Quantification Of Blood Glucose Research Articles

AN OPTICAL APPROACH FOR BLOODLESS, IN-VITRO AND NON-INVASIVE GLUCOSE MONITORING

Diabetes mellitus (DM) indicates elevated glucose concentration in blood. In type 1 diabetes, the pancreas produces inadequate insulin whereas in type 2 diabetes, the body is incapable to utilize the insulin present. Insulin is required to transport glucose into the cells. The insulin resistance by the cells causes the glucose level in the blood to increase. At present, the clinical methods available to diagnose DM are invasive. The diagnosis of DM is done by either pricking the fingertip or drawing blood from the vein followed by the quantification of blood glucose in terms of [Formula: see text]. Continuous monitoring is limited as skin is punctured or venous blood is extracted. Spectroscopic analysis of hair, nail, saliva and urine possess the potential to differentiate the hyperglycaemic from the healthy subjects facilitating non-intrusive diagnosis of diabetes. The variation in the incident wavelength following the interaction with the sample is measured by a spectrometer. Based on the energy of the excitation source, the molecular structures present in the sample will either vibrate or absorb and emit photons that produce a spectrum. The samples were collected from both the groups of subjects and pre-processed prior to further examination. The samples were then characterized using the Fourier-transform infrared (FTIR) spectroscopy. The spectral output was pre-processed, filtered and analyzed so as to discriminate between the diabetic and healthy subjects. Although the spectral band of nail and hair samples appears to be identical, a difference in the amplitude was observed between both diabetic and normal subjects at 1450, 1520, 1632, 2925 cm[Formula: see text]. The area under curve (AUC) in the range of 3600 to 3100 cm-1 is a prominent marker in the discrimination. The peak wavelength and AUC were utilized as a biomarker to discriminate the diabetic and normal individuals.

Hyperinsulinisme de l'enfant et de l'adolescent: quand la détermination de la concentration en insuline n'est pas toujours suffisante (version française)

Hypoglycemia in infants and children can lead to seizures, developmental delay, and permanent brain damage. Hyperinsulinism (HI) is the most common cause of both transient and permanent disorders of hypoglycemia. HI is characterized by dysregulated insulin secretion, which results in persistent mild to severe hypoglycemia. The various forms of HI represent a group of clinically, genetically, and morphologically heterogeneous disorders. Congenital hyperinsulinism is associated with mutations of SUR-1 and Kir6.2, glucokinase, glutamate dehydrogenase, short-chain 3-hydroxyacyl-CoA dehydrogenase, and ectopic expression on beta-cell plasma membrane of SLC16A1. Hyperinsulinism can be associated with perinatal stress such as birth asphyxia, maternal toxemia, prematurity, or intrauterine growth retardation, resulting in prolonged neonatal hypoglycemia. Mimickers of hyperinsulinism include neonatal panhypopituitarism, drug-induced hypoglycemia, insulinoma, antiinsulin and insulin-receptor stimulating antibodies, Beckwith-Wiedemann Syndrome, and congenital disorders of glycosylation. Laboratory testing for hyperinsulinism may include quantification of blood glucose, plasma insulin, plasma beta-hydroxybutyrate, plasma fatty acids, plasma ammonia, plasma acylcarnitine profile, and urine organic acids. Genetic testing is available through commercial laboratories for genes known to be associated with hyperinsulinism. Acute insulin response (AIR) tests are useful in phenotypic characterization. Imaging and histologic tools are also available for diagnosing and classifying hyperinsulinism. The goal of treatment in infants with hyperinsulinism is to prevent brain damage from hypoglycemia by maintaining plasma glucose levels above 700 mg/L (70 mg/dL) through pharmacologic or surgical therapy. The management of hyperinsulinism requires a multidisciplinary approach that includes pediatric endocrinologists, radiologists, surgeons, and pathologists who are trained in diagnosing, identifying, and treating hyperinsulinism.

Comparison of performance of partial least squares regression, secured principal component regression, and modified secured principal component regression for determination of human serum albumin, γ-globulin and glucose in buffer solutions and in vivo blood glucose quantification by near-infrared spectroscopy

The performances of three multivariate analysis methods--partial least squares (PLS) regression, secured principal component regression (sPCR) and modified secured principal component regression (msPCR)--are compared and tested for the determination of human serum albumin (HSA), gamma-globulin, and glucose in phosphate buffer solutions and blood glucose quantification by near-infrared (NIR) spectroscopy. Results from the application of PLS, sPCR and msPCR are presented, showing that the three methods can determine the concentrations of HSA, gamma-globulin and glucose in phosphate buffer solutions almost equally well provided that the prediction samples contain the same spectral information as the calibration samples. On the other hand, when some potential spectral features appear in new measurements, sPCR and msPCR outperform PLS significantly. The reason for this is that such spectral features are not included during calibration, which leads to a degradation in PLS prediction performance, while sPCR and msPCR can improve their predictions for the concentrations of the analytes by removing the uncalibrated features from the original spectra. This point is demonstrated by successfully applying sPCR and msPCR to in vivo blood glucose measurements. This work therefore shows that sPCR and msPCR may provide possible alternatives to PLS in cases where some uncalibrated spectral features are present in measurements used for concentration prediction.