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Background: In bi-hormonal closed-loop systems for treatment of diabetes, glucagon sometimes fails to prevent hypoglycemia. We evaluated glucagon responses during several closed-loop studies to determine factors, such as gain factors, responsible for glucagon success and failure. Methods: We extracted data from four closed-loop studies, examining blood glucose excursions over the 50 min after each glucagon dose and defining hypoglycemic failure as glucose values < 60 mg/dl. Secondly, we evaluated hyperglycemic excursions within the same period, where glucose was > 180 mg/dl. We evaluated several factors for association with rates of hypoglycemic failure or hyperglycemic excursion. These factors included age, weight, HbA1c, duration of diabetes, gender, automation of glucagon delivery, glucagon dose, proportional and derivative errors (PE and DE), insulin on board (IOB), night vs. day delivery, and point sensor accuracy. Results: We analyzed a total of 251 glucagon deliveries during 59 closed-loop experiments performed on 48 subjects. Glucagon successfully maintained glucose within target (60-180 mg/dl) in 195 (78%) of instances with 40 (16%) hypoglycemic failures and 16 (6%) hyperglycemic excursions. A multivariate logistic regression model identified PE (p < 0.001), DE (p < 0.001), and IOB (p < 0.001) as significant determinants of success in terms of avoiding hypoglycemia. Using a model of glucagon absorption and action, simulations suggested that the success rate for glucagon would be improved by giving an additional 0.8 μg/kg. Conclusion: We conclude that glucagon fails to prevent hypoglycemia when it is given at a low glucose threshold and when glucose is falling steeply. We also confirm that high IOB significantly increases the risk for glucagon failures. Tuning of glucagon subsystem parameters may help reduce this risk. [ABSTRACT FROM AUTHOR]

Competing Interests: We declare no competing interests.

Background: Exercise can rapidly drop glucose in people with type 1 diabetes. Ubiquitous wearable fitness sensors are not integrated into automated insulin delivery (AID) systems. We hypothesised that an AID can automate insulin adjustments using real-time wearable fitness data to reduce hypoglycaemia during exercise and free-living conditions compared with an AID not automating use of fitness data., Methods: Our study population comprised of individuals (aged 21-50 years) with type 1 diabetes from from the Harold Schnitzer Diabetes Health Center clinic at Oregon Health and Science University, OR, USA, who were enrolled into a 76 h single-centre, two-arm randomised (4-block randomisation), non-blinded crossover study to use (1) an AID that detects exercise, prompts the user, and shuts off insulin during exercise using an exercise-aware adaptive proportional derivative (exAPD) algorithm or (2) an AID that automates insulin adjustments using fitness data in real-time through an exercise-aware model predictive control (exMPC) algorithm. Both algorithms ran on iPancreas comprising commercial glucose sensors, insulin pumps, and smartwatches. Participants executed 1 week run-in on usual therapy followed by exAPD or exMPC for one 12 h primary in-clinic session involving meals, exercise, and activities of daily living, and 2 free-living out-patient days. Primary outcome was time below range (<3·9 mmol/L) during the primary in-clinic session. Secondary outcome measures included mean glucose and time in range (3·9-10 mmol/L). This trial is registered with ClinicalTrials.gov, NCT04771403., Findings: Between April 13, 2021, and Oct 3, 2022, 27 participants (18 females) were enrolled into the study. There was no significant difference between exMPC (n=24) versus exAPD (n=22) in time below range (mean [SD] 1·3% [2·9] vs 2·5% [7·0]) or time in range (63·2% [23·9] vs 59·4% [23·1]) during the primary in-clinic session. In the 2 h period after start of in-clinic exercise, exMPC had significantly lower mean glucose (7·3 [1·6] vs 8·0 [1·7] mmol/L, p=0·023) and comparable time below range (1·4% [4·2] vs 4·9% [14·4]). Across the 76 h study, both algorithms achieved clinical time in range targets (71·2% [16] and 75·5% [11]) and time below range (1·0% [1·2] and 1·3% [2·2]), significantly lower than run-in period (2·4% [2·4], p=0·0004 vs exMPC; p=0·012 vs exAPD). No adverse events occurred., Interpretation: AIDs can integrate exercise data from smartwatches to inform insulin dosing and limit hypoglycaemia while improving glucose outcomes. Future AID systems that integrate exercise metrics from wearable fitness sensors may help people living with type 1 diabetes exercise safely by limiting hypoglycaemia., Funding: JDRF Foundation and the Leona M and Harry B Helmsley Charitable Trust, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases., Competing Interests: Declaration of interests PGJ and JRC have a financial interest in Pacific Diabetes Technologies, a company that might have a commercial interest in the results of this research and technology. JRC also reports advisory board participation for Zealand Pharma, Novo Nordisk, Insulet, and AstraZeneca. PGJ reports advisory board participation for Eli Lilly. PGJ and JRC have received research funding at their institution from Dexcom. All other authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Exercise can cause dangerous fluctuations in blood glucose in people living with type 1 diabetes (T1D). Aerobic exercise, for example, can cause acute hypoglycemia secondary to increased insulin-mediated and noninsulin-mediated glucose utilization. Less is known about how resistance exercise (RE) impacts glucose dynamics. Twenty-five people with T1D underwent three sessions of either moderate or high-intensity RE at three insulin infusion rates during a glucose tracer clamp. We calculated time-varying rates of endogenous glucose production (EGP) and glucose disposal (R d ) across all sessions and used linear regression and extrapolation to estimate insulin- and noninsulin-mediated components of glucose utilization. Blood glucose did not change on average during exercise. The area under the curve (AUC) for EGP increased by 1.04 mM during RE (95% CI: 0.65-1.43, P < 0.001) and decreased proportionally to insulin infusion rate (0.003 mM per percent above basal rate, 95% CI: 0.001-0.006, P = 0.003). The AUC for R d rose by 1.26 mM during RE (95% CI: 0.41-2.10, P = 0.004) and increased proportionally with insulin infusion rate (0.04 mM per percent above basal rate, CI: 0.03-0.04, P < 0.001). No differences were observed between the moderate and high resistance groups. Noninsulin-mediated glucose utilization rose significantly during exercise before returning to baseline roughly 30-min postexercise. Insulin-mediated glucose utilization remained unchanged during exercise sessions. Circulating catecholamines and lactate rose during exercise despite relatively small changes observed in R d . Results provide an explanation of why RE may pose a lower overall risk for hypoglycemia. NEW & NOTEWORTHY Aerobic exercise is known to cause decreases in blood glucose secondary to increased glucose utilization in people living with type 1 diabetes (T1D). However, less is known about how resistance-type exercise impacts glucose dynamics. Twenty-five participants with T1D performed in-clinic weight-bearing exercises under a glucose clamp. Mathematical modeling of infused glucose tracer allowed for quantification of the rate of hepatic glucose production as well as rates of insulin-mediated and noninsulin-mediated glucose uptake experienced during resistance exercise.

