A review of biomarkers in the context of type 1 diabetes: Biological sensing for enhanced glucose control

Harnessing the role of microneedles as sensors: current status and future perspectives

In recent years, microneedles (MNs) have been transformed to serve a wide range of applications in the biomedical field. Their role as sensors in wearable devices has provided an alternative to blood-based monitoring of health and diagnostic methods. Hence, they have become a topic of research interest for several scientists working in the biomedical field. These MNs as sensors offer the continuous monitoring of biomarkers like glucose, nucleic acids, proteins, polysaccharides and electrolyte ions, which can therefore screen for and diagnose disease conditions in humans. The present review focuses on types of MN sensors and their applications. Various clinical trials and bottlenecks of MN R&D are also discussed.

Wearable Aptalyzer Integrates Microneedle and Electrochemical Sensing for In Vivo Monitoring of Glucose and Lactate in Live Animals

Continuous monitoring of clinically relevant biomarkers within the interstitial fluid (ISF) using microneedle (MN)-based assays, has the potential to transform healthcare. This study introduces the Wearable Aptalyzer, an integrated system fabricated by combining biocompatible hydrogel MN arrays for ISF extraction with an electrochemical aptamer-based biosensor for in situ monitoring of blood analytes. The use of aptamers enables continuous monitoring of a wide range of analytes, beyond what is possible with enzymatic monitoring. The Wearable Aptalyzer is used for real-time and multiplexed monitoring of glucose and lactate in ISF. Validation experiments using live mice and rat models of type 1 diabetes demonstrate strong correlation between the measurements collected from the Wearable Aptalyzer in ISF and those obtained from gold-standard techniques for blood glucose and lactate, for each analyte alone and in combination. The Wearable Aptalyzer effectively addresses the limitations inherent in enzymatic detection methods as well as solid MN biosensors and the need for reliable and multiplexed bioanalytical monitoring in vivo.

Wearable Clinic: From Microneedle-Based Sensors to Next-Generation Healthcare Platforms

The rapid development of wearable biosensing calls for next-generation devices that allow continuous, real-time, and painless monitoring of health status along with responsive medical treatment. Microneedles have exhibited great potential for the direct access of dermal interstitial fluid (ISF) in a minimally invasive manner. Recent studies of microneedle-based devices have evolved from conventional off-line detection to multiplexed, wireless, and integrated sensing. In this review, the classification and fabrication techniques of microneedles are first introduced, and then the representative examples of microneedles for transdermal monitoring with different sensing modalities are summarized. State-of-the-art advances in therapeutic and closed-loop systems are presented to formulate guidelines for the development of next-generation microneedle-based healthcare platforms. The potential challenges and prospects are discussed to pave a new avenue toward pragmatic applications in the real world.

Ketone-Based Alert System for Insulin Pump Failures

BACKGROUND

An increasing number of individuals with type 1 diabetes (T1D) manage glycemia with insulin pumps containing short-acting insulin. If insulin delivery is interrupted for even a few hours due to pump or infusion site malfunction, the resulting insulin deficiency can rapidly initiate ketogenesis and diabetic ketoacidosis (DKA).

METHODS

To detect an event of accidental cessation of insulin delivery, we propose the design of ketone-based alert system (K-AS). This system relies on an extended Kalman filter based on plasma 3-beta-hydroxybutyrate (BOHB) measurements to estimate the disturbance acting on the insulin infusion/injection input. The alert system is based on a novel physiological model capable of simulating the ketone body turnover in response to a change in plasma insulin levels. Simulated plasma BOHB levels were compared with plasma BOHB levels available in the literature. We evaluated the performance of the K-AS on 10 in silico subjects using the S2014 UVA/Padova simulator for two different scenarios.

RESULTS

The K-AS achieves an average detection time of 84 and 55.5 minutes in fasting and postprandial conditions, respectively, which compares favorably and improves against a detection time of 193 and 120 minutes, respectively, based on the current guidelines.

