Closed-loop Algorithm Research Articles

Anesthesia Management via an Automated Control System for Propofol, Remifentanil, and Rocuronium Compared to Management by Anesthesiologists: An Investigator-Initiated Study.

We previously developed an automated total intravenous anesthesia control system that uses new closed-loop system algorithms to administer propofol, remifentanil, and rocuronium based on the bispectral index and train-of-four data. We recently improved this automated control system by adding a safety mechanism and using a modified monitoring device. Patients scheduled for elective surgery were randomly assigned to closed-loop feedback control (automatic group) or the manual administration of propofol, remifentanil, and rocuronium (manual group). The proportion of time during which the proper management of three-agent anesthesia was maintained during surgery was determined as the primary endpoint. The proportion of time during which the three components of sedation, analgesia, and muscle relaxation were adequately controlled was 87.21 ± 12.79% in the automatic group, which was non-inferior to the proportion of 65.19 ± 20.16% in the manual group (p < 0.001). Adverse events during the operative or postoperative observation periods were significantly less frequent in the automatic group (54 patients, 90.0%) than in the manual group (60 patients, 100.0%; p = 0.027). Our three-agent automated control system, which features an improved muscle relaxation monitor and safety mechanism added to the basic control algorithms, maintained sedation, analgesia, and muscle relaxation appropriately in a manner non-inferior to anesthesiologists without compromising safety.

Ship longitudinal stabilization control based on CGSA and nonlinear switch modification

To further improve the ship's longitudinal motion stabilization control effect and the energy saving and robustness of the control method, this paper takes the training ship “YuKun” of Dalian Maritime University as the controlled plant. It analyzes the causes of the severe longitudinal motion of “YuKun”. In ship longitudinal pitch reduction control, the unstable controlled plant is transformed into a stable generalized controlled plant by Nyquist shaping, using the introduced mathematical tool of power function and gain adjustment. The controller is designed with a third-order closed-loop gain shaping algorithm (CGSA) and a switch nonlinear modification function. In the verification process, the performance index, Nyquist stability analysis, model perturbation simulation, and comparative.simulation experiments are used to prove that the designed control method has the advantages of stability, robustness, and improvement. The simulation results show that when the model is perturbed, the improved control method has the advantages of more energy saving, stability, and robustness.

927-P: Robustness of MiniMed Advanced Hybrid Closed-Loop (AHCL) Algorithm on a Spectrum of Glycemic Control

Objective: To evaluate effectiveness of MiniMed™ AHCL on outcomes of study participants with different glycemic management challenges. Methods: Adults (N=128, ≥18 years) with T1D from 16 investigational sites, underwent baseline run-in (~2wks) of continuous subcutaneous insulin infusion (CSII), sensor-augmented pump (SAP) or HCL therapy, followed by study period (3 months) with MiniMed™ AHCL. In this exploratory analysis, participants with different baseline glycemic characteristics (mean SG and SD of SG) were identified using Hierarchical Clustering Analysis with Ward’s method and stratified into 5 cohorts. AHCL glycemic outcomes were evaluated and compared to run-in outcomes. Results: After AHCL initiation, overall glycemic control improved regardless of baseline glycemic characteristics (i.e., low-to-high mean SG and SD of SG) (Table). As expected, those from Cluster 5 with highest baseline mean SG and SD of SG improved the most. While those from Cluster 1 with lowest baseline mean SG and SD of SG achieved the highest TIR. Although those from Cluster 2 achieved better glycemic outcomes compared to their baseline, they didn’t outperform those from Cluster 3, possibly due to their higher SD of SG and less aggressive carb ratio. Conclusion: Improved glycemic control was observed with MiniMed™ AHCL regardless of glycemic conditions at baseline. Disclosure J.Shin: Employee; Medtronic. Z.Dai: Employee; Medtronic. F.Niu: None.

