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Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) protect against diabetic cardiovascular diseases and nephropathy. However, their activity in diabetic retinopathy (DR) remains unclear. Our retrospective cohort study involving 1626 T2DM patients revealed superior efficacy of GLP-1 RAs in controlling DR compared to other glucose-lowering medications, suggesting their advantage in DR treatment. By single-cell RNA-sequencing analysis and immunostaining, we observed a high expression of GLP-1R in retinal endothelial cells, which was down-regulated under diabetic conditions. Treatment of GLP-1 RAs significantly restored the receptor expression, resulting in an improvement in retinal degeneration, vascular tortuosity, avascular vessels, and vascular integrity in diabetic mice. GO and GSEA analyses further implicated enhanced mitochondrial gene translation and mitochondrial functions by GLP-1 RAs. Additionally, the treatment attenuated STING signaling activation in retinal endothelial cells, which is typically activated by leaked mitochondrial DNA. Expression of STING mRNA was positively correlated to the levels of angiogenic and inflammatory factors in the endothelial cells of human fibrovascular membranes. Further investigation revealed that the cAMP-responsive element binding protein played a role in the GLP-1R signaling pathway on suppression of STING signaling. This study demonstrates a novel role of GLP-1 RAs in the protection of diabetic retinal vasculature by inhibiting STING-elicited inflammatory signals.

Multi-modal fusion of remote sensing images poses challenges because of the intricate imaging mechanisms and variations in radiation across different modalities. Specifically, the fusion of visible-light and vegetation-sensitive images encounters similar difficulties. Traditional methods have seldom considered the varied imaging mechanisms and radiation difference between modalities, resulting in discrepancies in the correspond features. To address the issue, we propose the VAM-Net (Vegetation-Attentive Multi-modal deep Network) combining a radiometric correction mechanism and a lightweight multi-modal adaptive feature selection method for fusing multi-modal images. First, the vegetation index (VDVI) is integrated into visible-light images to mitigate the radiometric differences between visible-light images and vegetation-sensitive images (e.g., infrared and red edge images). Then, a two-branch network incorporating attention mechanisms is designed to independently capture the texture features and select similar features cross two different modalities of images. Last, a new loss function is presented to ensure the learned features are suitable for multi-modal fusion. The VAM-Net is evaluated by visible-light and vegetation-sensitive images in three different areas, and the experimental results show that VAM-Net attains an average precision of 67.02%, and recall of 35.49%, and an average RMSE of 2.191px, demonstrating the accuracy and robustness of VAM-Net in multi-modal image fusion.

This paper introduces a framework for reconstructing fine-grained room-level models from indoor point clouds. The motivation behind our method stems from the consistent floorwise appearance of building shapes in urban buildings along the vertical direction. To this end, each floor’s points are horizontally sliced to obtain a representative cross-section, from which the linear primitives are detected and enhanced. These linear primitives help to divide the entire space into non-overlapping connected faces with shared edges. These faces are then classified as indoor or outdoor categories by solving a binary energy minimization formulation. The indoor faces are further grouped into each individual rooms with the support of the room semantic map. By propagating and tracing each room’s contour, 2D floor plan can be generated in a semantic-aware manner. These generated 2D floor plans are vertically stretched to match the heights of their respective rooms. Experimental results on six complex scenes from the S3DIS dataset, which encompass both linear and non-linear shapes, demonstrate that our created room models exhibit accurate geometry, correct topology, and rich semantics. The source code of our room-level modeling algorithm is available at https://github.com/indoor-modeling/indoor-modeling.

