Background There is emerging evidence that the nervous system regulates immune and metabolic alterations mediating Metabolic syndrome (MetS) pathogenesis via the vagus nerve. This study evaluated the effects of transcutaneous auricular vagus nerve stimulation (TAVNS) on key cardiovascular and inflammatory components of MetS. Methods We conducted an open label, randomized (2:1), two-arm, parallel-group controlled trial in MetS patients. Subjects in the treatment group ( n = 20) received 30 min of TAVNS with a NEMOS® device placed on the cymba conchae of the left ear, once weekly. Patients in the control group ( n = 10) received no stimulation. Hemodynamic, heart rate variability (HRV), biochemical parameters, and monocytes, progenitor endothelial cells, circulating endothelial cells, and endothelial micro particles were evaluated at randomization, after the first TAVNS treatment, and again after 8 weeks of follow-up. Results An improvement in sympathovagal balance (HRV analysis) was observed after the first TAVNS session. Only patients treated with TAVNS for 8 weeks had a significant decrease in office BP and HR, a further improvement in sympathovagal balance, with a shift of circulating monocytes towards an anti-inflammatory phenotype and endothelial cells to a reparative vascular profile. Conclusion These results are of interest for further study of TAVNS as treatment of MetS.
Chest radiographs (CXRs) are the most widely available radiographic imaging modality used to detect respiratory diseases that result in lung opacities. CXR reports often use non-standardized language that result in subjective, qualitative, and non-reproducible opacity estimates. Our goal was to develop a robust deep transfer learning framework and adapt it to estimate the degree of lung opacity from CXRs. Following CXR data selection based on exclusion criteria, segmentation schemes were used for ROI (Region Of Interest) extraction, and all combinations of segmentation, data balancing, and classification methods were tested to pick the top performing models. Multifold cross validation was used to determine the best model from the initial selected top models, based on appropriate performance metrics, as well as a novel Macro-Averaged Heatmap Concordance Score (MA HCS). Performance of the best model is compared against that of expert physician annotators, and heatmaps were produced. Finally, model performance sensitivity analysis across patient populations of interest was performed. The proposed framework was adapted to the specific use case of estimation of degree of CXR lung opacity using ordinal multiclass classification. Acquired between March 24, 2020, and May 22, 2020, 38,365 prospectively annotated CXRs from 17,418 patients were used. We tested three neural network architectures (ResNet-50, VGG-16, and ChexNet), three segmentation schemes (no segmentation, lung segmentation, and lateral segmentation based on spine detection), and three data balancing strategies (undersampling, double-stage sampling, and synthetic minority oversampling) using 38,079 CXR images for training, and validation with 286 images as the out-of-the-box dataset that underwent expert radiologist adjudication. Based on the results of these experiments, the ResNet-50 model with undersampling and no ROI segmentation is recommended for lung opacity classification, based on optimal values for the MAE metric and HCS (Heatmap Concordance Score). The degree of agreement between the opacity scores predicted by this model with respect to the two sets of radiologist scores (OR or Original Reader and OOBTR or Out Of Box Reader) in terms of performance metrics is superior to the inter-radiologist opacity score agreement.
BACKGROUND:Reduced heart rate (HR) during vagus nerve stimulation (VNS) is associated with therapy for heart failure, but stimulation frequency and amplitude are limited by patient tolerance. An understanding of physiological responses to parameter adjustments would allow differential control of therapeutic and side effects. To investigate selective modulation of the physiological responses to VNS, we quantified the effects and interactions of parameter selection on two physiological outcomes: one related to therapy (reduced HR) and one related to side effects (laryngeal muscle EMG). METHODS:We applied a broad range of stimulation parameters (mean pulse rates (MPR), intra-burst frequencies, and amplitudes) to the vagus nerve of anesthetized mice. We leveraged the in vivo recordings to parameterize and validate computational models of HR and laryngeal muscle activity across amplitudes and temporal patterns of VNS. We constructed a finite element model of excitation of fibers within the mouse cervical vagus nerve. RESULTS:HR decreased with increased amplitude, increased MPR, and decreased intra-burst frequency. EMG increased with increased MPR. Preferential HR effects over laryngeal EMG effects required combined adjustments of amplitude and MPR. The model of HR responses highlighted contributions of ganglionic filtering to VNS-evoked changes in HR at high stimulation frequencies. Overlap in activation thresholds between small and large modeled fibers was consistent with the overlap in dynamic ranges of related physiological measures (HR and EMG). CONCLUSION:The present study provides insights into physiological responses to VNS required for informed parameter adjustment to modulate selectively therapeutic effects and side effects.
