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Skincare is one of the most profitable product categories today. Consumers’ demand for skin-friendly products has stimulated the development of natural-ingredient-based cosmeceutical preparations over synthetic chemicals. Thus, natural polysaccharides have gained much attention since the promising potent efficacy in wound healing, moisturizing, antiaging, and whitening. The challenge is to raise awareness of polysaccharides with excellent bioactivities from natural sources and consequently incorporate them in novel and safer cosmetics. This review highlights the benefits of natural polysaccharides from plants, algae, and fungi on skin health, and points out some obstacles in the application of natural polysaccharides.

Yao, Y.Y., 2020. Water environment protection and utilization based on the perspective of marxist ecological theory. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 130–135. Coconut Creek (Florida), ISSN 0749-0208. According to the problem that the use and development of water resources cannot be lack of ecological protection as a basic idea to ensure the goal of protecting the ecology and saving water. Therefore, in order to better study the environmental protection and utilization of water ecology, this paper makes a simple discussion on the sustainable development and utilization of water resources based on the background of ecological environment protection and the Marxist ecological theory, in the theory and algorithm of water footprint On the basis of the research, the current status of water ecology in a county town and the utilization of water resources were studied. It was found that the local water resources utilization rate was low and the water ecological environment pollution was serious. Specific suggestions were put forward from the perspectives of water resources management and water ecological management. For the reference of relevant personnel. After research, it is proposed that the establishment of the overall framework of the water ecological compensation mechanism to rationally develop and utilize water resources, and increase the intensity of sewage treatment can help the sustainable development and utilization of water resources. This has a theoretical and theoretical basis for revealing the root causes of China's ecological crisis. Practical significance.

Incorporating β-glucan-rich oat bran (OB) can attenuate postprandial glycemic response (PPGR) in solid foods, but its effect in liquid matrices is unclear. This study investigated the ability of differently processed low-dose-β-glucan-containing beverages to lower PPGR, and the mechanisms of action. Twenty participants consumed five malt beverages made from cocoa powder: intact OB (Intact), OB treated with enzymatic hydrolysis (EnzymA, EnzymB) or extrusion (Extr), or no OB (Ctrl). Four-hour postprandial incremental areas under the curve (iAUC) and peak incremental concentrations (iCmax) of glucose, insulin, glucagon-like peptide 1 (GLP-1), gastric inhibitory polypeptide (GIP), and paracetamol were evaluated. The molecular weight (MW) and extractability of the β-glucan in all the test products were also assessed. The three-hour glucose iAUC significantly decreased by −26%, −28%, −32%, and −38% in Intact, EnzymA, EnzymB, and Extr, respectively, and the insulin levels of the oat-containing products were also significantly lower compared to Ctrl. Intact and Extr elicited a lower insulin iCmax and GLP-1 3 h iAUC compared to Ctrl. However, the GIP and paracetamol levels were not changed. All the processed OBs improved β-glucan extractability and lowered the MW of β-glucan compared to Intact. In conclusion, low-dose oat β-glucan in a beverage significantly reduced PPGR, with effects maintained across different oat processing methods.

In this study, the effects of konjac glucomannan (KGM) at different concentrations on the physiochemical and sensory properties of soy protein isolate (SPI), pea protein isolate (PPI), or peanut protein isolate (PNPI) compound gels were investigated. The results revealed that when the ratio of PNPI to KGM was 90:10, the denaturation temperature of PNPI could be significantly enhanced to 119.32°C by KGM modification. Concerning the textural and microstructural features, the amount of KGM addition had positive correlation with the hardness and chewiness of each compound gel, however, too much KGM addition will cause the unstable internal structure of the PNPI/KGM compound gels (70:30 and 60:40). Furthermore, sensory results indicated that PNPI/KGM (80:20), PPI/KGM (80:20), SPI/KGM (80:20) had great potential to be considered as prototypes for novel plant‐based products, which generated the highest acceptance scores of 5.04, 5.94, and 5.36 in each group, respectively.

