Examining Type 1 Diabetes Mathematical Models Using Experimental Data

Type 1 diabetes requires treatment with insulin injections and monitoring glucose levels in affected individuals. We explored the utility of two mathematical models in predicting glucose concentration levels in type 1 diabetic mice and determined disease pathways. We adapted two mathematical models, one with β-cells and the other with no β-cell component to determine their capability in predicting glucose concentration and determine type 1 diabetes pathways using published glucose concentration data for four groups of experimental mice. The groups of mice were numbered Mice Group 1–4, depending on the diabetes severity of each group, with severity increasing from group 1–4. A Markov Chain Monte Carlo method based on a Bayesian framework was used to fit the model to determine the best model structure. Akaike information criteria (AIC) and Bayesian information criteria (BIC) approaches were used to assess the best model structure for type 1 diabetes. In fitting the model with no β-cells to glucose level data, we varied insulin absorption rate and insulin clearance rate. However, the model with β-cells required more parameters to match the data and we fitted the β-cell glucose tolerance factor, whole body insulin clearance rate, glucose production rate, and glucose clearance rate. Fitting the models to the blood glucose concentration level gave the least difference in AIC of 1.2, and a difference in BIC of 0.12 for Mice Group 4. The estimated AIC and BIC values were highest for Mice Group 1 than all other mice groups. The models gave substantial differences in AIC and BIC values for Mice Groups 1–3 ranging from 2.10 to 4.05. Our results suggest that the model without β-cells provides a more suitable structure for modelling type 1 diabetes and predicting blood glucose concentration for hypoglycaemic episodes.

Plasmonic Sensor Based On Silver Nanoparticles For The Detection of Glucose

Sensors for detecting glucose concentrations are crucial to medical testing. Here, we introduce silver nanoparticles (Ag NPs) uniformly distributed in space to investigate the sensing properties for detecting glucose by using the finite-different time-domain (FDTD) and experimental methods. The results show that the transmittance of dip for the proposed structural model gradually decreases as the number of Ag NPs increases, when the concentration of glucose is constant. And the transmission spectrum shows slight red shift with the increasing of the glucose concentration. Moreover, the simulation results are in agreement with the experimental results. Especially, the maximum sensitivity S=1144.07407 nm/RIU can be realized for glucose concentration variation from 0.3 to 0.4 mol/L. The research results reveal an excellent sensing property that has important application value in medical detection.

Effects of Silymarin on Blood Glucose Concentration, Hepatic Histopathological Changes and FOXA2 and FOXA3 Gene Expression in Streptozotocin-Induced Diabetic Male Wistar Rats

Since the liver is among the primary organs susceptible to the effects of hyperglycaemia, diabetes mellitus (DM) could be a risk factor for the development and progression of liver damage. In present study, since no side-effects from the herbal medicine have been reported, the effect of silymarin on blood glucose concentration, hepatic histopathological changes and FOXA2 and FOXA3 gene expression, which are key genes in liver regeneration, was investigated. In this fundamental with experimental approach study, 40 male Wistar rats weighing 180-220 g were used. Rats were kept under the standard conditions of temperature of 20-22°C and humidity of 50% and consecutive 12-hour periods of light and darkness. Rats were randomly divided into five different groups (n=8 each), including healthy control rats, diabetic control rats, diabetic rats receiving silymarin (50, 100 and 150 mg/kg). Diabetes was induced by injecting streptozotocin (50 mg/kg B.W., i.p.). For 4 weeks silymarin groups received the drug once every three days through gavage and fasting blood glucose concentration measured once every 10 days. At the end of a month experiment, livers were harvested for hepatic histopathological and FOXA2 and FOXA3 gene expression changes analysis. In the diabetic rats treated with silymarin (50, 100 and 150 mg/kg), by comparison with the diabetic control group (p<0.05), glucose levels decreased significantly. Moreover, FOXA2 and FOXA3 expression in diabetic groups treated with silymarin significantly increased compared to diabetic control group (p<0.05). Hepatic histopathological changes were improved in the treated groups.The present study indicates that silymarin significantly decreased blood glucose concentration and increased the FOXA2 and FOXA3 gene products level. Hence, silymarin is able to improve some of the symptoms associated with diabetes and possesses hepatoprotective effects in streptozotocin-induced diabetic rats.