We present a robust insulin delivery system that includes automated meal detection and carbohydrate content estimation using machine learning for meal insulin dosing called robust artificial pancreas (RAP). We conducted a randomized, single-center crossover trial to compare postprandial glucose control in the four hours following unannounced meals using a hybrid model predictive control (MPC) algorithm and the RAP system. The RAP system includes a neural network model to automatically detect meals and deliver a recommended meal insulin dose. The meal detection algorithm has a sensitivity of 83.3%, false discovery rate of 16.6%, and mean detection time of 25.9 minutes. While there is no significant difference in incremental area under the curve of glucose, RAP significantly reduces time above range (glucose >180 mg/dL) by 10.8% (P = 0.04) and trends toward increasing time in range (70-180 mg/dL) by 9.1% compared with MPC. Time below range (glucose <70 mg/dL) is not significantly different between RAP and MPC., (© 2023. The Author(s).)

To reach the millions of people with tuberculosis (TB) undiagnosed each year, there is an important need to provide people-centered screening and testing services. Despite people-centered care being a key pillar of the WHO END-TB Strategy, there have been few attempts to formally characterize and integrate the preferences of people most affected by TB - including those who have increased exposure to TB, limited access to services, and/or are at increased risk for TB - into new tools and strategies to improve screening and diagnosis. This perspective emphasizes the importance of preference research among people most affected by TB, provides an overview of qualitative preference exploration and quantitative preference elicitation research methods, and outlines how preferences can be applied to improve the acceptability, accessibility, and appropriateness of TB screening and testing services via four key opportunities. These include the following: (1) Defining the most preferred features of novel screening, triage, and diagnostic tools, (2) exploring and prioritizing setting-specific barriers and facilitators to screening and testing, (3) understanding what features of community- and facility-based strategies for improving TB detection and treatment are most valued, and (4) identifying the most relevant and resonant communication strategies to increase individual- and community-level awareness and demand. Preference research studies and translation of their findings into policy/guidance and operationalization have enormous potential to close the existing gaps in detection in high burden settings by enhancing the people-centeredness and reach of screening and diagnostic services to people most affected by TB who are currently being missed and left behind., Competing Interests: Competing interests The authors declare no competing interests.

