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Glucose transporters GLUT1 belong to the major facilitator superfamily and are essential to human glucose uptake. The overexpression of GLUT1 in tumor cells designates it as a pivotal target for glycoconjugate anticancer drugs. However, the interaction mechanism of glycoconjugate drugs with GLUT1 remains largely unknown. Here, we employed all-atom molecular dynamics simulations, coupled to steered and umbrella sampling techniques, to examine the thermodynamics governing the transport of glucose and two glycoconjugate drugs (i.e., 6-D-glucose-conjugated methane sulfonate and 6-D-glucose chlorambucil) by GLUT1. We characterized the specific interactions between GLUT1 and substrates at different transport stages, including substrate recognition, transport, and releasing, and identified the key residues involved in these procedures. Importantly, our results described, for the first time, the free energy profiles of GLUT1-transporting glycoconjugate drugs, and demonstrated that H160 and W388 served as important gates to regulate their transport via GLUT1. These findings provide novel atomic-scale insights for understanding the transport mechanism of GLUT1, facilitating the discovery and rational design of GLUT1-targeted anticancer drugs.

Oxygen evolution reaction (OER) is a crucial half-reaction in electrochemical water splitting, and efficient and durable electrocatalysts are required to improve the sluggish OER kinetics. However, the inevitable formation of chemical oxygen species (COSs) in the OER process heavily impacts the reaction pathway and kinetics. Precisely identifying the COSs generated during OER and acknowledging their chemo-reactivity is highly beneficial for understanding the OER mechanism and facilitating the rational design of advanced catalysts. One of the major challenges in probing the COSs is the detection of COSs under working conditions due to the transient nature and relative low coverage. This review summarizes various COSs detected on different OER electrocatalysts, including adsorbed hydroxyl (M-OH*), adsorbed oxygen (M-O*), adsorbed superoxide intermediates (M-OOH* and M-OOn-*). With these COSs probed, the possible OER mechanisms with the inter-conversion of these COSs are described. Additionally, the detailed in situ techniques for characterizing specific COSs are also introduced. Finally, we discuss remaining challenges in identifying the COSs and provide some perspectives for the design of next-generation OER electrocatalysts. By emphasizing the COSs during OER, we aim to provide vivid images of the OER transformations on the atomic scales and encourage more studies on correlating the atomic pictures of OER pathways with the active sites as well as catalyst structures.

One type of new light-responsive hierarchical metal organic framework (MOF) has been successfully prepared using Co(NO3)3·6H2O as the metal salt and 4,4′-azobenzenedicarboxylic acid as the ligand by microwave method for the first time. It is found that MOF [Co(AzDC)] exhibits a light-responsive characteristic to SO2 adsorption due to the presence of azo group from the ligand. The light-responsive hierarchical MOFs are incorporated into Matrimid® 5218 (PI) matrix to prepare mixed matrix membranes (MMMs) for gas separation application. The morphology, crystallinity, chain mobility and thermal stability of MMMs are explored. Results show that Co(AzDC) may elevate both the CO2(SO2) permeability and CO2(SO2)/N2 selectivity of the MMMs. In particular, the Co(AzDC) doped MMMs exhibit the significantly improved CO2(SO2)/N2 selectivity from 33 (123) for PI control membrane to 78 (420) for MMMs, overcoming the 2008 Robeson upper bound for CO2/N2 system. Size-sieving effect of Co(AzDC) with pore size 0.35 ​nm enhances the selectivity, while the –N=N– group from Co(AzDC) shows affinity to CO2 molecular rather than N2, also elevating selectivity of MMMs. In brief, enhanced selectivity of high-performance membrane is attributed to incorporation of Co(AzDC) particles, which displays synergistic effects both in size-sieving and CO2-philic interaction for CO2/N2 separation. Smart highly selective interface is constructed in MMMs by switching the configuration of MOFs from cis to trans. The SO2 permeability and SO2/N2 selectivity of MMMs are investigated under both visible light and ultraviolet light states, and the SO2/N2 separation performance under visible light is notably improved in comparison with that under ultraviolet light state.

Sialidases are increasingly used in the production of sialyloligosaccharides, a significant component of human milk oligosaccharides. Elucidating the catalytic mechanism of sialidases is critical for the rational design of better biocatalysts, thereby facilitating the industrial production of sialyloligosaccharides. Through comparative all-atom molecular dynamics simulations, we investigated the structural dynamics of sialidases in Glycoside Hydrolase family 33 (GH33). Interestingly, several sialidases displayed significant conformational transition and formed a new cleft in the simulations. The new cleft was adjacent to the innate active site of the enzyme, which serves to accommodate the glycosyl acceptor. Furthermore, the residues involved in the specific interactions with the substrate were evolutionarily conserved in the whole GH33 family, highlighting their key roles in the catalysis of GH33 sialidases. Our results enriched the catalytic mechanism of GH33 sialidases, with potential implications in the rational design of sialidases.

