Bioelectronic medicine最新文献

Background: Seizure detection is challenging outside the clinical environment due to the lack of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We developed a novel, discreet, unobstructive in-ear sensing system that enables long-term electroencephalography (EEG) recording. This is the first study we are aware of that systematically compares the seizure detection utility of in-ear EEG with that of simultaneously recorded intracranial EEG. In addition, we present a similar comparison between simultaneously recorded in-ear EEG and scalp EEG.

Methods: In this foundational research, we conducted a clinical feasibility study and validated the ability of the ear-EEG system to capture focal-onset seizures against 1255 hrs of simultaneous ear-EEG data along with scalp or intracranial EEG in 20 patients with refractory focal epilepsy (11 with scalp EEG, 8 with intracranial EEG, and 1 with both).

Results: In a blinded, independent review of the ear-EEG signals, two epileptologists were able to detect 86.4% of the seizures that were subsequently identified using the clinical gold standard EEG modalities, with a false detection rate of 0.1 per day, well below what has been reported for ambulatory monitoring. The few seizures not detected on the ear-EEG signals emanated from deep within the mesial temporal lobe or extra-temporally and remained very focal, without significant propagation. Following multiple sessions of recording for a median continuous wear time of 13 hrs, patients reported a high degree of tolerance for the device, with only minor adverse events reported by the scalp EEG cohort.

Conclusions: These preliminary results demonstrate the potential of using ear-EEG to enable routine collection of complementary, prolonged, and remote neurophysiological evidence, which may permit real-time detection of paroxysmal events such as seizures and epileptiform discharges. This study suggests that the ear-EEG device may assist clinicians in making an epilepsy diagnosis, assessing treatment efficacy, and optimizing medication titration.

The effects of electromagnetic interference have been hiding in plain sight for millennia and are now being applied to the non-invasive stimulation of deep tissues. In the article by Missey et al., the effect of non-invasive stimulation of the hypoglossal nerve by an interference envelope of interfering carrier waves is examined in mice and participants with sleep apnea. This stimulation is capable of activating the nerve and reducing apnea-hypopnea events. Temporally interfering electric fields have potential applications far beyond hypoglossal stimulation and may represent a revolutionary new approach to treating illness and understanding the functional organization of the nervous system.

Background: Preclinical models of spinal cord stimulation (SCS) are lacking objective measurements to inform translationally applicable SCS parameters. The evoked compound action potential (ECAP) represents a measure of dorsal column fiber activation. This measure approximates the onset of SCS-induced sensations in humans and provides effective analgesia when used with ECAP-controlled closed-loop (CL)-SCS systems. Therefore, ECAPs may provide an objective surrogate for SCS dose in preclinical models that may support better understanding of SCS mechanisms and further translations to the clinics. This study assessed, for the first time, the feasibility of recording ECAPs and applying ECAP-controlled CL-SCS in freely behaving rats subjected to an experimental model of neuropathic pain.

Methods: Adult male Sprague-Dawley rats (200-300 g) were subjected to spared nerve injury (SNI). A custom-made six-contact lead was implanted epidurally covering T11-L3, as confirmed by computed tomography or X-ray. A specially designed multi-channel system was used to record ECAPs and to apply ECAP-controlled CL-SCS for 30 min at 50 Hz 200 µs. The responses of dorsal column fibers to SCS were characterized and sensitivity towards mechanical and cold stimuli were assessed to determine analgesic effects from ECAP-controlled CL-SCS. Comparisons between SNI rats and their controls as well as between stimulation parameters were made using omnibus analysis of variance (ANOVA) tests and t-tests.

Results: The recorded ECAPs showed the characteristic triphasic morphology and the ECAP amplitude (mV) increased as higher currents (mA) were applied in both SNI animals and controls (SNI SCS-ON and sham SCS-ON). Importantly, the use of ECAP-based SCS dose, implemented in ECAP-controlled CL-SCS, significantly reduced mechanical and cold hypersensitivity in SNI SCS-ON animals through the constant and controlled activation of dorsal column fibers. An analysis of conduction velocities of the evoked signals confirmed the involvement of large, myelinated fibers.