CONCLUSIONS

The K-AS leverages the rapid rate of increase of plasma BOHB to achieve short detection time in order to prevent BOHB levels from rising to dangerous levels, without any false-positive alarms. Moreover, the proposed novel insulin-BOHB model will allow us to understand the efficacy of treatment without compromising patient safety.

Insulin detection in diabetes mellitus: challenges and new prospects

Tremendous progress has been made towards achieving tight glycaemic control in individuals with diabetes mellitus through the use of frequent or continuous glucose measurements. However, in patients who require insulin, accurate dosing must consider multiple factors that affect insulin sensitivity and modulate insulin bolus needs. Accordingly, an urgent need exists for frequent and real-time insulin measurements to closely track the dynamic blood concentration of insulin during insulin therapy and guide optimal insulin dosing. Nevertheless, traditional centralized insulin testing cannot offer timely measurements, which are essential to achieving this goal. This Perspective discusses the advances and challenges in moving insulin assays from traditional laboratory-based assays to frequent and continuous measurements in decentralized (point-of-care and home) settings. Technologies that hold promise for insulin testing using disposable test strips, mobile systems and wearable real-time insulin-sensing devices are discussed. We also consider future prospects for continuous insulin monitoring and for fully integrated multisensor-guided closed-loop artificial pancreas systems.

Electrokinetic Active Particles for Motion-Based Biomolecule Detection

Detection of biomolecules is essential for patient diagnosis, disease management, and numerous other applications. Recently, nano- and microparticle-based detection has been explored for improving traditional assays by reducing required sample volumes and assay times as well as enhancing tunability. Among these approaches, active particle-based assays that couple particle motion to biomolecule concentration expand assay accessibility through simplified signal outputs. However, most of these approaches require secondary labeling, which complicates workflows and introduces additional points of error. Here, we show a proof-of-concept for a label-free, motion-based biomolecule detection system using electrokinetic active particles. We prepare induced-charge electrophoretic microsensors (ICEMs) for the capture of two model biomolecules, streptavidin and ovalbumin, and show that the specific capture of the biomolecules leads to direct signal transduction through ICEM speed suppression at concentrations as low as 0.1 nM. This work lays the foundation for a new paradigm of rapid, simple, and label-free biomolecule detection using active particles.

Wearable chemical sensors for biomarker discovery in the omics era

Biomarkers are crucial biological indicators in medical diagnostics and therapy. However, the process of biomarker discovery and validation is hindered by a lack of standardized protocols for analytical studies, storage and sample collection. Wearable chemical sensors provide a real-time, non-invasive alternative to typical laboratory blood analysis, and are an effective tool for exploring novel biomarkers in alternative body fluids, such as sweat, saliva, tears and interstitial fluid. These devices may enable remote at-home personalized health monitoring and substantially reduce the healthcare costs. This Review introduces criteria, strategies and technologies involved in biomarker discovery using wearable chemical sensors. Electrochemical and optical detection techniques are discussed, along with the materials and system-level considerations for wearable chemical sensors. Lastly, this Review describes how the large sets of temporal data collected by wearable sensors, coupled with modern data analysis approaches, would open the door for discovering new biomarkers towards precision medicine.

Resistance Training Improves Beta Cell Glucose Sensing and Survival in Diabetic Models

Resistance training increases insulin secretion and beta cell function in healthy mice. Here, we explored the effects of resistance training on beta cell glucose sensing and survival by using in vitro and in vivo diabetic models. A pancreatic beta cell line (INS-1E), incubated with serum from trained mice, displayed increased insulin secretion, which could be linked with increased expression of glucose transporter 2 (GLUT2) and glucokinase (GCK). When cells were exposed to pro-inflammatory cytokines (in vitro type 1 diabetes), trained serum preserved both insulin secretion and GCK expression, reduced expression of proteins related to apoptotic pathways, and also protected cells from cytokine-induced apoptosis. Using 8-week-old C57BL/6 mice, turned diabetic by multiple low doses of streptozotocin, we observed that resistance training increased muscle mass and fat deposition, reduced fasting and fed glycemia, and improved glucose tolerance. These findings may be explained by the increased fasting and fed insulinemia, along with increased beta cell mass and beta cell number per islet, observed in diabetic-trained mice compared to diabetic sedentary mice. In conclusion, we believe that resistance training stimulates the release of humoral factors which can turn beta cells more resistant to harmful conditions and improve their response to a glucose stimulus.