Absorption and scattering in aqueous media would attenuate light and make imaging difficult. Therefore, an artificial light source is usually utilized to assist imaging in the deep ocean. However, the artificial light source typically alters the light conditions to a large extent, resulting in the non-uniform illumination of images. To solve this problem, we propose a non-uniform illumination correction algorithm based on a fully convolutional network for underwater images. The proposed algorithm model the original image as the addition of the ideal image and a non-uniform light layer. We replace the traditional pooling layer with dilated convolution to expand the receptive field and achieve higher accuracy in non-uniform illumination recognition. To improve the perception ability of the network effectively, the original image and parameters which pre-trained on the ImageNet are concentrated. The concentrated information is used as input to the network. Due to the color shift and blurred details of the underwater image, we design the novel loss function, which includes three parts of feature loss, smooth loss, and adversarial loss. Moreover, we built a dataset of the underwater image with non-uniform illumination. Experiments show that our method performs better in subjective assessment and objective assessment than some traditional methods.

Underwater images suffer from low visibility and contrast caused by absorption and scattering, which leads to haze and some further limitations. The existing underwater single image dehazing methods cannot achieve a balance between the performance and computational complexity, and are difficult to produce satisfactory results in the regions with large distance. To overcome these problems, we propose a new underwater single image dehazing method, which includes an improved background light estimation based on the quad-tree subdivision iteration algorithm, and a novel transmission estimation method. For the background light estimation, we introduce a robust score for each region of the image, which can evaluate the region from both smoothness and color. For the transmission estimation, we propose the color space dimensionality reduction prior (CSDRP), which allows conversing an image from the three-dimensional RGB color space to a 2D color space, namely the UV color space. In the UV color space, by clustering the pixels into mounts of haze-lines and carefully setting the haze-free boundary, the transmission map can be figured out and used to produce an excellent dehazed image. Experimental results show that our method has competitive effects compared with mainstream underwater single image dehazing methods.

As a natural sweetening and solubilizing agent, rubusoside has great potential in the application of healthy beverages and pharmaceuticals. However, the direct extraction and purification of rubusoside from raw materials is inefficient. In this work, a novel β-glucosidase (CsBGL) was obtained from Chryseobacterium scophthalmum 1433 through screening of the environmental microorganisms. CsBGL markedly hydrolyzed sophorese (Glcβ1-2Glc) and laminaribiose (Glcβ1-3Glc), but for steviol glycosides, it only hydrolyzed the C-13/C-19-linked sophorese, instead of the C-13/C-19-linked Glcβ1-2[Glcβ1-3]Glc trisaccharide and Glcβ1-monosaccharide. It efficiently hydrolyzed stevioside (240 g/L) to produce rubusoside (99% yield) at 47.5°C for 70 min. Even when using a crude steviol glycosides extract (500 g/L) containing ∼226 g/L stevioside as the substrate, CsBGL could also convert stevioside to rubusoside (99% yield) at 47.5°C for 2 h, in which the rubusoside concentration increased from the initial 42 g/L to the final 222 g/L. These results reveal that CsBGL would be a promising biocatalyst for the industry-scale production of rubusoside from stevioside or/and the crude steviol glycosides extract.

Abstract The aim of this study was to investigate the association of sarcopenia and diabetic foot disease (DFD) in a cross-sectional study. Body composition was assessed using dual-energy X-ray-absorptiometry (DXA) among 1105 patients with type 2 diabetes (120 patients with newly diagnosed DFD [DFD duration less than 3 months]). Severity of DFD was assessed, referring to foot ulcers, Wagner grade and the percentage of amputation. Skeletal muscle index (SMI) was calculated, and sarcopenia was defined as SMI less than 7.0 kg/m2 (in men) or 5.4 kg/m2 (in women). SMI was significantly decreased in patients with DFD compared to patients without (6.79 ± 1.20 vs. 7.21 ± 1.05 kg/m2, P

The article discusses the study on the major subtypes of obesity such as the general and the abdominal obesity which are known to be associated with chronic diabetes complications, like cardiovascular diseases and diabetic retinopathy. Topics discussed include the diabetic kidney disease (DKD), type 2 diabetes (T2D) patients assess through DXA, and the parameters of general obesity such as body mass index (BMI), total body fat percentage(TBF), and fat mass index (FMI).