Metformin Preserves β-Cell Compensation in Insulin Secretion and Mass Expansion in Prediabetic Nile Rats

Prediabetes is a high-risk condition for type 2 diabetes (T2D). Pancreatic β-cells adapt to impaired glucose regulation in prediabetes by increasing insulin secretion and β-cell mass expansion. In people with prediabetes, metformin has been shown to prevent prediabetes conversion to diabetes. However, emerging evidence indicates that metformin has negative effects on β-cell function and survival. Our previous study established the Nile rat (NR) as a model for prediabetes, recapitulating characteristics of human β-cell compensation in function and mass expansion. In this study, we investigated the action of metformin on β-cells in vivo and in vitro. A 7-week metformin treatment improved glucose tolerance by reducing hepatic glucose output and enhancing insulin secretion. Although high-dose metformin inhibited β-cell glucose-stimulated insulin secretion in vitro, stimulation of β-cell insulin secretion was preserved in metformin-treated NRs via an indirect mechanism. Moreover, β-cells in NRs receiving metformin exhibited increased endoplasmic reticulum (ER) chaperones and alleviated apoptotic unfold protein response (UPR) without changes in the expression of cell identity genes. Additionally, metformin did not suppress β-cell mass compensation or proliferation. Taken together, despite the conflicting role indicated by in vitro studies, administration of metformin does not exert a negative effect on β-cell function or cell mass and, instead, early metformin treatment may help protect β-cells from exhaustion and decompensation.     

MicroRNAs,Parkinson’s Disease,and Diabetes Mellitus

Parkinson’s disease (PD) is a neurodegenerative disorder that affects 1% of the population over the age of 60. Diabetes Mellitus (DM) is a metabolic disorder that affects approximately 25% of adults over the age of 60. Recent studies showed that DM increases the risk of developing PD. The link between DM and PD has been discussed in the literature in relation to different mechanisms including mitochondrial dysfunction, oxidative stress, and protein aggregation. In this paper, we review the common microRNA (miRNA) biomarkers of both diseases. miRNAs play an important role in cell differentiation, development, the regulation of the cell cycle, and apoptosis. They are also involved in the pathology of many diseases. miRNAs can mediate the insulin pathway and glucose absorption. miRNAs can also regulate PD-related genes. Therefore, exploring the common miRNA biomarkers of both PD and DM can shed a light on how these two diseases are correlated, and targeting miRNAs is a potential therapeutic opportunity for both diseases.     

A practical development of engineering simulation-assisted educational AR environments

Engineering simulations have opened several gates for today’s chemical engineers. They are powerful tools to provide technical content as physics-based numerical solvers. Augmented reality (AR) and virtual reality (VR), on the other hand, are already underway to digitize environments in many fields. The combination of AR/VR environments and simulations in engineering education has been attracting widespread interest. Literature has demonstrated a massive amount of digital educational environments in several contexts as being complementary to conventional educational methods. Nevertheless, hosting technical content produced by engineering simulations with educational AR/VR is still challenging and requires expertise from multiple disciplines throughout the technical development. Present work provides a facile and agile methodology for low-cost hardware but content-wise rich AR software development. Inspired by the Covid-19 pandemic, a case study is developed to teach chemical-engineering concepts using a liquid-soap synthesis process. Accordingly, we assess and conclude the digital development process to guide inexperienced developers for the digitalization of teaching content. The present contribution serves as an example of the power of integrating AR/VR with traditional engineering simulations for educational purposes. The digital tool developed in this work is shared in the online version.     

给水管道腐蚀原因及防护措施探讨

给水管道在使用过程中很容易受到人为外力、管道材质、地下水、周围空气、土壤等因素的影响而腐蚀,影响了管道的使用质量和寿命,也带来较大的安全隐患。本文主要是从给水管道腐蚀原因出发,并探讨防护措施。     

致密砂岩油藏能量补充方式评价及优化

针对致密砂岩油藏大规模体积压裂开发后能量补充困难的问题,利用自主设计制作的大型人造三维岩心物理模型和物理模拟实验舱,开展致密砂岩油藏能量补充方式优化研究。实验结果表明:致密砂岩油藏压裂开发过程中,地层能量损耗严重,采取注水或注气的方式可有效进行能量补充;地层中裂缝规模越大,越有利于原油渗流,后续补充能量的传播范围越广,有助于进一步提高原油采收率;从提高驱油效率和扩大波及系数方面优选吞吐渗吸介质,CO₂均优于活性水,CO₂吞吐开发在矿场试验中取得了显著的增油效果,因此,CO₂吞吐作为一种有效的能量补充方式在致密油开发中展现了良好的应用前景。该文分析了致密砂岩储层水平井压裂开发的渗流规律,优选出致密砂岩储层大规模压裂开发后最佳渗吸介质,可为致密砂岩油藏开发设计提供重要的理论依据。     

Single Cell Bioprinting with Ultrashort Laser Pulses

Tissue engineering requires the precise positioning of mammalian cells and biomaterials on substrate surfaces or in preprocessed scaffolds. Although the development of 2D and 3D bioprinting technologies has made substantial progress in recent years, precise, cell-friendly, easy to use, and fast technologies for selecting and positioning mammalian cells with single cell precision are still in need. A new laser-based bioprinting approach is therefore presented, which allows the selection of individual cells from complex cell mixtures based on morphology or fluorescence and their transfer onto a 2D target substrate or a preprocessed 3D scaffold with single cell precision and high cell viability (93–99% cell survival, depending on cell type and substrate). In addition to precise cell positioning, this approach can also be used for the generation of 3D structures by transferring and depositing multiple hydrogel droplets. By further automating and combining this approach with other 3D printing technologies, such as two-photon stereolithography, it has a high potential of becoming a fast and versatile technology for the 2D and 3D bioprinting of mammalian cells with single cell resolution.     

Spatiotemporal Magnetocaloric Microenvironment for Guiding the Fate of Biodegradable Polymer Implants

The degradation behavior of implants is significantly important for bone repair. However, it is still unprocurable to spatiotemporally regulate the degradation of the implants to match bone ingrowth. In this paper, a magneto-controlled biodegradation model is established to explore the degradation behavior of magnetic scaffolds in a magnetothermal microenvironment generated by an alternating magnetic field (AMF). The results demonstrate that the scaffolds can be heated by magnetic nanoparticles (NPs) under AMF, which dramatically accelerated scaffold degradation. Especially, magnetic NPs modified by oleic acid with a better interface compatibility exhibit a greater heating efficiency to further facilitate the degradation. Furthermore, the molecular dynamics simulations reveal that the enhanced motion correlation between magnetic NPs and polymer matrix can accelerate the energy transfer. As a proof-of-concept, the feasibility of magneto-controlled degradation for implants is demonstrated, and an optimizing strategy for better heating efficiency of nanomaterials is provided, which may have great instructive significance for clinical medicine.     

Dynamic energy and mass balance model for an industrial alkaline water electrolyzer plant process

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss.