Modeling glucose and water dynamics in human skin

Noninvasive Glucose Sensing In Vivo

Blood glucose monitoring is an essential aspect of disease management for individuals with diabetes. Unfortunately, traditional methods require collecting a blood sample and thus are invasive and inconvenient. Recent developments in minimally invasive continuous glucose monitors have provided a more convenient alternative for people with diabetes to track their glucose levels 24/7. Despite this progress, many challenges remain to establish a noninvasive monitoring technique that works accurately and reliably in the wild. This review encompasses the current advancements in noninvasive glucose sensing technology in vivo, delves into the common challenges faced by these systems, and offers an insightful outlook on existing and future solutions.

Microneedle Patch for Painless Intradermal Collection of Interstitial Fluid Enabling Multianalyte Measurement of Small Molecules, SARS-CoV-2 Antibodies, and Protein Profiling

Blood sampling is a common practice to monitor health, but it entails a series of drawbacks for patients including pain and discomfort. Thus, there is a demand for more convenient ways to obtain samples. Modern analytical techniques enable monitoring of multiple bioanalytes in smaller samples, opening possibilities for new matrices, and microsampling technologies to be adopted. Interstitial fluid (ISF) is an attractive alternative matrix that shows good correlation with plasma concentration dynamics for several analytes and can be sampled in a minimally invasive and painless manner from the skin at the point-of-care. However, there is currently a lack of sampling devices compatible with clinical translation. Here, to tackle state-of-the-art limitations, a cost-effective and compact single-microneedle-based device designed to painlessly collect precisely 1.1 µL of dermal ISF within minutes is presented. The fluid is volume-metered, dried, and stably stored into analytical-grade paper within the microfluidic device. The obtained sample can be mailed to a laboratory, quantitatively analyzed, and provide molecular insights comparable to blood testing. In a human study, the possibility to monitor various classes of molecular analytes is demonstrated in ISF microsamples, including caffeine, hundreds of proteins, and SARS-CoV-2 antibodies, some being detected in ISF for the first time.

Energy-Efficient, On-Demand Activation of Biosensor Arrays for Long-Term Continuous Health Monitoring

Wearable biosensors for continuous health monitoring, particularly those used for glucose detection, have a limited operational lifetime due to biodegradation and fouling. As a result, patients must change sensors frequently, increasing cost and patient discomfort. Arrays of multiple sensors, where the individual devices can be activated on demand, increase overall operational longevity, thereby reducing cost and improving patient outcomes. This work demonstrates the feasibility of this approach via decomposition of combustible nitrocellulose membranes that protect the individual sensors from exposure to bioanalytes using a current pulse. Metal contacts, connected by graphene-loaded PEDOT:PSS polymer on the surface of the membrane, deliver the required energy to decompose the membrane. Nitrocellulose membranes with a thickness of less than 1 µm consistently transfer on to polydimethylsiloxane (PDMS) wells. An electrical energy as low as 68 mJ has been shown to suffice for membrane decomposition.

Phenomenological-based model of glucose transport from liver to abdominal subcutaneous adipose tissue

BACKGROUND

A good treatment for type 1 diabetes mellitus (T1DM) requires accurate measurements of blood glucose levels. Continuous glucose monitors (CGM) measure the glucose concentration in the interstitial fluid of the abdominal subcutaneous adipose tissue. However, glucose measured in the abdominal interstitial fluid does not represent blood glucose concentrations accurately due to the complex blood transport through the body and glucose diffusion in interstitial fluid.

METHODS

To gain insight into this problem, a phenomenological-based semiphysical model (PBSM) of glucose transport by volumetric flow and diffusion from the bloodstream to interstitial fluid was constructed. A published 10-step modeling procedure was used to obtain a model for glucose transport time through the blood vessels and from the blood capillaries to the interstitial fluid, glucose diffusion within the interstitial fluid, and glucose diffusion through the semipermeable coating of the sensor needle. For this model, a healthy person is considered at rest with average parameters.

RESULTS

The simulations performed using the PBSM allow obtaining the glucose transport time from the liver to the sensor needle. In this way, it is possible to reconstruct an accurate dynamic measurement of blood glucose from the measurements in the interstitial fluid of the abdominal subcutaneous adipose tissue.