Background: The GeneXpert diagnostic platform from the US based company Cepheid is an automated molecular diagnostic device that performs sample preparation and pathogen detection within a single cartridge-based assay. GeneXpert devices can enable diagnosis at the district level without the need for fully equipped clinical laboratories, are simple to use, and offer rapid results. Due to these characteristics, the platform is now widely used in low- and middle-income countries for diagnosis of diseases such as TB and HIV. Assays for SARS-CoV-2 are also being rolled out. We aimed to quantify public sector investments in the development of the GeneXpert platform and Cepheid's suite of cartridge-based assays., Methods: Public funding data were collected from the proprietor company's financial filings, grant databases, review of historical literature concerning key laboratories and researchers, and contacting key public sector entities involved in the technology's development. The value of research and development (R&D) tax credits was estimated based on financial filings., Results: Total public investments in the development of the GeneXpert technology were estimated to be $252 million, including >$11 million in funding for work in public laboratories leading to the first commercial product, $56 million in grants from the National Institutes of Health, $73 million from other U.S. government departments, $67 million in R&D tax credits, $38 million in funding from non-profit and philanthropic organizations, and $9.6 million in small business 'springboard' grants., Conclusion: The public sector has invested over $250 million in the development of both the underlying technologies and the GeneXpert diagnostic platform and assays, and has made additional investments in rolling out the technology in countries with high burdens of TB. The key role played by the public sector in R&D and roll-out stands in contrast to the lack of public sector ability to secure affordable pricing and maintenance agreements., Competing Interests: DG received a research grant for this analysis from Treatment Action Group as an independent researcher. The funder (Treatment Action Group) provided support in the form of salaries for authors DB, LM, SM, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. This does not alter our adherence to PLOS ONE policies on sharing data and materials. SD is an employee of Médecins Sans Frontières. Treatment Action Group and Médecins Sans Frontières have long advocated for lowering the price of GeneXpert tests in low- and middle income countries. The authors declare no other competing interests.

Aerobic exercise in type 1 diabetes (T1D) causes rapid increase in glucose utilization due to muscle work during exercise, followed by increased insulin sensitivity after exercise. Better understanding of these changes is necessary for models of exercise in T1D. Twenty-six individuals with T1D underwent three sessions at three insulin rates (100%, 150%, 300% of basal). After 3-h run-in, participants performed 45 min aerobic exercise (moderate or intense). We determined area under the curve for endogenous glucose production (AUC EGP ) and rate of glucose disappearance (AUC Rd ) over 45 min from exercise start. A novel application of linear regression of R d across the three insulin sessions allowed separation of insulin-mediated from non-insulin-mediated glucose uptake before, during, and after exercise. AUC Rd increased 12.45 mmol/L (CI = 10.33-14.58, P < 0.001) and 13.13 mmol/L (CI = 11.01-15.26, P < 0.001) whereas AUC EGP increased 1.66 mmol/L (CI = 1.01-2.31, P < 0.001) and 3.46 mmol/L (CI = 2.81-4.11, P < 0.001) above baseline during moderate and intense exercise, respectively. AUC EGP increased during intense exercise by 2.14 mmol/L (CI = 0.91-3.37, P < 0.001) compared with moderate exercise. There was significant effect of insulin infusion rate on AUC Rd equal to 0.06 mmol/L per % above basal rate (CI = 0.05-0.07, P < 0.001). Insulin-mediated glucose uptake rose during exercise and persisted hours afterward, whereas non-insulin-mediated effect was limited to the exercise period. To our knowledge, this method of isolating dynamic insulin- and non-insulin-mediated uptake has not been previously employed during exercise. These results will be useful in informing glucoregulatory models of T1D. The study has been registered at www.clinicaltrials.gov as NCT03090451. NEW & NOTEWORTHY Separating insulin and non-insulin glucose uptake dynamically during exercise in type 1 diabetes has not been done before. We use a multistep process, including a previously described linear regression method, over three insulin infusion sessions, to perform this separation and can graph these components before, during, and after exercise for the first time.