105-LB: Safety and Performance of an Advanced Hybrid Closed-Loop (AHCL) Algorithm with Ultra-rapid Lispro (URLi) and Lispro

Tuning a multi-model predictive control AHCL algorithm to the PK/PD properties of URLi may result in improved performance vs Lispro with no increased safety concerns. This was a randomized, double-blind, inpatient, 2-period crossover study in 22 adults with T1D on insulin pumps. Each URLi and Lispro treatment period had a 4-day inpatient visit with insulin doses calculated using the tuned AHCL algorithm. To challenge the algorithm, tests included unannounced exercise, 1 hr delayed bolus, underbolus, and overbolus. Participants (59% male) had mean ±SD age 43.4±13.77 years, T1D duration 25.9±9.61 yrs, and HbA1c 7.6±0.47%. Mean time in range (TIR; 70-180 mg/dL) during the overall inpatient period: URLi 79.4%; Lispro 78.7 % (p=0.80) with a trend towards decreased time &amp;lt;70 mg/dl (1.5 vs 2.4, p=0.08) for URLi. URLi had a significant difference in Level 1 hypoglycemia (30 vs 55 events, p = 0.01) but not Level 2 (4 vs 9 events, p=0.3). TIRs were similar including during meal/challenge periods (Table) with a trend towards greater TIR during the postprandial period and reduced time &amp;lt;70 mg/dl during exercise for URLi. There was greater TIR during overbolus with Lispro. No severe hypoglycemia events occurred. Results suggest reduced hypoglycemia with URLi vs Lispro with comparable glycemic control. The AHCL algorithm showed promising glycemic performance in a supervised setting when used with URLi or Lispro. Disclosure R. Pollom: None. E. Dassau: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. M. Katz: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. L. Nosek: None. H. Coester: None. E. Zijlstra: Other Relationship; Eli Lilly and Company, Speaker's Bureau; Gan &amp; Lee Pharmaceuticals, Novo Nordisk A/S. A. Ghosh: None. A. Haidar: Consultant; Eli Lilly and Company, Other Relationship; Bigfoot Biomedical, Inc., Research Support; Adocia, Dexcom, Inc., Tandem Diabetes Care, Inc. R. Jones: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. J. Leohr: None. S. E. Gleissner: None.

Unannounced Meal Challenges Using an Advanced Hybrid Closed-Loop System.

Background: The advanced hybrid closed-loop (AHCL) algorithm combines automated basal rates and corrections yet requires meal announcement for optimal outcomes. We aimed to compare the performance of the MiniMed™ 780G AHCL algorithm with and without meal announcement. Methods: In a single-arm study involving 14 adults with type 1 diabetes, we evaluated the safety and efficacy of AHCL when meals were not announced. Participants stayed at a supervised environment for 5 days, during which the outcomes of not announcing meals (≤80 g of carbohydrate) were assessed. Next, participants entered a 90-day at-home "unannounced" phase, during which all meals (≤80 g of carbohydrate) were unannounced, followed by a 90-day at-home phase in which all meals were announced. Results: Time in range (TIR 70-180 mg/dL) was lower in the unannounced versus announced periods (67.5% ± 12.5% vs. 77.7% ± 9.5%; P < 0.01, respectively), with more time spent in hyperglycemia range 180-250 mg/dL (22.7% ± 7.7% vs. 15.7% ± 7.2%) and >250 mg/dL (7.9% ± 6.4% vs. 3.6% ± 2.7%), but less time in hypoglycemia range 54-70 mg/dL (1.6% ± 1% vs. 2.8% ± 1.8%) and <54 mg/dL (0.3% ± 0.4% vs. 0.7% ± 0.9%). Not announcing meals containing up to 60 g of carbohydrate did not lead to increase in postprandial extreme dysglycemia >250 mg/dL, and up to 20 g of unannounced carbohydrates did not significantly change the TIR 70-180 mg/dL compared with full announcement. Conclusion: The AHCL system is optimized for use with meal announcement. While not announcing meals of ≤80 g carbohydrates appears to be safe, it results in suboptimal postprandial glycemic control, especially with high-carbohydrate meals. Not announcing small meals (≤20 g carbohydrate) does not deteriorate glycemic control. Clinical Trial Registration number: NCT04479826.

