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The electrical stimulation of meridian points in rats inhibits the withdrawal reflex of the nociceptive tail. Its pain mechanisms are well-documented. Moreover, electroacupuncture (EA) at special abdominal acupoints has been shown to induce a short-term hypoglycemia effect in streptozotocin diabetic rats. The Zusanli and Zhongwan acupoints have been widely used in traditional Chinese medicine to relieve symptoms of diabetes mellitus. It is still unclear whether they can affect extracellular glucose and lactate metabolites at the cellular level. The aim of this study is to evaluate these effects using a rat model for the analysis of extracellular neurochemicals. First, electrical stimulus of 2 ms 2 Hz square pulses (30 minutes) was applied to anesthetized intact rats (n = 7) at the Zusanli points. One and a half hours later, a second electrical stimulus (2 Hz pulses, 30 minutes) was delivered to two of the rats at the same spot. Another two rats received a different stimulation (100 Hz pulses, 30 minutes) at the same location. In the final three rats, a second electrical stimulus of 2 Hz pulses was delivered to non-acupoints. An automated micro-blood sample collector was used to examine the glucose, pyruvate and lactate concentrations. The EA signal has an influence on the biologic process of energy metabolism by mediating dynamic extracellular neurochemical changes. The EA at limb acupoints of the lower limbs induces a decrease in glucose, an increase in lactate metabolites and a decrease in the lactate/glucose ratio. Moreover, the increased lactate/glucose ratio suggests that the cell has an increased anaerobic glucose metabolism.

Exploring the Role of Glutathione in the Regulation of Immune Cell Function.

Does Oxidative Damage Cause Poor Healing?

Pathogenesis of Atopic Dermatitis in Singapore.

Proteomics and Colorectal Cancer Metastasis: Bird's-Eye View on Current Scenario and Our Contribution.

Zebrafish: A Small Fish Model for a Big Human Disease.

The Reign of a New Dictator: Circulating MicroRNA in Diabetes.

Engineering Artificial Vascularized Bone Grafts for the Repair of Large Bone Defects.

A 'Nano' Era for Blood Glucose Sensing.

Ancient Medicine with Newer Roles: Potential Role of Celastrol in the Treatment of Multiple Myeloma.

Proteins, Proteome and Proteomics.

A Novel Promising Biomarker and Therapy Target of Liver Cancer.

Understanding Diabetes

Prediabetes: The Gap between the Onset of Disease and Initiation of Treatment.

Diabetes: A Dietitian’s Perspective.

Use of Modelling for Better Diabetes Care.

No More Highs and Lows with Toujeo®: A New and Improved Insulin Injection.

Diagnosis of diabetes is usually achieved by obtaining a single reading of blood-glucose concentration value from the Oral Glucose Tolerance Test (OGTT). However, the result itself is inadequate in providing insight into the glucose-regulatory etiology of diabetes disease disorder, which is important for treatment purposes. The objective of this project was to conduct clinical simulation and parametric identification of OGTT model for diagnosis of diabetic patient, so as to classify diabetic or at-risk patients into different categories, depending on the nature of their blood-glucose tolerance response to oral injestion of a bolus of glucose. In other words, the patient classification depends on how the blood-glucose concentration varies with time; i.e. how much does it peak, how long does it takes to reach its peak value, how fast does it return to the fasting value, etc. during the oral glucose tolerance test.

To represent this blood-glucose concentration [y(t)] regulatory dynamics, the model selected is a second-order differential equation, of blood-glucose concentration response to a bolus of ingested glucose Gδ(t). This model was then applied to the test subjects by making the model solution-expression for y(t) match the monitored clinical data of blood-glucose concentration at different time intervals, through clinical simulation and parametric identification. The solutions obtained from the model to fit the clinical data were different for normal and diabetic test subjects. The clinical data of "normal" subjects could be simulated by means of an under-damped solution of the model, as: y(t) = (G/ω)e^-ωtsin ωt. The data of "diabetic" patients needed to be simulated by means of an over-damped solution of the model, as: y(t) = (G/ω)e^-Atsin hωt, where G represents the magnitude of the impulse input Gδ(t) to the model (in gms of glucose per litre of blood pool volume), ω is the damped oscillatory frequency of the model, w_n is the natural frequency of the system and .