Meta-Analysis Reveals Both the Promises and the Challenges of Clinical Metabolomics

Clinical metabolomics is a rapidly expanding field focused on identifying molecular biomarkers to aid in the efficient diagnosis and treatment of human diseases. Variations in study design, metabolomics methodologies, and investigator protocols raise serious concerns about the accuracy and reproducibility of these potential biomarkers. The explosive growth of the field has led to the recent availability of numerous replicate clinical studies, which permits an evaluation of the consistency of biomarkers identified across multiple metabolomics projects. Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related death and has the lowest five-year survival rate primarily due to the lack of an early diagnosis and the limited treatment options. Accordingly, PDAC has been a popular target of clinical metabolomics studies. We compiled 24 PDAC metabolomics studies from the scientific literature for a detailed meta-analysis. A consistent identification across these multiple studies allowed for the validation of potential clinical biomarkers of PDAC while also highlighting variations in study protocols that may explain poor reproducibility. Our meta-analysis identified 10 metabolites that may serve as PDAC biomarkers and warrant further investigation. However, 87% of the 655 metabolites identified as potential biomarkers were identified in single studies. Differences in cohort size and demographics, p-value choice, fold-change significance, sample type, handling and storage, data collection, and analysis were all factors that likely contributed to this apparently large false positive rate. Our meta-analysis demonstrated the need for consistent experimental design and normalized practices to accurately leverage clinical metabolomics data for reliable and reproducible biomarker discovery.

A computational framework for discovering digital biomarkers of glycemic control

Digital biomarkers can radically transform the standard of care for chronic conditions that are complex to manage. In this work, we propose a scalable computational framework for discovering digital biomarkers of glycemic control. As a feasibility study, we leveraged over 79,000 days of digital data to define objective features, model the impact of each feature, classify glycemic control, and identify the most impactful digital biomarkers. Our research shows that glycemic control varies by age group, and was worse in the youngest population of subjects between the ages of 2–14. In addition, digital biomarkers like prior-day time above range and prior-day time in range, as well as total daily bolus and total daily basal were most predictive of impending glycemic control. With a combination of the top-ranked digital biomarkers, we achieved an average F1 score of 82.4% and 89.7% for classifying next-day glycemic control across two unique datasets.

Concept of the "Universal Slope": Toward Substantially Shorter Decentralized Insulin Immunoassays

Decentralized sensing of analytes in remote locations is today a reality. However, the number of measurable analytes remains limited, mainly due to the requirement for time-consuming successive standard additions calibration used to address matrix effects and resulting in greatly delayed results, along with more complex and costly operation. This is particularly challenging in commonly used immunoassays of key biomarkers that typically require from 60 to 90 min for quantitation based on two standard additions, hence hindering their implementation for rapid and routine diagnostic applications, such as decentralized point-of-care (POC) insulin testing. In this work we have developed and demonstrated the theoretical framework for establishing a universal slope for direct calibration-free POC insulin immunoassays in serum samples using an electrochemical biosensor (developed originally for extended calibration by standard additions). The universal slope is presented as an averaged slope constant, relying on 68 standard additions-based insulin determinations in human sera. This new quantitative analysis approach offers reliable sample measurement without successive standard additions, leading to a dramatically simplified and faster assay (30 min vs 90 min when using 2 standard additions) and greatly reduced costs, without compromising the analytical performance while significantly reducing the analyses costs. The substantial improvements associated with the new universal slope concept have been demonstrated successfully for calibration-free measurements of serum insulin in 30 samples from individuals with type 1 diabetes using meticulous statistical analysis, supporting the prospects of applying this immunoassay protocol to routine decentralized POC insulin testing.