Objective: To assess the efficacy and feasibility of a dual-hormone (DH) closed-loop system with insulin and a novel liquid stable glucagon formulation compared with an insulin-only closed-loop system and a predictive low glucose suspend (PLGS) system., Research Design and Methods: In a 76-h, randomized, crossover, outpatient study, 23 participants with type 1 diabetes used three modes of the Oregon Artificial Pancreas system: 1 ) dual-hormone (DH) closed-loop control, 2 ) insulin-only single-hormone (SH) closed-loop control, and 3 ) PLGS system. The primary end point was percentage time in hypoglycemia (<70 mg/dL) from the start of in-clinic aerobic exercise (45 min at 60% VO 2max ) to 4 h after., Results: DH reduced hypoglycemia compared with SH during and after exercise (DH 0.0% [interquartile range 0.0-4.2], SH 8.3% [0.0-12.5], P = 0.025). There was an increased time in hyperglycemia (>180 mg/dL) during and after exercise for DH versus SH (20.8% DH vs. 6.3% SH, P = 0.038). Mean glucose during the entire study duration was DH, 159.2; SH, 151.6; and PLGS, 163.6 mg/dL. Across the entire study duration, DH resulted in 7.5% more time in target range (70-180 mg/dL) compared with the PLGS system (71.0% vs. 63.4%, P = 0.044). For the entire study duration, DH had 28.2% time in hyperglycemia vs. 25.1% for SH ( P = 0.044) and 34.7% for PLGS ( P = 0.140). Four participants experienced nausea related to glucagon, leading three to withdraw from the study., Conclusions: The glucagon formulation demonstrated feasibility in a closed-loop system. The DH system reduced hypoglycemia during and after exercise, with some increase in hyperglycemia., (© 2020 by the American Diabetes Association.)

Automated insulin delivery systems for people with type 1 diabetes rely on an accurate subcutaneous glucose sensor and an infusion cannula that delivers insulin in response to measured glucose. Integrating the sensor with the infusion cannula would provide substantial benefit by reducing the number of devices inserted into subcutaneous tissue. We describe the sensor chemistry and a calibration algorithm to minimize impact of insulin delivery artifacts in a new glucose sensing cannula. Seven people with type 1 diabetes undergoing automated insulin delivery used two sensing cannulae whereby one delivered a rapidly-acting insulin analog and the other delivered a control phosphate buffered saline (PBS) solution with no insulin. While there was a small artifact in both conditions that increased for larger volumes, there was no difference between the artifacts in the sensing cannula delivering insulin compared with the sensing cannula delivering PBS as determined by integrating the area-under-the-curve of the sensor values following delivery of larger amounts of fluid (P = 0.7). The time for the sensor to recover from the artifact was found to be longer for larger fluid amounts compared with smaller fluid amounts (10.3 ± 8.5 min vs. 41.2 ± 78.3 s, P < 0.05). Using a smart-sampling Kalman filtering smoothing algorithm improved sensor accuracy. When using an all-point calibration on all sensors, the smart-sampling Kalman filter reduced the mean absolute relative difference from 10.9% to 9.5% and resulted in 96.7% of the data points falling within the A and B regions of the Clarke error grid. Despite a small artifact, which is likely due to dilution by fluid delivery, it is possible to continuously measure glucose in a cannula that simultaneously delivers insulin., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: Since 2015, the World Health Organization (WHO) has recommended a commercially available lateral-flow urine LAM test (Alere-LAM) to assist in the diagnosis of tuberculosis (TB) in severely ill people living with HIV (PLHIV). The test can rapidly detect TB in severely ill PLHIV and can identify PLHIV most at-risk of death, leading to mortality reductions. However, its uptake in countries with high burdens of TB and HIV has been slow. To assess the current use landscape and identify barriers to the adoption of Alere-LAM, we conducted a questionnaire-based study in 31 high TB and HIV/AIDS burden countries. Methods : Between November 2018 and December 2019, we collected responses to a semi-structured questionnaire that had been emailed to staff and affiliates of National TB Programs or HIV/AIDS Programs, Ministries of Health, and TB or HIV institutes of 31 high TB/HIV burden countries. Questions concerned country policies, adoption, and current use of Alere-LAM testing, as well as testing algorithms and barriers preventing Alere-LAM uptake. Results: We received questionnaire responses from 24 out of 31 (77%) high TB/HIV burden countries. Of these 24 countries, 11 (46%) had adopted Alere-LAM policies, with only five (21%) countries currently using Alere-LAM testing. Testing algorithms were generally aligned with WHO recommendations. Fifteen countries (63%) said they were planning to implement Alere-LAM testing in the near future. The most commonly cited constraint to adoption and implementation was budget limitations. Additional barriers to Alere-LAM implementation included lack of country-specific data and piloting, administrative hurdles such as regulatory agency approval, lack of coordination between National TB and HIV programs, and small perceived patient population. Conclusion: Responses to our questionnaire demonstrate the persistent gap between country-level policy and real-world use of Alere-LAM, as well as specific barriers that must be addressed to scale-up testing in PLHIV., Competing Interests: Competing interests: MR and SS are employed by FIND. FIND is a not-for-profit NGO that collaborates in partnerships to develop, evaluate and implement new diagnostics for LMIC. FIND has product evaluation agreements with several private sector companies that design diagnostics and related products for treatment of tuberculosis and other diseases. These agreements strictly define FIND’s independence and neutrality vis-a-vis the companies whose products get evaluated and describe roles and responsibilities. CMD previously worked at FIND, Geneva. MP previously consulted for the Bill & Melinda Gates Foundation. He serves on the Scientific Advisory Committee of FIND, Geneva. KE is an advisor for Fujifilm which is developing a next generation LAM test. The other authors have no conflicts to disclose., (Copyright: © 2020 Singhroy DN et al.)