In order to facilitate differential diagnosis, we developed a non-dimensional diabetic index (DI) expressed as: [Ay_maxT_d/GT_max]. This index can be used to facilitate the diagnosis of diabetes as well as for assessing the risk to becoming diabetic.

Subjective cognitive decline (SCD), characterized by self-perceived subtle cognitive impairment ahead of the appearance of explicit and measurable cognitive deficits, is regarded as the preclinical manifestation of the pathological change continuum of Alzheimer’s disease (AD). We were committed to exploring the amyloid and glucose metabolic signatures related to imminent brain metabolic changes in SCD subjects. This study included 39 subjects (mean age = 71.9 years; 14 males and 25 females) diagnosed with SCD disease and 39 gender-matched healthy controls (HCs) (mean age = 75.2; 16 males and 23 females) with brain [18F] fluorodeoxyglucose positron emission tomography (PET) images and [18F] florbetapir PET images. The standardized uptake value ratios (SUVRs) of PET images within the regions of interest (ROIs) were calculated. Inter-group SUVR differences were assessed by two-sample $t$-testing and receiver operating characteristic curve (ROC) analyses. A generalized linear model (GLM) was employed to evaluate the correlations between amyloid and FDG uptake. Compared with HCs, SCD subjects showed significantly increased amyloid SUVR, as well as significantly increased glucose SUVR in the olfactory, amygdala, thalamus, heschl gyrus, superior and middle temporal gyrus and temporal pole (all $P<0.05$). The amyloid SUVR of thalamus was found to have a better ROC result (area under the curve (AUC): 0.77, 95% confidence interval (CI): 0.66–0.86) in the HC group, as was the case with the glucose SUVR of the middle temporal gyrus (AUC: 0.83, 95% CI: 0.73–0.91). There were significant positive correlations between amyloid and glucose SUVRs ($P<0.05$). The amyloid SUVR of the thalamus showed a significantly better main effect (odd ratio $=$ 2.91, 95% CI: 1.44–6.7, $P<0.001$), and the glucose SUVR of the heschl gyrus indicated an enhanced main effect (odd ratio $=$ 5.08, 95% CI: 1.86–18.15, $P<0.001$). SCD subjects demonstrated significant amyloid accumulation and glucose hypermetabolism in specific brain regions, and amyloid pathology overlapped with regions of glucose abnormality. These findings may advance the understanding of imminent pathological changes in the SCD stage and help to provide clinical guidelines for interventional management.

One of the major challenges in imaging biological tissues using optical techniques, such as optical coherence tomography (OCT), is the lack of light penetration due to highly turbid structures within the tissue. Optical clearing techniques enable the biological samples to be more optically homogeneous, allowing for deeper penetration of light into the tissue. This study investigates the effect of optical clearing utilizing various concentrations of glucose solution (10%, 30%, and 50%) on porcine skin. A gold-plated mirror was imaged beneath the tissue and percentage clearing was determined by monitoring the change in reflected light intensity from the mirror over time. The ratio of percentage clearing per tissue thickness for 10%, 30% and 50% glucose was determined to be 4.7 ±1.6% mm^-1 (n = 6), 10.6 ±2.0% mm^-1 (n = 7) and 21.8 ±2.2% mm^-1 (n = 5), respectively. It was concluded that while higher glucose concentration has the highest optical clearing effect, a suitable concentration should be chosen for the purpose of clearing, considering the osmotic stress on the tissue sample.

Noninvasive glucose monitoring development is critical for diabetic patient continuous monitoring. However, almost all the available devices are invasive and painful. Noninvasive methods such as using spectroscopy have shown some good results. Unfortunately, the drawback was that the tungsten halogen lamps usage that is impractical if applied on human skin. This paper compared the light emitting diode (LED) to traditional tungsten halogen lamps as light source for glucose detection where the type of light source plays an important role in achieving a good spectrum quality. Glucose concentration measurement has been developed as part of noninvasive technique using optical spectroscopy. Small change and overlapping in tungsten halogen results need to replace it with a more convenient light source such as LED. Based on the result obtained, the performance of LED for absorbance spectrum gives a significantly different and is directly proportional to the glucose concentration. The result shows a linear trend and successfully detects lowest at 60 to 160 mg/dL glucose concentration.