Microneedle Aptamer-Based Sensors for Continuous, Real-Time Therapeutic Drug Monitoring

The ability to continuously monitor the concentration of specific molecules in the body is a long-sought goal of biomedical research. For this purpose, interstitial fluid (ISF) was proposed as the ideal target biofluid because its composition can rapidly equilibrate with that of systemic blood, allowing the assessment of molecular concentrations that reflect full-body physiology. In the past, continuous monitoring in ISF was enabled by microneedle sensor arrays. Yet, benchmark microneedle sensors can only detect molecules that undergo redox reactions, which limits the ability to sense metabolites, biomarkers, and therapeutics that are not redox-active. To overcome this barrier, here, we expand the scope of these devices by demonstrating the first use of microneedle-supported electrochemical, aptamer-based (E-AB) sensors. This platform achieves molecular recognition based on affinity interactions, vastly expanding the scope of molecules that can be sensed. We report the fabrication of microneedle E-AB sensor arrays and a method to regenerate them for multiple uses. In addition, we demonstrate continuous molecular measurements using these sensors in flow systems in vitro using single and multiplexed microneedle array configurations. Translation of the platform to in vivo measurements is possible as we demonstrate with a first E-AB measurement in the ISF of a rodent. The encouraging results reported in this work should serve as the basis for future translation of microneedle E-AB sensor arrays to biomedical research in preclinical animal models.

Closing the loop for patients with Parkinson disease: where are we?

Although levodopa remains the most efficacious symptomatic therapy for Parkinson disease (PD), management of levodopa treatment during the advanced stages of the disease is extremely challenging. This difficulty is a result of levodopa's short half-life, a progressive narrowing of the therapeutic window, and major inter-patient and intra-patient variations in the dose-response relationship. Therefore, a suitable alternative to repeated oral administration of levodopa is being sought. Recent research efforts have focused on the development of novel levodopa delivery strategies and wearable physical sensors that track symptoms and disease progression. However, the need for methods to monitor the levels of levodopa present in the body in real time has been overlooked. Advances in chemical sensor technology mean that the development of wearable and mobile biosensors for continuous or frequent levodopa measurements is now possible. Such levodopa monitoring could help to deliver personalized and timely medication dosing to alleviate treatment-related fluctuations in the symptoms of PD. Therefore, with the aim of optimizing therapeutic management of PD and improving the quality of life of patients, we share our vision of a future closed-loop autonomous wearable 'sense-and-act' system. This system consists of a network of physical and chemical sensors coupled with a levodopa delivery device and is guided by effective big data fusion algorithms and machine learning methods.

An integrated wearable microneedle array for the continuous monitoring of multiple biomarkers in interstitial fluid

Implementations of wearable microneedle-based arrays of sensors for the monitoring of multiple biomarkers in interstitial fluid have lacked system integration and evidence of robust analytical performance. Here we report the development and testing of a fully integrated wearable array of microneedles for the wireless and continuous real-time sensing of two metabolites (lactate and glucose, or alcohol and glucose) in the interstitial fluid of volunteers performing common daily activities. The device works with a custom smartphone app for data capture and visualization, comprises reusable electronics and a disposable microneedle array, and is optimized for system integration, cost-effective fabrication via advanced micromachining, easier assembly, biocompatibility, pain-free skin penetration and enhanced sensitivity. Single-analyte and dual-analyte measurements correlated well with the corresponding gold-standard measurements in blood or breath. Further validation of the technology in large populations with concurrent validation of sensor readouts through centralized laboratory tests should determine the robustness and utility of real-time simultaneous monitoring of several biomarkers in interstitial fluid.

Current Status and Emerging Options for Automated Insulin Delivery Systems

Combining technologies including rapid insulin analogs, insulin pumps, continuous glucose monitors, and control algorithms has allowed for the creation of automated insulin delivery (AID) systems. These systems have proven to be the most effective technology for optimizing metabolic control and could hold the key to broadly achieving goal-level glycemic control for people with type 1 diabetes. The use of AID has exploded in the past several years with several options available in the United States and even more in Europe. In this article, we review the largest studies involving these AID systems, and then examine future directions for AID with an emphasis on usability.