Objective: Automated insulin delivery is the new standard for type 1 diabetes, but exercise-related hypoglycemia remains a challenge. Our aim was to determine whether a dual-hormone closed-loop system using wearable sensors to detect exercise and adjust dosing to reduce exercise-related hypoglycemia would outperform other forms of closed-loop and open-loop therapy., Research Design and Methods: Participants underwent four arms in randomized order: dual-hormone, single-hormone, predictive low glucose suspend, and continuation of current care over 4 outpatient days. Each arm included three moderate-intensity aerobic exercise sessions. The two primary outcomes were percentage of time in hypoglycemia (<70 mg/dL) and in a target range (70-180 mg/dL) assessed across the entire study and from the start of the in-clinic exercise until the next meal., Results: The analysis included 20 adults with type 1 diabetes who completed all arms. The mean time (SD) in hypoglycemia was the lowest with dual-hormone during the exercise period: 3.4% (4.5) vs. 8.3% (12.6) single-hormone ( P = 0.009) vs. 7.6% (8.0) predictive low glucose suspend ( P < 0.001) vs. 4.3% (6.8) current care where pre-exercise insulin adjustments were allowed ( P = 0.49). Time in hypoglycemia was also the lowest with dual-hormone during the entire 4-day study: 1.3% (1.0) vs. 2.8% (1.7) single-hormone ( P < 0.001) vs. 2.0% (1.5) predictive low glucose suspend ( P = 0.04) vs. 3.1% (3.2) current care ( P = 0.007). Time in range during the entire study was the highest with single-hormone: 74.3% (8.0) vs. 72.0% (10.8) dual-hormone ( P = 0.44)., Conclusions: The addition of glucagon delivery to a closed-loop system with automated exercise detection reduces hypoglycemia in physically active adults with type 1 diabetes., (© 2018 by the American Diabetes Association.)

The aim of this pilot study was to investigate the effect of exercise on sleep and nocturnal hypoglycaemia in adults with type 1 diabetes (T1D). In a 3-week crossover trial, 10 adults with T1D were randomized to perform aerobic, resistance or no exercise. During each exercise week, participants completed 2 separate 45-minutes exercise sessions at an academic medical center. Participants returned home and wore a continuous glucose monitor and a wrist-based activity monitor to estimate sleep duration. Participants on average lost 70 (±49) minutes of sleep (P = .0015) on nights following aerobic exercise and 27 (±78) minutes (P = .3) following resistance exercise relative to control nights. The odds ratio with confidence intervals of nocturnal hypoglycaemia occurring on nights following aerobic and resistance exercise was 5.4 (1.3, 27.2) and 7.0 (1.7, 37.3), respectively. Aerobic exercise can cause sleep loss in T1D possibly from increased hypoglycaemia., (© 2017 John Wiley & Sons Ltd.)

