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Dynamic path optimization is an important part of intelligent transportation systems (ITSs). Aiming at the shortcomings of the current dynamic path optimization method, the improved ant colony algorithm was used to optimize the dynamic path. Through the actual investigation and analysis, the influencing factors of the multiobjective planning model were determined. The ant colony algorithm was improved by using the analytic hierarchy process (AHP) to transform path length, travel time, and traffic flow into the comprehensive weight-influencing factor. Meanwhile, directional guidance and dynamic optimization were introduced to the improved ant colony algorithm. In the simulated road network, the length of the optimal path obtained by the improved ant colony algorithm in the simulation road network is 3.015, which is longer than the length of the optimal path obtained by the basic ant colony algorithm (2.902). The travel time of the optimal path obtained by the improved ant colony algorithm (376 s) is significantly shorter than that of the basic ant colony algorithm (416.3 s). The number of iterations of the improved ant colony algorithm (45) is less than that of the basic ant colony algorithm (58). In the instance network, the number of iterations of the improved ant colony algorithm (18) is less than that of the basic ant colony algorithm (26). The travel time of the optimal path obtained by the improved ant colony algorithm (377.1 s) is significantly shorter than that of the basic ant colony algorithm (426 s) and the spatial shortest distance algorithm (424 s). Compared with the basic ant colony algorithm and the spatial shortest distance algorithm, the results of the optimal path obtained by the improved ant colony algorithm were more accurate, and the effectiveness of the improved ant colony algorithm was verified.

Deep learning allows automatic segmentation of teeth on cone beam computed tomography (CBCT). However, the segmentation performance of deep learning varies among different training strategies. Our aim was to propose a 3.5D U-Net to improve the performance of the U-Net in segmenting teeth on CBCT. This study retrospectively enrolled 24 patients who received CBCT. Five U-Nets, including 2Da U-Net, 2Dc U-Net, 2Ds U-Net, 2.5Da U-Net, 3D U-Net, were trained to segment the teeth. Four additional U-Nets, including 2.5Dv U-Net, 3.5Dv5 U-Net, 3.5Dv4 U-Net, and 3.5Dv3 U-Net, were obtained using majority voting. Mathematical morphology operations including erosion and dilation (E&D) were applied to remove diminutive noise speckles. Segmentation performance was evaluated by fourfold cross validation using Dice similarity coefficient (DSC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV). Kruskal–Wallis test with post hoc analysis using Bonferroni correction was used for group comparison. P  < 0.05 was considered statistically significant. Performance of U-Nets significantly varies among different training strategies for teeth segmentation on CBCT ( P  < 0.05). The 3.5Dv5 U-Net and 2.5Dv U-Net showed DSC and PPV significantly higher than any of five originally trained U-Nets (all P  < 0.05). E&D significantly improved the DSC, accuracy, specificity, and PPV (all P  < 0.005). The 3.5Dv5 U-Net achieved highest DSC and accuracy among all U-Nets. The segmentation performance of the U-Net can be improved by majority voting and E&D. Overall speaking, the 3.5Dv5 U-Net achieved the best segmentation performance among all U-Nets.

Background Chronic neuropathic pain is a frequent sequel to peripheral nerve injury and maladaptive nervous system function. Divanillyl sulfone (DS), a novel structural derivative of 4,4′-dihydroxydibenzyl sulfoxide from a traditional Chinese medicine Gastrodia elata with anti-nociceptive effects, significantly alleviated neuropathic pain following intrathecal injection. Here, we aimed to investigate the underlying mechanisms of DS against neuropathic pain. Methods A chronic constrictive injury (CCI) mouse model of neuropathic pain induced by sciatic nerve ligation was performed to evaluate the effect of DS by measuring the limb withdrawal using Von Frey filament test. Immunofluorescence staining was used to assess the cell localizations and expressions of Iba-1, ASC, NLRP3, and ROS, the formation of autolysosome. The levels of NLRP3-related proteins (caspase-1, NLRP3, and IL-1β), mitophagy-related proteins (LC3, Beclin-1, and p62), and apoptosis-related proteins (Bcl-XL and Bax) were detected by Western blotting. The apoptosis of BV-2 cell and caspase activity were evaluated by flow cytometry. Results DS significantly alleviated the neuropathic pain by increasing the mechanical withdrawal threshold and inhibiting the activation of NLRP3 in CCI-induced model mice. Our findings indicated that DS promoted the mitophagy by increasing the LC3II and Beclin 1 and decreasing the levels of p62 protein in BV-2 cell. This is accompanied by the inhibition of NLRP3 activation, which was shown as inhibited the expression of NLRP3 in lysates as well as the secretion of mature caspase-1 p10 and IL-1β p17 in supernatants in cultured BV-2 microglia. In addition, DS could promote mitophagy-induced improvement of dysfunctional mitochondria by clearing intracellular ROS and restoring mitochondrial membrane potential. Conclusion Together, our findings demonstrated that DS ameliorate chronic neuropathic pain in mice by suppressing NLRP3 inflammasome activation induced by mitophagy in microglia. DS may be a promising therapeutic agent for chronic neuropathic pain.

