Glucose monitoring plays a crucial role in managing diabetes, one of the most prevalent diseases worldwide. The development of fast-responsive, cost-effective, and biocompatible glucose sensors is essential for improving patient care. This study investigates the glucose sensing performance of pristine and Co-doped hematite synthesized via the hydrothermal method and integrated into fiber-optic evanescent wave probes. Structural and optical characterizations confirmed the enhanced properties of the Co-doped hematite. The Co-doped sensor exhibited reasonable sensitivity and a significantly improved limit of detection (LoD) of 3.99 mM compared to 6.12 mM for the pristine hematite. Density functional theory calculations further revealed an increase in glucose adsorption energy from -0.24 eV for the pristine surface to -1.28 eV for the Co-doped surface. Charge density difference and projected density of states analyses showed enhanced charge transfer and orbital delocalization upon doping, consistent with the experimentally observed improvement in LoD. These findings position Co-doped hematite as a promising candidate for noninvasive, nonenzymatic glucose detection and underscore the value of integrating experimental and theoretical approaches in biosensing technologies.

This study introduces a 2-D Photonic Crystal (PhC) biosensor designed, simulated, and evaluated for detecting glucose concentrations in urine by utilizing refractive index variations. The sensor demonstrates exceptional performance, achieving a sensitivity of 20,040.30 nm/RIU for glucose levels ranging from 0-15 mg/dl, a quality factor of 10,424.55, and a detection limit as low as 8 × 10-10, surpassing benchmarks reported in the literature. With compact dimensions of 16.8 × 17.6 µm2 and compatibility with modern fabrication techniques, the proposed design is well suited for integration into portable diagnostic devices. A comprehensive comparative analysis underscores its superior sensitivity, ultra-high quality factor, and compact design, establishing it as a major advancement in glucose detection technology.

Implantable electrodes have been utilized for decades to stimulate, sense, or monitor a broad range of biological processes, with examples ranging from glucose monitoring devices to cochlear implants. While the underlying science related to the application of electrodes is a mature field, preclinical and clinical studies have demonstrated that there are still significant challenges in vivo associated with a lack of control over tissue-material interfacial interactions, especially over longer time frames. Herein we discuss the current challenges and opportunities for implantable electrodes and the associated bioelectronic interfaces across the clinical landscape with a focus on emerging technologies and the obstacles of biofouling, microbial colonization, and the foreign body response. Overcoming these challenges is predicted to open the door for a new generation of implantable medical devices and significant associated clinical impact. STATEMENT OF SIGNIFICANCE: Implantable electrodes have been utilised for decades to stimulate, sense, or monitor a broad range of biological processes, with examples ranging from glucose monitoring devices to cochlear implants. Next-generation bioelectronic implantable medical devices promise an explosion of new applications that have until this point in time been impossible to achieve. However, there are several persistent biological challenges hindering the realisation of these new applications. We present a clinical perspective on how these biological challenges have shaped the device market and clinical trial landscape. Specifically, we present statistical breakdowns of current device applications and discuss biofouling, the foreign body response, and microbial colonisation as the main factors that need to be addressed before a new generation of devices can be explored.

Diabetes and its complications pose a serious threat to human life and health. It has become a public health problem of wide concern worldwide. Currently, diabetes is mainly treated with insulin injection in clinic. However, manual insulin injection still has many shortcomings. In recent years, with the deepening of research, it has been found that an automated insulin delivery system (AID), which combines a continuous glucose monitoring device with an insulin pump, can significantly improve the effectiveness of diabetes treatment and reduce the incidence of complications in patients. This paper firstly introduces the composition of the AID system and its working principle, and then details the development history and current status of the related technologies from the aspects of continuous glucose monitoring technology, insulin pumps and the development of closed-loop control algorithms, etc. Finally, this paper looks forward to the application prospect and future development of AID system in the field of diabetes treatment, providing theoretical reference for further research.

The COVID-19 pandemic has catalyzed the rapid expansion of telemedicine for managing chronic conditions such as type 1 diabetes (T1D) in children and adolescents. This narrative review aims to explore the role of telemedicine in pediatric T1D management by comparing its use before and after the pandemic. We conducted a comprehensive literature review covering studies published between 2000 and 2024, focusing on telemedicine applications in pediatric T1D care. The review includes clinical trials, systematic reviews, and observational studies examining telemedicine's impact on glycemic control, patient satisfaction, and healthcare delivery. Results reveal that telemedicine has enhanced access to care, improved glycated hemoglobin (HbA1c) levels, and reduced diabetic ketoacidosis and hypoglycemic events. Patients and caregivers expressed high satisfaction, especially when using continuous glucose monitoring and insulin pump technologies integrated with telemedicine platforms. However, challenges such as digital literacy gaps, variability in healthcare provider training, and logistical issues like reimbursement policies persist. The pandemic highlighted the potential of telemedicine to supplement traditional in-person care, showing promise in enhancing patient outcomes and reducing healthcare burdens. Further research is needed to optimize telemedicine models for T1D, addressing barriers to implementation and exploring its long-term cost-effectiveness. This review underscores telemedicine's evolving role as a complementary approach in managing pediatric T1D, advocating for the development of standardized care protocols to fully integrate digital health solutions into routine clinical practice.