CONCLUSIONS

PBSMs with parameters interpretability illustrate the connection of glucose concentrations in the interstitial fluid with that currently in the blood. Implementing this model in a CGM will result in more reliable measurements of blood glucose levels for T1DM treatment.

E-Skin: The Dawn of a New Era of On-Body Monitoring Systems

Real-time "on-body" monitoring of human physiological signals through wearable systems developed on flexible substrates (e-skin) is the next target in human health control and prevention, while an alternative to bulky diagnostic devices routinely used in clinics. The present work summarizes the recent trends in the development of e-skin systems. Firstly, we revised the material development for e-skin systems. Secondly, aspects related to fabrication techniques were presented. Next, the main applications of e-skin systems in monitoring, such as temperature, pulse, and other bio-electric signals related to health status, were analyzed. Finally, aspects regarding the power supply and signal processing were discussed. The special features of e-skin as identified contribute clearly to the developing potential as in situ diagnostic tool for further implementation in clinical practice at patient personal levels.

The Influence of Skin Thickness on Flash Glucose Monitoring System Accuracy in Dogs with Diabetes Mellitus

Simple Summary

A flash glucose monitoring system (FGMS) has been validated for use in dogs with diabetes mellitus and diabetic ketoacidosis. It continuously measures the glucose in the interstitial fluid through a small filament (5 mm long) inserted under the skin. Interstitial glucose concentrations are reportedly comparable to whole blood glucose concentrations. However, several factors can influence the performance of interstitial sensors, including the proportion of interstitial fluid in a tissue. The influence of skin thickness on flash glucose monitoring system accuracy has not been investigated in previous studies; therefore, the aim of this study was to evaluate whether FGMS accuracy is affected by skin thickness. On the basis of our results, skin thickness seems to affect FGMS measurements; the mean bias was significantly inversely correlated (p = 0.02; r = −0.6) with the mean skin thickness, and clinical accuracy according to ISO 15197:2013 criteria was observed only in dogs with skin thickness > 5 mm, with 99% of the results falling in zone A + B of the Parkes consensus error grid analysis. In dogs with thin skin (<5 mm), the clinical accuracy was low, and the results should be interpreted with caution.

Abstract

A flash glucose monitoring system (FGMS) has been validated for use in diabetic dogs. However, it is unknown whether skin thickness affects FGMS measurements. The aim of this study was to evaluate whether FGMS accuracy is affected by skin thickness. Fourteen client-owned diabetic dogs on insulin treatment were prospectively enrolled in the study. The dogs were divided into two groups according to their ultrasound-measured skin thickness: dogs with skin thickness < 5 mm (Group 1) and dogs with skin thickness > 5 mm (Group 2). On days 1, 7 and 14, glucose curves were obtained simultaneously using the FGMS and a validated portable blood glucose meter. Paired measurements were used to calculate the mean bias and to determine accuracy according to ISO 15197:2013 criteria. The mean bias was significantly inversely correlated (p = 0.02; r = −0.6) with the mean skin thickness. Clinical accuracy was observed only in Group 2, with 99% of the results in zone A + B of the Parkes consensus error grid analysis. In conclusion, skin thickness seems to affect FGMS measurements, and the device is accurate in dogs with thicker skin (>5 mm); in dogs with thin skin (<5 mm), the clinical accuracy is low, and the results should be interpreted with caution.

Real-time intradermal continuous glucose monitoring using a minimally invasive microneedle-based system

Continuous glucose monitoring (CGM) has the potential to greatly improve diabetes management. The aim of this work is to show a proof-of-concept CGM device which performs minimally invasive and minimally delayed in-situ glucose sensing in the dermal interstitial fluid, combining the advantages of microneedle-based and commercially available CGM systems. The device is based on the integration of an ultra-miniaturized electrochemical sensing probe in the lumen of a single hollow microneedle, separately realized using standard silicon microfabrication methods. By placing the sensing electrodes inside the lumen facing an opening towards the dermal space, real-time measurement purely can be performed relying on molecular diffusion over a short distance. Furthermore, the device relies only on passive capillary lumen filling without the need for complex fluid extraction mechanisms. Importantly, the transdermal portion of the device is 50 times smaller than that of commercial products. This allows access to the dermis and simultaneously reduces tissue trauma, along with being virtually painless during insertion. The three-electrode enzymatic sensor alone was previously proven to have satisfactory sensitivity (1.5 nA/mM), linearity (up to 14 mM), selectivity, and long-term stability (up to 4 days) in-vitro. In this work we combine this sensor technology with microneedles for reliable insertion in forearm skin. In-vivo human tests showed the possibility to correctly and dynamically track glycaemia over time, with approximately 10 min delay with respect to capillary blood control values, in line with the expected physiological lag time. The proposed device can thus reduce discomfort and potentially enable less invasive real-time CGM in diabetic patients.

