Optical sensors for continuous glucose monitoring

Deep learning-augmented T-junction droplet generation

Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.

Carbon Nanomaterial Fluorescent Probes and Their Biological Applications

Fluorescent carbon nanomaterials have broadly useful chemical and photophysical attributes that are conducive to applications in biology. In this review, we focus on materials whose photophysics allow for the use of these materials in biomedical and environmental applications, with emphasis on imaging, biosensing, and cargo delivery. The review focuses primarily on graphitic carbon nanomaterials including graphene and its derivatives, carbon nanotubes, as well as carbon dots and carbon nanohoops. Recent advances in and future prospects of these fields are discussed at depth, and where appropriate, references to reviews pertaining to older literature are provided.

A Polarity-Sensitive Far-Red Fluorescent Probe for Glucose Sensing through Skin

The field of glucose biosensors for diabetes management has been of great interest over the past 60 years. Continuous glucose monitoring (CGM) is important to continuously track the glucose level to provide better management of the disease. Concanavalin A (ConA) can reversibly bind to glucose and mannose molecules and form a glucose biosensor via competitive binding. Here, we developed a glucose biosensor using ConA and a fluorescent probe, which generated a fluorescent intensity change based on solvatochromism, the reversible change in the emission spectrum dependent on the polarity of the solvent. The direction in which the wavelength shifts as the solvent polarity increases can be defined as positive (red-shift), negative (blue-shift), or a combination of the two, referred to as reverse. To translate this biosensor to a subcutaneously implanted format, Cyanine 5.5 (Cy5.5)-labeled small mannose molecules were used, which allows for the far-red excitation wavelength range to increase the skin penetration depth of the light source and returned emission. Three Cy5.5-labeled small mannose molecules were synthesized and compared when used as the competing ligand in the competitive binding biosensor. We explored the polarity-sensitive nature of the competing ligands and examined the biosensor's glucose response. Cy5.5-mannotetraose performed best as a biosensor, allowing for the detection of glucose from 25 to 400 mg/dL. Thus, this assay is responsive to glucose within the physiologic range when its concentration is increased to levels needed for an implantable design. The biosensor response is not statistically different when placed under different skin pigmentations when comparing the percent increase in fluorescence intensity. This shows the ability of the biosensor to produce a repeatable signal across the physiologic range for subcutaneous glucose monitoring under various skin tones.

Optical Glucose Sensors Based on Chitosan-Capped ZnS-Doped Mn Nanomaterials

The primary goal of glucose sensing at the point of care is to identify glucose concentrations within the diabetes range. However, lower glucose levels also pose a severe health risk. In this paper, we propose quick, simple, and reliable glucose sensors based on the absorption and photoluminescence spectra of chitosan-capped ZnS-doped Mn nanomaterials in the range of 0.125 to 0.636 mM glucose corresponding to 2.3 mg/dL to 11.4 mg/dL. The detection limit was 0.125 mM (or 2.3 mg/dL), much lower than the hypoglycemia level of 70 mg/dL (or 3.9 mM). Chitosan-capped ZnS-doped Mn nanomaterials retain their optical properties while improving sensor stability. This study reports for the first time how the sensors' efficacy was affected by chitosan content from 0.75 to 1.5 wt.%. The results showed that 1 %wt chitosan-capped ZnS-doped Mn is the most-sensitive, -selective, and -stable material. We also put the biosensor through its paces with glucose in phosphate-buffered saline. In the same range of 0.125 to 0.636 mM, the sensors-based chitosan-coated ZnS-doped Mn had a better sensitivity than the working water environment.

Continuous Glucose Monitoring Enabled by Fluorescent Nanodiamond Boronic Hydrogel

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.

Difunctional Hydrogel Optical Fiber Fluorescence Sensor for Continuous and Simultaneous Monitoring of Glucose and pH

It is significant for people with diabetes to know their body's real-time glucose level, which can guide the diagnosis and treatment. Therefore, it is necessary to research continuous glucose monitoring (CGM) as it gives us real-time information about our health condition and its dynamic changes. Here, we report a novel hydrogel optical fiber fluorescence sensor segmentally functionalized with fluorescein derivative and CdTe QDs/3-APBA, which can continuously monitor pH and glucose simultaneously. In the glucose detection section, the complexation of PBA and glucose will expand the local hydrogel and decrease the fluorescence of the quantum dots. The fluorescence can be transmitted to the detector by the hydrogel optical fiber in real time. As the complexation reaction and the swelling-deswelling of the hydrogel are all reversible, the dynamic change of glucose concentration can be monitored. For pH detection, the fluorescein attached to another segment of the hydrogel exhibits different protolytic forms when pH changes and the fluorescence changes correspondingly. The significance of pH detection is compensation for pH errors in glucose detection because the reaction between PBA and glucose is sensitive to pH. The emission peaks of the two detection units are 517 nm and 594 nm, respectively, so there is no signal interference between them. The sensor can continuously monitor glucose in 0-20 mM and pH in 5.4-7.8. The advantages of this sensor are multi-parameter simultaneous detection, transmission-detection integration, real-time dynamic detection, and good biocompatibility.