Polymers have been integral to the advancement of biomedicine, owing to their exceptional versatility and functionality. Among these, polyvinyl alcohol (PVA) and chitosan both natural polymers stand out for their remarkable biocompatibility, biodegradability, and unique properties. This review article provides a comprehensive examination of the diverse applications of PVA and chitosan in three pivotal areas: tissue engineering, drug delivery, and biosensors. In tissue engineering, the discussion centres on how PVA and chitosan are engineered into scaffolds that not only support cell growth and differentiation but also promote tissue regeneration by closely mimicking the extracellular matrix. These scaffolds offer the necessary mechanical strength and adaptability for various biomedical applications. For drug delivery, the article delves into the development of sophisticated controlled release systems and targeted drug carriers, highlighting the polymers' customizable properties and their mucoadhesive nature, which make them highly effective across multiple drug delivery methods. Furthermore, the potential of PVA and chitosan in biosensor technology is explored, particularly their ability to interact with biomolecules and their intrinsic conductivity attributes that are essential for creating sensitive, reliable, and biocompatible sensors for medical diagnostics. By synthesizing recent research findings and suggesting future research directions, this review underscores the versatility and critical role of PVA and chitosan in pushing the boundaries of biomedical innovation. It offers valuable insights for researchers and scientists dedicated to advancing healthcare through the application of these natural polymers.

There have been many developments in diabetes technology in recent years, with continuous glucose monitoring (CGM), insulin pump therapy (CSII) and automated insulin delivery (AID) becoming progressively accepted in outpatient diabetes care. However, the use of such advanced diabetes technology in the inpatient setting is still limited for several reasons, including logistical challenges and staff training needs. On the other hand, hospital settings with altered diet and stress-induced hyperglycemia often pose challenges to tight glycemic control using conventional treatment tools. Integrating smarter glucose monitoring and insulin delivery devices into the increasingly technical hospital environment could reduce diabetes-related morbidity and mortality. This narrative review describes the most recent literature on the use of diabetes technology in the hospital and suggests avenues for further research.

Advanced diabetes technology has the potential to improve glycemic control in hospitalized people with and without diabetes, and could add particular value in certain conditions, such as nutrition therapy or perioperative management. Taken together, CGM allows for more accurate and patient-friendly follow-up and ad hoc titration of therapy. AID may also provide benefits, including improved glycemic control and reduced nursing workload. Before advanced diabetes technology can be used on a large scale in the hospital, further research is needed on efficacy, accuracy and safety, while implementation factors such as cost and staff training must also be overcome.

Wearable epidermal electronics with non- or minimally-invasive characteristics can collect, transduce, communicate, and interact with accessible physicochemical health indicators on the skin. However, due to the stratum corneum layer, rich information about body health is buried under the skin stratum corneum layer, for example, in the skin interstitial fluid. Microneedle patches are typically designed with arrays of special microsized needles of length within 1000 µm. Such characteristics potentially enable the access and sample of biomolecules under the skin or give therapeutical treatment painlessly and transdermally. Integrating microneedle patches with various electronics allows highly efficient transdermal bioelectronics, showing their great promise for biomedical and healthcare applications. This comprehensive review summarizes and highlights the recent progress on integrated transdermal bioelectronics based on microneedle patches. The design criteria and state-of-the-art fabrication techniques for such devices are initially discussed. Next, devices with different functions, including but not limited to health monitoring, drug delivery, and therapeutical treatment, are highlighted in detail. Finally, key issues associated with current technologies and future opportunities are elaborated to sort out the state of recent research, point out potential bottlenecks, and provide future research directions.

Going extended periods of time without eating increases risk for binge eating and is a primary target of leading interventions for binge-spectrum eating disorders (B-EDs). However, existing treatments for B-EDs yield insufficient improvements in regular eating and subsequently, binge eating. These unsatisfactory clinical outcomes may result from limitations in assessment and promotion of regular eating in therapy. Detecting the absence of eating using passive sensing may improve clinical outcomes by facilitating more accurate monitoring of eating behaviours and powering just-in-time adaptive interventions. We developed an algorithm for detecting meal consumption (and extended periods without eating) using continuous glucose monitor (CGM) data and machine learning.

Adults with B-EDs (N = 22) wore CGMs and reported eating episodes on self-monitoring surveys for 2 weeks. Random forest models were run on CGM data to distinguish between eating and non-eating episodes.

The optimal model distinguished eating and non-eating episodes with high accuracy (0.82), sensitivity (0.71), and specificity (0.94).

These findings suggest that meal consumption and extended periods without eating can be detected from CGM data with high accuracy among individuals with B-EDs, which may improve clinical efforts to target dietary restriction and improve the field's understanding of its antecedents and consequences.

Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The translation of these software-based ANNs into dedicated computing hardware opens a route toward automated insulin delivery systems ultimately enhancing the quality of life for diabetic patients. ANNs are transforming this field, potentially leading to implantable smart prediction devices and ultimately to a fully artificial pancreas. However, this transition presents several challenges, including the need for specialized, compact, lightweight, and low-power hardware. Organic polymer-based electronics are a promising solution as they have the ability to implement the behavior of neural networks, operate at low voltage, and possess key attributes like flexibility, stretchability, and biocompatibility. Here, the study focuses on implementing software-based neural networks for glucose prediction into hardware systems. How to minimize network requirements, downscale the architecture, and integrate the neural network with electrochemical neuromorphic organic devices, meeting the strict demands of smart implants for in-body computation of glucose prediction is investigated.

This study integrates hollow microneedle arrays (HMNA) with a novel jellyfish-shaped electrochemical sensor for the detection of key biomarkers, including uric acid (UA), glucose, and pH, in artificial interstitial fluid. The jellyfish-shaped sensor displayed linear responses in detecting UA and glucose via differential pulse voltammetry (DPV) and chronoamperometry, respectively. Notably, the open circuit potential (OCP) of the system showed a linear variation with pH changes, validating its pH-sensing capability. The sensor system demonstrates exceptional electrochemical responsiveness within the physiological concentration ranges of these biomarkers in simulated epidermis sensing applications. The detection linear ranges of UA, glucose, and pH were 0~0.8 mM, 0~7 mM, and 4.0~8.0, respectively. These findings highlight the potential of the HMNA-integrated jellyfish-shaped sensors in real-world epidermal applications for comprehensive disease diagnosis and health monitoring.

