Predicting Glucose Sensor Behavior in Blood Using Transport Modeling: Relative Impacts of Protein Biofouling and Cellular Metabolic Effects

Novak, Matthew T.; Yuan, Fan; Reichert, William M.

doi:10.1177/193229681300700615

Cited by 18 publications

(30 citation statements)

References 34 publications

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“…Beyond limiting glucose uptake, dietary levels of genistein have also been shown to have beneficial effects on inflammatory and metabolic disorders, though the molecular mechanisms of these results are still yet to be fully understood [20]. The sensors surrounded by inflammatory macrophage gels exhibited signal declines that recapitulated those reported previously in both whole blood and in small animal studies [2,4,6]. In this study, the extent of signal decline was proportional to the cell’s metabolic activity where genistein-treated macrophages < untreated macrophages < LPS and PMA-treated macrophages.…”

Section: Introductionmentioning

confidence: 86%

“…Similar to our previous study, commercially available Medtronic Minimed Sof-Sensors were used as the candidate sensors in this study [2]. Sensors went through a pre-treatment calibration stage to allow for sensor equilibration and to account for sensor-to-sensor variability.…”

Section: Methodsmentioning

confidence: 99%

“…A growing body of literature is elucidating how tissue reactions to the presence of the sensor affect its function during this seven day window [1–3]. Previously, work by the authors demonstrated the negative impact that early stage inflammatory cell aggregation could have on sensor response in a whole blood ex vivo system [2]. Beyond showing a diminished signal with respect to time, the previous study demonstrated through computational modeling how the presence of macrophages proximal to the sensor surface could create a “glucose depletion zone” where the interstitial concentration of glucose with respect to distance decreases near the sensor surface due to cellular glucose consumption.…”

Section: Introductionmentioning

confidence: 99%

“…Beyond showing a diminished signal with respect to time, the previous study demonstrated through computational modeling how the presence of macrophages proximal to the sensor surface could create a “glucose depletion zone” where the interstitial concentration of glucose with respect to distance decreases near the sensor surface due to cellular glucose consumption. Additionally, it was found that the associated proteinaceous mat had virtually no effect on sensor performance [2]. …”

Section: Introductionmentioning

confidence: 99%

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Macrophage embedded fibrin gels: An in vitro platform for assessing inflammation effects on implantable glucose sensors

2014

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The erroneous and unpredictable behavior of percutaneous glucose sensors just days following implantation has limited their clinical utility for diabetes management. Recent research has implicated the presence of adherent inflammatory cells as the key mitigating factor limiting sensor functionality in this period of days post-implantation. Here we present a novel in vitro platform to mimic the cell-embedded provisional matrix that forms adjacent to the sensor immediately after implantation for the focused investigation of the effects of early stage tissue response on sensor function. This biomimetic surrogate is formed by imbibing fibrin-based gels with physiological densities of inflammatory RAW 264.7 macrophages. When surrounding functional sensors, macrophage-embedded fibrin gels contribute to sensor signal declines that are similar in both shape and magnitude to those observed in previous whole blood and small animal studies. Signal decline in the presence of gels is both metabolically-mediated and sensitive to cell type and activation. Computational modeling of the experimental setup is also presented to validate the design by showing that the cellular glucose uptake parameters necessary to achieve such experimental declines align well with literature values. Together, these data suggest this in vitro provisional matrix surrogate may serve as an effective screening tool for testing the biocompatibility of future glucose sensor designs.

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Section: Introductionmentioning

confidence: 86%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Macrophage embedded fibrin gels: An in vitro platform for assessing inflammation effects on implantable glucose sensors

2014

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“…23,24 Functionally speaking, sensor behavior during this period would best be considered as anomalous and erratic, further limiting sensor efficacy even during the FDA-approved time window.…”

Section: Modeling Early Stage Sensor Responsementioning

confidence: 99%

Modeling the Physiological Factors Affecting Glucose Sensor Function in Vivo

Novak

Reichert

2015

J Diabetes Sci Technol

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For implantable sensors to become a more viable option for continuous glucose monitoring strategies, they must be able to persist in vivo for periods longer than the 3-to 7-day window that is the current industry standard. Recent studies have attributed such limited performance to tissue reactions resulting from implantation. While in vivo biocompatibility studies have provided much in the way of understanding histology surrounding an implanted sensor, little is known about how each constituent of the foreign body response affects sensor function. Due to the ordered composition and geometry of implantassociated tissue reactions, their effects on sensor function may be computationally modeled and analyzed in a way that would be prohibitive using in vivo studies. This review both explains how physiologically accurate computational models of implant-associated tissue reaction can be designed and shows how they have been utilized thus far. Going forward, these in silico models of implanted sensor behavior may soon complement in vivo studies to provide valuable information for improved sensor designs.

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Wearable Glucose Monitoring and Implantable Drug Delivery Systems for Diabetes Management

Zhang

Lim

et al. 2021

Adv Healthcare Materials

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The global cost of diabetes care exceeds $1 trillion each year with more than $327 billion being spent in the United States alone. Despite some of the advances in diabetes care including continuous glucose monitoring systems and insulin pumps, the technology associated with managing diabetes has largely remained unchanged over the past several decades. With the rise of wearable electronics and novel functional materials, the field is well‐poised for the next generation of closed‐loop diabetes care. Wearable glucose sensors implanted within diverse platforms including skin or on‐tooth tattoos, skin‐mounted patches, eyeglasses, contact lenses, fabrics, mouthguards, and pacifiers have enabled noninvasive, unobtrusive, and real‐time analysis of glucose excursions in ambulatory care settings. These wearable glucose sensors can be integrated with implantable drug delivery systems, including an insulin pump, glucose responsive insulin release implant, and islets transplantation, to form self‐regulating closed‐loop systems. This review article encompasses the emerging trends and latest innovations of wearable glucose monitoring and implantable insulin delivery technologies for diabetes management with a focus on their advanced materials and construction. Perspectives on the current unmet challenges of these strategies are also discussed to motivate future technological development toward improved patient care in diabetes management.

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Predicting Glucose Sensor Behavior in Blood Using Transport Modeling: Relative Impacts of Protein Biofouling and Cellular Metabolic Effects

Abstract: Abbreviations: (ANCOVA) analysis of covariance, (PBS) phosphate-buffered saline, (PPP) platelet-poor plasma, (SEM) scanning electron microscope Keywords: biocompatibility, biomaterials, biosensors, modeling

Cited by 18 publications

References 34 publications

Macrophage embedded fibrin gels: An in vitro platform for assessing inflammation effects on implantable glucose sensors

Macrophage embedded fibrin gels: An in vitro platform for assessing inflammation effects on implantable glucose sensors

Modeling the Physiological Factors Affecting Glucose Sensor Function in Vivo

Wearable Glucose Monitoring and Implantable Drug Delivery Systems for Diabetes Management

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