Miniaturized Planar Room Temperature Ionic Liquid Electrochemical Gas Sensor for Rapid Multiple Gas Pollutants Monitoring

The growing impact of airborne pollutants and explosive gases on human health and occupational safety has escalated the demand of sensors to monitor hazardous gases. This paper presents a new miniaturized planar electrochemical gas sensor for rapid measurement of multiple gaseous hazards. The gas sensor features a porous polytetrafluoroethylene substrate that enables fast gas diffusion and room temperature ionic liquid as the electrolyte. Metal sputtering was utilized for platinum electrodes fabrication to enhance adhesion between the electrodes and the substrate. Together with carefully selected electrochemical methods, the miniaturized gas sensor is capable of measuring multiple gases including oxygen, methane, ozone and sulfur dioxide that are important to human health and safety. Compared to its manually-assembled Clark-cell predecessor, this sensor provides better sensitivity, linearity and repeatability, as validated for oxygen monitoring. With solid performance, fast response and miniaturized size, this sensor is promising for deployment in wearable devices for real-time point-of-exposure gas pollutant monitoring.

Optimal experiment design for model selection in biochemical networks

Background

Mathematical modeling is often used to formalize hypotheses on how a biochemical network operates by discriminating between competing models. Bayesian model selection offers a way to determine the amount of evidence that data provides to support one model over the other while favoring simple models. In practice, the amount of experimental data is often insufficient to make a clear distinction between competing models. Often one would like to perform a new experiment which would discriminate between competing hypotheses.

Results

We developed a novel method to perform Optimal Experiment Design to predict which experiments would most effectively allow model selection. A Bayesian approach is applied to infer model parameter distributions. These distributions are sampled and used to simulate from multivariate predictive densities. The method is based on a k-Nearest Neighbor estimate of the Jensen Shannon divergence between the multivariate predictive densities of competing models.

Conclusions

We show that the method successfully uses predictive differences to enable model selection by applying it to several test cases. Because the design criterion is based on predictive distributions, which can be computed for a wide range of model quantities, the approach is very flexible. The method reveals specific combinations of experiments which improve discriminability even in cases where data is scarce. The proposed approach can be used in conjunction with existing Bayesian methodologies where (approximate) posteriors have been determined, making use of relations that exist within the inferred posteriors.

Interstitium versus Blood Equilibrium in Glucose Concentration and its Impact on Subcutaneous Continuous Glucose Monitoring Systems

The relationship between both interstitial and blood glucose remains a debated topic, on which there is still no consensus. The experimental evidence suggests that blood and interstitial fluid glucose levels are correlated by a kinetic equilibrium, which as a consequence has a time and magnitude gradient in glucose concentration between blood and interstitium. Furthermore, this equilibrium can be perturbed by several physiological effects (such as foreign body response, wound-healing effect, etc.), with a consequent reduction of interstitial fluid glucose versus blood glucose correlation. In the present study, the impact of operating in the interstitium on continuous glucose monitoring systems (CGMs) will be discussed in depth, both for the application of CGMs in the management of diabetes and in other critical areas, such as tight glycaemic control in critically ill patients.

Parameter uncertainty in biochemical models described by ordinary differential equations

Improved mechanistic understanding of biochemical networks is one of the driving ambitions of Systems Biology. Computational modeling allows the integration of various sources of experimental data in order to put this conceptual understanding to the test in a quantitative manner. The aim of computational modeling is to obtain both predictive as well as explanatory models for complex phenomena, hereby providing useful approximations of reality with varying levels of detail. As the complexity required to describe different system increases, so does the need for determining how well such predictions can be made. Despite efforts to make tools for uncertainty analysis available to the field, these methods have not yet found widespread use in the field of Systems Biology. Additionally, the suitability of the different methods strongly depends on the problem and system under investigation. This review provides an introduction to some of the techniques available as well as gives an overview of the state-of-the-art methods for parameter uncertainty analysis.