In this paper, a dual wavelength short near-infrared system is described for the detection of glucose levels. The system aims to improve the accuracy of blood glucose detection in a cost-effective and non-invasive way. The accuracy of the method is evaluated using real-time samples collected with the reference finger prick glucose device. A feed forward neural network (FFNN) regression method is employed to predict glucose levels based on the input data obtained from NIR technology. The system calculates glucose evaluation metrics and performs Surveillance error grid (SEG) analysis. The coefficient of determination R 2 and mean absolute error are observed 0.99 and 2.49 mg/dl, respectively. Additionally, the system determines the root mean square error (RMSE) as 3.02 mg/dl. It also shows that the mean absolute percentage error (MAPE) is 1.94% and mean squared error (MSE) is 9.16 ( m g / d l ) 2 for FFNN. The SEG analysis shows that the glucose values measured by the system fall within the clinically acceptable range when compared to the reference method. Finally, the system uses the multi-class classification method of the multilayer perceptron (MLP) and K-nearest neighbors (KNN) classifier to classify glucose levels with an accuracy of 99%.

Herein, we demonstrate the detection of glucose in a noninvasive and nonenzymatic manner by utilizing an extended gate field-effect transistor (EGFET) based on the organic molecule pyrene phosphonic acid (PyP4OH8) incorporated nickel metal-organic framework (NiOM-MOF). The prepared electrode responds selectively to glucose instead of sucrose, fructose, maltose, ascorbic acid, and uric acid in a 1× phosphate buffer saline solution. Also, utilizing the scanning Kelvin probe system, the sensing electrode's work function (Φ) is measured to validate the glucose-sensing mechanism. The sensitivity, detection range, response time, limit of detection, and limit of quantification of the electrode are determined to be 24.5 μA mM-1 cm-2, 20 μM to 10 mM, less than 5 s, 2.73 μM, and 8.27 μM, respectively. Most interestingly, the developed electrode follows the Michaelis-Menten kinetics, and the calculated rate constant (km) 0.07 mM indicates a higher affinity of NiOM-MOF toward glucose. The real-time analysis has revealed that the prepared electrode is sensitive to detect glucose in real human saliva, and it can be an alternative device for the noninvasive detection of glucose. Overall, the outcomes of the EGFET studies demonstrate that the prepared electrodes are well-suited for expeditious detection of glucose levels in saliva.

Monitoring blood glucose levels is crucial for individuals with diabetes. Noninvasive methods for measuring serum glucose levels have been explored to aid in blood glucose control for diabetes management.

We introduced a noncontact optical glucometer (NCGM) for measuring glucose levels in the aqueous humor of the human eye. We also investigated the correlation between glucose levels in the NCGM and the aqueous humor, blood samples, and self-monitoring blood glucose devices.

The optical system used in this study measured both the near-infrared absorption and polarized rotatory distribution of glucose molecules in the human aqueous humor. This prospective study's outcomes were eye aqueous glucose level, preoperative blood glucose level, intraoperative blood glucose level, and NCGM reading of patients in a single center in Taiwan.

The NCGM's measurements showed a strong correlation with blood glucose levels (intra-class correlation [ICC]: 0.95 to 0.98) and aqueous humor glucose levels (ICC: 0.76), indicating its ability to noninvasively measure blood glucose levels in human subjects.

This NCGM may offer a convenient, pain-free, and rapid tool for measuring blood glucose levels in diabetic patients. The device could represent a significant advancement in noncontact hybrid optical glucose measurement systems.

The Chinese Society of Critical Care Medicine (CSCCM) has developed clinical practice guidelines for nutrition assessment and monitoring for patients in adult intensive care units (ICUs) in China. This guideline focuses on nutrition evaluation and metabolic monitoring to achieve optimal and personalized nutrition therapy for critically ill patients. This guideline was developed by experts in critical care medicine and evidence-based medicine methodology and was developed after a thorough review of the system and a summary of relevant trials or studies published from 2000 to July 2023. A total of 18 recommendations were formed and consensus was reached through discussions and reviews by expert groups in critical care medicine, parenteral and enteral nutrition, and surgery. The recommendations are based on currently available evidence and cover several key fields, including screening and assessment, evaluation and assessment of enteral feeding intolerance, metabolic and nutritional measurement and monitoring during nutrition therapy, and organ function evaluation related to nutrition supply. Each question was analyzed according to the Population, Intervention, Comparison, and Outcome (PICO) principle. In addition, interpretations were provided for four questions that did not reach a consensus but may have potential clinical and research value. The plan is to update this nutrition assessment and monitoring guideline using the international guideline update method within 3-5 years.

Diabetes technology has proliferated extensively over the past few decades with vast ameliorations in glucose monitoring and in insulin delivery systems. From a treatment based on daily insulin injections, we have moved to increasingly advanced technologies. Despite such advancements which have allowed better glycemic control, decreased diabetes-related complications, and improved the quality of life among diabetic patients, it has left many individuals unsatisfied with the current rate of commercial artificial pancreas development, stemming the need for further research into novel technologies. Accordingly, the Juvenile Diabetes Research Foundation has marked three generations for the development of an artificial pancreas comprising historical landmarks and future prospects which aim to produce an advanced technological system that attempts to mimic the endogenous pancreas, eliminating the need for user input. This review presents a synopsis of the development and evolution of insulin pumps, starting with the earliest technologies available such as continuous subcutaneous insulin infusion and continuous glucose monitoring as separate components, to currently available integrated advanced closed-loop hybrid systems and possible future technologies. The aim of the review is to provide insight of the advantages and limitations of past and currently available insulin pumps with the hope of driving research into novel technologies that attempt to mimic endogenous pancreatic function as closely as possible.

