Canagliflozin : something new for type 2 diabetes, but is it safe and efficacious?

Evaluation of Inagaki N, Kondo K, Yoshinari T, et al. Efficacy and safety of canagliflozin in Japanese patients with type 2 diabetes: a randomized, double-blind, placebo-controlled, 12-week study. Diabetes Obes Metab 2013. [Epub ahead of print] and Cefalu WT, Leiter LA, Yoon KH, et al. Efficacy and safety of canagliflozin versus glimepiride in patients with type 2 diabetes inadequately controlled with metformin (CANTATA-SU): 52 week results from a randomized, double-blind, phase 3 non-inferiority trial. Lancet 2013;382:941-50 INTRODUCTION Inhibition of the sodium-glucose cotransporter 2 (SGLT2), to promote the excretion of glucose, is a new paradigm in the treatment of type 2 diabetes. AREAS COVERED Canagliflozin is an SGLT2 inhibitor, which has been the subject of two recent clinical trials, which are evaluated. EXPERT OPINION Studies with canagliflozin, in subjects with type 2 diabetes, have shown that its use is associated with reductions in HbA1c and body weight and small reductions in blood pressure and triglycerides, while increasing high-density lipoprotein cholesterol and low-density lipoprotein cholesterol. As monotherapy in Japanese subjects, or in comparison with glimepiride in CANTATA-SU (CANagliflozin Treatment and Trial Analysis versus SUlphonylurea), canagliflozin causes a low incidence of hypoglycemia, and this is an advantage over glimepiride. However, one of the disadvantages with canagliflozin, which was also highlighted in CANTATA-SU, is that canagliflozin can cause urogenital infections, which are not observed with other antidiabetic drugs. The Federal Drug Administration has recently approved canagliflozin for use in type 2 diabetes, while directing that a clinical outcome safety trial be undertaken. We are concerned that canagliflozin has been approved for use in type 2 diabetes prior to a clinical outcome study of efficacy being undertaken and without the outcome of further safety testing.

Dapagliflozin – do we need it registered for type 2 diabetes?

INTRODUCTION: Inhibitors of the sodium-glucose co-transporter 2 (SGLT2) promote the excretion of glucose to reduce glycated hemoglobin (HbA1c) levels. Canagliflozin was the first SGLT2 inhibitor to be approved by the US FDA for use in the treatment of type 2 diabetes, and recently dapagliflozin has also been approved. AREAS COVERED: We evaluated a recent Phase III clinical trial with dapagliflozin. EXPERT OPINION: Dapagliflozin was studied as add-on therapy to sitagliptin with or without metformin, and was shown to lower HbA1c levels and body weight. The incidence of hypoglycaemia was low with dapagliflozin, but it did increase the incidence of urogenital infections. As no clear benefits have been identified for dapagliflozin over canagliflozin, which was the first gliflozin registered by the FDA, we do not fully understand why it was necessary to register dapagliflozin. Given that there are no completed cardiovascular/clinical outcome studies with dapagliflozin, and therefore no evidence of beneficial effect, it also seems premature to be using it extensively or considering it as an alternative to the clinically proven metformin.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Amplitude of accommodation in type 1 diabetes

Purpose People with diabetes have accelerated age-related biometric ocular changes compared with people without diabetes. We determined the effect of Type 1 diabetes on amplitude of accommodation. Method There were 43 participants (33 ± 8 years) with type 1 diabetes and 32 (34 ± 8 years) age-balanced participants without diabetes. There was no significant difference in the mean equivalent refractive error and visual acuity between the two groups. Amplitude of accommodation was measured using two techniques: objective — by determining the accommodative response to a stimulus in a COAS-HD wavefront aberrometer (Wavefront Sciences), and subjective — with a Badal hand optometer (Rodenstock). The influences of age and diabetes duration (in years) on amplitude of accommodation were analyzed using multiple regression analysis. Results Across both groups, objective amplitude was less than subjective amplitude by 1.4 ± 1.2 D. People with diabetes had lower objective (2.7 ± 1.6 D) and subjective (4.0 ± 1.7 D) amplitudes than people without diabetes (objective 4.1 ± 2.1 D, subjective 5.6 ± 2.1 D). For objective amplitude and the whole group, the duration of diabetes contributed 57% of the variation as did age. For the objective amplitude and only the diabetes group this was 78%. For subjective amplitude, the corresponding proportions were 68% and 103%. Conclusions Both objective and subjective techniques showed lowered amplitude of accommodation in participants with type 1 diabetes when compared with age-matched controls. The loss correlated strongly with duration of diabetes. The results suggest that individuals with diabetes will experience presbyopia earlier in life than people without diabetes, possibly due to metabolic changes in the lens.

Corneal confocal microscopy shown an improvement in small-fibre neuropathy in subjects with type 1 diabetes on continuous subcutaneous insulin infusion compared to multiple daily injection

Improved glycemic control is the only treatment that has been shown to be effective for diabetic peripheral neuropathy in patients with type 1 diabetes (1). Continuous subcutaneous insulin infusion (CSII) is superior to multiple daily insulin injection (MDI) for reducing HbA1c and hypoglycemic events (2). Here, we have compared the benefits of CSII compared withMDI for neuropathy over 24months....

