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In this article, we demonstrate an improved efficient fibre sensor with a high sensitivity to measure glucose concentrations in the physiological range of human beings, operating in a broad spectral bandwidth from the near- to mid-infrared. The sensor consists of a dual-peak long period grating (DPLPG) with a period of 150 μm inscribed in an optical fibre with a diameter of 80 μm. The investigation of sensing for refractive index results in a sensitivity of ~−885.7 nm/refractive index unit (RIU) and ~2008.6 nm/RIU in the range of 1.30–1.44. The glucose measurement is achieved by the immobilisation of a layer of enzyme of glucose oxidase (GOD) onto the fibre surface for the selective enhancement of sensitivity for glucose. The sensor can measure glucose concentrations with a maximum sensitivity of −36.25 nm/(mg/mL) in the range of 0.1–3.0 mg/mL. To the best of our knowledge, this is the highest sensitivity ever achieved for a measurement of glucose with a long period grating-based sensor, indicating its potential for many applications including pharmaceutical, biomedical and food industries.

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.

Porous materials are currently the basis of many optical sensors because of their ability to provide a higher interaction between the light and the analyte, directly within the optical structure. In this study, mesoporous TiO2 layers were fabricated using a bottom-up synthesis approach in order to develop optical sensing structures. In comparison with more typical top-down fabrication strategies where the bulk constitutive material is etched in order to obtain the required porous medium, the use of a bottom-up fabrication approach potentially allows increasing the interconnectivity of the pore network, hence improving the surface and depth homogeneity of the fabricated layer and reducing production costs by synthesizing the layers on a larger scale. The sensing performance of the fabricated mesoporous TiO2 layers was assessed by means of the measurement of several glucose dilutions in water, estimating a limit of detection even below 0.15 mg/mL (15 mg/dL). All of these advantages make this platform a very promising candidate for the development of low-cost and high-performance optical sensors.

In this review, a selection of works on the sensing of biomarkers related to diabetes mellitus (DM) and diabetic retinopathy (DR) are presented, with the scope of helping and encouraging researchers to design sensor-array machine-learning (ML)-supported devices for robust, fast, and cost-effective early detection of these devastating diseases. First, we highlight the social relevance of developing systematic screening programs for such diseases and how sensor-arrays and ML approaches could ease their early diagnosis. Then, we present diverse works related to the colorimetric and electrochemical sensing of biomarkers related to DM and DR with non-invasive sampling (e.g., urine, saliva, breath, tears, and sweat samples), with a special mention to some already-existing sensor arrays and ML approaches. We finally highlight the great potential of the latter approaches for the fast and reliable early diagnosis of DM and DR.

The measurement and quantification of glucose concentrations is a field of major interest, whether motivated by potential clinical applications or as a prime example of biosensing in basic research. In recent years, optical sensing methods have emerged as promising glucose measurement techniques in the literature, with surface-enhanced infrared absorption (SEIRA) spectroscopy combining the sensitivity of plasmonic systems and the specificity of standard infrared spectroscopy. The challenge addressed in this paper is to determine the best method to estimate the glucose concentration in aqueous solutions in the presence of fructose from the measured reflectance spectra. This is referred to as the inverse problem of sensing and usually solved via linear regression. Here, instead, several advanced machine learning regression algorithms are proposed and compared, while the sensor data are subject to a pre-processing routine aiming to isolate key patterns from which to extract the relevant information. The most accurate and reliable predictions were finally made by a Gaussian process regression model which improves by more than 60% on previous approaches. Our findings give insight into the applicability of machine learning methods of regression for sensor calibration and explore the limitations of SEIRA glucose sensing.

For the hundreds of millions of worldwide diabetic patients, glucose test strips are the most important and commonly used tool for monitoring blood glucose levels. Commercial test strips use glucose oxidases as recognition agents, which increases the cost and reduces the durability of test strips. To lower the cost of glucose sensors, we developed a paper-based electrical sensor with molecularly imprinted glucose recognition sites and demonstrated the determination of various glucose concentrations in bovine blood solutions. The sensing electrode is integrated with molecular recognition sites in the conductive polymer. A calibration graph as a function of glucose concentration in aqueous solution was acquired and matched with a correlation coefficient of 0.989. We also demonstrated the determination of the added glucose concentrations ranging from 2.2 to 11.1 mM in bovine blood samples with a linear correlation coefficient of 0.984. This non-enzymatic glucose sensor has the potential to reduce the health care cost of test strips as well as make glucose sensor test strips more accessible to underserved communities.

Printed electronics have led to new possibilities in the detection and quantification of a wide range of molecules important for medical, biotechnological, and environmental fields. The integration with microfluidics is often adopted to avoid hand-deposition of little volumes of reagents and samples on miniaturized electrodes that strongly depend on operator’s skills. Here we report design, fabrication and test of an easy-to-use electrochemical sensor platform with microfluidics entirely realized with Aerosol Jet Printing (AJP). We printed a six-electrochemical-sensors platform with AJP and we explored the possibility to aerosol jet print directly on it a microfluidic structure without any support material. Thus, the sacrificial material removal and/or the assembly with sensors steps are avoided. The repeatability observed when printing both conductive and ultraviolet (UV)-curable polymer inks can be supported from the values of relative standard deviation of maximum 5% for thickness and 9% for line width. We designed the whole microfluidic platform to make the sample deposition (20 μL) independent from the operator. To validate the platform, we quantified glucose at different concentrations using a standard enzyme-mediated procedure. Both mediator and enzyme were directly aerosol jet printed on working electrodes (WEs), thus the proposed platform is entirely fabricated by AJP and ready to use. The chronoamperometric tests show limit of detection (LOD) = 2.4 mM and sensitivity = 2.2 ± 0.08 µA/mM confirming the effectiveness of mediator and enzyme directly aerosol jet printed to provide sensing in a clinically relevant range (3–10 mM). The average relative standard inter-platform deviation is about 8%. AJP technique can be used for fabricating a ready-to-use microfluidic device that does not need further processing after fabrication, but is promptly available for electrochemical sample analysis.

