symptoms are coincidental with pathological changes in LMNs and UMNs, the causal relationship between the two is unclear. For example, research on the extra-motor symptoms associated with this condition suggests that an imbalance of metals, including copper, zinc, iron, and manganese, is initially induced in the sensory ganglia due to a malfunction of metal binding proteins and transporters. It is proposed that the resultant metal dyshomeostasis may promote mitochondrial dysfunction in the satellite glial cells of these sensory ganglia, causing sensory neuron disturbances and sensory symptoms. Sensory neuron hyperactivation can result in LMN impairments, while metal dyshomeostasis in spinal cord and brain stem parenchyma induces mitochondrial dysfunction in LMNs and UMNs. These events could prompt intracellular calcium dyshomeostasis, pathological TDP-43 formation, and reactive microglia with neuroinflammation, which in turn activate the apoptosis signaling pathways within the LMNs and UMNs. Our model suggests that the degeneration of LMNs and UMNs is incidental to the metal-induced changes in the spinal cord and brain stem. Over time psychiatric symptoms may appear as the metal dyshomeostasis and mitochondrial dysfunction affect other brain regions, including the reticular formation, hippocampus, and prefrontal cortex. It is proposed that metal dyshomeostasis in combination with mitochondrial dysfunction could be the underlying mechanism responsible for the initiation and progression of the pathological changes associated with both the motor and extra-motor symptoms of ALS.

TinyFSCV: FSCV for the Masses

The ability to monitor neurochemical dynamics in target brain regions with a high degree of temporal resolution has assisted researchers in investigating the pathogenesis, and pathophysiology of a variety of neurological and psychiatric disorders. Current systems for neurochemical monitoring are bulky or expensive, limiting widespread exploration of this research field and preventing large-scale parallel experimentation. In this paper, we present a new miniaturized research platform, the TinyFSCV system, which can be used to monitor dynamic changes in neurochemicals through Fast-Scan Cyclic Voltammetry (FSCV). This system contains a precision voltage output circuit that can accurately output potentials between -0.55 to 2 V and scan a connected electrochemical cell at up to 400 V/s, the required speed to sense most neurochemicals with FSCV. In addition, the device includes precision current measurement circuity with a measurement range of -115 to [Formula: see text] capable of taking measurements at up to 56 KS/s. Four experiments are conducted to demonstrate the capability of the system. These consisted of: static bench tests, static ferrocene tests, and static and dynamic dopamine tests. These experiments demonstrate the ability of the miniaturized platform to accurately sense and measure neurochemicals. Ultimately, the TinyFSCV system is a platform that can enable large-scale, low-cost parallel experimentation to take place in the field of neurochemical monitoring. In addition, this device will increase the accessibility of neurochemical sensing, providing advanced tools and techniques to more researchers, and facilitating widespread exploration of the field of neurodynamics.

Development of a miniature device for emerging deep brain stimulation paradigms

Deep brain stimulation (DBS) is a neuromodulatory approach for treatment of several neurological and psychiatric disorders. A new focus on optimising the waveforms used for stimulation is emerging regarding the mechanism of DBS treatment. Many existing DBS devices offer only a limited set of predefined waveforms, mainly rectangular, and hence are inapt for exploring the emerging paradigm. Advances in clinical DBS are moving towards incorporating new stimulation parameters, yet we remain limited in our capacity to test these in animal models, arguably a critical first step. Accordingly, there is a need for the development of new miniature, low-power devices to enable investigation into the new DBS paradigms in preclinical settings. The ideal device would allow for flexibility in the stimulation waveforms, while remaining suitable for chronic, tetherless, biphasic deep brain stimulation. In this work, we elucidate several key parameters in a DBS system, identify gaps in existing solutions, and propose a new device to support preclinical DBS. The device allows for a high degree of flexibility in the output waveform with easily altered shape, frequency, pulse-width and amplitude. The device is suitable for both traditional and modern stimulation schemes, including those using non-rectangular waveforms, as well as delayed feedback schemes. The device incorporates active charge balancing to ensure safe operation, and allows for simple production of custom biphasic waveforms. This custom waveform output is unique in the field of preclinical DBS devices, and could be advantageous in performing future DBS studies investigating new treatment paradigms. This tetherless device can be easily and comfortably carried by an animal in a back-mountable configuration. The results of in-vitro tests are presented and discussed.