Noninvasive measurement of glucose in artificial plasma with near-infrared and Raman spectroscopy

Online detection of concentrate grade in the antimony flotation process based on in situ Raman spectroscopy combined with a CNN-GRU hybrid model

Froth flotation is the most critical process for separating stibnite from raw ore. Concentrate grade is a vital production indicator in the antimony flotation process. It is a direct reflection of the product quality of the flotation process and an essential basis for the dynamic adjustment of its operating parameters. Existing methods of measuring concentrate grades suffer from expensive measurement equipment, difficult maintenance of complex sampling systems, and extended testing times. This paper presents a nondestructive and fast methodology to quantify the concentrate grade in the antimony flotation process based on in situ Raman spectroscopy. A particular Raman spectroscopic measuring system is designed for on-line measurement of the Raman spectra of the mixed minerals from the froth layer during the antimony flotation process. To obtain representative Raman spectra that better characterize the concentrate grades, a traditional Raman spectroscopic system has been redesigned to account for the different interferences during actual flotation field acquisition. A one-dimensional convolutional neural network (1D-CNN) is combined with a gated recurrent unit (GRU) and applied to construct a model for online prediction of concentrate grades based on continuously collected Raman spectra of mixed minerals in the froth layer. With an average prediction error of 4.37% and a maximum prediction deviation of 10.56%, the quantitative analysis of concentrate grade by the model demonstrates that our method is distinguished by high accuracy, low deviation, and in situ analysis, and it essentially satisfies the requirements for online quantitative determination of concentrate grade in the antimony flotation site.

Non-Invasive Monitoring of Human Health by Photoacoustic Spectroscopy

For certain diseases, the continuous long-term monitoring of the physiological condition is crucial. Therefore, non-invasive monitoring methods have attracted widespread attention in health care. This review aims to discuss the non-invasive monitoring technologies for human health based on photoacoustic spectroscopy. First, the theoretical basis of photoacoustic spectroscopy and related devices are reported. Furthermore, this article introduces the monitoring methods for blood glucose, blood oxygen, lipid, and tumors, including differential continuous-wave photoacoustic spectroscopy, microscopic photoacoustic spectroscopy, mid-infrared photoacoustic detection, wavelength-modulated differential photoacoustic spectroscopy, and others. Finally, we present the limitations and prospects of photoacoustic spectroscopy.

Analysis of bodily fluids using vibrational spectroscopy: a direct comparison of Raman scattering and infrared absorption techniques for the case of glucose in blood serum

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies.

Insulin-loaded hydroxypropyl methyl cellulose-co-polyacrylamide-co-methacrylic acid hydrogels used as rectal suppositories to regulate the blood glucose of diabetic rats

The purpose of this study was developing a novel hydroxypropyl methyl cellulose-co-polyacrylamide-co-methacrylic acid (HPMC-co-PAM-co-PMAA) hydrogel, which was used as rectal suppository to regulate the blood glucose of diabetes. HPMC-co-PAM-co-PMAA hydrogel was fabricated via free-radical polymerization. Fourier transform infrared spectroscopy (FTIR) and Raman spectra were used to confirm the fabrication of HPMC-co-PAM-co-PMAA hydrogel. Their inner morphology was observed with scanning electron microscope (SEM). The extracts of hydrogel were applied to study their cell viability. The hypoglycemic effects of insulin (INS)-loaded HPMC-co-PAM-co-PMAA hydrogels were investigated by rectal administration. FTIR and Raman spectra confirmed the obtaining of HPMC-co-PAM-co-PMAA hydrogels. Many micro-pores were found in the SEM photograph of HPMC-co-PAM-co-PMAA hydrogels. Cell experiments indicated that HPMC-co-PAM-co-PMAA hydrogel was out of cytotoxicity. In vitro release profiles showed that INS-loaded hydrogel could release INS at a continuous manner in pH 7.4 buffer (rectal conditions). Animal experiments suggested that INS-loaded hydrogel had an obvious hypoglycemic effect. Therefore, as a convenient and economic method of administration, INS-loaded HPMC-co-PAM-co-PMAA hydrogels could be used as rectal suppositories to regulate blood glucose.

Rapid and simultaneous analysis of five alkaloids in four parts of Coptidis Rhizoma by near-infrared spectroscopy