The Impact of Glucose Oxidase Immobilization on Dendritic Gold Nanostructures on the Performance of Glucose Biosensors

In recent years, many efforts have been made to develop rapid, sensitive and user-friendly glucose biosensors for monitoring blood glucose concentration in patients. In this study, the electrochemical glucose biosensors based on graphite rod (GR) electrode electrochemically modified with dendritic gold nanostructures (DGNs) and glucose oxidase (GOx) were developed. Phenazine methosulfate was used as a soluble redox mediator. Three GOx immobilization methods: adsorption on DGNs and cross-linking with glutaraldehyde (GA) vapour (GA-GOx/DGNs/GR), covalent immobilization on DGNs modified with 11-mercaptoundecanoic acid self-assembled monolayer (SAM) (GOx-SAM/DGNs/GR) and covalent immobilization on SAM with additional cross-linking with GA vapour (GA-GOx-SAM/DGNs/GR), were used. It was determined that GA significantly improved the stability of the enzyme layer. The difference of maximal current generated during the enzymatic reaction (ΔI_max) equal to 272.06 ± 8.69 µA was obtained using a biosensor based on GA-GOx/DGNs/GR electrodes. However, the highest ΔI_max equal to 384.20 ± 16.06 µA was obtained using GA-GOx-SAM/DGNs/GR electrode. ΔI_max for biosensors based on the GA-GOx-SAM/DGNs/GR electrode was 1.41 times higher than for the GA-GOx/DGNs/GR, whereas the linear dynamic range from 0.1 to 10 mM was the same using all three GOx immobilization methods. The limit of detection using GA-GOx-SAM/DGNs/GR and GA-GOx/DGNs/GR electrodes was 0.019 and 0.022 mM, respectively. The ability to detect glucose in the serum by developed biosensors was evaluated.

Deep Learning-Enabled Technologies for Bioimage Analysis

Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.

Toilet-based continuous health monitoring using urine

Regular health monitoring can result in early detection of disease, accelerate the delivery of medical care and, therefore, considerably improve patient outcomes for countless medical conditions that affect public health. A substantial unmet need remains for technologies that can transform the status quo of reactive health care to preventive, evidence-based, person-centred care. With this goal in mind, platforms that can be easily integrated into people's daily lives and identify a range of biomarkers for health and disease are desirable. However, urine - a biological fluid that is produced in large volumes every day and can be obtained with zero pain, without affecting the daily routine of individuals, and has the most biologically rich content - is discarded into sewers on a regular basis without being processed or monitored. Toilet-based health-monitoring tools in the form of smart toilets could offer preventive home-based continuous health monitoring for early diagnosis of diseases while being connected to data servers (using the Internet of Things) to enable collection of the health status of users. In addition, machine learning methods can assist clinicians to classify, quantify and interpret collected data more rapidly and accurately than they were able to previously. Meanwhile, challenges associated with user acceptance, privacy and test frequency optimization should be considered to facilitate the acceptance of smart toilets in society.

Comprehensive Review on Wearable Sweat-Glucose Sensors for Continuous Glucose Monitoring

The incidence of diabetes is increasing at an alarming rate, and regular glucose monitoring is critical in order to manage diabetes. Currently, glucose in the body is measured by an invasive method of blood sugar testing. Blood glucose (BG) monitoring devices measure the amount of sugar in a small sample of blood, usually drawn from pricking the fingertip, and placed on a disposable test strip. Therefore, there is a need for non-invasive continuous glucose monitoring, which is possible using a sweat sensor-based approach. As sweat sensors have garnered much interest in recent years, this study attempts to summarize recent developments in non-invasive continuous glucose monitoring using sweat sensors based on different approaches with an emphasis on the devices that can potentially be integrated into a wearable platform. Numerous research entities have been developing wearable sensors for continuous blood glucose monitoring, however, there are no commercially viable, non-invasive glucose monitors on the market at the moment. This review article provides the state-of-the-art in sweat glucose monitoring, particularly keeping in sight the prospect of its commercialization. The challenges relating to sweat collection, sweat sample degradation, person to person sweat amount variation, various detection methods, and their glucose detection sensitivity, and also the commercial viability are thoroughly covered.