Extracellular Vesicles in Type 1 Diabetes: A Versatile Tool

Type 1 diabetes is a chronic autoimmune disease affecting nearly 35 million people. This disease develops as T-cells continually attack the β-cells of the islets of Langerhans in the pancreas, which leads to β-cell death, and steadily decreasing secretion of insulin. Lowered levels of insulin minimize the uptake of glucose into cells, thus putting the body in a hyperglycemic state. Despite significant progress in the understanding of the pathophysiology of this disease, there is a need for novel developments in the diagnostics and management of type 1 diabetes. Extracellular vesicles (EVs) are lipid-bound nanoparticles that contain diverse content from their cell of origin and can be used as a biomarker for both the onset of diabetes and transplantation rejection. Furthermore, vesicles can be loaded with therapeutic cargo and delivered in conjunction with a transplant to increase cell survival and long-term outcomes. Crucially, several studies have linked EVs and their cargos to the progression of type 1 diabetes. As a result, gaining a better understanding of EVs would help researchers better comprehend the utility of EVs in regulating and understanding type 1 diabetes. EVs are a composition of biologically active components such as nucleic acids, proteins, metabolites, and lipids that can be transported to particular cells/tissues through the blood system. Through their varied content, EVs can serve as a flexible aid in the diagnosis and management of type 1 diabetes. In this review, we provide an overview of existing knowledge about EVs. We also cover the role of EVs in the pathogenesis, detection, and treatment of type 1 diabetes and the function of EVs in pancreas and islet β-cell transplantation.

Clinical Evaluation of a Novel Insulin Immunosensor

BACKGROUND

The estimation of available active insulin remains a limitation of automated insulin delivery systems. Currently, insulin pumps calculate active insulin using mathematical decay curves, while quantitative measurements of insulin would explicitly provide person-specific PK insulin dynamics to assess remaining active insulin more accurately, permitting more effective glucose control.

METHODS

We performed the first clinical evaluation of an insulin immunosensor chip, providing near real-time measurements of insulin levels. In this study, we sought to determine the accuracy of the novel insulin sensor and assess its therapeutic risk and benefit by presenting a new tool developed to indicate the potential therapeutic consequences arising from inaccurate insulin measurements.

RESULTS

Nine adult participants with type-1 diabetes completed the study. The change from baseline in immunosensor-measured insulin levels was compared with values obtained by standard enzyme-linked immunosorbant assay (ELISA) after preprandial injection of insulin. The point-of-care quantification of insulin levels revealed similar temporal trends as those from the laboratory insulin ELISA. The results showed that 70% of the paired immunosensor-reference values were concordant, which suggests that the patient could take action safely based on insulin concentration obtained by the novel sensor.

CONCLUSIONS

This proposed technology and preliminary feasibility evaluation show encouraging results for near real-time evaluation of insulin levels, with the potential to improve diabetes management. Real-time measurements of insulin provide person-specific insulin dynamics that could be used to make more informed decisions regarding insulin dosing, thus helping to prevent hypoglycemia and improve diabetes outcomes.

Recent advances in flexible and wearable sensors for monitoring chemical molecules

In recent years, real-time health management has received increasing attention, benefiting from the rapid development of flexible and wearable devices. Conventionally, flexible and wearable devices are used for collecting health data such as electrophysiological signals, blood pressure, heart rate, etc. The monitoring of chemical factors has shown growing significance, providing the basis for the screening, diagnosis, and treatment of many diseases. Nowadays, in order to understand the health status of the human body more comprehensively and accurately, researchers in the community have started putting effort into developing wearable devices for monitoring chemical factors. Progressively, more flexible chemical sensors with wearable real-time health-monitoring functionality have been developed thanks to advances relating to wireless communications and flexible electronics. In this review, we describe the variety of chemical molecules and information that can currently be monitored, including pH levels, glucose, lactate, uric acid, ion levels, cytokines, nutrients, and other biomarkers. This review analyzes the pros and cons of the most advanced wearable chemical sensors in terms of wearability. At the end of this review, we discuss the current challenges and development trends relating to flexible and wearable chemical sensors from the aspects of materials, electrode designs, and soft-hard interface connections.