Background The liver is an important immunological organ and liver inflammation is part of the pathophysiology of non-alcoholic steatohepatitis, a condition that may promote cirrhosis, liver cancer, liver failure, and cardiovascular disease. Despite dense innervation of the liver parenchyma, little is known about neural regulation of liver function in inflammation. Here, we study vagus nerve control of the liver response to acute inflammation. Methods Male C57BL/6 J mice were subjected to either sham surgery, surgical vagotomy, or electrical vagus nerve stimulation followed by intraperitoneal injection of the TLR2 agonist zymosan. Animals were euthanized and tissues collected 12 h after injection. Samples were analyzed by qPCR, RNAseq, flow cytometry, or ELISA. Results Hepatic mRNA levels of pro-inflammatory mediators Ccl2, Il-1β, and Tnf-α were significantly higher in vagotomized mice compared with mice subjected to sham surgery. Differences in liver Ccl2 levels between treatment groups were largely reflected in the plasma chemokine (C–C motif) ligand 2 (CCL2) concentration. In line with this, we observed a higher number of macrophages in the livers of vagotomized mice compared with sham as measured by flow cytometry. In mice subjected to electrical vagus nerve stimulation, hepatic mRNA levels of Ccl2, Il1β, and Tnf-α, and plasma CCL2 levels, were significantly lower compared with sham. Interestingly, RNAseq revealed that a key activation marker for hepatic stellate cells (HSC), Pnpla3 , was the most significantly differentially expressed gene between vagotomized and sham mice. Of note, several HSC-activation associated transcripts were higher in vagotomized mice, suggesting that signals in the vagus nerve contribute to HSC activation. In support of this, we observed significantly higher number of activated HSCs in vagotomized mice as compared with sham as measured by flow cytometry. Conclusions Signals in the cervical vagus nerve controlled hepatic inflammation and markers of HSC activation in zymosan-induced peritonitis.
The emerging field of bioelectronic medicine (BEM) is poised to make a significant impact on the treatment of several neurological and inflammatory disorders. With several BEM therapies being recently approved for clinical use and others in late-phase clinical trials, the 2022 BEM summit was a timely scientific meeting convening a wide range of experts to discuss the latest developments in the field. The BEM Summit was held over two days in New York with more than thirty-five invited speakers and panelists comprised of researchers and experts from both academia and industry. The goal of the meeting was to bring international leaders together to discuss advances and cultivate collaborations in this emerging field that incorporates aspects of neuroscience, physiology, molecular medicine, engineering, and technology. This Meeting Report recaps the latest findings discussed at the Meeting and summarizes the main developments in this rapidly advancing interdisciplinary field. Our hope is that this Meeting Report will encourage researchers from academia and industry to push the field forward and generate new multidisciplinary collaborations that will form the basis of new discoveries that we can discuss at the next BEM Summit.
Collection of electroencephalographic (EEG) data provides an opportunity to non-invasively study human brain plasticity, learning and the evolution of various neuropsychiatric disorders. Traditionally, due to sophisticated hardware, EEG studies have been largely limited to research centers which restrict both testing contexts and repeated longitudinal measures. The emergence of low-cost "wearable" EEG devices now provides the prospect of frequent and remote monitoring of the human brain for a variety of physiological and pathological brain states. In this manuscript, we survey evidence that EEG wearables provide high-quality data and review various software used for remote data collection. We then discuss the growing body of evidence supporting the feasibility of remote and longitudinal EEG data collection using wearables including a discussion of potential biomedical applications of these protocols. Lastly, we discuss some additional challenges needed for EEG wearable research to gain further widespread adoption.