Objective This systematic review provides an overview of machine learning (ML) methods for predicting diabetic peripheral neuropathy (DPN). Method We searched PubMed, Embase, Cochrane Library, and Web of Science databases with the search period limited from their inception to December 3, 2024 (the last search date). The search terms were restricted to “diabetes,” “neuropathy,” and “machine learning.” All studies that developed or validated prognostic models for DPN using ML were considered. Prediction model Risk of Bias ASsessment Tool (PROBAST) was used to assess the risk of bias and applicability of included studies. Results A total of 888 studies were retrieved and 15 articles were included. Most were retrospective studies, with sample sizes ranging from 90 to 102,876 patients. All 15 studies utilised internal validation methods, three studies employed both internal and external validation methods. Internal validation methods like cross-validation were widely used, with area under the curve (AUC) ranging from 0.640 to 0.900. A total of six studies reported complete AUC values yielding a pooled AUC of 0.773 (CI: 0.707–0.839, I²= 99.14). A total of 34 different ML algorithms were utilised across the studies, with the top five being logistic regression, random forest, support vector machine, decision tree, and XGBoost. Calibration was reported in 6 studies, showing satisfactory performance. All studies had a high risk of bias, but most models demonstrated good applicability. Conclusion Existing DPN prediction models demonstrate good performance in discrimination. However, the evaluation indicates that the overall risk of bias in the included studies is high, and their applicability is limited. Future efforts should prioritize prospective, large, multicentre datasets, external validation, and adherence to PROBAST guidelines to reduce bias and enhance applicability for clinical application.

The tubers of Curcuma kwangsiensis are regarded as an important medicinal material in China. In C. kwangsiensis cultivation, tuber expansion is key to yield and quality, but the regulatory mechanisms are not well understood. In this study, metabolomic and transcriptomic analyses were conducted to elucidate the mechanism underlying tuber expansion development. The results showed that auxin (IAA), jasmonic acid (JA), gibberellin (GA 3) , ethylene (ETH), and brassinolide (BR) levels increased during tuber expansion development. Metabolomic analysis showed that 197 differentially accumulated metabolites (DAMs) accumulated during tuber expansion development and these also play important roles in the accumulation of carbohydrates and secondary metabolites. 6962 differentially expressed genes (DEGs) were enriched in plant hormone signal transduction, starch and sucrose metabolism, linoleic acid metabolism, MAPK signaling pathway as well as sesquiterpenoid and triterpenoid biosynthesis. Comprehensive analysis revealed that DEGs and DAMs of plant hormone signal transduction, ABC transporters and biosynthesis of phenylpropanoids and terpenoids are critical pathways in regulating tuber expansion. In addition, some transcription factors ( ARF , C2H2 , C3H , NAC , bHLH , GRAS and WRKY ) as well as hub genes ( HDS , HMGR , ARF7 , PP2CA , PAL and CCOMT ) are also involved in this process. This study lays a theoretical basis for the molecular mechanism of tuber expansion in C. kwangsiensis .

The farnesoid X receptor (FXR) has been recognized as a potential drug target for the treatment of non-alcoholic fatty liver disease (NAFLD). FXR agonists benefit NAFLD by modulating bile acid synthesis and transport, lipid metabolism, inflammation, and fibrosis pathways. However, there are still great challenges involved in developing safe and effective FXR agonists. To investigate the critical factors contributing to their activity on the FXR, 3D-QSAR molecular modeling was applied to a series of isoxazole derivatives, using comparative molecular field analysis (CoMFA (q2 = 0.664, r2 = 0.960, r2pred = 0.872)) and comparative molecular similarity indices analysis (CoMSIA (q2 = 0.706, r2 = 0.969, r2pred = 0.866)) models, which demonstrated strong predictive ability in our study. The contour maps generated from molecular modeling showed that the presence of hydrophobicity at the R2 group and electronegativity group at the R3 group in these compounds is crucial to their agonistic activity. A molecular dynamics (MD) simulation was carried out to further understand the binding modes and interactions between the FXR and its agonists in preclinical or clinical studies. The conformational motions of loops L: H1/H2 and L: H5/H6 in FXR–ligand binding domain (LBD) were crucial to the protein stability and agonistic activity of ligands. Hydrophobic interactions were formed between residues (such as LEU287, MET290, ALA291, HIS294, and VAL297) in helix H3 and ligands. In particular, our study found that residue ARG331 participated in salt bridges, and HIS447 participated in salt bridges and hydrogen bonds with ligands; these interactions were significant to protein–ligand binding. Eight new potent FXR agonists were designed according to our results, and their activities were predicted to be better than that of the first synthetic FXR agonist, GW4064.