Minimizing the impact of time lag variability on accuracy evaluation of continuous glucose monitoring systems

BACKGROUND

Despite all commercially available continuous glucose monitoring (CGM) systems being designed to operate in the extracellular interstitial fluid, and even though there is a well-recognized time lag between the interstitial and the venous compartments, the accuracy of the CGM device readings is still evaluated against the glucose concentration in venous blood (VB) samples, thus resulting in a perceived decrease in accuracy. This article explains how different time lag compensation methods (no compensation, compensation with a fixed delay, compensation with a variable delay based on an intercompartmental diffusional model) have an impact on how CGM accuracy is evaluated.

METHODS

The data set used consisted of 210 CGM/blood glucose data pairs from 18 diabetes subjects (15 type 1 and 3 type 2) selected from a data base collected during two independent clinical trials. All CGM measurements were performed using the GlucoMen ®Day CGM system (A. Menarini Diagnostics, Italy), and the reference VB glucose measurements by means of a standard laboratory instrument. For each applied time lag compensation method, the CGM accuracy evaluation was performed as recommended by the POCT05-A consensus guideline.

RESULTS

The perceived accuracy of the CGM device significantly improved when applying both the fixed or the variable delay compensation method. However, it is worth noting how the variable delay method, which relies on a closer description of the intercompartmental diffusion processes, provided the best perception of the clinical accuracy of the device.

CONCLUSIONS

When assessing the accuracy of a CGM system, a crucial step in data analysis is to account for time lag, which enables minimization of the apparent decline in system accuracy.

Glucose sensing in human epidermis using mid-infrared photoacoustic detection

No reliable non-invasive glucose monitoring devices are currently available. We implemented a mid-infrared (MIR) photoacoustic (PA) setup to track glucose in vitro in deep epidermal layers, which represents a significant step towards non-invasive in vivo glucose measurements using MIR light. An external-cavity quantum-cascade laser (1010-1095 cm(-1)) and a PA cell of only 78 mm(3) volume were employed to monitor glucose in epidermal skin. Skin samples are characterized by a high water content. Such samples investigated with an open-ended PA cell lead to varying conditions in the PA chamber (i.e., change of light absorption or relative humidity) and cause unstable signals. To circumvent variations in relative humidity and possible water condensation, the PA chamber was constantly ventilated by a 10 sccm N(2) flow. By bringing the epidermal skin samples in contact with aqueous glucose solutions with different concentrations (i.e., 0.1-10 g/dl), the glucose concentration in the skin sample was varied through passive diffusion. The achieved detection limit for glucose in epidermal skin is 100 mg/dl (SNR=1). Although this lies within the human physiological range (30-500 mg/dl) further improvements are necessary to non-invasively monitor glucose levels of diabetes patients. Furthermore spectra of epidermal tissue with and without glucose content have been recorded with the tunable quantum-cascade laser, indicating that epidermal constituents do not impair glucose detection.

Quantifying the composition of human skin for glucose sensor development

BACKGROUND

Glucose is heterogeneously distributed within human skin. In order to develop a glucose measurement method for human skin, both a good quantification of the different compartments of human skin and an understanding of glucose transport processes are essential. This study focused on the composition of human skin. In addition, the extent to which intersubject variability in skin composition alters glucose dynamics in human skin was investigated.

METHODS

To quantify the composition of the three layers of human skin-epidermis, dermis, and adipose tissue-cell and blood vessel volumes were calculated from skin biopsies. These results were combined with data from the literature. The composition was applied as input for a previously developed computational model that calculates spatiotemporal glucose dynamics in human skin. The model was used to predict the physiological effects of intersubject variability in skin composition on glucose profiles in human skin.

RESULTS

According to the model, the lag time of glucose dynamics in the epidermis was sensitive to variation in the volumes of interstitial fluid, cells, and blood of all layers. Data showed most variation/uncertainty in the volume composition of the adipose tissue. This variability mainly influences the dynamics in the adipose tissue.

CONCLUSIONS

This study identified the intersubject variability in human skin composition. The study shows that this variability has significant influence on the glucose dynamics in human skin. In addition, it was determined which volumes are most critical for the quantification and interpretation of measurements in the different layers.

