Bioelectronic medicine最新文献

The octopus has many features that make it advantageous for revealing principles of motor circuits and control and predicting behavior. Here, an array of carbon electrodes providing single-unit electrophysiology recordings were implanted into the octopus anterior nerve cord. The number of spikes and arm movements in response to stimulation at different locations along the arm were recorded. We observed that the number of spikes occurring within the first 100 ms after stimulation were predictive of the resultant movement response. Machine learning models showed that temporal electrophysiological features could be used to predict whether an arm movement occurred with 88.64% confidence, and if it was a lateral arm movement or a grasping motion with 75.45% confidence. Both supervised and unsupervised methods were applied to gain streaming measurements of octopus arm movements and how their motor circuitry produces rich movement types in real time. For kinematic analysis, deep learning models and unsupervised dimensionality reduction identified a consistent set of features that could be used to distinguish different types of arm movements. The neural circuits and the computational models identified here generated predictions for how to evoke a particular, complex movement in an orchestrated sequence for an individual motor circuit. This study demonstrates how real-time motor behaviors can be predicted and distinguished, contributing to the development of brain-machine interfaces. The ability to accurately model and predict complex movement patterns has broad implications for advancing technologies in robotics, neuroprosthetics, and artificial intelligence, paving the way for more sophisticated and adaptable systems.

The field of bioelectronic medicine has advanced rapidly from rudimentary electrical therapies to cutting-edge closed-loop systems that integrate real-time physiological monitoring with adaptive neuromodulation. Early innovations, such as cardiac pacemakers and deep brain stimulation, paved the way for these sophisticated technologies. This review traces the historical and technological progression of bioelectronic medicine, culminating in the emerging potential of closed-loop devices for multiple disorders of the brain and body. We emphasize both invasive techniques, such as implantable devices for brain, spinal cord and autonomic regulation, while we introduce new prospects for non-invasive neuromodulation, including focused ultrasound and newly developed autonomic neurography enabling precise detection and titration of inflammatory immune responses. The case for closed-loop non-invasive autonomic neuromodulation (incorporating autonomic neurography and splenic focused ultrasound stimulation) is presented through its applications in conditions such as sepsis and chronic inflammation, illustrating its capacity to revolutionize personalized healthcare. Today, invasive or non-invasive closed-loop systems have yet to be developed that dynamically modulate autonomic nervous system function by responding to real-time physiological and molecular signals; it represents a transformative approach to therapeutic interventions and major opportunity by which the bioelectronic field may advance. Knowledge gaps remain and likely contribute to the lack of available closed loop autonomic neuromodulation systems, namely, (1) significant exogenous and endogenous noise that must be filtered out, (2) potential drift in the signal due to temporal change in disease severity and/or therapy induced neuroplasticity, and (3) confounding effects of exogenous therapies (e.g., concurrent medications that dysregulate autonomic nervous system functions). Leveraging continuous feedback and real-time adjustments may overcome many of these barriers, and these next generation systems have the potential to stand at the forefront of precision medicine, offering new avenues for individualized and adaptive treatment.

Background: Current inflammatory bowel disease (IBD) treatments often fail to achieve lasting remission and have adverse effects. Vagus nerve stimulation (VNS) offers a promising therapy due to its anti-inflammatory effects. Its invasive nature, however, has led to the development of non-invasive methods like transcutaneous auricular VNS (taVNS). This study assesses taVNS's impact on acute colitis progression, inflammatory, anti-inflammatory, and apoptosis-related markers.

Methods: Male C57BL/6 mice (11-12 weeks) were used for dextran sulfate sodium (DSS)- and dinitrobenzene sulfonic acid (DNBS)-induced colitis studies. The administration of taVNS or no stimulation (anesthesia without stimulation) for 10 min per mouse began one day before colitis induction and continued daily until sacrifice. Ulcerative colitis (UC)-like colitis was induced by administering 5% DSS in drinking water for 5 days, after which the mice were sacrificed. Crohn's disease (CD)-like colitis was induced through a single intrarectal injection of DNBS/ethanol, with the mice sacrificed after 3 days. Disease activity index (DAI), macroscopic evaluations, and histological damage were assessed. Colon, spleen, and blood samples were analyzed via qRT-PCR and ELISA. One-way or two-way ANOVA with Bonferroni and Šídák tests were applied.

Results: taVNS improved DAI, macroscopic, and histological scores in DSS colitis mice, but only partially mitigated weight loss and DAI in DNBS colitis mice. In DSS colitis, taVNS locally decreased colonic inflammation by downregulating pro-inflammatory markers (IL-1β, TNF-α, Mip1β, MMP 9, MMP 2, and Nos2) at the mRNA level and upregulating anti-inflammatory TGF-β in non-colitic conditions at both mRNA and protein levels and IL-10 mRNA levels in both non-colitic and colitic conditions. Systemically, taVNS decreased splenic TNF-α in non-colitic mice and increased serum levels of TGF-β in colitic mice and splenic levels in non-colitic and colitic mice. Effects were absent in DNBS-induced colitis. Additionally, taVNS decreased pro-apoptotic markers (Bax, Bak1, and caspase 8) in non-colitic and colitic conditions and increased the pro-survival molecule Bad in non-colitic mice.

Conclusions: This study demonstrates that taVNS has model-dependent local and systemic effects, reducing inflammation and apoptosis in UC-like colitis while offering protective benefits in non-colitic conditions. These findings encourage further research into underlying mechanisms and developing adjunct therapies for UC.

Background: Drug-resistant hypertension affects approximately 9-18% of the United States hypertensive population. Recognized as hypertension that is resistant to three or more medications, drug-resistant hypertension can lead to fatal sequelae, such as heart failure, aortic dissection, and other vast systemic disease. The disruption of the homeostatic mechanisms that stabilize blood pressure can be treated procedurally when medication fails. These procedures include carotid body stimulation, renal denervation, sympathectomies, dorsal root ganglia stimulation, and more recently spinal cord stimulation and have all been utilized in the treatment of drug-resistant hypertension.

Methods: To identify the clinical trials of neuromodulation in drug-resistant hypertension, a PubMed search was performed that included all original clinical trials of neuromodulation treating drug-resistant hypertension. The 838 articles found were sorted using Covidence to find 33 unique primary clinical trials. There were no methods used to assess risk of bias as a meta-analysis was not feasible due to heterogeneity.

Results: Renal denervation and carotid body stimulation have both shown promising results with multiple clinical trials, while sympathectomies have mostly been retired due to the irreversible adverse effects caused. Dorsal root ganglion stimulation showed varying success rates. Spinal cord stimulation is a novel treatment of drug-resistant hypertension that shows promising initial results but requires further investigation and prospective studies of the treatment to provide guidelines for future DRH treatment. The limitations of the review are reporting bias and absence of a meta-analysis that compares the treatment modality due to the heterogeneity of reported outcomes.

Conclusion: Innovation in neuromodulation is necessary to provide alternative avenues of treatment in the face of contraindications for standard treatment. Treatment of drug-resistant hypertension is essential to delay dangerous sequelae. This review's objective is to summarize the clinical trials for treatment of drug-resistant hypertension following PRISMA guidelines and suggests future directions in the treatment of drug-resistant hypertension.

The purpose of this study was to investigate the effects of different electrical stimulation methods (bilateral electroacupuncture (BEA), unilateral EA (UEA), transcutaneous electrical acustimulation (TEA, stimulation via surface electrodes placed at acupoints), and sacral nerve stimulation (SNS)) on visceral pain in a rodent model of irritable bowel syndrome (IBS). Ten-day-old male and female pups were treated with 0.2 ml of 0.5% acetic acid (AA) solution. Visceral sensitivity was assessed using an electromyogram (EMG) in response to graded colorectal distension. In the first experiment, bilateral EA at ST36 acupoint was performed with different parameters in male rats to determine the best stimulation parameters. In the second experiment, male rats were randomly assigned into the Sham, BEA, UEA, TEA, and SNS groups to determine the best stimulation method. Lastly, the AA-treated female rats were randomly assigned into the BEA and sham groups to investigate a potential treatment difference between the sexes. Two distinct sets of stimulation parameters were used: Set 1 (100 Hz, 0.5 ms pulse width, 0.1 s ON, 0.4 s OFF, 0.4-3.0 mA current) and Set 2 (25 Hz, 0.5 ms pulse width, 2 s ON, 3 s OFF, 0.4-3.0 mA current).Results (1) The parameter set of 100Hz was found to be most effective in reducing visceral pain. (2) Both acute UEA and TEA effectively relieved visceral pain, whereas acute SNS did not exhibit such an effect. (3) Acute BEA improved visceral pain in both male and female rats.Conclusions These findings suggest that transcutaneous ST36 stimulation is as effective as direct ST36 stimulation and unilateral ST36 stimulation is comparable to bilateral stimulation. Development of a novel therapy using unilateral transcutaneous ST36 stimulation is warranted.