In geo- and astrophysics, low Prandtl number convective flows often interact with magnetic fields. Although a static magnetic field acts as a stabilizing force on such flow fields, we find that self-organized convective flow structures reach an optimal state where the heat transport significantly increases and convective velocities reach the theoretical free-fall limit, i.e. the maximum possible velocity a fluid parcel can achieve when its potential buoyant energy is fully converted into kinetic energy. Our measurements show that the application of a static magnetic field leads to an anisotropic, highly ordered flow structure and a decrease of the turbulent fluctuations. When the magnetic field strength is increased beyond the optimum state, Hartmann braking becomes dominant and leads to a reduction of the heat and momentum transport. The results are relevant for the understanding of magneto-hydrodynamic convective flows in planetary cores and stellar interiors in regions with strong toroidal magnetic fields oriented perpendicular to temperature gradients.

In humans, Interleukin-8 (IL-8 or CXCL8) is a granulocytic chemokine with multiple roles within the tumor microenvironment (TME), such as recruiting immunosuppressive cells to the tumor, increasing tumor angiogenesis, and promoting epithelial-to-mesenchymal transition (EMT). All of these effects of CXCL8 on individual cell types can result in cascading alterations to the TME. The changes in the TME components such as the cancer-associated fibroblasts (CAFs), the immune cells, the extracellular matrix, the blood vessels, or the lymphatic vessels further influence tumor progression and therapeutic resistance. Emerging roles of the microbiome in tumorigenesis or tumor progression revealed the intricate interactions between inflammatory response, dysbiosis, metabolites, CXCL8, immune cells, and the TME. Studies have shown that CXCL8 directly contributes to TME remodeling, cancer plasticity, and the development of resistance to both chemotherapy and immunotherapy. Further, clinical data demonstrate that CXCL8 could be an easily measurable prognostic biomarker in patients receiving immune checkpoint inhibitors. The blockade of the CXCL8-CXCR1/2 axis alone or in combination with other immunotherapy will be a promising strategy to improve antitumor efficacy. Herein, we review recent advances focusing on identifying the mechanisms between TME components and the CXCL8-CXCR1/2 axis for novel immunotherapy strategies.

Enzymatic stereoselectivity has typically been unrivalled by most chemical catalysts, especially in the conversion of small substrates. According to the ‘lock-and-key theory’ 1 , 2 , enzymes have confined active sites to accommodate their specific reacting substrates, a feature that is typically absent from chemical catalysts. An interesting case in this context is the formation of cyanohydrins from ketones and HCN, as this reaction can be catalysed by various classes of catalysts, including biological, inorganic and organic ones 3 – 7 . We now report the development of broadly applicable confined organocatalysts for the highly enantioselective cyanosilylation of aromatic and aliphatic ketones, including the challenging 2-butanone. The selectivity (98:2 enantiomeric ratio (e.r.)) obtained towards its pharmaceutically relevant product is unmatched by any other catalyst class, including engineered biocatalysts. Our results indicate that confined chemical catalysts can be designed that are as selective as enzymes in converting small, unbiased substrates, while still providing a broad scope. The development of confined organocatalysts for the enantioselective cyanosilylation of small, unbiased substrates, including 2-butanone, is shown to lead to catalysts that are as selective as enzymes, with excellent levels of control.

