TGFβ-1 Induced Cross-Linking of the Extracellular Matrix of Primary Human Dermal Fibroblasts

Excessive cross-linking is a major factor in the resistance to the remodelling of the extracellular matrix (ECM) during fibrotic progression. The role of TGFβ signalling in impairing ECM remodelling has been demonstrated in various fibrotic models. We hypothesised that increased ECM cross-linking by TGFβ contributes to skin fibrosis in Systemic Sclerosis (SSc). Proteomics was used to identify cross-linking enzymes in the ECM of primary human dermal fibroblasts, and to compare their levels following treatment with TGFβ-1. A significant upregulation and enrichment of lysyl-oxidase-like 1, 2 and 4 and transglutaminase 2 were found. Western blotting confirmed the upregulation of lysyl hydroxylase 2 in the ECM. Increased transglutaminase activity in TGFβ-1 treated ECM was revealed from a cell-based assay. We employed a mass spectrometry-based method to identify alterations in the ECM cross-linking pattern caused by TGFβ-1. Cross-linking sites were identified in collagens I and V, fibrinogen and fibronectin. One cross-linking site in fibrinogen alpha was found only in TGFβ-treated samples. In conclusion, we have mapped novel cross-links between ECM proteins and demonstrated that activation of TGFβ signalling in cultured dermal fibroblasts upregulates multiple cross-linking enzymes in the ECM.     

Incorporating microgrids coupling with utilization of flexible switching to enhance self-healing ability of electric distribution systems

Electric distribution networks have to deal with issues caused by natural disasters. These problems possess unique characteristics, and their severity can make load restoration methods impotent. One solution that can help in alleviating the aftermath is the use of microgrids (MGs). Employing the cumulative capacity of the generation resources through MG coupling facilitates the self-healing capability and leads to better-coordinated energy management during the restoration period, while the switching capability of the system should also be considered. In this paper, to form and schedule dynamic MGs in distribution systems, a novel model based on mixed-integer linear programming (MILP) is proposed. This approach employs graph-related theories to formulate the optimal formation of the networked MGs and management of their proper participation in the load recovery process. In addition, the Benders decomposition technique is applied to alleviate computability issues of the optimization problem. The validity and applicability of the proposed model are evaluated by several simulation studies.     

Photomemory and Pulse Monitoring Featured Solution-Processed Near-Infrared Graphene/Organic Phototransistor with Detectivity of 2.4 × 1013 Jones

Emerging graphene/organic phototransistors are eye-catching technologies owing to their unique merits including easy/low-cost fabrication, temperature independent, and achieving various functions. However, their development in the near-infrared (NIR) region is experiencing a bottleneck of inferior sensitivity due to low exciton dissociation efficiency and inefficient charge extraction rate. Here, a novel-design solution-processed graphene/organic NIR phototransistor is reported, that is, creatively introducing electron extraction layer of ZnO on graphene channel and employing organic ternary bulk heterojunction as photosensitive layer, successfully breaking that bottleneck. The phototransistor exhibits a high responsivity of 6.1 × 10⁶ A W⁻¹, a superior detectivity of 2.4 × 10¹³ Jones, and a remarkable minimum detection power of 1.75 nW cm⁻² under 850 nm radiation. Considering its excellent NIR detection performance, a noncontact transmission-type pulse monitoring is carried out with no external circuit support, from which human pulse signal and heart rate can be displayed in real time. The phototransistor, interestingly, can be switched into a photomemory function with a retention time of 1000 s in the atmosphere through a gate voltage of −20 V. The design takes the characteristics of graphene/organic phototransistors to a higher level, beyond the limit of sensitivity, and opens up a novel approach for developing multifunction devices.     

Molecular Characteristics of Amyloid Precursor Protein (APP) and Its Effects in Cancer

Amyloid precursor protein (APP) is a type 1 transmembrane glycoprotein, and its homologs amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2) are highly conserved in mammals. APP and APLP are known to be intimately involved in the pathogenesis and progression of Alzheimer’s disease and to play important roles in neuronal homeostasis and development and neural transmission. APP and APLP are also expressed in non-neuronal tissues and are overexpressed in cancer cells. Furthermore, research indicates they are involved in several cancers. In this review, we examine the biological characteristics of APP-related family members and their roles in cancer.