On-Off and Proportional Closed-Loop Adaptive Deep Brain Stimulation Reduces Motor Symptoms in Freely Moving Hemiparkinsonian Rats

ObjectivesClosed-loop adaptive deep brain stimulation (aDBS) continuously adjusts stimulation parameters, with the potential to improve efficacy and reduce side effects of deep brain stimulation (DBS) for Parkinson’s disease (PD). Rodent models can provide an effective platform for testing aDBS algorithms and establishing efficacy before clinical investigation. In this study, we compare two aDBS algorithms, on-off and proportional modulation of DBS amplitude, with conventional DBS in hemiparkinsonian rats. Materials and MethodsDBS of the subthalamic nucleus (STN) was delivered wirelessly in freely moving male and female hemiparkinsonian (N = 7) and sham (N = 3) Wistar rats. On-off and proportional aDBS, based on STN local field potential beta power, were compared with conventional DBS and three control stimulation algorithms. Behavior was assessed during cylinder tests (CT) and stepping tests (ST). Successful model creation was confirmed via apomorphine-induced rotation test and Tyrosine Hydroxylase–immunocytochemistry. Electrode location was histologically confirmed. Data were analyzed using linear mixed models. ResultsContralateral paw use in parkinsonian rats was reduced to 20% and 25% in CT and ST, respectively. Conventional, on-off, and proportional aDBS significantly improved motor function, restoring contralateral paw use to approximately 45% in both tests. No improvement in motor behavior was observed with either randomly applied on-off or low-amplitude continuous stimulation. Relative STN beta power was suppressed during DBS. Relative power in the alpha and gamma bands decreased and increased, respectively. Therapeutically effective adaptive DBS used approximately 40% less energy than did conventional DBS. ConclusionsAdaptive DBS, using both on-off and proportional control schemes, is as effective as conventional DBS in reducing motor symptoms of PD in parkinsonian rats. Both aDBS algorithms yield substantial reductions in stimulation power. These findings support using hemiparkinsonian rats as a viable model for testing aDBS based on beta power and provide a path to investigate more complex closed-loop algorithms in freely behaving animals.

Course keeping control for very large ship using hyperbolic tangent function based on nonlinear decoration technique

To solve the problems of difficult course keeping, high energy output, and large wear of very large ships under different sea conditions, a robust controller combining the closed-loop gain shaping algorithm and nonlinear decoration is proposed in this paper. Firstly, a linear controller is designed by using the third-order closed-loop gain shaping algorithm and takes the hyperbolic tangent function as the nonlinear decoration of the controller output, and the robustness of the system is proved by H∞ robust control theory. Secondly, taking ‘Vale Brasil’, an ore carrier with a displacement of 400,000 tons, as the test plant. The nonlinear Nomoto model and nonlinear Norrbin model were established, which were compared with the control effect from the existing controller. Thirdly, simulation experiments were carried out under normal sea state and heavy sea state to prove the effectiveness. The results indicate that the proposed control strategy can achieve the required course faster, and enhances the smoothness of rudder angle actuation compared with the existing controller. It can maintain good control ability under different sea conditions. The proposed controller has the advantages of simple parameter adjustment, better robustness, less energy consumption, and reduced rudder angle. It is more in line with engineering practice and increases ship operation benefits.

Implementation of Automatic DSP Code Generation Based on Closed-loop Algorithm for Three-level Inverters

Wind energy has the advantages of wide distribution, renewable, and non-polluting, so it is receiving more and more attention from more and more countries. As more and more wind power systems are integrated into the grid, it has an impact on the stability of the grid. To keep the power system stable, there is an urgent need for a grid simulator that can simulate various behaviors of the grid and test the reliability of the wind turbine before grid integration. Inverters, especially multilevel inverters, as the core part of the grid simulator, have been widely studied by scholars in recent years. However, compared to conventional inverters, multilevel inverters are characterized by high code development effort, great difficulty, and a long development period. In this paper, we adopt an automatic DSP code generation method with MATLAB hardware support package and give a complete system design method and development flow based on MATLAB and TMSF28335 automatic code generation. Finally, we take the closed-loop three-level MMC inverter as an example, propose an equalization algorithm suitable for automatic code generation for the capacitor-voltage balancing part, and verify the feasibility of the DSP automatic code generation in a multilevel inverter development. The feasibility of DSP automatic code generation in the development of a multilevel inverter is verified. The experimental results show that the proposed equalization algorithm with variable reference coefficient and DSP automatic code generation method can be used in the development of a multilevel inverter, which can improve development efficiency and reduce development costs.