Perceived needs for supported self-management of type 2 diabetes : a qualitative investigation of the potential for a web-based intervention

The estimated one million Australians with type 2 diabetes face significant risks of morbidity and premature mortality. Inadequate diabetes self-management is associated with poor glycaemic control, which is further impaired by comorbid dysphoria. Regular access to ongoing self-management and psychological support is limited, especially in rural and regional locations. Web-based interventions can provide complementary support to patients’ usual care. Semi-structured interviews were undertaken with two samples that comprised (a) 13 people with type 2 diabetes and (b) 12 general practitioners (GPs). Interviews explored enablers and barriers to self-care, emotional challenges, needs for support, and potential web-based programme components. Patients were asked about the potential utility of a web-based support programme, and GPs were asked about likely circumstances of patient referral to it. Thematic analysis was used to summarise responses. Most perceived facilitators and barriers to self-management were similar across the groups. Both groups highlighted the centrality of dietary self-management, valued shared decision-making with health professionals, and endorsed the idea of web-based support. Some emotional issues commonly identified by patients varied to those perceived by GPs, resulting in different attributions for impaired self-care. A web-based programme that supported self-management and psychological/emotional needs appears likely to hold promise in yielding high acceptability and perceived utility.

The OnTrack Diabetes web-based program for type 2 diabetes and dysphoria self-management: A randomized controlled trial protocol

Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

Graphene-type sheets of Nb1-xWxS2 : synthesis and in situ functionalization

Enlightened by the discovery of graphenes, a variety of inorganic analogues have been synthesized and characterized in recent years. Solvated Nb1-xWxS2 analogues of graphene-type sheets were prepared by lithiation and exfoliation of multistacked Nb1-xWxS2 coin roll nanowires (CRNWs), followed by in situ functionalization with gold nanoparticles to synthesize gold-loaded Nb1-xWxS2/Au nanocomposites. The Nb1-xWxS2 nanosheets and the corresponding Nb1-xWxS2/Au nanocomposites were characterized by high resolution electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDX), scanning transmission electron microscopy (STEM), dynamic light scattering (DLS) and scanning force microscopy (AFM). The graphene-type sheets are stable in water and other solvents and can be functionalized similarly as chalcogen-terminated surfaces (e.g. with Au nanoparticles).

Hybrid chalcogenide nanoparticles : 2D-WS2 nanocrystals inside nested WS2 fullerenes

The MOCVD assisted formation of nested WS2 inorganic fullerenes (IF-WS2) was performed by enhancing surface diffusion with iodine, and fullerene growth was monitored by taking TEM snapshots of intermediate products. The internal structure of the core-shell nanoparticles was studied using scanning electron microscopy (SEM) after cross-cutting with a focused ion beam (FIB). Lamellar reaction intermediates were found occluded in the fullerene particles. In contrast to carbon fullerenes, layered metal chalcogenides prefer the formation of planar, plate-like structures where the dangling bonds at the edges are stabilized by excess S atoms. The effects of the reaction and annealing temperatures on the composition and morphology of the final product were investigated, and the strength of the WS2 shell was measured by intermittent contact-mode AFM. The encapsulated lamellar structures inside the hollow spheres may lead to enhanced tribological activities.

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Partial shading and rapidly changing irradiance conditions significantly impact on the performance of photovoltaic (PV) systems. These impacts are particularly severe in tropical regions where the climatic conditions result in very large and rapid changes in irradiance. In this paper, a hybrid maximum power point (MPP) tracking (MPPT) technique for PV systems operating under partially shaded conditions witapid irradiance change is proposed. It combines a conventional MPPT and an artificial neural network (ANN)-based MPPT. A low cost method is proposed to predict the global MPP region when expensive irradiance sensors are not available or are not justifiable for cost reasons. It samples the operating point on the stairs of I–V curve and uses a combination of the measured current value at each stair to predict the global MPP region. The conventional MPPT is then used to search within the classified region to get the global MPP. The effectiveness of the proposed MPPT is demonstrated using both simulations and an experimental setup. Experimental comparisons with four existing MPPTs are performed. The results show that the proposed MPPT produces more energy than the other techniques and can effectively track the global MPP with a fast tracking speed under various shading patterns.

Robust clustering of multi-type relational data via a heterogeneous manifold ensemble

High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

Hybrid CuTCNQ/AgTCNQ metal-organic charge transfer complexes via galvanic replacement vs. corrosion recrystallization

This study reports a hybrid of two metal-organic semiconductors that are based on organic charge transfer complexes of 7,7,8,8-tetracyanoquinodimethane (TCNQ). It is shown that the spontaneous reaction between semiconducting microrods of CuTCNQ with Ag+ ions leads to the formation of a CuTCNQ/AgTCNQ hybrid, both in aqueous solution and acetonitrile, albeit with completely different reaction mechanisms. In an aqueous environment, the reaction proceeds by a complex galvanic replacement (GR) mechanism, wherein in addition to AgTCNQ nanowires, Ag0 nanoparticles and Cu(OH)2 crystals decorate the surface of CuTCNQ microrods. Conversely, in acetonitrile, a GR mechanism is found to be thermodynamically unfavorable and instead a corrosion-recrystallization mechanism leads to the decoration of CuTCNQ microrods with AgTCNQ nanoplates, resulting in a pure CuTCNQ/AgTCNQ hybrid metal-organic charge transfer complex. While hybrids of two different inorganic semiconductors are regularly reported, this report pioneers the formation of a hybrid involving two metal-organic semiconductors that will expand the scope of TCNQ-based charge transfer complexes for improved catalysis, sensing, electronics and biological applications.

Adaptive finite element analysis of elliptic problems based on bubble-type local mesh generation

A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.