Optical coherence tomography (OCT) is a noninvasive imaging technique with large penetration depth into the tissue, but limited chemical specificity. By incorporating functional co-monomers, hydrogels can be designed to respond to specific molecules and undergo reversible volume changes. In this study, we present implantable and wearable biocompatible hydrogel sensors combined with OCT to monitor their thickness change as a tool for continuous and real-time monitoring of glucose concentration and pH. The results demonstrate the potential of combining hydrogel biosensors with OCT for non-contact continuous in-vivo monitoring of physiological parameters.

α-Amanitin (AMN) is one of the deadliest toxins from mushrooms, present in the deadly mushroom species Amanita phalloides. It is a bicyclic octapeptide and represents up to 40% of the amatoxins in mushrooms, damaging the liver and kidneys. Current methods of detecting amatoxins are time-consuming and require the use of expensive equipment. A novel label-free electrochemical immunosensor was successfully developed for rapid detection of α-amanitin, which was fabricated by immobilization of anti-α-amanitin antibodies onto a functionalized cellulose nanofibrous membrane-modified carbon screen-printed electrode. An oxidation peak of the captured amanitin on the tethered antibodies was observed at 0.45 V. The performance of the nanofibrous membrane on the electrode and necessary fabrication steps were investigated by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Due to its unique structural features and properties such as high specific surface area and microporous structure, the nanofibrous membrane as an immunosensor matrix for antibody tethering improved the electrochemical performance of the immunosensor by more than 3 times compared with cast membranes. Under the optimal conditions, the assembled immunosensor exhibited high sensitivity toward α-amanitin detection in the range of 0.009-2 ng mL-1 with a limit of detection of 8.3 pg mL-1. The results clearly indicate that the fabricated nanofiber-based-immunosensor is suitable for point-of-care detection of lethal α-amanitin in human urine without any pretreatment within 30 min.

Diabetes Mellitus incidence and its negative outcomes have dramatically increased worldwide and are expected to further increase in the future due to a combination of environmental and social factors. Several methods of measuring glucose concentration in various body compartments have been described in the literature over the years. Continuous advances in technology open the road to novel measuring methods and innovative measurement sites. The aim of this comprehensive review is to report all the methods and products for non-invasive glucose measurement described in the literature over the past five years that have been tested on both human subjects/samples and tissue models. A literature review was performed in the MDPI database, with 243 articles reviewed and 124 included in a narrative summary. Different comparisons of techniques focused on the mechanism of action, measurement site, and machine learning application, outlining the main advantages and disadvantages described/expected so far. This review represents a comprehensive guide for clinicians and industrial designers to sum the most recent results in non-invasive glucose sensing techniques' research and production to aid the progress in this promising field.

Over the past few years, therapeutic drug monitoring (TDM) has gained practical significance in antimicrobial precision therapy. Yet two categories of mainstream TDM techniques (chromatographic analysis and immunoassays) that are widely adopted nowadays retain certain inherent limitations. The use of biosensors, an innovative strategy for rapid evaluation of antimicrobial concentrations in biological samples, enables the implementation of point-of-care testing (POCT) and continuous monitoring, which may circumvent the constraints of conventional TDM and provide strong technological support for individualized antimicrobial treatment. This comprehensive review summarizes the investigations that have harnessed biosensors to detect antimicrobial drugs in biological matrices, provides insights into the performance and characteristics of each sensing form, and explores the feasibility of translating them into clinical practice. Furthermore, the future trends and obstacles to achieving POCT and continuous monitoring are discussed. More efforts are necessary to address the four key 'appropriateness' challenges to deploy biosensors in clinical practice, paving the way for personalized antimicrobial stewardship.

For diabetics, taking regular blood glucose measurements is crucial. However, traditional blood glucose monitoring methods are invasive and unfriendly to diabetics. Recent studies have proposed a biofluid-based glucose sensing technique that creatively combines wearable devices with noninvasive glucose monitoring technology to enhance diabetes management. This is a revolutionary advance in the diagnosis and management of diabetes, reflects the thoughtful modernization of medicine, and promotes the development of digital medicine. This paper reviews the research progress of noninvasive continuous blood glucose monitoring (CGM), with a focus on the biological liquids that replace blood in monitoring systems, the technical principles of continuous noninvasive glucose detection, and the output and calibration of sensor signals. In addition, the existing limits of noninvasive CGM systems and prospects for the future are discussed. This work serves as a resource for further promoting the development of noninvasive CGM systems.

Continuous glucose monitoring (CGM) sensors measure interstitial glucose concentration every 1-5 min for days or weeks. New CGM-based diabetes therapies are often tested in in silico clinical trials (ISCTs) using diabetes simulators. Accurate models of CGM sensor inaccuracies and failures could help improve the realism of ISCTs. However, the modeling of CGM failures has not yet been fully addressed in the literature. This work aims to develop a mathematical model of CGM gaps, i.e., occasional portions of missing data generated by temporary sensor errors (e.g., excessive noise or artifacts).

Two datasets containing CGM traces collected in 167 adults and 205 children, respectively, using the Dexcom G6 sensor (Dexcom Inc., San Diego, CA) were used. Four Markov models, of increasing complexity, were designed to describe three main characteristics: number of gaps for each sensor, gap distribution in the monitoring days, and gap duration. Each model was identified on a portion of each dataset (training set). The remaining portion of each dataset (real test set) was used to evaluate model performance through a Monte Carlo simulation approach. Each model was used to generate 100 simulated test sets with the same size as the real test set. The distributions of gap characteristics on the simulated test sets were compared with those observed on the real test set, using the two-sample Kolmogorov-Smirnov test and the Jensen-Shannon divergence.

A six-state Markov model, having two states to describe normal sensor operation and four states to describe gap occurrence, achieved the best results. For this model, the Kolmogorov-Smirnov test found no significant differences between the distribution of simulated and real gap characteristics. Moreover, this model obtained significantly lower Jensen-Shannon divergence values than the other models.