Glycemic Control by Treatment Modalities: National Registry-Based Population Data in Children and Adolescents with Type 1 Diabetes

Introduction: The aim of the study was to assess the differences in key parameters of type 1 diabetes (T1D) control associated with treatment and monitoring modalities including newly introduced hybrid closed-loop (HCL) algorithm in children and adolescents with T1D (CwD) using the data from the population-wide pediatric diabetes registry ČENDA. Methods: CwD younger than 19 years with T1D duration >1 year were included and divided according to the treatment modality and type of CGM used: multiple daily injection (MDI), insulin pump without (CSII) and with HCL function, intermittently scanned continuous glucose monitoring (isCGM), real-time CGM (rtCGM), and intermittent or no CGM (noCGM). HbA1c, times in glycemic ranges, and glucose risk index (GRI) were compared between the groups. Results: Data of a total of 3,251 children (mean age 13.4 ± 3.8 years) were analyzed. 2,187 (67.3%) were treated with MDI, 1,064 (32.7%) with insulin pump, 585/1,064 (55%) with HCL. The HCL users achieved the highest median TIR 75.4% (IQR 6.3) and lowest GRI 29.1 (7.8), both p < 0.001 compared to other groups, followed by MDI rtCGM and CSII groups with TIR 68.8% (IQR 9.0) and 69.0% (7.5), GRI 38.8 (12.5) and 40.1 (8.5), respectively (nonsignificant to each other). These three groups did not significantly differ in their HbA1c medians (51.8 [IQR 4.5], 50.7 [4.5], and 52.7 [5.7] mmol/mol, respectively). NoCGM groups had the highest HbA1c and GRI and lowest TIR regardless of the treatment modality. Conclusion: This population-based study shows that the HCL technology is superior to other treatment modalities in CGM-derived parameters and should be considered as a treatment of choice in all CwD fulfilling the indication criteria.

The Design of Brainstem Interfaces: Characterisation of Physiological Artefacts and Implications for Closed-loop Algorithms.

Surgical neuromodulation through implantable devices allows for stimulation delivery to subcortical regions, crucial for symptom control in many debilitating neurological conditions. Novel closed-loop algorithms deliver therapy tailor-made to endogenous physiological activity, however rely on precise sensing of signals such as subcortical oscillations. The frequency of such intrinsic activity can vary depending on subcortical target nucleus, while factors such as regional anatomy may also contribute to variability in sensing signals. While artefact parameters have been explored in more 'standard' and commonly used targets (such as the basal ganglia, which are implanted in movement disorders), characterisation in novel candidate nuclei is still under investigation. One such important area is the brainstem, which contains nuclei crucial for arousal and autonomic regulation. The brainstem provides additional implantation targets for treatment indications in disorders of consciousness and sleep, yet poses distinct anatomical challenges compared to central subcortical targets. Here we investigate the region-specific artefacts encountered during activity and rest while streaming data from brainstem implants with a cranially-mounted device in two patients. Such artefacts result from this complex anatomical environment and its interactions with physiological parameters such as head movement and cardiac functions. The implications of the micromotion-induced artefacts, and potential mitigation, are then considered for future closed-loop stimulation methods.

