Bioelectronic medicine最新文献

{"title":"Focused ultrasound neuromodulation on a multiwell MEA.","authors":"Marta Saccher, Shinnosuke Kawasaki, Martina Proietti Onori, Geeske M van Woerden, Vasiliki Giagka, Ronald Dekker","doi":"10.1186/s42234-021-00083-7","DOIUrl":"10.1186/s42234-021-00083-7","url":null,"abstract":"<p><strong>Background: </strong>Microelectrode arrays (MEA) enable the measurement and stimulation of the electrical activity of cultured cells. The integration of other neuromodulation methods will significantly enhance the application range of MEAs to study their effects on neurons. A neuromodulation method that is recently gaining more attention is focused ultrasound neuromodulation (FUS), which has the potential to treat neurological disorders reversibly and precisely.</p><p><strong>Methods: </strong>In this work, we present the integration of a focused ultrasound delivery system with a multiwell MEA plate.</p><p><strong>Results: </strong>The ultrasound delivery system was characterised by ultrasound pressure measurements, and the integration with the MEA plate was modelled with finite-element simulations of acoustic field parameters. The results of the simulations were validated with experimental visualisation of the ultrasound field with Schlieren imaging. In addition, the system was tested on a murine primary hippocampal neuron culture, showing that ultrasound can influence the activity of the neurons.</p><p><strong>Conclusions: </strong>Our system was demonstrated to be suitable for studying the effect of focused ultrasound on neuronal cultures. The system allows reproducible experiments across the wells due to its robustness and simplicity of operation.</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8793260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39723783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcutaneous auricular vagus nerve stimulation (taVNS) for the treatment of pediatric nephrotic syndrome: a pilot study.","authors":"Kumail Merchant, Stavros Zanos, Timir Datta-Chaudhuri, Clifford S Deutschman, Christine B Sethna","doi":"10.1186/s42234-021-00084-6","DOIUrl":"10.1186/s42234-021-00084-6","url":null,"abstract":"<p><strong>Background: </strong>Children with frequently relapsing nephrotic syndrome (FRNS) and steroid resistant nephrotic syndrome (SRNS) are exposed to immunosuppressant medications with adverse side effects and variable efficacy. Transcutaneous auricular vagus nerve stimulation (taVNS) modulates the immune system via the inflammatory reflex and has become a therapy of interest for treating immune-mediated illnesses.</p><p><strong>Methods: </strong>An open-label, pilot study of tavNS for five minutes daily for 26 weeks via a TENS 7000 unit was conducted.</p><p><strong>Results: </strong>Three FRNS participants and 4 SRNS participants had a mean age of 9.5±4.2 years (range 4 to 17). Those with FRNS remained relapse-free during the study period; two participants continued treatment and remained in remission for 15 and 21 months, respectively. Three SRNS participants experienced a reduction in first morning UPC (mean of 42%, range 25-76%). Although UPC decreased (13.7%) in one SRNS participant with congenital nephrotic syndrome, UPC remained in nephrotic range. All but one participant (non-compliant with treatment) experienced a reduction in TNF (7.33pg/mL vs. 5.46pg/mL, p=0.03). No adverse events or side effects were reported.</p><p><strong>Conclusions: </strong>taVNS was associated with clinical remission in FRNS and moderately reduced proteinuria in non-congenital SRNS. Further study of taVNS as a treatment for nephrotic syndrome in children is warranted. ClinicalTrials.gov Identifier: NCT04169776, Registered November 20, 2019, https://clinicaltrials.gov/ct2/show/NCT04169776 .</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790887/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39720951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robotic Kinematic measures of the arm in chronic Stroke: part 2 - strong correlation with clinical outcome measures.","authors":"Caio B Moretti,&nbsp;Taya Hamilton,&nbsp;Dylan J Edwards,&nbsp;Avrielle Rykman Peltz,&nbsp;Johanna L Chang,&nbsp;Mar Cortes,&nbsp;Alexandre C B Delbe,&nbsp;Bruce T Volpe,&nbsp;Hermano I Krebs","doi":"10.1186/s42234-021-00082-8","DOIUrl":"10.1186/s42234-021-00082-8","url":null,"abstract":"<p><strong>Background: </strong>A detailed sensorimotor evaluation is essential in planning effective, individualized therapy post-stroke. Robotic kinematic assay may offer better accuracy and resolution to understand stroke recovery. Here we investigate the added value of distal wrist measurement to a proximal robotic kinematic assay to improve its correlation with clinical upper extremity measures in chronic stroke. Secondly, we compare linear and nonlinear regression models.</p><p><strong>Methods: </strong>Data was sourced from a multicenter randomized controlled trial conducted from 2012 to 2016, investigating the combined effect of robotic therapy and transcranial direct current stimulation (tDCS). 