Secondary failure of platelet recovery (SFPR) is a common complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), occurring in approximately 20% of cases, and is closely associated with poor patient prognosis. The purpose of this study is to analyze the risk factors associated with SFPR following allo-HSCT, develop a nomogram-based predictive model for SFPR, and validate its accuracy. Clinical data of patients who underwent allo-HSCT in the Department of Hematology at the First Hospital of Lanzhou University from January 2016 to December 2023 were collected. Variables with P  < 0.05 in univariate analysis were included in a logistic multivariate stepwise regression to identify the final variables for the model. An SFPR nomogram prediction model was developed using R software and internally validated using the Bootstrap method. The accuracy of the prediction model was assessed through receiver operating characteristic(ROC) and calibration curves, while decision curve analysis evaluated its clinical predictive performance. Based on the body mass index(BMI), chromosome karyotype, transplant type, acute graft-versus-host disease(aGVHD) and post-transplant Interleukin-6(IL-6) and Procalcitonin(PCT), the predicted area under the ROC curve of SFPR is 0.778 (95% CI 0.697–0.858). The absolute error between the predicted risk of SFPR and the actual risk is 0.019. The SFPR nomogram prediction model developed in this study exhibits high accuracy and excellent predictive efficiency, thereby possessing significant clinical guidance value.

Osteoarthritis (OA) is a chronic, degenerative joint disease presenting a significant global health threat. While current therapeutic approaches primarily target symptom relief, their efficacy in repairing joint damage remains limited. Recent research has highlighted mesenchymal stem cells (MSCs) as potential contributors to cartilage repair, anti-inflammatory modulation, and immune regulation in OA patients. Notably, MSCs from different sources and their derivatives exhibit variations in their effectiveness in treating OA. Moreover, pretreatment and gene editing techniques of MSCs can enhance their therapeutic outcomes in OA. Additionally, the combination of novel biomaterials with MSCs has shown promise in facilitating the repair of damaged cartilage. This review summarizes recent studies on the role of MSCs in the treatment of OA, delving into their advantages and exploring potential directions for development, with the aim of providing fresh insights for future research in this critical field.

Curcumin (CUR) possesses pronounced anti-inflammatory and antioxidant activities. Generally, the clinical application of CUR is restricted due to its apparent unstability and poor absorption, and the biological activities of CUR may be closely associated with its metabolites. Tetrahydrocurcumin (THC) and octahydrocurcumin (OHC) are two major hydrogenated metabolites of CUR with appreciable biological potentials. Here, we comparatively explored the anti-inflammatory and antioxidant activities of CUR, THC, and OHC in lipopolysaccharide- (LPS-) induced RAW264.7 macrophages. The results revealed that CUR, THC, and OHC dose-dependently inhibited the generation of NO and MCP-1 as well as the gene expression of MCP-1 and iNOS. Additionally, CUR, THC, and OHC significantly inhibited NF-κB activation and p38MAPK and ERK phosphorylation, while substantially upregulated the Nrf2 target gene expression (HO-1, NQO-1, GCLC, and GCLM). Nevertheless, zinc protoporphyrin (ZnPP), a typical HO-1 inhibitor, significantly reversed the alleviative effect of CUR, THC, and OHC on LPS-stimulated ROS generation. These results demonstrated that CUR, THC, and OHC exerted beneficial effect on LPS-stimulated inflammatory and oxidative responses, at least partially, through inhibiting the NF-κB and MAPKs pathways and activating Nrf2-regulated antioxidant gene expression. Particularly, THC and OHC might exert superior antioxidant and anti-inflammatory activities to CUR in LPS-stimulated RAW264.7 cells, which can be further explored to be a promising novel effective agent for inflammatory treatment.

Traditional Chinese medicine (TCM) performs a good clinical practice and is showing a bright future in the treatment of diabetes mellitus (DM). TCM treatment has certain advantages of less toxicity and/or side effects, and herbs could provide multiple therapeutic effects. Berberine (BBR) is a classical natural medicine. In this review, we summarize the application of BBR in the treatment of DM from two aspects. First, modern pharmacological effects of BBR on glucose metabolism are summarized, such as improving insulin resistance, promoting insulin secretion, inhibiting gluconeogenesis in liver, stimulating glycolysis in peripheral tissue cells, modulating gut microbiota, reducing intestinal absorption of glucose, and regulating lipid metabolism. BBR is used to treat diabetic nephropathy (DPN), diabetic neuropathy (DN), and diabetic cardiomyopathy due to its antioxidant and anti-inflammatory activities. Second, the clinical application of BBR is reviewed, such as listing some clinical trials on the effectiveness and safety of BBR, explaining applicable stage and syndrome, the reasonable dose and dose formulation, and the toxicity and/or side effects. This review provides scientific evidence about BBR, as well as introducing some traditional Chinese medical theory and clinical experience, in order to guide clinician to use BBR more suitably and reasonably.