To investigate the changes of Cold-Inducible RNA-Binding Protein (CIRBP) expression in mouse spinal cord injury model. Seventy-five female C57BL/6 mice were randomly divided into five groups, 15 mice per group. According to different degrees of spinal cord injury, they were divided into Mild spinal cord injury, Moderate spinal cord injury, Severe spinal cord injury, Spinal cord amputation group, and Sham surgery group, all constructed with spinal cord percussion. All groups were dissected 1, 3, 5, 14, and 21 days after modeling. HE staining was used to observe the pathological changes in the spinal cord, The Basso mouse scale (BMS) was used for motor function scoring, and immunofluorescence was used to detect the expression of NeuN, IBA-1, and CIRBP in spinal cord tissues. HE results showed that inflammation was more pronounced in moderate, severe, and amputation injuries compared to the Sham surgery group. Moderate injury group and Severe injury group inflammation increased consistently over time. The severe injury group had severe tissue structure destruction and increased astrocytes significantly. Combined with the mouse BMS motor function score, the mouse severe injury group model was more stable. Compared with the Sham surgery group, there was a significant decrease in NeuN over time (P < 0.01) and a significant increase in IBA-1 and CIRBP (P < 0.01) in the severe injury group. Moreover, IBA-1 has significant co-localization with CIRBP. CIRBP expression is significantly elevated in a mouse spinal cord injury model, Which may be related to the proliferation of microglia during spinal cord injury.

To understand the effect of the hydroxyl group and processing temperatures on dielectric losses of flame retardants and flame-retardant polymers, the performance difference between 6-methyldibenzo[c,e][1,2]oxaphosphinine 6-oxide (DOPO-Me) and 6-(hydroxymethyl)dibenzo[c,e][1,2]oxaphosphinine 6-oxide (DOPO-HM) has been investigated, respectively, in non-polar and polar polymers at 7–20 GHz. DOPO-HM and DOPO-Me differ by only one OH group. The former demonstrates a lower dissipation factor (Df) than the latter, owing to hydrogen bonds. In polystyrene and crosslinked polyphenylene oxide, both flame retardants increase a dielectric loss of flame-retardant polymers, with DOPO-HM being less detrimental because of its higher crystallizability and lower plasticization. In polar poly(methyl methacrylate) (PMMA), conformational changes in PMMA main chains caused by flame retardants and high processing temperatures lead to an early Df drop of PMMA at low loadings of the flame retardants. At high loadings, a change in the physical form of flame retardants from a primitive crystalline state to an amorphous state increases a dielectric loss of flame retardant PMMA, with DOPO-HM resulting in a slightly higher dielectric loss than DOPO-Me. These results prove that the effect of a hydroxyl group in organophosphorus structures on the dielectric loss of flame-retardant polymers is crucially dependent on its interaction with the polymer matrix.

Fractured karstic carbonate reservoirs have obvious multi-scale characteristics and severe heterogeneity due to the development of abundant karst caves and fractures with different scales. Darcy and non-Darcy flows coexist due to this property. Therefore, selecting the appropriate flow equations for different regions in the numerical simulation of fluid flows, particularly two-phase and multiphase flows, is a critical topic. This paper compares and analyses the displacement distance differences of waterfront travel using the Darcy, Forchheimer and Barree–Conway equations, as well as analyzes the influence of the Forchheimer constant, fluid viscosity, flow rate and absolute permeability on inertia action based on the Buckley–Leverett theory. The results show that the Forchheimer number/Reynolds number of water/oil two-phase flow is not a constant value and varies with water saturation, making it difficult to determine whether the inertial action should be considered solely based on these values; the influence of inertial action can be measured well by comparing the difference between the displacement distances of the waterflood front, and the quantitative standard is given for the selection of the flow equation of different regions by calculating the allowable error of the displacement distance of the waterflood front. The magnitude of the inertial effect is affected by the physical properties of the fluid and reservoir medium and the fluid velocity. The smaller the difference in the viscosity of the oil/water fluid, the smaller the inertial effect is. This technique was used a preliminary attempt to analyze the fractured karstic carbonate reservoirs at Tarim, and the results confirmed the validity of the method described in this article.