24 kinematic metrics were derived from 4 shoulder-elbow tasks and 35 metrics from 3 wrist and forearm evaluation tasks. A correlation-based feature selection was performed, keeping only features substantially correlated with the target attribute (R > 0.5.) Nonlinear models took the form of a multilayer perceptron neural network: one hidden layer and one linear output.</p><p><strong>Results: </strong>Shoulder-elbow metrics showed a significant correlation with the Fugl Meyer Assessment (upper extremity, FMA-UE), with a R = 0.82 (P < 0.001) for the linear model and R = 0.88 (P < 0.001) for the nonlinear model. Similarly, a high correlation was found for wrist kinematics and the FMA-UE (R = 0.91 (P < 0.001) and R = 0.92 (P < 0.001) for the linear and nonlinear model respectively). The combined analysis produced a correlation of R = 0.91 (P < 0.001) for the linear model and R = 0.91 (P < 0.001) for the nonlinear model.</p><p><strong>Conclusions: </strong>Distal wrist kinematics were highly correlated to clinical outcomes, warranting future investigation to explore our nonlinear wrist model with acute or subacute stroke populations.</p><p><strong>Trial registration: </strong>http://www.clinicaltrials.gov . Actual study start date September 2012. First registered on 15 November 2012. Retrospectively registered. Unique identifiers: NCT01726673 and NCT03562663 .</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"21"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39858131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robotic Kinematic measures of the arm in chronic Stroke: part 1 - Motor Recovery patterns from tDCS preceding intensive training.","authors":"Caio B Moretti,&nbsp;Dylan J Edwards,&nbsp;Taya Hamilton,&nbsp;Mar Cortes,&nbsp;Avrielle Rykman Peltz,&nbsp;Johanna L Chang,&nbsp;Alexandre C B Delbem,&nbsp;Bruce T Volpe,&nbsp;Hermano I Krebs","doi":"10.1186/s42234-021-00081-9","DOIUrl":"https://doi.org/10.1186/s42234-021-00081-9","url":null,"abstract":"<p><strong>Background: </strong>Effectiveness of robotic therapy and transcranial direct current stimulation is conventionally assessed with clinical measures. Robotic metrics may be more objective and sensitive for measuring the efficacy of interventions on stroke survivor's motor recovery. This study investigated if robotic metrics detect a difference in outcomes, not seen in clinical measures, in a study of transcranial direct current stimulation (tDCS) preceding robotic therapy. Impact of impairment severity on intervention response was also analyzed to explore optimization of outcomes by targeting patient sub-groups.</p><p><strong>Methods: </strong>This 2020 study analyzed data from a double-blind, sham-controlled, randomized multi-center trial conducted from 2012 to 2016, including a six-month follow-up. 82 volunteers with single chronic ischemic stroke and right hemiparesis received anodal tDCS or sham stimulation, prior to robotic therapy. Robotic therapy involved 1024 repetitions, alternating shoulder-elbow and wrist robots, for a total of 36 sessions. Shoulder-elbow and wrist kinematic and kinetic metrics were collected at admission, discharge, and follow-up.</p><p><strong>Results: </strong>No difference was detected between the tDCS or sham stimulation groups in the analysis of robotic shoulder-elbow or wrist metrics. Significant improvements in all metrics were found for the combined group analysis. Novel wrist data showed smoothness significantly improved (P < ·001) while submovement number trended down, overlap increased, and interpeak interval decreased. Post-hoc analysis showed only patients with severe impairment demonstrated a significant difference in kinematics, greater for patients receiving sham stimulation.</p><p><strong>Conclusions: </strong>Robotic data confirmed results of clinical measures, showing intensive robotic therapy is beneficial, but no additional gain from tDCS. Patients with severe impairment did not benefit from the combined intervention. Wrist submovement characteristics showed a delayed pattern of motor recovery compared to the shoulder-elbow, relevant to intensive intervention-related recovery of upper extremity function in chronic stroke.</p><p><strong>Trial registration: </strong>http://www.clinicaltrials.gov . Actual study start date September 2012. First registered on 15 November 2012. Retrospectively registered. Unique identifiers: NCT01726673 and NCT03562663 .</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"20"},"PeriodicalIF":0.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39858130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Injectable wireless microdevices: challenges and opportunities.","authors":"Adam Khalifa, Sunwoo Lee, Alyosha Christopher Molnar, Sydney Cash","doi":"10.1186/s42234-021-00080-w","DOIUrl":"10.1186/s42234-021-00080-w","url":null,"abstract":"<p><p>In the past three decades, we have witnessed unprecedented progress in wireless implantable medical devices that can monitor physiological parameters and interface with the nervous system. These devices are beginning to transform healthcare. To provide an even more stable, safe, effective, and distributed interface, a new class of implantable devices is being developed; injectable wireless microdevices. Thanks to recent advances in micro/nanofabrication techniques and powering/communication methodologies, some wireless implantable devices are now on the scale of dust (< 0.5 mm), enabling their full injection with minimal insertion damage. Here we review state-of-the-art fully injectable microdevices, discuss their injection techniques, and address the current challenges and opportunities for future developments.