A Markov model describing CGM gaps was developed and validated on two real datasets. The model describes well the number of gaps for each sensor, the gap distribution over monitoring days, and the gap durations. Such a model can be integrated into existing diabetes simulators to realistically simulate CGM gaps in ISCTs and thus enable the development of more effective and robust diabetes management strategies.

Diabetes mellitus is a prevalent chronic health condition that has caused millions of deaths worldwide. Monitoring blood glucose levels is crucial in diabetes management, aiding in clinical decision making and reducing the incidence of hypoglycemic episodes, thereby decreasing morbidity and mortality rates. Despite advancements in glucose monitoring (GM), the development of noninvasive, rapid, accurate, sensitive, selective, and stable systems for continuous monitoring remains a challenge. Addressing these challenges is critical to improving the clinical utility of GM technologies in diabetes management. In this concept, cyclodextrins (CDs) can be instrumental in the development of GM systems due to their high supramolecular recognition capabilities based on the host-guest interaction. The introduction of CDs into GM systems not only impacts the sensitivity, selectivity, and detection limit of the monitoring process but also improves biocompatibility and stability. These findings motivated the current review to provide a comprehensive summary of CD-based blood glucose sensors and their chemistry of glucose detection, efficiency, and accuracy. We categorize CD-based sensors into four groups based on their modification strategies, including CD-modified boronic acid, CD-modified mediators, CD-modified nanoparticles, and CD-modified functionalized polymers. These findings shed light on the potential of CD-based sensors as a promising tool for continuous GM in diabetes mellitus management.

Type 1 diabetes mellitus is a chronic autoimmune disease that affects millions of people and generates high healthcare costs due to frequent complications when inappropriately managed. Our paper aimed to review the latest technologies used in T1DM management for better glycemic control and their impact on daily life for people with diabetes. Continuous glucose monitoring systems provide a better understanding of daily glycemic variations for children and adults and can be easily used. These systems diminish diabetes distress and improve diabetes control by decreasing hypoglycemia. Continuous subcutaneous insulin infusions have proven their benefits in selected patients. There is a tendency to use more complex systems, such as hybrid closed-loop systems that can modulate insulin infusion based on glycemic readings and artificial intelligence-based algorithms. It can help people manage the burdens associated with T1DM management, such as fear of hypoglycemia, exercising, and long-term complications. The future is promising and aims to develop more complex ways of automated control of glycemic levels to diminish the distress of individuals living with diabetes.

Critically ill patients are prone to high glycemic variations irrespective of their diabetes status. This mandates frequent blood glucose (BG) monitoring and regulation of insulin therapy. Even though the most commonly employed capillary BG monitoring is convenient and rapid, it is inaccurate and prone to high bias, overestimating BG levels in critically ill patients. The targets for BG levels have also varied in the past few years ranging from tight glucose control to a more liberal approach. Each of these has its own fallacies, while tight control increases risk of hypoglycemia, liberal BG targets make the patients prone to hyperglycemia. Moreover, the recent evidence suggests that BG indices, such as glycemic variability and time in target range, may also affect patient outcomes. In this review, we highlight the nuances associated with BG monitoring, including the various indices required to be monitored, BG targets and recent advances in BG monitoring in critically ill patients.

The Sencell sensor uses glucose-induced changes in an osmotic pressure chamber for continuous glucose measurement. A final device shall have the size of a grain of rice. The size limiting factor is the piezo-resistive pressure transducers inside the core sensor technology (resulting chamber volume: 70 µL. To achieve the necessary miniaturization, these pressure transducers were replaced by small (4000 × 400 × 150 nm³) nano-granular tunneling resistive (NTR) pressure sensors (chamber volume: 750 nL). For benchmark testing, we filled the miniaturized chamber with bovine serum albumin (BSA, 1 mM) and exposed it repeatedly to distilled water followed by 1 mM BSA solution. Thereafter, we manufactured sensors with glucose testing chemistry (ConcanavalinA/dextran) and investigated sensor performance with dynamic glucose changes between 0 and 300 mg/dL. Evaluation of the miniaturized sensors resulted in reliable pressure changes, both in the BSA benchmark experiment (30-35 mBar) and in the dynamic in vitro continuous glucose test (40-50 mBar). These pressure results were comparable to similar experiments with the previous larger in vitro sensors (30-50 mBar). In conclusion, the NTR pressure sensor technology was successfully employed to reduce the size of the core osmotic pressure chamber by more than 95% without loss in the osmotic pressure signal.

Glucose and insulin metabolism are altered in hemodialysis patients, and diabetes management is difficult in these patients. We aimed to validate flash glucose monitoring (FGM) in hemodialysis patients with and without diabetes mellitus as an attractive option for glucose monitoring not requiring regular self-punctures.

We measured interstitial glucose using a FreeStyle Libre device in eight hemodialysis patients with and seven without diabetes mellitus over 14 days and compared the results to simultaneously performed self-monitoring of capillary blood glucose (SMBG).

In 720 paired measurements, mean flash glucose values were significantly lower than self-measured capillary values (6.17±2.52 vs. 7.15±2.41 mmol/L, p=1.3 E-86). Overall, the mean absolute relative difference was 17.4%, and the mean absolute difference was 1.20 mmol/L. The systematic error was significantly larger in patients without vs. with diabetes (- 1.17 vs. - 0.82 mmol/L) and on dialysis vs. interdialytic days (-1.09 vs. -0.90 mmol/L). Compared to venous blood glucose (72 paired measurements), the systematic error of FGM was even larger (5.89±2.44 mmol/L vs. 7.78±7.25 mmol/L, p=3.74E-22). Several strategies to reduce the systematic error were evaluated, including the addition of +1.0 mmol/L as a correction term to all FGM values, which significantly improved accuracy.

FGM systematically underestimates blood glucose in hemodialysis patients but, taking this systematic error into account, the system may be useful for glucose monitoring in hemodialysis patients with or without diabetes.