Background: There is currently no stable liquid form of glucagon commercially available. The aim of this study is to assess the speed of absorption and onset of action of G-Pump™ glucagon at 3 doses as compared to GlucaGen®, all delivered subcutaneously via an OmniPod®., Methods: Nineteen adult subjects with type 1 diabetes participated in this Phase 2, randomized, double-blind, cross-over, pharmacokinetic/pharmacodynamic study. Subjects were given 0.3, 1.2, and 2.0 µg/kg each of G-Pump glucagon and GlucaGen via an OmniPod., Results: G-Pump glucagon effectively increased blood glucose levels in a dose-dependent fashion with a glucose Cmax of 183, 200, and 210 mg/dL at doses of 0.3, 1.2, and 2.0 µg/kg, respectively (P = ns vs GlucaGen). Mean increases in blood glucose from baseline were 29.2, 52.9, and 77.7 mg/dL for G-Pump doses of 0.3, 1.2, and 2.0 µg/kg, respectively. There were no statistically significant differences between treatments in the glucose T50%-early or glucagon T50%-early with one exception. The glucagon T50%-early was greater following G-Pump treatment at the 2.0 μg/kg dose (13.9 ± 4.7 min) compared with GlucaGen treatment at the 2.0 μg/kg dose (11.0 ± 3.1 min, P = .018). There was more pain and erythema at the infusion site with G-Pump as compared to GlucaGen. No serious adverse events were reported, and no unexpected safety issues were observed., Conclusions: G-Pump glucagon is a novel, stable glucagon formulation with similar PK/PD properties as GlucaGen, but was associated with more pain and infusion site reactions as the dose increased, as compared to GlucaGen., Competing Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JRC has a financial interest in Pacific Diabetes Technologies, Inc, a company that may have a commercial interest in the results of this research and technology. This potential conflict of interest has been reviewed and managed by OHSU. BN, PS, MC, and SP are employees of Xeris Pharmaceuticals., (© 2016 Diabetes Technology Society.)

Objective: To evaluate subjects with type 1 diabetes for hepatic glycogen depletion after repeated doses of glucagon, simulating delivery in a bihormonal closed-loop system., Research Design and Methods: Eleven adult subjects with type 1 diabetes participated. Subjects underwent estimation of hepatic glycogen using (13)C MRS. MRS was performed at the following four time points: fasting and after a meal at baseline, and fasting and after a meal after eight doses of subcutaneously administered glucagon at a dose of 2 µg/kg, for a total mean dose of 1,126 µg over 16 h. The primary and secondary end points were, respectively, estimated hepatic glycogen by MRS and incremental area under the glucose curve for a 90-min interval after glucagon administration., Results: In the eight subjects with complete data sets, estimated glycogen stores were similar at baseline and after repeated glucagon doses. In the fasting state, glycogen averaged 21 ± 3 g/L before glucagon administration and 25 ± 4 g/L after glucagon administration (mean ± SEM) (P = NS). In the fed state, glycogen averaged 40 ± 2 g/L before glucagon administration and 34 ± 4 g/L after glucagon administration (P = NS). With the use of an insulin action model, the rise in glucose after the last dose of glucagon was comparable to the rise after the first dose, as measured by the 90-min incremental area under the glucose curve., Conclusions: In adult subjects with well-controlled type 1 diabetes (mean A1C 7.2%), glycogen stores and the hyperglycemic response to glucagon administration are maintained even after receiving multiple doses of glucagon. This finding supports the safety of repeated glucagon delivery in the setting of a bihormonal closed-loop system., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

In this article, we present several important contributions necessary for enabling an artificial endocrine pancreas (AP) system to better respond to exercise events. First, we show how exercise can be automatically detected using body-worn accelerometer and heart rate sensors. During a 22 hour overnight inpatient study, 13 subjects with type 1 diabetes wearing a Zephyr accelerometer and heart rate monitor underwent 45 minutes of mild aerobic treadmill exercise while controlling their glucose levels using sensor-augmented pump therapy. We used the accelerometer and heart rate as inputs into a validated regression model. Using this model, we were able to detect the exercise event with a sensitivity of 97.2% and a specificity of 99.5%. Second, from this same study, we show how patients' glucose declined during the exercise event and we present results from in silico modeling that demonstrate how including an exercise model in the glucoregulatory model improves the estimation of the drop in glucose during exercise. Last, we present an exercise dosing adjustment algorithm and describe parameter tuning and performance using an in silico glucoregulatory model during an exercise event., (© 2015 Diabetes Technology Society.)