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.
Abstract Background Alzheimer’s disease (AD), a progressive neurodegenerative disorder, is becoming increasingly prevalent as our population ages. It is characterized by the buildup of amyloid beta plaques and neurofibrillary tangles containing hyperphosphorylated-tau. The current treatments for AD do not prevent the long-term progression of the disease and pre-clinical models often do not accurately represent its complexity. Bioprinting combines cells and biomaterials to create 3D structures that replicate the native tissue environment and can be used as a tool in disease modeling or drug screening. Methods This work differentiated both healthy and diseased patient–derived human induced pluripotent stems cells (hiPSCs) into neural progenitor cells (NPCs) that were bioprinted using the Aspect RX1 microfluidic printer into dome-shaped constructs. The combination of cells, bioink, and puromorphamine (puro)-releasing microspheres were used to mimic the in vivo environment and direct the differentiation of the NPCs into basal forebrain-resembling cholinergic neurons (BFCN). These tissue models were then characterized for cell viability, immunocytochemistry, and electrophysiology to evaluate their functionality and physiology for use as disease-specific neural models. Results Tissue models were successfully bioprinted and the cells were viable for analysis after 30- and 45-day cultures. The neuronal and cholinergic markers β-tubulin III (Tuj1), forkhead box G1 (FOXG1), and choline acetyltransferase (ChAT) were identified as well as the AD markers amyloid beta and tau. Further, immature electrical activity was observed when the cells were excited with potassium chloride and acetylcholine. Conclusions This work shows the successful development of bioprinted tissue models incorporating patient derived hiPSCs. Such models can potentially be used as a tool to screen promising drug candidates for treating AD. Further, this model could be used to increase the understanding of AD progression. The use of patient derived cells also shows the potential of this model for use in personalized medicine applications.
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.
Neuroinflammation is an important biological process induced by complex interactions between immune cells and neuronal cells in the central nervous system (CNS). Recent research on the bidirectional communication between neuronal and immunological systems has provided evidence for how immune and inflammatory processes are regulated by nerve activation. One example is the gateway reflex, in which immune cells bypass the blood brain barrier and infiltrate the CNS to cause neuroinflammation. We have found several modes of the gateway reflex in mouse models, in which gateways for immune cells are established at specific blood vessels in the spinal cords and brain in experimental autoimmune encephalomyelitis and systemic lupus erythematosus models, at retinal blood vessels in an experimental autoimmune uveitis model, and the ankle joints in an inflammatory arthritis model. Several environmental stimulations, including physical and psychological stresses, activate neurological pathways that alter immunological responses via the gateway reflex, thus contributing to the development/suppression of autoimmune diseases. In the manuscript, we describe the discovery of the gateway reflex and recent insights on how they regulate disease development. We hypothesize that artificial manipulation of specific neural pathways can establish and/or close the gateways to control the development of autoimmune diseases.
