Diabetes is a major public health problem in China. Diabetes self-management is critical for patients to achieved better health outcomes, however, previous studies have shown suboptimal diabetes self-management performance. We conducted a systematic review and meta-analysis to identify factors associated with diabetes self-management in Chinese adults. The results showed that confrontation, resignation, overall health beliefs, perceived susceptibility, perceived barriers, and self-efficacy were factors associated with overall diabetes self-management performance and six aspects of diabetes self-management behaviors. There is some limited evidence to suggest that provider-patient communication, married individuals, higher educational level, and higher household income level may also be linked to better diabetes self-management practice. Having healthcare insurance and utilizing chronic illness resources generally appeared to have a favorable effect on diabetes self-management performance. In addition, there were a number of factors for which the evidence is too limited to be able to ascertain its strength of association with diabetes self-management practice. The findings of this review suggest that diabetes self-management behaviors are affected by a wide range of personal and environmental factors, which allow health care providers to develop theory-based strategies to improve diabetes-self-management behaviors in this population.

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BackgroundSelf-reported diabetes has been found to be valid to evaluate people's diabetes status in the population of several countries. However, no such study has been conducted to assess the validity of self-reported diabetes in the Chinese population, the largest population with the highest rate of diabetes. The aim of our study is to evaluate the validity of self-reported diabetes among the middle-aged and older Chinese population.MethodsData from 11 601 participants, aged ≥45, of the China Health and Retirement Longitudinal Study (CHARLS) during 2011–2012, were analysed. Prevalent self-reported diabetes was compared with reference definition defined by fasting glucose, glycated haemoglobin and medication use. Sensitivity, specificity, positive predicted value, negative predicted value and κ value were calculated overall, by 5-year age groups, by education levels and by living areas.ResultsThe sensitivity of prevalent self-reported diabetes was 41.5%, and the specificity was 98.6%. The sensitivity of self-reported diabetes increased with education levels, and was much higher among urban residents than rural residents (58.2% vs 35.0%). The specificity was above 98% among all age groups, in different education levels, and in rural and urban areas. Self-reported diabetes had substantial agreement with reference definition among participants with above vocational school education or those living in urban areas (κ=0.658 and 0.646, respectively).ConclusionsAlthough the sensitivity of self-reported diabetes was poor among middle-aged and older Chinese adults, the specificity and positive predictive values were fairly good. Furthermore, self-reported diabetes performed well among those with more than vocational school educations or those living in urban areas.

Cell-based therapy is emerging as a promising strategy to repair damaged tissues (e.g., neuro, bone, cartilage, and skin) and the effective delivery of cells is prerequisite to regenerative Cell therapeutics hold tremendous regenerative potential and the therapeutic effect depends on the effective delivery of cells. However, current cell delivery carriers with unsuitable cytocompatibility and topological structure demonstrate poor cell viability during injection. Therefore, porous shapememory cryogel microspheres (CMS) are prepared from methacrylated gelatin (GelMA) by combining an emulsion technique with gradient-cooling cryogelation. Pore sizes of the CMS are adjusted via the gradient-cooling procedure, with the optimized pore size (15.5 ± 6.0 µm) being achieved on the 30-min gradient-cooled variant (CMS-30). Unlike hydrogel microspheres (HMS), CMS promotes human bone marrow stromal cell (hBMSC) and human umbilical vein endothelial cell (HUVEC) adhesion, proliferated with high levels of stemness for 7 d, and protects cells during the injection process using a 26G syringe needle. Moreover, CMS-30 enhances the osteogenic differentiation of hBMSCs in osteoinductive media. CMS can serve as building blocks for delivering multiple cell types. Here, hBMSC-loaded and HUVEC-loaded CMS-30, mixed at a 1:1 ratio, are injected subcutaneously into nude mice for 2 months. Results show the development of vascularized bone-like tissue with high levels of OCN and CD31. These findings indicate that GelMA CMS of a certain pore size can effectively deliver multiple cells to achieve functional tissue regeneration.

In this paper we implement the 7-point checklist, a set of dermoscopic criteria widely used by clinicians for melanoma detection, on smart handheld devices, such as the Apple iPhone and iPad. The application developed is using sophisticated image processing and pattern recognition algorithms, yet it is light enough to run on a handheld device with limited memory and computational speed. When combined with a commercially available handheld dermoscope that provides proper lesion illumination, this application provides a truly self-contained handheld system for melanoma detection. Such a device can be used in a clinical setting for routine skin screening, or as an assistive diagnostic device in underserved areas and in developing countries with limited healthcare infrastructure.

We have developed a portable library for automated detection of melanoma termed SkinScan© that can be used on smartphones and other handheld devices. Compared to desktop computers, embedded processors have limited processing speed, memory, and power, but they have the advantage of portability and low cost. In this study we explored the feasibility of running a sophisticated application for automated skin cancer detection on an Apple iPhone 4. Our results demonstrate that the proposed library with the advanced image processing and analysis algorithms has excellent performance on handheld and desktop computers. Therefore, deployment of smartphones as screening devices for skin cancer and other skin diseases can have a significant impact on health care delivery in underserved and remote areas.

The crystal structure of P2Y receptor (P2YR), a class A GPCR, revealed a special extra-helical site for its antagonist, BPTU, which locates in-between the membrane and the protein. However, due to the limitation of crystallization experiments, the membrane was mimicked by use of detergents, and the information related to the binding of BPTU to the receptor in the membrane environment is rather limited. In the present work, we conducted a total of ∼7.5 μs all-atom simulations in explicit solvent using conventional molecular dynamics and multiple enhanced sampling methods, with models of BPTU and a POPC bilayer, both in the absence and presence of P2YR. Our simulations revealed that BPTU prefers partitioning into the interface of polar/lipophilic region of the lipid bilayer before associating with the receptor. Then, it interacts with the second extracellular loop of the receptor and reaches the binding site through the lipid-receptor interface. In addition, by use of funnel-metadynamics simulations which efficiently enhance the sampling of bound and unbound states, we provide a statistically accurate description of the underlying binding free energy landscape. The calculated absolute ligand-receptor binding affinity is in excellent agreement with the experimental data (Δ G = -11.5 kcal mol, Δ G= -11.7 kcal mol). Our study broadens the view of the current experimental/theoretical models and our understanding of the protein-ligand recognition mechanism in the lipid environment. The strategy used in this work is potentially applicable to investigate ligands association/dissociation with other membrane-embedded sites, allowing identification of compounds targeting membrane receptors of pharmacological interest.

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