Near-Infrared Spectroscopy (NIRS) was first used to develop a method for rapid and simultaneous determination of 5 active alkaloids (berberine, coptisine, palmatine, epiberberine and jatrorrhizine) in 4 parts (rhizome, fibrous root, stem and leaf) of Coptidis Rhizoma. A total of 100 samples from 4 main places of origin were collected and studied. With HPLC analysis values as calibration reference, the quantitative analysis of 5 marker components was performed by two different modeling methods, partial least-squares (PLS) regression as linear regression and artificial neural networks (ANN) as non-linear regression. The results indicated that the 2 types of models established were robust, accurate and repeatable for five active alkaloids, and the ANN models was more suitable for the determination of berberine, coptisine and palmatine while the PLS model was more suitable for the analysis of epiberberine and jatrorrhizine. The performance of the optimal models was achieved as follows: the correlation coefficient (R) for berberine, coptisine, palmatine, epiberberine and jatrorrhizine was 0.9958, 0.9956, 0.9959, 0.9963 and 0.9923, respectively; the root mean square error of validation (RMSEP) was 0.5093, 0.0578, 0.0443, 0.0563 and 0.0090, respectively. Furthermore, for the comprehensive exploitation and utilization of plant resource of Coptidis Rhizoma, the established NIR models were used to analysis the content of 5 active alkaloids in 4 parts of Coptidis Rhizoma and 4 main origin of places. This work demonstrated that NIRS may be a promising method as routine screening for off-line fast analysis or on-line quality assessment of traditional Chinese medicine (TCM).

Noninvasive Continuous Glucose Monitoring Using a Multisensor-Based Glucometer and Time Series Analysis

Daily continuous glucose monitoring is very helpful in the control of glucose levels for people with diabetes and impaired glucose tolerance. In this study, a multisensor-based, noninvasive continuous glucometer was developed, which can continuously estimate glucose levels via monitoring of physiological parameter changes such as impedance spectroscopy at low and high frequency, optical properties, temperature and humidity. Thirty-three experiments were conducted for six healthy volunteers and three volunteers with diabetes. Results showed that the average correlation coefficient between the estimated glucose profiles and reference glucose profiles reached 0.8314, with a normalized root mean squared error (NRMSE) of 14.6064. The peak time of postprandial glucose was extracted from the glucose profile, and its estimated value had a correlation coefficient of 0.9449 with the reference value, wherein the root mean square error (RMSE) was 6.8958 min. Using Clarke error grid (CEG) analysis, 100% of the estimated glucose values fell in the clinically acceptable zones A and B, and 92.86% fell in zone A. The application of a multisensor-based, noninvasive continuous glucometer and time series analysis can endure the time delay between human physiological parameters and glucose level changes, so as to potentially accomplish noninvasive daily continuous glucose monitoring.

Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy

This research was to develop a method for noninvasive and fast blood glucose assay in vivo. Near-infrared (NIR) spectroscopy, a more promising technique compared to other methods, was investigated in rats with diabetes and normal rats. Calibration models are generated by two different multivariate strategies: partial least squares (PLS) as linear regression method and artificial neural networks (ANN) as non-linear regression method. The PLS model was optimized individually by considering spectral range, spectral pretreatment methods and number of model factors, while the ANN model was studied individually by selecting spectral pretreatment methods, parameters of network topology, number of hidden neurons, and times of epoch. The results of the validation showed the two models were robust, accurate and repeatable. Compared to the ANN model, the performance of the PLS model was much better, with lower root mean square error of validation (RMSEP) of 0.419 and higher correlation coefficients (R) of 96.22%.

Lipids in hepatic glycogen storage diseases: pathophysiology, monitoring of dietary management and future directions

Hepatic glycogen storage diseases (GSD) underscore the intimate relationship between carbohydrate and lipid metabolism. The hyperlipidemias in hepatic GSD reflect perturbed intracellular metabolism, providing biomarkers in blood to monitor dietary management. In different types of GSD, hyperlipidemias are of a different origin. Hypertriglyceridemia is most prominent in GSD type Ia and associated with long-term outcome morbidity, like pancreatitis and hepatic adenomas. In the ketotic subtypes of GSD, hypertriglyceridemia reflects the age-dependent fasting intolerance, secondary lipolysis and increased mitochondrial fatty acid oxidation. The role of high protein diets is established for ketotic types of GSD, but non-traditional dietary interventions (like medium-chain triglycerides and the ketogenic diet) in hepatic GSD are still controversial and necessitate further studies. Patients with these rare inherited disorders of carbohydrate metabolism meet several criteria of the metabolic syndrome, therefore close monitoring for cardiovascular diseases in ageing GSD patients may be justified.

Determination of the recovered-fiber content in paperboard samples by applying mid-infrared spectroscopy

Paperboard is widely used in different applications, such as packaging and graphic printing, among others. Consumption of recycled paper is growing, which has led the paper-mill packaging industry to apply strict quality controls. This means that it is very important to develop methods to test the quality of recycled products. In this article, we focus on determining the recovered-fiber content of paperboard samples by applying Fourier transform mid-infrared (FT-MIR) spectroscopy in combination with multivariate statistical methods. To this end, two very fast, nondestructive approaches were applied: classification and quantification. The first approach is based on classifying unknown paperboard samples into two groups: high and low recovered-fiber content. Conversely, under the quantification approach, the content of recovered fiber in the incoming paperboard samples is determined. The experimental results presented in this article show that the classification approach, which classifies unknown incoming paperboard samples, is highly accurate and that the quantification approach has a root mean square error of prediction of about 4.1.