</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2021-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8697496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39610115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Electrically-evoked vagus nerve recordings using transmural endoscopy in a swine model.","authors":"","doi":"10.1186/s42234-021-00070-y","DOIUrl":"10.1186/s42234-021-00070-y","url":null,"abstract":"","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"18"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8611881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39652235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework for automated sorting of neural spikes from Neuralynx-acquired tetrode recordings in freely-moving mice.","authors":"Joshua J Strohl, Joseph T Gallagher, Pedro N Gómez, Joshua M Glynn, Patricio T Huerta","doi":"10.1186/s42234-021-00079-3","DOIUrl":"10.1186/s42234-021-00079-3","url":null,"abstract":"<p><strong>Background: </strong>Extracellular recording represents a crucial electrophysiological technique in neuroscience for studying the activity of single neurons and neuronal populations. The electrodes capture voltage traces that, with the help of analytical tools, reveal action potentials ('spikes') as well as local field potentials. The process of spike sorting is used for the extraction of action potentials generated by individual neurons. Until recently, spike sorting was performed with manual techniques, which are laborious and unreliable due to inherent operator bias. As neuroscientists add multiple electrodes to their probes, the high-density devices can record hundreds to thousands of neurons simultaneously, making the manual spike sorting process increasingly difficult. The advent of automated spike sorting software has offered a compelling solution to this issue and, in this study, we present a simple-to-execute framework for running an automated spike sorter.</p><p><strong>Methods: </strong>Tetrode recordings of freely-moving mice are obtained from the CA1 region of the hippocampus as they navigate a linear track. Tetrode recordings are also acquired from the prelimbic cortex, a region of the medial prefrontal cortex, while the mice are tested in a T maze. All animals are implanted with custom-designed, 3D-printed microdrives that carry 16 electrodes, which are bundled in a 4-tetrode geometry.</p><p><strong>Results: </strong>We provide an overview of a framework for analyzing single-unit data in which we have concatenated the acquisition system (Cheetah, Neuralynx) with analytical software (MATLAB) and an automated spike sorting pipeline (MountainSort). We give precise instructions on how to implement the different steps of the framework, as well as explanations of our design logic. We validate this framework by comparing manually-sorted spikes against automatically-sorted spikes, using neural recordings of the hippocampus and prelimbic cortex in freely-moving mice.</p><p><strong>Conclusions: </strong>We have efficiently integrated the MountainSort spike sorter with Neuralynx-acquired neural recordings. Our framework is easy to implement and provides a high-throughput solution. We predict that within the broad field of bioelectronic medicine, those teams that incorporate high-density neural recording devices to their armamentarium might find our framework quite valuable as they expand their analytical footprint.</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"17"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8609830/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39759922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motor improvements enabled by spinal cord stimulation combined with physical training after spinal cord injury: review of experimental evidence in animals and humans.","authors":"Ismael Seáñez,&nbsp;Marco Capogrosso","doi":"10.1186/s42234-021-00077-5","DOIUrl":"https://doi.org/10.1186/s42234-021-00077-5","url":null,"abstract":"<p><p>Electrical spinal cord stimulation (SCS) has been gaining momentum as a potential therapy for motor paralysis in consequence of spinal cord injury (SCI). Specifically, recent studies combining SCS with activity-based training have reported unprecedented improvements in motor function in people with chronic SCI that persist even without stimulation. In this work, we first provide an overview of the critical scientific advancements that have led to the current uses of SCS in neurorehabilitation: e.g. the understanding