The investigation of the low-cost deoxygenation of guaiacol (GUA, a model bio-oil compound) is of importance for upgrading bio-oil. At present, common sulfide catalysts for GUA deoxygenation reactions cause contamination of the liquid product, and noble metal catalysts are economically disadvantageous. In this study, four reduced Fe-based oxides with different Ce doping ratios were prepared and their effects on the in-situ deoxygenation performance of GUA in aqueous/methanol hydrogen donor solvents were explored. The results based on the deoxygenation degree, conversion degree, and higher heating value (HHV) of the products showed that the oxide catalyst with a Fe/Ce molar ratio of 2:1 in the methanol solvent performed very well. After selecting an excellent catalyst and a better hydrogen donor solvent, four factors (reaction temperature, reaction time, volume ratio of GUA dosage and methanol dosage, and the ratio of catalyst dosage at the bottom of the reactor to that at the top) in the deoxygenation degree of GUA were investigated using an orthogonal experimental method to further explore the performance of the catalyst. The results showed that the reaction temperature and time greatly influenced GUA deoxygenation. Under optimal experimental conditions, the deoxygenation degree and conversion degree of GUA could reach 34.36% and 92.56%, respectively, based on the relative peak area of gas chromatography–mass spectrometry, and the HHV of the liquid product was 32.27 MJ/kg. Although Fe/Ce catalysts mainly promote demethoxylation, demethylation, and methylation, the stability and quality of the liquid products were improved compared with GUA owing to the reduction in phenolic hydroxyl and ether content. The reduced catalyst in the process of GUA in-situ deoxygenation reactions in methanol maintained a steady performance, as revealed by X-ray diffraction and X-ray fluorescence.

Bio-oil is a renewable energy and a promising alternative to oil, but its disadvantages such as high oxygen content, low higher heating value (HHV), and instability are needed upgrading. For ketones account for a relatively large proportion of bio-oil, acetone is chosen as a single model compound for hydrodeoxygenation (HDO) in this work. The acetone HDO investigation was carried out in a high pressure reactor, using the reduced Fe-based oxygen carrier1 (OC1) and Ce-doping reduced Fe/Al oxygen carrier2 (OC2). The OCs’ evolution was analyzed by XRD, and the liquid phase products were tested by GC–MS. The results showed the OCs played the dual role of carrying oxygen and catalysis and the HDO capability of OC2 on acetone was better than that of OC1. In addition, two molecular structure models of OC1* (reduced iron-based oxygen carrier) and OC2* (Ce-modified Fe/Al reduced oxygen carrier) were established, and the acetone adsorption on OCs* and the H2O dissociation process were simulated with density functional theory (DFT). The analysis showed that the oxygen vacancies generated by Ce-doping and the Al2O3 carrier changed the optimal adsorption sites of acetone and H2O, then promoted the acetone adsorption and H2O dissociation reaction, improved the OCs performance, verifying that OC2 had better HDO performance on acetone. This work provides guidance for the improvement of crude bio-oil upgrading.

In this study, we investigated the anticancer effects of FS-7, a flavonoid salicylate derivative, in human gastric carcinoma MGC-803 cell line and studied its preliminary anticancer effects. FS-7 displayed greater in vitro cytotoxicity against MGC-803 cell line compared with 5-Fu and had a certain extent of selectivity to cancer cells. The flow cytometry analysis revealed that FS-7 induced apoptosis MGC-803 cells and mainly caused cells arrest in the G2/M phase in a concentration-dependent manner. Additionally, FS-7 inhibited the colony formation and cell migration in a concentration-dependent manner. Notably, FS-7 noticeably down-regulated glycolysis-related protein HIF-1α, HK-II and PFKP expression in a concentration-dependent manner, possibly causing glycolysis inhibition. Importantly, compared with 5-Fu, FS-7 showed better anticancer activity in the MGC-803 xenograft murine tumor models. Collectively, the present study provided a promising anticancer drug candidate for gastric cancer therapy.