Development of a Novel Insulin Sensor for Clinical Decision-Making

BACKGROUND

Clinical decision support systems that incorporate information from frequent insulin measurements to enhance individualized diabetes management remain an unmet goal. The development of a disposable insulin strip for fast decentralized point-of-care detection replacing the current centralized lab-based methods used in clinical practice would be highly desirable to improve the establishment of individual insulin absorption patterns and algorithm modeling processes.

METHODS

We carried out the development and optimization of a novel decentralized disposable insulin electrochemical sensor focusing on obtaining high analytical and operational performance toward achieving a true point-of-care insulin testing device for clinical on-site application.

RESULTS

Our novel insulin immunosensor demonstrated an attractive performance and efficient user-friendly operation by providing high sensitivity capability to detect endogenous and analog insulin with a limit of detection of 30.2 pM (4.3 µiU/mL), rapid time-to-result, stability toward remote site application, and scalable low-cost fabrication with an estimated cost-of-goods for disposable consumables of below $5, capable of near real-time insulin detection in a microliter (≤10 µL) sample droplet of undiluted serum within 30 minutes.

CONCLUSIONS

The results obtained in the optimization and characterization of our novel insulin sensor illustrate its suitability for its potential application in remote clinical environments for frequent insulin monitoring. Future work will test the insulin sensor in a clinical research setting to assess its efficacy in individuals with type 1 diabetes.

Emergence of microneedles as a potential therapeutics in diabetes mellitus

Diabetes mellitus is a severe condition in which the pancreas produces inadequate insulin or the insulin generated is ineffective for utilisation by the body; as a result, insulin therapy is required for control blood sugar levels in patients having type 1 diabetes and is widely recommended in advanced type 2 diabetes patients with uncontrolled diabetes despite dual oral therapy, while subcutaneous insulin administration using hypodermic injection or pump-mediated infusion is the traditional route of insulin delivery and causes discomfort, needle phobia, reduced adherence, and risk of infection. Therefore, transdermal insulin delivery has been extensively explored as an appealing alternative to subcutaneous approaches for diabetes management which not only is non-invasive and easy, but also avoids first-pass metabolism and prevents gastrointestinal degradation. Microneedles have been commonly investigated in human subjects for transdermal insulin administration because they are minimally invasive and painless. The different types of microneedles developed for the transdermal delivery of anti-diabetic drugs are discussed in this review, including solid, dissolving, hydrogel, coated, and hollow microneedles. Numerous microneedle products have entered the market in recent years. But, before the microneedles can be effectively launched into the market, a significant amount of investigation is required to address the numerous challenges. In conclusion, the use of microneedles in the transdermal system is an area worth investigating because of its significant benefits over the oral route in the delivery of anti-diabetic medications and biosensing of blood sugar levels to assure improved clinical outcomes in diabetes management.

Integrated Wearable Sensors for Sensing Physiological Pressure Signals and β-Hydroxybutyrate in Physiological Fluids

Flexible and wearable sensors have attracted much attention for their applications in health monitoring and the human-machine interaction. The most studied wearable sensors have been demonstrated for sensing a limited range of metabolites such as ions, glucose, uric acid, lactate, etc. Both sweat and urine contain numerous other physiologically relevant metabolites indicative of health and wellness. This work demonstrates the use of the wearable sensor for the detection of β-hydroxybutyrate (HB) in sweat. HB is an important biomarker for diabetic ketoacidosis, a condition caused by the accumulation of ketone bodies in hyperglycemia or metabolic acidosis patients. Herein, we fabricated an integrated sensing system coupling an HB detection chamber with a serpentine electrode for sensing physiological signals such as pulse beat, vocal cord vibration, etc. The real-time HB detection was based on a β-hydroxybutyrate dehydrogenase enzymatic reaction. The stability of the enzyme and the cofactor couple was achieved by cross-linking networks and a redox mediator, thereby achieving high selectivity and low detection limits to HB in urine and sweat. The dual-functional sensor was integrated with a signal processing circuitry for signal transduction, conditioning, processing, wireless transmission, and real-time convenient health monitoring display to a smartphone via home-developed software.