Semantic closed-loop based visual mapping algorithm for automated valet parking

Simultaneous localization and mapping (SLAM) is one of the core technologies to realize automated valet parking (AVP). Currently, advanced visual feature-based SLAM systems suffer from feature extraction failure and tracking loss due to the constraints of textureless scenes, unclear illumination, and dynamic conditions. To address these problems, this paper proposes a visual SLAM algorithm based on a semantic closed-loop detection algorithm using surround-view cameras and inertial measurement units (IMU) as sensors. The algorithm combines semantic features and the idea of inverse index to improve the traditional keyframes selection methods and the closed-loop detection algorithms, effectively avoiding the tedious and complicated feature point matching and improving the computational efficiency of the computer. Experiments show that the algorithm in this paper achieves better results in terms of precision and recall, absolute trajectory error (ATE), and relative pose error (RPE), and can meet the demand for SLAM and subsequent navigation in indoor parking lots.

A Modulation Scheme Based on Virtual Voltage Levels for Capacitor Voltage Balancing of the Four-Level Diode Clamped Converter

This paper proposes a modulation scheme based on the concept of virtual voltage levels for regulating the DC-link capacitor voltages of a four-level diode clamped converter under restricted operating conditions. The proposed virtual-level space vector modulation (VL-SVM) scheme sets the average neutral point currents to zero, which results in no net change in dc-link capacitor voltages and thereby voltage balancing. In addition, a closed-loop algorithm is developed to compensate for any voltage drift due to unideal practical conditions. Consequently, the modulation of the reference voltages results in the desired output voltages while regulating the DC-link capacitor voltages at various operating points. In the proposed modulation scheme, switching frequencies are not significantly increased, and they are lower than those in the classic virtual-vector SVM method. The simulation results demonstrate the effectiveness of the proposed modulation scheme and highlight its main benefits and features. The simulation results are verified through a laboratory-type experimental setup.

Maximizing Glycemic Benefits of Using Faster Insulin Formulations in Type 1 Diabetes: In Silico Analysis Under Open- and Closed-Loop Conditions.

Background: Ultrarapid-acting insulin analogs that could improve or even prevent postprandial hyperglycemia are now available for both research and clinical care. However, clear glycemic benefits remain elusive, especially when combined with automated insulin delivery (AID) systems. In this work, we study two insulin formulations in silico and highlight adjustments of both open-loop and closed-loop insulin delivery therapies as a critical step to achieve clinically meaningful improvements. Methods: Subcutaneous insulin transport models for two faster analogs, Fiasp (Novo Nordisk, Bagsværd, Denmark) and AT247 (Arecor, Saffron Walden, United Kingdom), were identified using data collected from prior clamp experiments, and integrated into the UVA/Padova type 1 diabetes simulator (adult cohort, N = 100). Pump therapy parameters and the aggressiveness of our full closed-loop algorithm were adapted to the new insulin pharmacokinetic and pharmacodynamic profiles through a sequence of in silico studies. Finally, we assessed these analogs' glycemic impact with and without modified therapy parameters in simulated conditions designed to match clinical trial data. Results: Simply switching to faster insulin analogs shows limited improvements in glycemic outcomes. However, when insulin acceleration is accompanied by therapy adaptation, clinical significance is found comparing time-in-range (70-180 mg/dL) with Aspart versus AT247 in open-loop (+5.1%); and Aspart versus Fiasp (+5.4%) or AT247 (+10.6%) in full closed-loop with no clinically significant differences in the exposure to hypoglycemia. Conclusion: In silico results suggest that properly adjusting intensive insulin therapy profiles, or AID tuning, to faster insulin analogs is necessary to obtain clinically significant improvements in glucose control.

A Water Tank Level Control System with Time Lag Using CGSA and Nonlinear Switch Decoration

Tank level control has some unavoidable factors such as disturbance, non-linearity, and time lag. This paper proposes a simple and robust control scheme with nice energy-saving effects and smooth output to improve the quality of the controller and meet real-world application requirements. A linear controller is first designed using a third-order closed-loop gain-shaping algorithm. We then use an arcsine function to modify the system with non-linear switching to reduce the effect of the non-linear modification on the dynamic performance of the control system. Furthermore, we use the Nyquist stability criterion to demonstrate the stability of the closed-loop system in the presence of time lag. The results of the final simulation experiment show that the controller not only has high control quality but also has the characteristics of energy saving and smooth output under the condition of lag and pump performance constraints. These features are necessary for extending the life of the pump and enhancing the applicability of the tank level controller.