Conclusions: The use of ECAP-based SCS dose implemented in ECAP-controlled CL-SCS produced analgesia in animals subjected to an experimental model of neuropathic pain. This approach may offer a better method for translating SCS parameters between species that will improve understanding of the mechanisms of SCS action to further advance future clinical applications.

Regaining motor function in individuals with cerebral palsy (CP) has been predominantly studied in children, resulting in an underrepresentation of adults in research efforts. We tested the efficacy of noninvasive spinal neuromodulation with neurorehabilitation (Spinal Cord Innovation in Pediatrics; SCiP™ therapy). A 60-year-old CP participant underwent 8 weeks of SCiP™ therapy, resulting in significant motor recovery measured by 14.2-points increase in gross motor function measure (GMFM-88) score, ~ three times the Minimal Clinically Important Difference (MCID) of 5-points. This represented gains in kneeling, sitting, and walking functions. The improvement in GMFM-88 score was maintained above the MCID at the follow up visit (10.3 points above the baseline), twenty weeks following the last therapy session, indicating a persistent effect of the therapy. Our preliminary findings support the therapeutic promise of SCiP™ therapy for enhancing motor function in CP adults. Broader investigations are needed to establish its wider applicability.

Efferent cholinergic signaling is a critical and targetable source of immunoregulation. The vagus nerve (VN) is the primary source of cholinergic signaling in the body, and partially innervates hepatic functionality through the liver-brain axis. Virus-induced disruption of cholinergic signaling may promote pathogenesis in hepatotropic and neurotropic viruses. Therefore, restoring VN functionality could be a novel therapeutic strategy to alleviate pathogenic inflammation in hepatotropic and neurotropic viral infections alike. In this minireview, we discuss the physiological importance of cholinergic signaling in maintaining liver-brain axis homeostasis. Next, we explore mechanisms by which the VN is perturbed by viral infections, and how non-invasive restoration of cholinergic signaling pathways with bioelectronic medicine (BEM) might ameliorate hepatic inflammation and neuroinflammation in certain viral infections.

Nearly 5 decades ago, the effect of trigeminal nerve stimulation (TNS) on cerebral blood flow was observed for the first time. This implication directly led to further investigations and TNS' success as a therapeutic intervention. Possessing unique connections with key brain and brainstem regions, TNS has been observed to modulate cerebral vasodilation, brain metabolism, cerebral autoregulation, cerebral and systemic inflammation, and the autonomic nervous system. The unique range of effects make it a prime therapeutic modality and have led to its clinical usage in chronic conditions such as migraine, prolonged disorders of consciousness, and depression. This review aims to present a comprehensive overview of TNS research and its broader therapeutic potentialities. For the purpose of this review, PubMed and Google Scholar were searched from inception to August 28, 2023 to identify a total of 89 relevant studies, both clinical and pre-clinical. TNS harnesses the release of vasoactive neuropeptides, modulation of neurotransmission, and direct action upon the autonomic nervous system to generate a suite of powerful multitarget therapeutic effects. While TNS has been applied clinically to chronic pathological conditions, these powerful effects have recently shown great potential in a number of acute/traumatic pathologies. However, there are still key mechanistic and methodologic knowledge gaps to be solved to make TNS a viable therapeutic option in wider clinical settings. These include bimodal or paradoxical effects and mechanisms, questions regarding its safety in acute/traumatic conditions, the development of more selective stimulation methods to avoid potential maladaptive effects, and its connection to the diving reflex, a trigeminally-mediated protective endogenous reflex. The address of these questions could overcome the current limitations and allow TNS to be applied therapeutically to an innumerable number of pathologies, such that it now stands at the precipice of becoming a ground-breaking therapeutic modality.