Background: Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor with a dismal prognosis. Despite intensive study on tumor biology, the underlying mechanisms of the unlimited proliferation and progressive local invasion are still poorly understood, and no effective treatment has been developed for GBM patients., Aims: We determine the role of TRPM7 channels in the growth, migration, and infiltration of malignant glioma cells., Methods: Using a combination of RT-PCR, Western blot, and patch-clamp techniques, we demonstrated the expression of functional TRPM7 channels of A172 cells, a human glioma cell line, as well as in human glioma tissues. Furthermore, we evaluated the role of TRPM7 in growth, migration, and infiltration of A172 cells with MTT and transwell migration and invasion assays., Results: We showed the expression of functional TRPM7 channels in both A172 cells and human glioma tissues. Suppression of TRPM7 expression with TRPM7-siRNA dramatically reduced the proliferation, migration, and invasion of A172 cells. Pharmacological inhibition of TRPM7 channel with 2-aminoethoxydiphenyl borate (2-APB) showed a similar effect as TRPM7-siRNA., Conclusion: We demonstrate that human glioma cells express functional TRPM7 channel and that activation of this channel plays an important role in the proliferation, migration, and invasion of malignant glioma cells. TRPM7 channel may represent a novel and promising target for therapeutic intervention of malignant glioma., (© 2014 John Wiley & Sons Ltd.)

Automated control of blood glucose in patients with type-1 diabetes has not yet been fully implemented. The aim of this study was to design and clinically evaluate a system that integrates a control algorithm with off-the-shelf subcutaneous sensors and pumps to automate the delivery of the hormones glucagon and insulin in response to continuous glucose sensor measurements. The automated component of the system runs an adaptive proportional derivative control algorithm which determines hormone delivery rates based on the sensed glucose measurements and the meal announcements by the patient. We provide details about the system design and the control algorithm, which incorporates both a fading memory proportional derivative controller (FMPD) and an adaptive system for estimating changing sensitivity to insulin based on a glucoregulatory model of insulin action. For an inpatient study carried out in eight subjects using Dexcom SEVEN PLUS sensors, prestudy HbA1c averaged 7.6, which translates to an estimated average glucose of 171 mg/dL. In contrast, during use of the automated system, after initial stabilization, glucose averaged 145 mg/dL and subjects were kept within the euglycemic range (between 70 and 180 mg/dL) for 73.1% of the time, indicating improved glycemic control. A further study on five additional subjects in which we used a newer and more reliable glucose sensor (Dexcom G4 PLATINUM) and made improvements to the insulin and glucagon pump communication system resulted in elimination of hypoglycemic events. For this G4 study, the system was able to maintain subjects' glucose levels within the near-euglycemic range for 71.6% of the study duration and the mean venous glucose level was 151 mg/dL.

Stroke/brain ischemia is a leading cause of death and long-term disabilities. Increased oxidative stress plays an important role in the pathology of brain ischemia. Hydrogen peroxide (H(2)O(2)) is a major oxidant known to cause neuronal injury; however, the detailed mechanism remains unclear. Previous studies have suggested that H(2)O(2)-induced injury is associated with increased intracellular Ca(2+), mediated by glutamate receptors or voltage-gated Ca(2+) channels. Here, we demonstrate that, at concentrations relevant to stroke, H(2)O(2) induces a Ca(2+)-dependent injury of mouse cortical neurons in the absence of activation of these receptors/channels. With the culture medium containing blockers of glutamate receptors and voltage-gated Ca(2+) channels, brief exposure of neurons to H(2)O(2) induced a dose-dependent injury. Reducing [Ca(2+)](e) inhibited whereas increasing [Ca(2+)](e) potentiated the H(2)O(2) injury. Fluorescent Ca(2+) imaging confirmed the increase of [Ca(2+)](i) by H(2)O(2) in the presence of the blockers of glutamate receptors and voltage-gated Ca(2+) channels. Addition of 2-aminoethoxydiphenyl borate, an inhibitor of transient receptor potential melastatin 7 (TRPM7) channels, or the use of TRPM7-small interference RNA, protected the neurons from H(2)O(2) injury. In contrast, overexpressing TRPM7 channels in human embryonic kidney 293 cells increased H(2)O(2) injury. Our findings indicate that H(2)O(2) can induce Ca(2+) toxicity independent of glutamate receptors and voltage-gated Ca(2+) channels. Activation of TRPM7 channels is involved in such toxicity.