Review of Modern Insulin Pumps and the Perioperative Management of the Type 1 Diabetic Patient for Ambulatory Dental Surgery

The use of continuous insulin pump systems for effective management of glycemic control in the patient with type 1 diabetes mellitus (T1DM) is steadily increasing. Although the types of devices and their respective manufacturers vary, insulin pumps all utilize similar underlying concepts based on the delivery of exogenous insulin to patients with T1DM in manners that more closely approximate the normal biologic function and performance of the pancreas. As insulin pumps becomes more commonplace and their use more widespread, the sedation or anesthesia provider must ensure familiarity with the basic knowledge of pump function and the various perioperative management considerations. This review provides a concise overview of the pathophysiology of T1DM, introduces foundational aspects of common insulin pump systems, and discusses several general recommendations regarding the perioperative management of insulin pumps during dental surgeries.

Continuous Ketone Monitoring: A New Paradigm for Physiologic Monitoring

In this issue of JDST, Alva and colleagues present for the first time, development of a continuous ketone monitor (CKM) tested both in vitro and in humans. Their sensor measured betahydroxybutyrate (BHB) in interstitial fluid (ISF). The sensor was based on wired enzyme electrochemistry technology using BHB dehydrogenase. The sensor required only a single retrospective calibration without a need for further adjustments over 14 days. The device produced a linear response over the 0-8 mM range with good accuracy. This novel CKM could provide a new dimension of useful automatically collected information for managing diabetes. Passively collected ISF ketone information would be useful for predicting and managing ketoacidosis in patients with type 1 diabetes, as well as other states of abnormal ketonemia. Although additional studies of this CKM will be required to assess performance in intended patient populations and prospective factory calibration will be required to support real time measurements, this novel monitor has the potential to greatly improve outcomes for people with diabetes. In the future, a CKM might be integrated with a continuous glucose monitor in the same sensor platform.

Wearable and Mobile Sensors for Personalized Nutrition

While wearable and mobile chemical sensors have experienced tremendous growth over the past decade, their potential for tracking and guiding nutrition has emerged only over the past three years. Currently, guidelines from doctors and dietitians represent the most common approach for maintaining optimal nutrition status. However, such recommendations rely on population averages and do not take into account individual variability in responding to nutrients. Precision nutrition has recently emerged to address the large heterogeneity in individuals' responses to diet, by tailoring nutrition based on the specific requirements of each person. It aims at preventing and managing diseases by formulating personalized dietary interventions to individuals on the basis of their metabolic profile, background, and environmental exposure. Recent advances in digital nutrition technology, including calories-counting mobile apps and wearable motion tracking devices, lack the ability of monitoring nutrition at the molecular level. The realization of effective precision nutrition requires synergy from different sensor modalities in order to make timely reliable predictions and efficient feedback. This work reviews key opportunities and challenges toward the successful realization of effective wearable and mobile nutrition monitoring platforms. Non-invasive wearable and mobile electrochemical sensors, capable of monitoring temporal chemical variations upon the intake of food and supplements, are excellent candidates to bridge the gap between digital and biochemical analyses for a successful personalized nutrition approach. By providing timely (previously unavailable) dietary information, such wearable and mobile sensors offer the guidance necessary for supporting dietary behavior change toward a managed nutritional balance. Coupling of the rapidly emerging wearable chemical sensing devices-generating enormous dynamic analytical data-with efficient data-fusion and data-mining methods that identify patterns and make predictions is expected to revolutionize dietary decision-making toward effective precision nutrition.