SLAC microresonator RF (SMuRF) electronics: A tone-tracking readout system for superconducting microwave resonator arrays.

We describe the newest generation of the SLAC Microresonator RF (SMuRF) electronics, a warm digital control and readout system for microwave-frequency resonator-based cryogenic detector and multiplexer systems, such as microwave superconducting quantum interference device multiplexers (μmux) or microwave kinetic inductance detectors. Ultra-sensitive measurements in particle physics and astronomy increasingly rely on large arrays of cryogenic sensors, which in turn necessitate highly multiplexed readout and accompanying room-temperature electronics. Microwave-frequency resonators are a popular tool for cryogenic multiplexing, with the potential to multiplex thousands of detector channels on one readout line. The SMuRF system provides the capability for reading out up to 3328 channels across a 4-8GHz bandwidth. Notably, the SMuRF system is unique in its implementation of a closed-loop tone-tracking algorithm that minimizes RF power transmitted to the cold amplifier, substantially relaxing system linearity requirements and effective noise from intermodulation products. Here, we present a description of the hardware, firmware, and software systems of the SMuRF electronics, comparing achieved performance with science-driven design requirements. In particular, we focus on the case of large-channel-count, low-bandwidth applications, but the system has been easily reconfigured for high-bandwidth applications. The system described here has been successfully deployed in lab settings and field sites around the world and is baselined for use on upcoming large-scale observatories.

Data-Driven State of Charge Estimation for Power Battery With Improved Extended Kalman Filter

Accurately monitoring battery state of charge (SOC) is essential for battery system safety. However, single and open-loop combination algorithms are mainly used for SOC estimation currently, which may have the problems of low accuracy and poor reliability. Here, a closed-loop combination algorithm with the variance-compensation extended Kalman filter (VCEKF) and back-propagation (BP) neural network is developed for SOC estimation. First, the second-order resistance–capacitance model is established, and the model’s parameters are identified by the forgetting factor recursive least square (FFRLS). Second, the extended Kalman filter (EKF), the variance compensation algorithm, and the BP neural network are merged under a closed-loop structure. Specifically, the variance compensation algorithm updates the process noise covariance of the EKF algorithm in real-time, while the BP neural network simultaneously provides compensation value to obtain the finally estimated SOC. Afterward, the proposed algorithm is testified under different driving schedules. Experimental results show that the accurate SOC estimation under different driving schedules is realized using the proposed algorithm and also illustrate a better performance than the commonly used open-loop algorithm and EKF-based algorithms.

Green energy-saving robust control for ship course-keeping system based on nonlinear switching feedback

To further save energy and reduce carbon emissions, a simple and robust green energy-saving control algorithm was proposed under the premise that the ship achieved an excellent course-keeping effect. To this end, the controller is designed by employing the third-order closed-loop gain shaping algorithm, and the final control law is obtained via the nonlinear switching feedback technique. The robustness of the system is proved by the Nyquist stability criterion. An evaluation model is carefully established for energy-saving and carbon-reduction of the course-keeping controller. The nonlinear Nomoto and Norrbin models for MV “Yukun” are implemented for simulating and further assessing under normal and heavy sea conditions. Compared with the nonlinear decoration controller, the proposed controller enhances the ship's course-keeping accuracy, shortens the delay time and settling time of the controller, lessens the steering angle and steering frequency of the rudder, increases the robustness of the system, and reduces the comprehensive energy-saving index by 26.1% under normal sea conditions. Meanwhile, good controller performance and green energy-saving effects are more in line with the requirements of navigation practice, which is essential for ships to achieve safe, economical, green, and low-carbon navigation.

Evaluating the Impact of Applying Personal Glucose Targets in a Closed-Loop System for People With Type 1 Diabetes.