Background No effective treatment for NAION with strong evidence has been established till date. The aim of this investigator-led, prospective, non-randomized, open-label, uncontrolled multi-center exploratory clinical trial is to evaluate the efficacy and safety of transdermal electrical stimulation (TdES) using skin electrodes in patients with NAION. Methods Five patients with monocular NAION underwent TdES (10-ms biphasic pulses, 1.0 mA, 20 Hz, 30 min) of the affected eye six times at 2-week intervals. The primary endpoint was the logarithm of the mini-mum angle of resolution (logMAR) visual acuity at 12 weeks compared with 0 weeks. The secondary endpoints were changes in the best-corrected logMAR visual acuity, Early Treatment of Diabetic Retinopathy Study (ETDRS) visual acuity, and mean deviation (MD) of the Humphrey field analyzer (HFA) 10–2 and HFA Esterman test scores. Additionally, the safety of TdES was evaluated. Results LogMAR visual acuity improved by ≥ 0.1 in two eyes, and ETDRS visual acu-ity improved by ≥ 5 characters in one eye. The mean change in logMAR visual acuity from week 0 showed an increasing trend. The mean MD of HFA 10–2 showed no obvious change, while HFA Esterman score improved in four eyes. All patients completed the study according to the protocol, and no treatment-related adverse events were observed. Conclusions TdES treatment may have improved visual acuity and visual field in some patients. Further sham-controlled study in larger cohort is needed on its effectiveness. Trial registration UMIN, UMIN000036220. Registered 15 March, 2019, https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000041261 .
New sensors and modulators that interact wirelessly with medical modalities unlock uncharted avenues for in situ brain recording and stimulation. Ongoing miniaturization, material refinement, and sensitization to specific neurophysiological and neurochemical processes are spurring new capabilities that begin to transcend the constraints of traditional bulky and invasive wired probes. Here we survey current state-of-the-art agents across diverse realms of operation and evaluate possibilities depending on size, delivery, specificity and spatiotemporal resolution. We begin by describing implantable and injectable micro- and nano-scale electronic devices operating at or below the radio frequency (RF) regime with simple near field transmission, and continue with more sophisticated devices, nanoparticles and biochemical molecular conjugates acting as dynamic contrast agents in magnetic resonance imaging (MRI), ultrasound (US) transduction and other functional tomographic modalities. We assess the ability of some of these technologies to deliver stimulation and neuromodulation with emerging probes and materials that provide minimally invasive magnetic, electrical, thermal and optogenetic stimulation. These methodologies are transforming the repertoire of readily available technologies paired with compatible imaging systems and hold promise toward broadening the expanse of neurological and neuroscientific diagnostics and therapeutics.
Purpose Eighty percent of patients infected by SARS-CoV-2 report persistence of one symptom beyond the 4-week convalescent period. Those with orthostatic tachycardia and orthostatic symptoms mimicking postural tachycardia syndrome, they are defined as Long-COVID POTS [LCP]. This case-control study investigated potential differences in autonomic cardiovascular regulation between LCP patients and healthy controls. Methods Thirteen LCP and 16 healthy controls, all female subjects, were studied without medications. Continuous blood pressure and ECG were recorded during orthostatic stress test, respiratory sinus arrhythmia, and Valsalva maneuver. Time domain and power spectral analysis of heart rate [HR] and systolic blood pressure [SBP] variability were computed characterizing cardiac autonomic control and sympathetic peripheral vasoconstriction. Results LCP had higher deltaHR (+ 40 ± 6 vs. + 21 ± 3 bpm, p = 0.004) and deltaSBP (+ 8 ± 4 vs. -1 ± 2 mmHg, p = 0.04) upon standing; 47% had impaired Valsalva maneuver ratio compared with 6.2% in controls ( p = 0.01). Spectral analysis revealed that LCP had lower RMSSD (32.1 ± 4.6 vs. 48.9 ± 6.8 ms, p = 0.04) and HF RRI , both in absolute (349 ± 105 vs. 851 ± 253ms 2 , p = 0.03) and normalized units (32 ± 4 vs. 46 ± 4 n.u., p = 0.02). LF SBP was similar between groups. Conclusions LCP have reduced cardiovagal modulation, but normal sympathetic cardiac and vasoconstrictive functions. Impaired parasympathetic function may contribute to the pathogenesis of Long-COVID POTS syndrome.