Hypoglycemia screening of asymptomatic newborns on the 2nd day of life

BACKGROUND: Neonatal hypoglycemia management in the first 48 hours is guided by the American Academy of Pediatrics (AAP) and Pediatric Endocrine Society (PES) recommendations. Our aim was to determine the incidence of hypoglycemia via point of care test (POCT) on the 2nd day of life (DOL) among healthy, asymptomatic neonates regardless of risk factors. METHODS: In this prospective observational study, preprandial point of care glucose concentration was measured on the 2nd DOL in 150 healthy, asymptomatic neonates in the newborn nursery. We used 50 mg/dl (2.8 mmol/L) as the hypoglycemia threshold based on PES recommendations. RESULTS: The incidence of hypoglycemia on the second DOL was 10% among asymptomatic neonates (no risk factors = 8% ; late preterm birth (LPT) + small for gestational age (SGA) = 16% ; large for gestational age (LGA) + infant of diabetic mother (IDM) = 6%). SGA + LPT neonates accounted for the majority of the hypoglycemic cases (53.3%) and exhibited a trend towards the lowest glucose concentration (p = 0.09). CONCLUSION: The incidence of hypoglycemia on DOL 2 among asymptomatic neonates is high and of unclear significance in the absence of dedicated neurodevelopmental follow-up.

LaFeO3 Modified with Ni for Hydrogen Evolution Via Photocatalytic Glucose Reforming in Liquid Phase

In this work, the optimization of Ni amount on LaFeO3 photocatalyst was studied in the photocatalytic molecular hydrogen production from glucose aqueous solution under UV light irradiation. LaFeO3 was synthesized via solution combustion synthesis and different amount of Ni were dispersed on LaFeO3 surface through deposition method in aqueous solution and using NaBH4 as reducing agent. The prepared samples were characterized with different techniques: Raman spectroscopy, UltraViolet-Visible Diffuse Reflectance Spettroscopy (UV–Vis-DRS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), X-ray Fluorescence (XRF), Transmission Electron microscopy (TEM), and Scanning Electron microscopy (SEM) analyses. For all the investigated photocatalysts, the presence of Ni on perovskite surface resulted in a better activity compared to pure LaFeO3. In particular, it is possible to identify an optimal amount of Ni for which it is possible to obtain the best hydrogen production. Specifically, the results showed that the optimal Ni amount was equal to nominal 0.12 wt% (0.12Ni/LaFeO3), for which the photocatalytic H2 production was equal to 2574 μmol/L after 4 h of UV irradiation. The influence of different of photocatalyst dosage and initial glucose concentration was also evaluated. The results of the optimization of operating parameters indicated that the highest molecular hydrogen production was achieved on 0.12Ni/LaFeO3 sample with 1.5 g/L of catalyst dosage and 1000 ppm initial glucose concentration. To determine the reactive species that play the most significant role in the photocatalytic hydrogen production, photocatalytic tests in the presence of different radical scavengers were performed. The results showed that •OH radical plays a significant role in the photocatalytic conversion of glucose in H2. Moreover, photocatalytic tests carried out with D2O instead of H2O evidenced the role of water molecules in the photocatalytic production of molecular hydrogen in glucose aqueous solution.

High-Sensitivity Biosensor Based on Glass Resonance PhC Cavities for Detection of Blood Component and Glucose Concentration in Human Urine

In this work, a novel structure of an all-optical biosensor based on glass resonance cavities with high detection accuracy and sensitivity in two-dimensional photon crystal is designed and simulated. The free spectral range in which the structure performs well is about FSR = 630 nm. This sensor measures the concentration of glucose in human urine. Analyses to determine the glucose concentration in urine for a normal range (0~15 mg/dL) and urine despite glucose concentrations of 0.625, 1.25, 2.5, 5 and 10 g/dL in the wavelength range 1.326404~1.326426 μm have been conducted. The detection range is RIU = 0.2 × 10−7. The average bandwidth of the output resonance wavelengths is 0.34 nm in the lowest case. In the worst case, the percentage of optical signal power transmission is 77% with an amplitude of 1.303241 and, in the best case, 100% with an amplitude of 1.326404. The overall dimensions of the biosensor are 102.6 µm2 and the sensitivity is equal to S = 1360.02 nm/RIU and the important parameter of the Figure of Merit (FOM) for the proposed biosensor structure is equal to FOM = 1320.23 RIU−1.

Sensing Glucose Concentration Using Symmetric Metasurfaces under Oblique Incident Terahertz Waves

In this article, a planar metamaterial sensor designed at terahertz (THz) frequencies is utilized to sense glucose concentration levels that cover hypoglycemia, normal, and hyperglycemia conditions that vary from 54 to 342 mg/dL. The sensor was developed using a symmetric complementary split rectangular resonator at an oblique incidence angle. The resonance frequency shift was used as a measure of the changes in the glucose level of the samples. The increase in the glucose concentration level exhibited clear and noticeable redshifts in the resonance frequency. For instance, a 67.5 GHz redshift has been observed for a concentration level of 54 mg/dL and increased up to 122 GHz for the 342 mg/dL concentration level. Moreover, a high sensitivity level of 75,700 nm/RIU was observed for this design. In the future, the proposed THz sensors may have potential applications in diagnosing hypocalcemia and hyperglycemia cases.