Continuous monitoring of glucose allows diabetic patients to better maintain blood glucose level by altering insulin dosage or diet according to prevailing glucose values and thus to prevent potential hyperglycemia and hypoglycemia. However, current continuous glucose monitoring (CGM) relies mostly on enzyme electrodes or micro-dialysis probes, which suffer from insufficient stability, susceptibility to corrosion of electrodes, weak or inconsistent correlation, and inevitable interference. A fluorescence-based glucose sensor in the skin will likely be more stable, have improved sensitivity, and can resolve the issues of electrochemical interference from the tissue. This study develops a fluorescent nanodiamond boronic hydrogel system in porous microneedles for CGM. Fluorescent nanodiamond is one of the most photostable fluorophores with superior biocompatibility. When surface functionalized, the fluorescent nanodiamond can integrate with boronic polymer and form a hydrogel, which can produce fluorescent signals in response to environmental glucose concentration. In this proof-of-concept study, the strategy for building a miniatured device with fluorescent nanodiamond hydrogel is developed. The device demonstrates remarkable long-term photo and signal stability in vivo with both small and large animal models. This study presents a new strategy of fluorescence based CGM toward treatment and control of diabetes.

In recent years, glucose monitoring has been revolutionized by the development of continuous glucose monitoring systems (CGMS), which are wearable non/minimally invasive devices that measure glucose concentration almost continuously for several consecutive d/wk. The Abbott FreeStyle Libre is the CGMS used most commonly. It has adequate clinical accuracy both in dogs and cats, even though the accuracy is lower in the hypoglycemic range. It allows an accurate identification of glycemic excursions occurring throughout the day as well as of glucose variations during consecutive days, enabling the clinician to make a more informed decision about the insulin dose and frequency of administration.

To introduce a wireless high-definition endoscopic system (WHES) and compare it with a Storz high-definition (HD) system for image resolution, colour resolution, weight, and costs.

The WHES incorporated a portable light-emitting diode light source and a wireless camera module, which can be compatible with different types of endoscopes. Images were wirelessly transmitted to a monitor or mobile platform such as smartphone through a receiver. The International Standards Organization 12233 resolution chart image was used for the comparison of image resolution and Munsell Colour Checker Chart for colour resolution. In all, 38 endourologists used a Likert questionnaire to blindly evaluate cystoscopic images from a patient with haematuria. The surgical team was asked about the overall performance of the WHES in 20 laparoscopic adrenalectomies using a unvalidated subjective survey.

There was no difference in image resolution between the two systems (5.82 vs 5.89  line pairs/mm). Without lens and respective light sources, there were better purple (ΔE = 21.48 vs 28.73), blue (ΔE = 34.88 vs 38.6) and red colour resolution (ΔE = 29.01 vs 35.45) for the WHES camera (P  <  0.05), but orange (ΔE = 43.45 vs 36.52) and yellow (ΔE = 52.7 vs 35.93) resolutions were better for the Storz HD camera (P  <  0.05). Comparing the WHES to a Storz laparoscopic system, the Storz system still had better resolution of orange and yellow, while the resolution of purple, blue, and red was similar for the two systems. The expert comments on resolution, brightness, and colour for cystoscopy were not statistically different, but the ergonomics score for the WHES was higher (3.7 vs 3.33, P = 0.038). The overall cost of the WHES was $23  000-25  000 compared with $45  000-50  000 for a Storz system. There were 100% general satisfaction for the WHES in the survey.

We developed a new WHES that provides the same resolution images as a Storz laparoscopic system and acceptable colour resolution with the advantages of wireless connection, small volume, low cost, portability, and high-speed wireless transmission.

Simultaneous detection of uric acid and glucose using a non-invasive approach can be a promising strategy for related diseases, e.g., diabetes, gout, kidney disease, and cardiovascular disease. In this study, we have proposed a dual-function wearable electrochemical sensor for uric acid and glucose detection in sweat. The sensor with a four-electrode system was prepared by printing the ink on a common rubber glove. CV and chronoamperometry were used to characterize the prepared sensor's electrochemical sensing performance. The sensors exhibited the linear range from 0 to 1.6 mM and 0 to 3.7 mM towards uric acid and glucose electrochemical sensing in phosphate-buffered solution, with the corresponding limit of detection of 3.58 μM and 9.10 μM obtained, respectively. Moreover, the sensors had shown their feasibility of real sample sensing in sweat. The linear detection range for uric acid (0 to 40 μM) and glucose (0 to 1.6 mM) in the sweat can well cover their concentration range in physiological conditions. The prepared dual-function wearable electrochemical sensor features easy preparation, fast detection, high sensitivity, high selectivity, and the practical application potential in uric acid and glucose sensing.

Foreign body response (FBR) is a major challenge that affects implantable biosensors and medical devices, including glucose biosensors, leading to a deterioration in device response over time. Polymer shields are often used to mitigate this issue. Zwitterionic polymers (ZPs) are a promising class of materials that reduce biofouling of implanted devices. A series of ZPs each containing tetherable epoxide functional groups was synthesised for application as a polymer shield for eventual application as implantable glucose biosensors. The polymer shields were initially tested for the ability to resist fibrinogen adsorption and fibroblast adhesion. All synthesised ZPs showed comparable behaviour to a commercial Lipidure ZP in resisting fibrinogen adsorption. Nafion, a common anionic shield used against electrochemical interferents, showed higher protein adsorption and comparable cell adhesion resistance as uncoated control surfaces. However, a poly(2-methacryloyloxyethyl phosphorylcholine-co-glycidyl methacrylate) (MPC)-type ZP showed similar behaviour to Lipidure, with approximately 50% reduced fibrinogen adsorption and 80% decrease in fibroblast adhesion compared to uncoated controls. An MPC-coated amperometric glucose biosensor showed comparable current density and a 1.5-fold increase in sensitivity over an uncoated control biosensor, whereas all other polymer shields tested, including Lipidure, Nafion and a poly(ethyleneglycol) polymer, resulted in lower sensitivity and current density. Collectively, these characteristics make MPC-polymer shield coatings an appealing possibility for use in implantable glucose sensors and other implanted devices with the aim of reducing FBR while maintaining sensor performance.