that SCS activates dormant spinal circuits below the lesion by recruiting large-to-medium diameter sensory afferents within the posterior roots. We discuss how this led to the standardization of implant position which resulted in consistent observations by independent clinical studies that SCS in combination with physical training promotes improvements in motor performance and neurorecovery. While all reported participants were able to move previously paralyzed limbs from day 1, recovery of more complex motor functions was gradual, and the timeframe for first observations was proportional to the task complexity. Interestingly, individuals with SCI classified as AIS B and C regained motor function in paralyzed joints even without stimulation, but not individuals with motor and sensory complete SCI (AIS A). Experiments in animal models of SCI investigating the potential mechanisms underpinning this neurorecovery suggest a synaptic reorganization of cortico-reticulo-spinal circuits that correlate with improvements in voluntary motor control. Future experiments in humans and animal models of paralysis will be critical to understand the potential and limits for functional improvements in people with different types, levels, timeframes, and severities of SCI.</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"16"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8555080/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39563782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using multielectrode arrays to investigate neurodegenerative effects of the amyloid-beta peptide.","authors":"Steven Schulte, Manuela Gries, Anne Christmann, Karl-Herbert Schäfer","doi":"10.1186/s42234-021-00078-4","DOIUrl":"10.1186/s42234-021-00078-4","url":null,"abstract":"<p><strong>Background: </strong>Multielectrode arrays are widely used to analyze the effects of potentially toxic compounds, as well as to evaluate neuroprotective agents upon the activity of neural networks in short- and long-term cultures. Multielectrode arrays provide a way of non-destructive analysis of spontaneous and evoked neuronal activity, allowing to model neurodegenerative diseases in vitro. Here, we provide an overview on how these devices are currently used in research on the amyloid-β peptide and its role in Alzheimer's disease, the most common neurodegenerative disorder.</p><p><strong>Main body: </strong>Most of the studies analysed here indicate fast responses of neuronal cultures towards aggregated forms of amyloid-β, leading to increases of spike frequency and impairments of long-term potentiation. This in turn suggests that this peptide might play a crucial role in causing the typical neuronal dysfunction observed in patients with Alzheimer's disease.</p><p><strong>Conclusions: </strong>Although the number of studies using multielectrode arrays to examine the effect of the amyloid-β peptide onto neural cultures or whole compartments is currently limited, they still show how this technique can be used to not only investigate the interneuronal communication in neural networks, but also making it possible to examine the effects onto synaptic currents. This makes multielectrode arrays a powerful tool in future research on neurodegenerative diseases.</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"15"},"PeriodicalIF":0.0,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554832/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39838119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Historical perspectives, challenges, and future directions of implantable brain-computer interfaces for sensorimotor applications.","authors":"Santosh Chandrasekaran, Matthew Fifer, Stephan Bickel, Luke Osborn, Jose Herrero, Breanne Christie, Junqian Xu, Rory K J Murphy, Sandeep Singh, Matthew F Glasser, Jennifer L Collinger, Robert Gaunt, Ashesh D Mehta, Andrew Schwartz, Chad E Bouton","doi":"10.1186/s42234-021-00076-6","DOIUrl":"10.1186/s42234-021-00076-6","url":null,"abstract":"<p><p>Almost 100 years ago experiments involving electrically stimulating and recording from the brain and the body launched new discoveries and debates on how electricity, movement, and thoughts are related. Decades later the development of brain-computer interface technology began, which now targets a wide range of applications. Potential uses include augmentative communication for locked-in patients and restoring sensorimotor function in those who are battling disease or have suffered traumatic injury. Technical and surgical challenges still surround the development of brain-computer technology, however, before it can be widely deployed. In this review we explore these challenges, historical perspectives, and the remarkable achievements of clinical study participants who have bravely forged new paths for future beneficiaries.</p>","PeriodicalId":72363,"journal":{"name":"Bioelectronic medicine","volume":" ","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8456563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39437486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}