Silicone-containing thermoresponsive membranes to form an optical glucose biosensor

Glucose biosensors that could be subcutaneously injected and interrogated without a physically connected electrode and transmitter affixed to skin would represent a major advancement in reducing the user burden of...

Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities

With the global population prevalence of diabetes surpassing 463 million cases in 2019 and diabetes leading to millions of deaths each year, there is a critical need for feasible, rapid, and non-invasive methodologies for continuous blood glucose monitoring in contrast to the current procedures that are either invasive, complicated, or expensive. Breath analysis is a viable methodology for non-invasive diabetes management owing to its potential for multiple disease diagnoses, the nominal requirement of sample processing, and immense sample accessibility; however, the development of functional commercial sensors is challenging due to the low concentration of volatile organic compounds (VOCs) present in exhaled breath and the confounding factors influencing the exhaled breath profile. Given the complexity of the topic and the skyrocketing spread of diabetes, a multifarious review of exhaled breath analysis for diabetes monitoring is essential to track the technological progress in the field and comprehend the obstacles in developing a breath analysis-based diabetes management system. In this review, we consolidate the relevance of exhaled breath analysis through a critical assessment of current technologies and recent advancements in sensing methods to address the shortcomings associated with blood glucose monitoring. We provide a detailed assessment of the intricacies involved in the development of non-invasive diabetes monitoring devices. In addition, we spotlight the need to consider breath biomarker clusters as opposed to standalone biomarkers for the clinical applicability of exhaled breath monitoring. We present potential VOC clusters suitable for diabetes management and highlight the recent buildout of breath sensing methodologies, focusing on novel sensing materials and transduction mechanisms. Finally, we portray a multifaceted comparison of exhaled breath analysis for diabetes monitoring and highlight remaining challenges on the path to realizing breath analysis as a non-invasive healthcare approach.

A Versatile Multichannel Instrument for Measurement of Ratiometric Fluorescence Intensity and Phosphorescence Lifetime

Optical biosensing is being actively investigated for minimally-invasive monitoring of key biomarkers both in vitro and in vivo. However, typical benchtop instruments are not portable and are not well suited to high-throughput, real-time analysis. This paper presents a versatile multichannel instrument for measurement of emission intensity and lifetime values arising from luminescent biosensor materials. A detailed design description of the opto-electronic hardware as well as the control software is provided, elaborating a flexible, user-configurable system that may be customized or duplicated for a wide range of applications. This article presents experimental measurements that prove the in vitro and in vivo functionality of the system. Such tools may be adopted for many research and development purposes, including evaluation of new biosensor materials, and may also serve as prototypes for future miniaturized handheld or wearable devices.

Brain neurochemical monitoring

Brain neurochemical monitoring aims to provide continuous and accurate measurements of brain biomarkers. It has enabled significant advances in neuroscience for application in clinical diagnostics, treatment, and prevention of brain diseases. Microfabricated electrochemical and optical spectroscopy sensing technologies have been developed for precise monitoring of brain neurochemicals. Here, a comprehensive review on the progress of sensing technologies developed for brain neurochemical monitoring is presented. The review provides a summary of the widely measured clinically relevant neurochemicals and commonly adopted recognition technologies. Recent advances in sampling, electrochemistry, and optical spectroscopy for brain neurochemical monitoring are highlighted and their application are discussed. Existing gaps in current technologies and future directions to design industry standard brain neurochemical sensing devices for clinical applications are addressed.

Molecular Boronic Acid-Based Saccharide Sensors

Boronic acids can reversibly bind diols, a molecular feature that is ubiquitous within saccharides, leading to their use in the design and implementation of sensors for numerous saccharide species. There is a growing understanding of the importance of saccharides in many biological processes and systems; while saccharide or carbohydrate sensing in medicine is most often associated with detection of glucose in diabetes patients, saccharides have proven to be relevant in a range of disease states. Herein the relevance of carbohydrate sensing for biomedical applications is explored, and this review seeks to outline how the complexity of saccharides presents a challenge for the development of selective sensors and describes efforts that have been made to understand the underpinning fluorescence and binding mechanisms of these systems, before outlining examples of how researchers have used this knowledge to develop ever more selective receptors.