The fourth industrial revolution has led to the development and application of health monitoring sensors that are characterized by digitalization and intelligence. These sensors have extensive applications in medical care, personal health management, elderly care, sports, and other fields, providing people with more convenient and real-time health services. However, these sensors face limitations such as noise and drift, difficulty in extracting useful information from large amounts of data, and lack of feedback or control signals. The development of artificial intelligence has provided powerful tools and algorithms for data processing and analysis, enabling intelligent health monitoring, and achieving high-precision predictions and decisions. By integrating the Internet of Things, artificial intelligence, and health monitoring sensors, it becomes possible to realize a closed-loop system with the functions of real-time monitoring, data collection, online analysis, diagnosis, and treatment recommendations. This review focuses on the development of healthcare artificial sensors enhanced by intelligent technologies from the aspects of materials, device structure, system integration, and application scenarios. Specifically, this review first introduces the great advances in wearable sensors for monitoring respiration rate, heart rate, pulse, sweat, and tears; implantable sensors for cardiovascular care, nerve signal acquisition, and neurotransmitter monitoring; soft wearable electronics for precise therapy. Then, the recent advances in volatile organic compound detection are highlighted. Next, the current developments of human-machine interfaces, AI-enhanced multimode sensors, and AI-enhanced self-sustainable systems are reviewed. Last, a perspective on future directions for further research development is also provided. In summary, the fusion of artificial intelligence and artificial sensors will provide more intelligent, convenient, and secure services for next-generation healthcare and biomedical applications.
Background Autonomic nerve stimulation is used as a treatment for a growing number of diseases. We have previously demonstrated that application of efferent vagus nerve stimulation (eVNS) has promising glucose lowering effects in a rat model of type 2 diabetes. This paradigm combines high frequency pulsatile stimulation to block nerve activation in the afferent direction with low frequency stimulation to activate the efferent nerve section. In this study we explored the effects of the parameters for nerve blocking on the ability to inhibit nerve activation in the afferent direction. The overarching aim is to establish a blocking stimulation strategy that could be applied using commercially available implantable pulse generators used in the clinic. Methods Male rats ( n = 20) had the anterior abdominal vagus nerve implanted with a multi-electrode cuff. Evoked compound action potentials (ECAP) were recorded at the proximal end of the electrode cuff. The efficacy of high frequency stimulation to block the afferent ECAP was assessed by changes in the threshold and saturation level of the response. Blocking frequency and duty cycle of the blocking pulses were varied while maintaining a constant 4 mA current amplitude. Results During application of blocking at lower frequencies (≤ 4 kHz), the ECAP threshold increased (ANOVA, p < 0.001) and saturation level decreased ( p < 0.001). Application of higher duty cycles (> 70%) led to an increase in evoked neural response threshold ( p < 0.001) and a decrease in saturation level ( p < 0.001). During the application of a constant pulse width and frequency (1 or 1.6 kHz, > 70% duty cycle), the charge delivered per pulse had a significant influence on the magnitude of the block (ANOVA, p = 0.003), and was focal (< 2 mm range). Conclusions This study has determined the range of frequencies, duty cycles and currents of high frequency stimulation that generate an efficacious, focal axonal block of a predominantly C-fiber tract. These findings could have potential application for the treatment of type 2 diabetes.
Trunk stability is crucial for people with trunk paralysis resulting from spinal cord injuries (SCI), as it plays a significant role in performing daily life activities and preventing from fall-related accidents. Traditional therapy used assistive methods or seating modifications to provide passive assistance while restricting their daily functionality. The recent emergence of neuromodulation techniques has been reported as an alternative therapy that could improve trunk and sitting functions following SCI. The aim of this review was to provide a broad perspective on the existing studies using neuromodulation techniques and identify their potentials in terms of trunk recovery for people with SCI. Five databases were searched (PubMed, Embase, Science Direct, Medline-Ovid, and Web of Science) from inception to December 31, 2022 to identify relevant studies. A total of 21 studies, involving 117 participants with SCI, were included in this review. According to these studies, neuromodulation significantly improved the reaching ability, restored trunk stability and seated posture, increased sitting balance, as well as elevated activity of trunk and back muscles, which were considered early predictors of trunk recovery after SCI. However, there is limited evidence regarding neuromodulation techniques on the improvement of trunk and sitting functions. Therefore, future large-scale randomized controlled trials are warranted to validate these preliminary findings.