The increasing prevalence of chronic diseases is a driver for emerging big data technologies for healthcare including digital platforms for data collection, systems for active patient engagement and education, therapy specific predictive models, optimized patient pathway models. Powerful bioelectronic medicine tools for data collection, analysis and visualization allow for joint processing of large volumes of heterogeneous data, which in turn can produce new insights about patient outcomes and alternative interpretations of clinical patterns that can lead to implementation of optimized clinical decisions and clinical patient pathway by healthcare professionals.With this perspective, we identify innovative solutions for disease management and evaluate their impact on patients, payers and society, by analyzing their impact in terms of clinical outcomes (effectiveness, safety, and quality of life) and economic outcomes (cost-effectiveness, savings, and productivity).As a result, we propose a new approach based on the main pillars of innovation in the disease management area, i.e. progressive patient care models, patient-centric approaches, bioelectronics for precise medicine, and lean management that, combined with an increase in appropriate private-public-citizen-partnership, leads towards Patient-Centric Healthcare.

The vagus nerve regulates inflammation and cytokine release through the inflammatory reflex. Recent pilot clinical trials using implantable bioelectronic devices have demonstrated the efficacy of vagus nerve stimulation (VNS) in adult patients with inflammatory bowel diseases (IBD) as an alternative to drug treatments. However, the use of non-invasive VNS should be of interest in adults with IBD and even more in pediatric IBD. In this issue of Bioelectronic Medicine, Sahn et al. report that non-invasive transcutaneous auricular VNS attenuated signs and symptoms in a pediatric cohort with mild to moderate IBD thus opening new therapeutic avenues in the management of pediatric but also adult IBD patients.

Gastrointestinal (GI) disorders, which extend from the esophagus to the anus, are the most common diseases of the GI tract. Among these disorders, pain, encompassing both abdominal and visceral pain, is a predominant feature, affecting the patients' quality of life and imposing a substantial financial burden on society. Pain signals originating from the gut intricately shape brain dynamics. In response, the brain sends appropriate descending signals to respond to pain through neuronal inhibition. However, due to the heterogeneous nature of the disease and its limited pathophysiological understanding, treatment options are minimal and often controversial. Consequently, many patients with GI disorders use complementary and alternative therapies such as neuromodulation to treat visceral pain. Neuromodulation intervenes in the central, peripheral, or autonomic nervous system by alternating or modulating nerve activity using electrical, electromagnetic, chemical, or optogenetic methodologies. Here, we review a few emerging noninvasive neuromodulation approaches with promising potential for alleviating pain associated with functional dyspepsia, gastroparesis, irritable bowel syndrome, inflammatory bowel disease, and non-cardiac chest pain. Moreover, we address critical aspects, including the efficacy, safety, and feasibility of these noninvasive neuromodulation methods, elucidate their mechanisms of action, and outline future research directions. In conclusion, the emerging field of noninvasive neuromodulation appears as a viable alternative therapeutic avenue for effectively managing visceral pain in GI disorders.

Background: Noninvasive ultrasound (US) has been used therapeutically for decades, with applications in tissue ablation, lithotripsy, and physical therapy. There is increasing evidence that low intensity US stimulation of organs can alter physiological and clinical outcomes for treatment of health disorders including rheumatoid arthritis and diabetes. One major translational challenge is designing portable and reliable US devices that can be used by patients in their homes, with automated features to detect rib location and aid in efficient transmission of energy to organs of interest. This feasibility study aimed to assess efficacy in rib bone detection without conventional imaging, using a single channel US pitch-catch technique integrated into an US therapy device to detect pulsed US reflections from ribs.

Methods: In 20 healthy volunteers, the location of the ribs and spleen were identified using a diagnostic US imaging system. Reflected ultrasound signals were recorded at five positions over the spleen and adjacent ribs using the therapy device. Signals were classified as between ribs (intercostal), partially over a rib, or fully over a rib using four models: threshold-based time domain classification, threshold-based frequency domain classification, logistic regression, and support vector machine (SVM).

Results: SVM performed best overall on the All Participants cohort with accuracy up to 96.25%. All models' accuracies were improved by separating participants into two cohorts based on Body Mass Index (BMI) and re-fitting each model. After separation into Low BMI and High BMI cohorts, a simple time-thresholding approach achieved accuracies up to 100% and 93.75%, respectively.

Conclusion: These results demonstrate that US reflection signal classification can accurately provide low complexity, real-time automated onboard rib detection and user feedback to advance at-home therapeutic US delivery.