Multivariate calibration is an important tool for spectroscopic measurement of analyte concentrations. We present a detailed study of a hybrid multivariate calibration technique, constrained regularization (CR), and demonstrate its utility in noninvasive glucose sensing using Raman spectroscopy. Similar to partial least squares (PLS) and principal component regression (PCR), CR builds an implicit model and requires knowledge only of the concentrations of the analyte of interest. Calibration is treated as an inverse problem in which an optimal balance between model complexity and noise rejection is achieved. Prior information is included in the form of a spectroscopic constraint that can be obtained conveniently. When used with an appropriate constraint, CR provides a better calibration model compared to PLS in both numerical and experimental studies.

We propose a novel optical method for glucose measurement based on diffuse photon-pair density wave (DPPDW) in a multiple scattering medium (MSM) where the light scattering of photon-pair is induced by refractive index mismatch between scatters and phantom solution. Experimentally, the DPPDW propagates in MSM via a two-frequency laser (TFL) beam wherein highly correlated pairs of linear polarized photons are generated. The reduced scattering coefficient ${\mu }_{2s}^{\prime }$ and absorption coefficient ${\mu }_{2a}$ of DPPDW are measured simultaneously in terms of the amplitude and phase measurements of the detected heterodyne signal under arrangement at different distances between the source and detection fibers in MSM. The results show that the sensitivity of glucose detection via glucose-induced change of reduced scattering coefficient ($\delta {\mu }_{2s}^{\prime }$) is 0.049%mM${}^{-1}$ in a 1% intralipid solution. In addition, the linear range of $\delta {\mu }_{2s}^{\prime }$ vs glucose concentration implies that this DPPDW method can be used to monitor glucose concentration continuously and noninvasively subcutaneously.

Optical immersion clearing is a technique that has been widely studied for more than two decades and that is used to originate a temporary transparency effect in biological tissues. If applied in cooperation with clinical methods it provides optimization of diagnosis and treatment procedures. This technique turns biological tissues more transparent through two main mechanisms — tissue dehydration and refractive index (RI) matching between tissue components. Such matching is obtained by partial replacement of interstitial water by a biocompatible agent that presents higher RI and it can be completely reversible by natural rehydration in vivo or by assisted rehydration in ex vivo tissues. Experimental data to characterize and discriminate between the two mechanisms and to find new ones are necessary. Using a simple method, based on collimated transmittance and thickness measurements made from muscle samples under treatment, we have estimated the diffusion properties of glucose, ethylene glycol (EG) and water that were used to perform such characterization and discrimination. Comparing these properties with data from literature that characterize their diffusion in water we have observed that muscle cell membrane permeability limits agent and water diffusion in the muscle. The same experimental data has allowed to calculate the optical clearing (OC) efficiency and make an interpretation of the internal changes that occurred in muscle during the treatments. The same methodology can now be used to perform similar studies with other agents and in other tissues in order to solve engineering problems at design of inexpensive and robust technologies for a considerable improvement of optical tomographic techniques with better contrast and in-depth imaging.

Our aim was to evaluate homeostatic regulation of organ energy metabolism after exercise using ¹⁸F-FDG and 3D-PET. Five male subjects were studied after exercise task of two different intensities (40% and 70% VO_2max). Other 5 males were studied as control. ROIs were drawn to quantify organ glucose metabolism (rMRGlc). ANOVA was applied among groups, and significant differences (p<0.05) were determined by post-hoc analysis (Scheffe's test). Present study with mild and moderate exercise loads demonstrated linear increases or decreases in glucose uptake by skeletal muscles and viscera, suggestive of homeostatic energy regulation. This supports, ¹⁸FDG-3DPET method can be used as one index of organ energy metabolism up to 70% VO_2max, which might have contributions in rehabilitation science.