Blood glucose (BG) monitoring is important for critically ill patients, as poor sugar control has been associated with increased mortality in hospitalized patients. However, constant BG monitoring can be resource-intensive and pose a healthcare burden in clinical practice. In this study, we aimed to develop a personalized machine-learning model to predict dysglycemia from electrocardiogram (ECG) data. We used the Medical Information Mart for Intensive Care III database as our source of data and obtained more than 20 ECG records from each included patient during a single hospital admission. We focused on lead II recordings, along with corresponding blood sugar data. We processed the data and used ECG features from each heartbeat as inputs to develop a one-class support vector machine algorithm to predict dysglycemia. The model was able to predict dysglycemia using a single heartbeat with an AUC of 0.92 ± 0.09, a sensitivity of 0.92 ± 0.10, and specificity of 0.84 ± 0.04. After applying 10 s majority voting, the AUC of the model's dysglycemia prediction increased to 0.97 ± 0.06. This study showed that a personalized machine-learning algorithm can accurately detect dysglycemia from a single-lead ECG.

Hydrogels with a three-dimensional network structure are particularly outstanding in water absorption and water retention because water exists stably in the interior, making the gel appear elastic and solid. Although traditional hydrogels have good water absorption and high water content, they have poor mechanical properties and are not strong enough to be applied in some scenarios today. The proposal of double-network hydrogels has dramatically improved the toughness and mechanical strength of hydrogels that can adapt to different environments. Based on ensuring the properties of hydrogels, they themselves will not be damaged by excessive pressure and tension. This review introduces preparation methods for double-network hydrogels and ways to improve the mechanical properties of three typical gels. In addition to improving the mechanical properties, the biocompatibility and swelling properties of hydrogels enable them to be applied in the fields of biomedicine, intelligent sensors, and ion adsorption.

Good glycaemic control is a crucial part of diabetes management. Traditional assessment methods, including HbA1c checks and self-monitoring of blood glucose, can be unreliable and inaccurate. Continuous glucose monitoring (CGM) offers a non-invasive and more detailed alternative. Availability of this technology is increasing worldwide. However, there is no current comprehensive evidence on the acceptability and feasibility of these devices. This is a protocol for a mixed-methods systematic review of qualitative and quantitative evidence about acceptability and feasibility of CGM in people with diabetes.

We will search MEDLINE, Embase, CINAHL, and CENTRAL for qualitative and quantitative evidence about the feasibility and acceptability of CGM in all populations with diabetes (any type) using search terms for "continuous glucose monitoring" and "diabetes". We will not apply any study-type filters. Searches will be restricted to studies conducted in humans and those published from 2011 onwards. We will not restrict the search by language. Study selection and data extraction will be carried out by two reviewers independently using Rayyan and Eppi-Reviewer, respectively, with disagreements resolved by discussion. Data extraction will include key information about each study, as well as qualitative evidence in the form of participant quotes from primary studies and themes and subthemes based on the authors' analysis. Quantitative data relating to acceptability and feasibility including data loss, adherence, and quantitative ratings of acceptability will be extracted as means and standard deviations or n/N as appropriate. Qualitative evidence will be analysed using framework analysis informed by the Theoretical Framework of Acceptability. Where possible, quantitative evidence will be combined using random-effects meta-analysis; otherwise, a narrative synthesis will be performed. The most appropriate method for integrating qualitative and quantitative findings will be selected based on the data available.

Ongoing assessment of the acceptability of interventions has been identified as crucially important to scale-up and implementation. This review will provide new knowledge with the potential to inform a programme theory of CGM as well as future roll-out to potentially vulnerable populations, including those with severe mental illness.

PROSPERO CRD42021255141.

The rise and fall of the health technology startup Theranos is emblematic of the promise and peril of point-of-care testing (POCT). Instruments that deliver immediate results from minimally invasive samples at the location of collection can provide powerful tools to deliver health data in clinical and public health contexts. Yet, POCT availability is driven largely by market interests, which limits the development of inexpensive tests for diverse health conditions that can be used in resource-limited settings. These constraints, combined with complex regulatory hurdles and substantial ethical challenges, have contributed to the underutilization of POCT in human biology research.

We evaluate current POCT capabilities and limitations, discuss promising applications for POCT devices in resource-limited settings, and discuss the future of POCT.

As evidenced by publication trends, POCT platforms have rapidly advanced in recent years, gaining traction among clinicians and health researchers. We highlight POCT devices of potential interest to population-based researchers and present specific examples of POCT applications in human biology research.

Several barriers can limit POCT applications, including cost, lack of regulatory approval for non-clinical use, requirements for expensive equipment, and the dearth of validation in remote field conditions. Despite these issues, we see immense potential for emerging POCT technology capable of analyzing new sample types and used in conjunction with increasingly common technology (e.g., smart phones). We argue that the fallout from Theranos may ultimately provide an opportunity to advance POCT, leading to more ethical data collection and novel opportunities in human biology research.

Using continuous glucose monitoring (CGM) in critically ill adult patients requiring insulin therapy has increased with inconsistent results. Thus, we conducted a meta-analysis to assess the effect of CGM and frequent point-of-care (POC) measurements in such a patient population.

We searched PubMed, Embase, Cochrane Library, China national knowledge infrastructure, and Wanfang for relevant articles from inception to Jan 15, 2022. Randomized controlled trials (RCTs) were considered if they focused on critically ill patients who required insulin and were treated with CGM or any POC measurements. We used the Cochrane risk evaluating tool to assess study quality. Subgroup analysis and publication bias were also conducted.