CamAPS FX is a hybrid closed-loop smartphone app used to manage type one diabetes. The closed-loop algorithm has a default target glucose of 5.8 mmol/L (104.5 mg/dL), but users can select personal glucose targets (adjustable between 4.4 mmol/L and 11.0 mmol/L [79 mg/dL and 198 mg/dL, respectively]). In this post-hoc analysis, we evaluated the impact of personal glucose targets on glycemic control using data from participants in five randomized controlled trials. Personal glucose targets were widely used, with 20.3% of all days in the data set having a target outside the default target bin (5.5-6.0 mmol/L [99-108 mg/dL]). Personal glucose targets >6.5 mmol/L (117 mg/dL) were associated with significantly less time in target range (3.9-10.0 mmol/L [70-180 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: mean difference = -3.2 percentage points [95% CI: -5.3 to -1.2; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: -10.8 percentage points [95% CI: -14.1 to -7.6; P < .001]). Personal targets >6.5 mmol/L (117 mg/dL) were associated with significantly lower time (<3.9 mmol/L [<70 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: -1.85 percentage points [95% CI: -2.37 to -1.34; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: -2.68 percentage points [95% CI: -3.49 to -1.86; P < .001]). Discrete study populations showed differences in glucose control when applying similar personal targets.

Progressive Acceleration of Insulin Exposure Over 7 Days of Infusion Set Wear.

Insulin exposure varies over 3 days of insulin infusion set (IIS) wear making day-to-day insulin dosing challenging for people with diabetes (PWD). Here we report insulin pharmacodynamic (PD) and pharmacokinetic (PK) data extending these observations to 7 days of IIS wear. PWD (A1C ≤8.5%, C-peptide <0.6 nmol/L, ≥6 months pump use) were enrolled in a crossover euglycemic clamp pilot study comparing conventional Teflon angled IISs with an investigational extended-wear IIS. PK/PD data from six participants were obtained for 5 h postbolus. Although PD data were unstable, PK profiles (pooled data from both groups) of insulin lispro (0.15 U/kg bolus) showed statistically significant progressive decreases from days 0 to 7 for tmax (P < 0.001), Cmax (P < 0.05), and mean residence time (P < 0.0001). Area under the insulin concentration curve (AUC0-300) declined by ∼24% from days 0 to 7 (P < 0.05). These results confirm/extend previous observations showing progressive acceleration of insulin exposure over IIS wear time. This may have implications for PWD and designers of closed-loop algorithms, although larger studies are necessary to confirm this. The study was registered in clinicaltrials.gov (NCT04398030).

Phase-adaptive brain stimulation of striatal D1 medium spiny neurons in dopamine-depleted mice

Brain rhythms are strongly linked with behavior, and abnormal rhythms can signify pathophysiology. For instance, the basal ganglia exhibit a wide range of low-frequency oscillations during movement, but pathological “beta” rhythms at ~ 20 Hz have been observed in Parkinson’s disease (PD) and in PD animal models. All brain rhythms have a frequency, which describes how often they oscillate, and a phase, which describes the precise time that peaks and troughs of brain rhythms occur. Although frequency has been extensively studied, the relevance of phase is unknown, in part because it is difficult to causally manipulate the instantaneous phase of ongoing brain rhythms. Here, we developed a phase-adaptive, real-time, closed-loop algorithm to deliver optogenetic stimulation at a specific phase with millisecond latency. We combined this Phase-Adaptive Brain STimulation (PABST) approach with cell-type-specific optogenetic methods to stimulate basal ganglia networks in dopamine-depleted mice that model motor aspects of human PD. We focused on striatal medium spiny neurons expressing D1-type dopamine receptors because these neurons can facilitate movement. We report three main results. First, we found that our approach delivered PABST within system latencies of 13 ms. Second, we report that closed-loop stimulation powerfully influenced the spike-field coherence of local brain rhythms within the dorsal striatum. Finally, we found that both 4 Hz PABST and 20 Hz PABST improved movement speed, but we found differences between phase only with 4 Hz PABST. These data provide causal evidence that phase is relevant for brain stimulation, which will allow for more precise, targeted, and individualized brain stimulation. Our findings are applicable to a broad range of preclinical brain stimulation approaches and could also inform circuit-specific neuromodulation treatments for human brain disease.