Lung cancer is the leading cause of cancer-related deaths. Traditional chemotherapy causes serious toxicity due to the wide bodily distribution of these drugs. Curcumin is a potential anticancer agent but its low water solubility, poor bioavailability and rapid metabolism significantly limits clinical applications. Here we developed a liposomal curcumin dry powder inhaler (LCD) for inhalation treatment of primary lung cancer. LCDs were obtained from curcumin liposomes after freeze-drying. The LCDs had a mass mean aerodynamic diameter of 5.81 μm and a fine particle fraction of 46.71%, suitable for pulmonary delivery. The uptake of curcumin liposomes by human lung cancer A549 cells was markedly greater and faster than that of free curcumin. The high cytotoxicity on A549 cells and the low cytotoxicity of curcumin liposomes on normal human bronchial BEAS-2B epithelial cells yielded a high selection index partly due to increased cell apoptosis. Curcumin powders, LCDs and gemcitabine were directly sprayed into the lungs of rats with lung cancer through the trachea. LCDs showed higher anticancer effects than the other two medications with regard to pathology and the expression of many cancer-related markers including VEGF, malondialdehyde, TNF-α, caspase-3 and BCL-2. LCDs are a promising medication for inhalation treatment of lung cancer with high therapeutic efficiency. Key words: Curcumin, Dry powder inhaler, Liposome, Primary lung cancer, Pulmonary delivery

Study region: Weizhou Island, Northern part of the South China Sea. Study focus: Research on precipitation variability is important for understanding the water cycle and to evaluate risk of flood and drought risks. We studied precipitation variability, including amounts and intensity, on a sea island (Weizhou Island) using a long time-series daily precipitation dataset. An innovative trend test (Şen trend test) and M-K trend test were used to analyze trends of rainfall variability. The Concentration Index (CI1) and the precipitation concentration index (CI2) were used, respectively, to evaluate the intensity and seasonality of rainfall. The continuous wavelet transform (CWT) was used to analyze CI1 and CI2. NCEP/NCAR data were used to determine if large scale circulation has an influence on Weizhou Island rainfall variability. New hydrological insights: (1) Rainfall amounts had a non-homogeneous temporal distribution during periods of 1961–1990, 1981–2010 and 1961–2010 on Weizhou Island. (2) Large scale atmospheric circulation may be the major atmospheric driving force of precipitation changes. (3) Precipitation has a cyclical nature on Weizhou Island. (4) Precipitation pattern on Weizhou Island is also affected by oceanic climate. The results provide a scientific basis for water resource management on Weizhou Island.

Aims: The present study aimed to investigate the effect of metformin on diabetes-accelerated atherosclerosis and whether Nod-like receptor protein 3 (NLRP3) inflammasome is a target for metformin. Materials and methods: ApoE−/− male mice were divided randomly into control, streptozocin-induced diabetes mellitus and metformin groups. Metabolic parameters, atherosclerotic lesion, activation of NLRP3 inflammasomes and related signaling pathways were detected. THP-1-differentiated macrophages were used in in vitro experiments. Results: Compared with control mice, increased plasma lipids and proinflammatory interleukin-1β, aggravated macrophage infiltration into the atherosclerotic lesion, and accelerated development of atherosclerosis were observed in diabetic mice, which were associated with the activation of NLRP3 inflammasomes and dysregulation of thioredoxin-1 and thioredoxin-interacting protein. Treatment with metformin alleviated diabetes-induced metabolic disorders and atherosclerosis, as well as NLRP3 inflammasomes activation and dysregulation of thioredoxin-1/thioredoxin-interacting protein. In vitro experiments showed that high glucose induced the accumulation of reactive oxygen species and activated NLRP3 inflammasomes, which was significantly suppressed by treatment with metformin or antioxidant N-acetyl-L-cysteine. Moreover, Compound C, an inhibitor of adenosine 5′-monophosphate-activated protein kinase (AMPK), blocked the anti-inflammatory effect of metformin, indicating that metformin inhibited high glucose-induced NLRP3 inflammasomes activation through AMPK activation. Moreover, high glucose decreased thioredoxin-1 expression and increased thioredoxin-interacting protein expression, which was also reversed by metformin. Conclusions: Metformin inhibited NLRP3 inflammasomes activation and suppressed diabetes-accelerated atherosclerosis in apoE−/− mice, which at least partially through activation of AMPK and regulation of thioredoxin-1/thioredoxin-interacting protein.