We finally included 19 RCTs with 1,852 participants. The quality of the included studies were at a low to moderate levels. Overall, CGM devices significantly reduced hypoglycemia incidence (Risk ratio (RR) 0.35; 95% CI, 0.25-0.49; P<0.00001) than the POC measurement. Further subgroup and sensitivity analyses confirmed this result. The CGM group also had lower overall mortality (RR 0.54; 95% CI, 0.34-0.86; P=0.01), lower glucose variability, and nosocomial infection. The time in, below, or above target blood glucose range, insulin use, and length of stay in the ICU were comparable between the two groups. In addition, few studies provided data in favor of decreased nursing workload and medical costs in the CGM group.

The CGM technique could significantly reduce hypoglycemia incidence, overall mortality, and glucose variability compared to POC measurement in critically ill patients. However, further large, well-designed RCTs are required to confirm our results.

Hospitalization of persons with diabetes in an inpatient diabetes unit is challenging, notably for patients having different profiles. We aimed to evaluate the feasibility and the benefit of a continuous glucose monitoring (CGM) telemetry system to control glucose excursions in hospitalized patients with diabetes, according to their diabetes type and the reasons for their hospitalization.

A prospective pilot study was conducted in 53 insulin-requiring diabetes patients hospitalized in the general ward. Glucose was monitored using Guardian Connect (GC, Medtronic) to adopt insulin therapy. The time in range (TIR, target 70-180 mg/dL), the time below range (TBR), and the time above range (TAR) were recorded by GC between the start of hospitalization (SH) and end of hospitalization (EH), and analyzed according to the diabetes type (type 1 diabetes n = 28, type 2 diabetes n = 25) and the reasons for hospitalization (acute complications n = 35, therapeutic education n = 18). Patient and caregiver satisfaction was also assessed.

In patients with type 2 diabetes and those hospitalized for acute complications, TIR significantly increased between the SH and EH, from 75.7% (95%CI 48.5-84.6) to 82.2% (95%CI 63.2-91.8) P = 0.043 and from 58.3% (95%CI 46.3-69.7) to 66.4% (95%CI 55.6-75.5) P = 0.031, respectively, and TAR significantly decreased, with no change in TBR. In patients with diabetes hospitalized for therapeutic education, TBR significantly decreased from 3.4% (95%CI 0-9.4) to 0% (95%CI 0-3.8) P = 0.037. Finally, 94% of patients and caregivers deemed the GC system useful.

CGM telemetry system use is feasible and well accepted in patients hospitalized in diabetes care unit and could be useful to improve therapeutic education and metabolic control, especially for specific homogenous populations with diabetes.

Type 1 diabetes is a self-managed condition. Regular monitoring of blood glucose (BG) levels has been the cornerstone of diabetes management. Finger prick BG testing traditionally has been the standard method employed. More recently, rapid advancements in the development of continuous glucose monitoring devices have led to increased use of technology to help children and young people with diabetes manage their condition. These devices have the potential to improve diabetes control and reduce hypoglycaemia especially if used in conjunction with a pump to automate insulin delivery. This paper aims to provide an update on main CGM devices available and practical considerations for doctors if they come across a child with diabetes who is using one of these devices.

Most current invasive analytic devices for disease diagnosis and monitoring require the collection of blood, which causes great discomfort for patients and may potentially cause infection. This explains the great need for noninvasive devices that utilize other bodily fluids like sweat, saliva, tears, or urine. Among them, eye tears are easily accessible, less complex in composition, and less susceptible to dilution. Tears also contain valuable clinical information for the diagnosis of ocular and systemic diseases as the tear analyte level shows great correlation with the blood analyte level. These unique advantages make tears a promising platform for use in clinical settings. As the volume of tear film and the rate of tear flow are only microliters in size, the use of microfluidic technology in analytic devices allows minimal sample consumption. Hence, more and more microfluidic tear analytic devices have been proposed, and their working mechanisms can be broadly categorized into four main types: (a) electrochemical, (b) photonic crystals, (c) fluorescence, and (d) colorimetry. These devices are being developed toward the application of point-of-care tests with rapid yet accurate results. This review aims to provide a general overview of the recent developmental trend of microfluidic devices for tear analysis. Moreover, the fundamental principle behind each type of device along with their strengths and weaknesses will be discussed, especially in terms of their abilities and potential in being used in point-of-care settings.

Although there are many techniques to detect pathogenic bacteria, most of them are only suited for in vitro diagnostics. We report a urinary catheter-based colorimetric sensor for potential on-body detection of E. coli, the most prevalent bacterial species in urinary tract infections associated with the use of urinary catheters. In urine, indole is secreted by E. coli and reacts with a nitrosating agent incorporated in a silicone catheter. A red dimeric product, indoxyl red, is generated within silicone rubber to allow for color-based indole sensing with high sensitivity, linearity, and specificity. This reaction is initiated by the nitrosation reaction of indole at its C-3 position via reagents like sodium nitrite or S-nitroso-N-acetyl-penicillamine under aerobic conditions. The generated 3-nitrosoindole undergoes tautomerization, dimerization, and deoximation to form indoxyl red with high absorbance at 537 nm. In contrast to other indole sensors, the presented method can be applied in real catheters to detect indole and E. coli in biofluids such as urine. The is because (1) S-nitroso-N-acetyl-penicillamine, the nitrosating agent, can be impregnated into silicone elastomers, (2) indole from urine is extracted into silicone due to its hydrophobicity, and (3) the high acidity and oxygen solubility of silicone facilitates the sensing reaction within the silicone matrix. This silicone-based colorimetric sensor clearly differentiates E. coli below and above 10⁵ CFU/mL, which is the threshold concentration of bacteriuria. We expect that early diagnosis of urinary tract infections using the naked eye is possible by functionalizing an exposed section of urinary catheters with the proposed molecular probe.