The protective effects of time spent outdoors emphasize the major role of daylight in myopia. Based on the pathophysiology of myopia, the impact of blue light stimulation on the signaling cascade, from melanopsin at the blind spot to clinically relevant biomarkers for myopia, was investigated. Parameters and site of light stimulation are mainly defined by the photopigment melanopsin, that is sensitive to blue light with a peak wavelength of 480 nm and localized on the intrinsically photosensitive retinal ganglion cells (ipRGC) whose axons converge to the optic disc, corresponding to the physiological blind spot. Blue light at the blind spot (BluSpot) stimulation provides the opportunity to activate the vast majority of ipRGC and avoids additional involvement of rods and cones which may exert incalculable effects on the signaling cascade.Experimental studies have applied anatomical, histochemical, electrophysiological, imaging, and psychophysical methods to unravel the mode of action of BluSpot stimulation. Results indicate activation of melanopsin, improvement of contrast sensitivity, gain in electrical retinal activity, and increase of choroidal thickness following BluSpot stimulation. Short-term changes of clinically relevant biomarkers lead to the hypothesis that BluSpot stimulation may exert antimyopic effects with long-term application.

Background/objectives: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation intervention that shows promise as a potential treatment for depression. However, the clinical efficacy of tDCS varies, possibly due to individual differences in head anatomy affecting tDCS dosage. While functional changes in brain activity are more commonly reported in major depressive disorder (MDD), some studies suggest that subtle macroscopic structural differences, such as cortical thickness or brain volume reductions, may occur in MDD and could influence tDCS electric field (E-field) distributions. Therefore, accounting for individual anatomical differences may provide a pathway to optimize functional gains in MDD by formulating personalized tDCS dosage.

Methods: To address the dosing variability of tDCS, we examined a subsample of sixteen active-tDCS participants' data from the larger ELECT clinical trial (NCT01894815). With this dataset, individualized neuroimaging-derived computational models of tDCS current were generated for (1) classifying treatment response, (2) elucidating essential stimulation features associated with treatment response, and (3) computing a personalized dose of tDCS to maximize the likelihood of treatment response in MDD.

Results: In the ELECT trial, tDCS was superior to placebo (3.2 points [95% CI, 0.7 to 5.5; P = 0.01]). Our algorithm achieved over 90% overall accuracy in classifying treatment responders from the active-tDCS group (AUC = 0.90, F1 = 0.92, MCC = 0.79). Computed precision doses also achieved an average response likelihood of 99.981% and decreased dosing variability by 91.9%.

Conclusion: These findings support our previously developed precision-dosing method for a new application in psychiatry by optimizing the statistical likelihood of tDCS treatment response in MDD.

Background: Integrating advanced machine-learning (ML) algorithms into clinical practice is challenging and requires interdisciplinary collaboration to develop transparent, interpretable, and ethically sound clinical decision support (CDS) tools. We aimed to design a ML-driven CDS tool to predict opioid overdose risk and gather feedback for its integration into the University of Florida Health (UFHealth) electronic health record (EHR) system.

Methods: We used user-centered design methods to integrate the ML algorithm into the EHR system. The backend and UI design sub-teams collaborated closely, both informed by user feedback sessions. We conducted seven user feedback sessions with five UF Health primary care physicians (PCPs) to explore aspects of CDS tools, including workflow, risk display, and risk mitigation strategies. After customizing the tool based on PCPs' feedback, we held two rounds of one-on-one usability testing sessions with 8 additional PCPs to gather feedback on prototype alerts. These sessions informed iterative UI design and backend processes, including alert frequency and reappearance circumstances.

Results: The backend process development identified needs and requirements from our team, information technology, UFHealth, and PCPs. Thirteen PCPs (male = 62%, White = 85%) participated across 7 user feedback sessions and 8 usability testing sessions. During the user feedback sessions, PCPs (n = 5) identified flaws such as the term "high risk" of overdose potentially leading to unintended consequences (e.g., immediate addiction services referrals), offered suggestions, and expressed trust in the tool. In the first usability testing session, PCPs (n = 4) emphasized the need for natural risk presentation (e.g., 1 in 200) and suggested displaying the alert multiple times yearly for at-risk patients. Another 4 PCPs in the second usability testing session valued the UFHealth-specific alert for managing new or unfamiliar patients, expressed concerns about PCPs' workload when prescribing to high-risk patients, and recommended incorporating the details page into training sessions to enhance usability.

Conclusions: The final backend process for our CDS alert aligns with PCP needs and UFHealth standards. Integrating feedback from PCPs in the early development phase of our ML-driven CDS tool helped identify barriers and facilitators in the CDS integration process. This collaborative approach yielded a refined prototype aimed at minimizing unintended consequences and enhancing usability.