BACKGROUND:Neurostimulation is an effective therapy for treating and management of refractory chronic pain. However, the complex nature of pain and infrequent in-clinic visits, determining subject's long-term response to the therapy remains difficult. Frequent measurement of pain in this population can help with early diagnosis, disease progression monitoring, and evaluating long-term therapeutic efficacy. This paper compares the utilization of the common subjective patient-reported outcomes with objective measures captured through a wearable device for predicting the response to neurostimulation therapy.METHOD:Data is from the ongoing international prospective post-market REALITY clinical study, which collects long-term patient-reported outcomes from 557 subjects implanted by Spinal Cord Stimulator (SCS) or Dorsal Root Ganglia (DRG) neurostimulators. The REALITY sub-study was designed for collecting additional wearables data on a subset of 20 participants implanted with SCS devices for up to six months post implantation. We first implemented a combination of dimensionality reduction algorithms and correlation analyses to explore the mathematical relationships between objective wearable data and subjective patient-reported outcomes. We then developed machine learning models to predict therapy outcome based on the subject's response to the numerical rating scale (NRS) or patient global impression of change (PGIC).RESULTS:Principal component analysis showed that psychological aspects of pain were associated with heart rate variability, while movement-related measures were strongly associated with patient-reported outcomes related to physical function and social role participation. Our machine learning models using objective wearable data predicted PGIC and NRS outcomes with high accuracy without subjective data. The prediction accuracy was higher for PGIC compared with the NRS using subjective-only measures primarily driven by the patient satisfaction feature. Similarly, the PGIC questions reflect an overall change since the study onset and could be a better predictor of long-term neurostimulation therapy outcome.CONCLUSIONS:The significance of this study is to introduce a novel use of wearable data collected from a subset of patients to capture multi-dimensional aspects of pain and compare the prediction power with the subjective data from a larger data set. The discovery of pain digital biomarkers could result in a better understanding of the patient's response to therapy and their general well-being.
Background The purpose of this study was to evaluate if kilohertz frequency alternating current (KHFAC) stimulation of peripheral nerve could serve as a treatment for lumbar radiculopathy. Prior work shows that KHFAC stimulation can treat sciatica resulting from chronic sciatic nerve constriction. Here, we evaluate if KHFAC stimulation is also beneficial in a more physiologic model of low back pain which mimics nucleus pulposus (NP) impingement of a lumbar dorsal root ganglion (DRG). Methods To mimic a lumbar radiculopathy, autologous tail NP was harvested and placed upon the right L5 nerve root and DRG. During the same surgery, a cuff electrode was implanted around the sciatic nerve with wires routed to a headcap for delivery of KHFAC stimulation. Male Lewis rats (3 mo., n = 18) were separated into 3 groups: NP injury + KHFAC stimulation ( n = 7), NP injury + sham cuff ( n = 6), and sham injury + sham cuff ( n = 5). Prior to surgery and for 2 weeks following surgery, animal tactile sensitivity, gait, and static weight bearing were evaluated. Results KHFAC stimulation of the sciatic nerve decreased behavioral evidence of pain and disability. Without KHFAC stimulation, injured animals had heightened tactile sensitivity compared to baseline ( p < 0.05), with tactile allodynia reversed during KHFAC stimulation ( p < 0.01). Midfoot flexion during locomotion was decreased after injury but improved with KHFAC stimulation ( p < 0.05). Animals also placed more weight on their injured limb when KHFAC stimulation was applied ( p < 0.05). Electrophysiology measurements at end point showed decreased, but not blocked, compound nerve action potentials with KHFAC stimulation ( p < 0.05). Conclusions KHFAC stimulation decreases hypersensitivity but does not cause additional gait compensations. This supports the idea that KHFAC stimulation applied to a peripheral nerve may be able to treat chronic pain resulting from sciatic nerve root inflammation.