Impact of tissue heterogeneity on noninvasive near-infrared glucose measurements in interstitial fluid of rat skin

BACKGROUND

Movement of the optical interface used to collect noninvasive near-infrared spectra is known to dramatically increase prediction errors for glucose concentration measurements within the interstitial fluid of living rat skin. Prediction errors increase by more than 2.5-fold when the interface is moved before each non-invasive measurement compared to measurements where the interface position is constant throughout. Chemical heterogeneity of the skin matrix is examined as a possible mechanism for the strong sensitivity to the interface placement during noninvasive measurements conducted from transmission near-infrared absorption spectroscopy.

METHOD

Microspectroscopy was performed over a region of the near-infrared spectrum (4000-5000 cm(-1)) to map the concentrations of water, collagen protein, fat, and keratin protein within the skin tissue matrix through which noninvasive spectra are collected. Maps were created for multiple samples of skin excised from male and female animals. Sets of near-infrared spectra were constructed to simulate noninvasive spectra in accord with the basic tissue composition found from the microspectroscopic maps with added information corresponding to a span of glucose concentrations ranging from 5 to 35 mM and Gaussian-distributed noise.

RESULTS

Microspectroscopic maps of rat skin reveal similar patterns of heterogeneity for major chemical components of skin samples excised from both male and female animals. These maps demonstrate concentration domains with dimensions similar to the size of the fiber interface used to collect noninvasive spectra. Partial least squares calibration models generated from sets of simulated spectra demonstrate increases in prediction errors for glucose when the spectral matrix is changed in accord with the degree of chemical heterogeneity displayed in the skin maps. Prediction errors typically increase between 100 and 1000% when comparing errors generated from spectra that represent a single tissue composition versus spectra that represent a varied skin composition in accord with the distribution displayed in the skin maps.

CONCLUSIONS

The distribution of the major components of skin is not uniform, but establishes domains within the skin matrix that strongly impact prediction errors for the noninvasive spectroscopic measurement of glucose within the interstitial fluid of rat dermis tissue. The observed increase in prediction error (>2.5-fold) determined from actual noninvasive measurements is within the lower range of prediction error increases demonstrated by this simulation study. These findings implicate that chemical heterogeneity within the tissue matrix is a major factor in the sensitivity of the location of the fiber interface used to collect noninvasive spectral data.

A tale of two compartments: interstitial versus blood glucose monitoring

Self-monitoring of blood glucose was described as one of the most important advancements in diabetes management since the invention of insulin in 1920. Recent advances in glucose sensor technology for measuring interstitial glucose concentrations have challenged the dominance of glucose meters in diabetes management, while raising questions about the relationships between interstitial and blood glucose levels. This article will review the differences between interstitial and blood glucose and some of the challenges in measuring interstitial glucose levels accurately.

Requirements for calibration in noninvasive glucose monitoring by Raman spectroscopy

BACKGROUND

In the development of noninvasive glucose monitoring technology, it is highly desirable to derive a calibration that relies on neither person-dependent calibration information nor supplementary calibration points furnished by an existing invasive measurement technique (universal calibration).

METHOD

By appropriate experimental design and associated analytical methods, we establish the sufficiency of multiple factors required to permit such a calibration. Factors considered are the discrimination of the measurement technique, stabilization of the experimental apparatus, physics-physiology-based measurement techniques for normalization, the sufficiency of the size of the data set, and appropriate exit criteria to establish the predictive value of the algorithm.

RESULTS

For noninvasive glucose measurements, using Raman spectroscopy, the sufficiency of the scale of data was demonstrated by adding new data into an existing calibration algorithm and requiring that (a) the prediction error should be preserved or improved without significant re-optimization, (b) the complexity of the model for optimum estimation not rise with the addition of subjects, and (c) the estimation for persons whose data were removed entirely from the training set should be no worse than the estimates on the remainder of the population. Using these criteria, we established guidelines empirically for the number of subjects (30) and skin sites (387) for a preliminary universal calibration. We obtained a median absolute relative difference for our entire data set of 30 mg/dl, with 92% of the data in the Clarke A and B ranges.

CONCLUSIONS

Because Raman spectroscopy has high discrimination for glucose, a data set of practical dimensions appears to be sufficient for universal calibration. Improvements based on reducing the variance of blood perfusion are expected to reduce the prediction errors substantially, and the inclusion of supplementary calibration points for the wearable device under development will be permissible and beneficial.