Acidosis is a common feature of the human brain during ischemic stroke and is known to cause neuronal injury. However, the mechanism underlying acidosis-mediated injury of the human brain remains elusive. We show that a decrease in the extracellular pH evoked inward currents characteristic of acid-sensing ion channels (ASICs) and increased intracellular Ca(2+) in cultured human cortical neurons. Acid-sensing ion channels in human cortical neurons show electrophysiological and pharmacological properties distinct from those in neurons of the rodent brain. Reverse transcriptase-PCR and western blot detected a high level of the ASIC1a subunit with little or no expression of other ASIC subunits. Treatment of human cortical neurons with acidic solution induced substantial cell injury, which was attenuated by the ASIC1a blockade. Thus, functional homomeric ASIC1a channels are predominantly expressed in neurons from the human brain. Activation of these channels has an important role in acidosis-mediated injury of human brain neurons.

Acid-sensing ion channels (ASICs) are voltage-independent Na(+) channels activated by extracellular protons. ASIC1a is expressed in neurons in mammalian brain and is implicated in long term potentiation of synaptic transmission that contributes to learning and memory. In ischemic brain injury, however, activation of this Ca(2+)-permeable channel plays a critical role in acidosis-mediated, glutamate-independent, Ca(2+) toxicity. We report here the identification of insulin as a regulator of ASIC1a surface expression. In modeled ischemia using Chinese hamster ovary cells, serum depletion caused a significant increase in ASIC1a surface expression that resulted in the potentiation of ASIC1a activity. Among the components of serum, insulin was identified as the key factor that maintains a low level of ASIC1a on the plasma membrane. Neurons subjected to insulin depletion increased surface expression of ASIC1a with resultant potentiation of ASIC1a currents. Intracellularly, ASIC1a is predominantly localized to the endoplasmic reticulum in Chinese hamster ovary cells, and this intracellular localization is also observed in neurons. Under conditions of serum or insulin depletion, the intracellular ASIC1a is translocated to the cell surface, increasing the surface expression level. These results reveal an important trafficking mechanism of ASIC1a that is relevant to both the normal physiology and the pathological activity of this channel.

Transient receptor potential melastatin 7 (TRPM7) channels are novel Ca(2+)-permeable non-selective cation channels ubiquitously expressed. Activation of TRPM7 channels has been shown to be involved in cellular Mg(2+) homeostasis, diseases caused by abnormal magnesium absorption, and in Ca(2+)-mediated neuronal injury under ischemic conditions. Here we show strong evidence suggesting that TRPM7 channels also play an important role in cellular Zn(2+) homeostasis and in Zn(2+)-mediated neuronal injury. Using a combination of fluorescent Zn(2+) imaging, small interfering RNA, pharmacological analysis, and cell injury assays, we show that activation of TRPM7 channels augmented Zn(2+)-induced injury of cultured mouse cortical neurons. The Zn(2+)-mediated neurotoxicity was inhibited by nonspecific TRPM7 blockers Gd(3+) or 2-aminoethoxydiphenyl borate, and by knockdown of TRPM7 channels with small interfering RNA. In addition, Zn(2+)-mediated neuronal injury under oxygen-glucose deprivation conditions was also diminished by silencing TRPM7. Furthermore, we show that overexpression of TRPM7 channels in HEK293 cells increased intracellular Zn(2+) accumulation and Zn(2+)-induced cell injury, while silencing TRPM7 by small interfering RNA attenuated the Zn(2+)-mediated cell toxicity. Thus, TRPM7 channels may represent a novel target for neurological disorders where Zn(2+) toxicity plays an important role.

Monosodium glutamate (MSG), a common flavor enhancer in various canned food and stereotypically associated with food in Chinese restaurants, has been claimed and tested to have side effects including headache and dizziness. However, the mechanism behind MSG-induced headache was not clear. Using dissociated mouse neuronal culture and cell injury assays, we determined whether incubation of neurons with clinically relevant concentrations of MSG induces cell swelling or death, and whether any measure can be taken to prevent or reduce MSG effects. We demonstrated that (1) Treatment with MSG induces a dose-dependent swelling and death of mature neurons (12-14 days in culture) with little effect on young immature neurons (<1 week in culture). The threshold concentration of MSG for neuronal injury is 3 microM; (2) MSG only injures neurons with little effect on glial cells; (3) Boiling MSG does not affect its toxicity but the addition of Vitamin C provides significant protection against MSG toxicity; (4) Pretreatment of neurons with a low dose of MSG reduces subsequent injury by a large dose of MSG. Together, our studies suggest that the side effect of MSG may be mediated, at least in part, by its toxic effect on brain neurons. Pre-exposure to low doses of MSG or the use of Vitamin C may prevent or reduce the side effects of MSG.