We report fabrication of a microneedle-based three-electrode integrated electrochemical sensor and in-vitro characterization of this sensor for glucose sensing applications. A piece of silicon was sequentially dry and wet etched to form a 15 × 15 array of tall (approximately 380 µm) sharp silicon microneedles. Iron catalyst was deposited through a SU-8 shadow mask to form the working electrode and counter electrode. A multi-walled carbon nanotube forest was grown directly on the silicon microneedle array and platinum nano-particles were electrodeposited. Silver was deposited on the Si microneedle array through another shadow mask and chlorinated to form a Ag/AgCl reference electrode. The 3-electrode electrochemical sensor was tested for various glucose concentrations in the range of 3~20 mM in 0.01 M phosphate buffered saline (PBS) solution. The sensor’s amperometric response to the glucose concentration is linear and its sensitivity was found to be 17.73 ± 3 μA/mM-cm2. This microneedle-based sensor has a potential to be used for painless diabetes testing applications.

Besides being the favorite carbon and energy source for the budding yeast Sacchromyces cerevisiae, glucose can act as a signaling molecule to regulate multiple aspects of yeast physiology. Yeast cells have evolved several mechanisms for monitoring the level of glucose in their habitat and respond quickly to frequent changes in the sugar availability in the environment: the cAMP/PKA pathways (with its two branches comprising Ras and the Gpr1/Gpa2 module), the Rgt2/Snf3-Rgt1 pathway and the main repression pathway involving the kinase Snf1. The cAMP/PKA pathway plays the prominent role in responding to changes in glucose availability and initiating the signaling processes that promote cell growth and division. Snf1 (the yeast homologous to mammalian AMP-activated protein kinase) is primarily required for the adaptation of yeast cell to glucose limitation and for growth on alternative carbon source, but it is also involved in the cellular response to various environmental stresses. The Rgt2/Snf3-Rgt1 pathway regulates the expression of genes required for glucose uptake. Many interconnections exist between the diverse glucose sensing systems, which enables yeast cells to fine tune cell growth, cell cycle and their coordination in response to nutritional changes.

A semiconducting water-soluble core-shell quantum dots (QDs) system capped with thiolated ligand was used in this study for the sensitive detection of glucose in aqueous samples. The QDs selected are of CdSe-coated ZnS and were prepared in house based on a hot injection technique. The formation of ZnS shell at the outer surface of CdSe core was made via a specific process namely, SILAR (successive ionic layer adsorption and reaction). The distribution, morphology, and optical characteristics of the prepared core-shell QDs were assessed by transmission electron microscopy (TEM) and spectrofluorescence, respectively. From the analysis, the results show that the mean particle size of prepared QDs is in the range of 10–12 nm and that the optimum emission condition was displayed at 620 nm. Further, the prepared CdSe/ZnS core shell QDs were modified by means of a room temperature ligand-exchange method that involves six organic ligands, L-cysteine, L-histidine, thio-glycolic acid (TGA or mercapto-acetic acid, MAA), mercapto-propionic acid (MPA), mercapto-succinic acid (MSA), and mercapto-undecanoic acid (MUA). This process was chosen in order to maintain a very dense water solubilizing environment around the QDs surface. From the analysis, the results show that the CdSe/ZnS capped with TGA (CdSe/ZnS-TGA) exhibited the strongest fluorescence emission as compared to others; hence, it was tested further for the glucose detection after their treatment with glucose oxidase (GOx) and horseradish peroxidase (HRP) enzymes. Here in this study, the glucose detection is based on the fluorescence quenching effect of the QDs, which is correlated to the oxidative reactions occurred between the conjugated enzymes and glucose. From the analysis of results, it can be inferred that the resultant GOx:HRP/CdSe/ZnS-TGA QDs system can be a suitable platform for the fluorescence-based determination of glucose in the real samples.

Perturbations in glucose homeostasis is critical for human health, as hyperglycemia (defining diabetes) leads to premature death caused by macrovascular and microvascular complications. However, the simple and accurate detection of glucose in the blood at low cost remains a challenging task, although it is of great importance for the diagnosis and therapy of diabetic patients. In this work, carbon quantum dots decorated with copper oxide nanostructures (CQDs/Cu2O) are prepared by a simple hydrothermal approach, and their potential for electrochemical non-enzymatic glucose sensing is evaluated. The proposed sensor exhibits excellent electrocatalytic activity towards glucose oxidation in alkaline solutions. The glucose sensor is characterized by a wide concentration range from 6 µM to 6 mM, a sensitivity of 2.9 ± 0.2 µA·µM−1·cm−2, and a detection limit of 6 µM at a signal-to-noise ratio S/N = 3. The sensors are successfully applied for glucose determination in human serum samples, demonstrating that the CQDs/Cu2O-based glucose sensor satisfies the requirements of complex sample detection with adapted potential for therapeutic diagnostics.