Based on Serum Pharmacochemistry and Virtual Screening Technique Analysis Used to Explore the Potential Active Ingredients and Possible Anti- Coronary Heart Disease Mechanisms of Salvia miltiorrhiza Bunge.

AIMS AND OBJECTIVE: This study aimed to identify the bioactive compounds and explore the multi-target mechanisms of Salvia miltiorrhiza Bunge (SMB) against coronary heart disease (CHD) using an integrated serum pharmacochemistry and network pharmacology approach. MATERIALS AND METHODS: The chemical constituents of SMB were characterized by UPLC-MS. The absorbed ingredients and metabolites after oral SMB administration were identified in rat serum. Therapeutic targets of SMB against CHD were predicted by intersecting the targets of absorbed compounds from databases and CHD-associated genes. Protein-protein interaction network, pathway analysis, molecular docking, and molecular dynamic simulation were performed. RESULTS: A total of 61 SMB-derived compounds were identified in rat serum. Network analysis revealed 111 candidate targets highly related to CHD pathways. Further topological analysis identified 10 hub targets and 20 key active compounds, constructing an informative compoundtarget- pathway network. PTGS2 and TNF were predicted as primary targets of SMB against CHD based on molecular dynamic simulation. CONCLUSION: This integrated approach identified bioactive compounds and multi-target mechanisms of SMB against CHD. The results provide scientific evidence supporting SMB's clinical efficacy and reveal potential anti-CHD targets.

Te-induced fabrication of Pt3PdTe0.2 alloy nanocages by the self-diffusion of Pd atoms with unique MOR electrocatalytic performance.

The key to the application of direct methanol fuel cells is to improve the activity and durability of Pt-based catalysts. Based on the upshift of the d-band centre and exposure to more Pt active sites, Pt3PdTe0.2 catalysts with significantly enhanced electrocatalytic performance for the methanol oxidation reaction (MOR) were designed in this study. A series of different Pt3PdTex (x = 0.2, 0.35, and 0.4) alloy nanocages with hollow and hierarchical structures were synthesized using cubic Pd nanoparticles as sacrificial templates and PtCl62- and TeO32- metal precursors as oxidative etching agents. The Pd nanocubes were oxidized into an ionic complex, which was further co-reduced with Pt and Te precursors by reducing agents to form the hollow Pt3PdTex alloy nanocages with a face-centred cubic lattice. The sizes of the nanocages were around 30-40 nm, which were larger than the Pd templates (18 nm) and the thicknesses of the walls were 7-9 nm. The Pt3PdTe0.2 alloy nanocages exhibited the highest catalytic activities and stabilities toward the MOR after electrochemical activation in sulfuric acid solution. CO-stripping tests suggested the enhanced CO-tolerant ability due to the doping of Te. The specific activity of Pt3PdTe0.2 for the MOR reached 2.71 mA cm-2 in acidic conditions, which was higher than those of Pd@Pt core-shell and PtPd1.5 alloy nanoparticles and commercial Pt/C. A DMFC with Pt3PdTe0.2 as the anodic catalyst output a higher power density by 2.6 times than that of commercial Pt/C, demonstrating its practicable application in clean energy conversions. Density functional theory (DFT) confirmed that the alloyed Te atoms altered the electron distributions of Pt3PdTe0.2, which could lower the Gibbs free energy of the rate-determining methanol dehydrogenation step and greatly improve the MOR catalytic activity and durability.

Resource saving and carbon footprint reduction potential of urban symbiosis strategy in express packaging waste recycling network.

The booming express delivery industry corresponds to the environmental challenges caused by massive express packaging waste (EPW). An efficient logistics network is necessary link to support EPW recycling. This study, therefore, designed a circular symbiosis network for EPW recycling based on urban symbiosis strategy. The treatment of EPW in this network includes reuse, recycling and replacing. An optimization model with multi-depot collaboration combining material flow analysis and optimization methods was developed and a hybrid non-dominated sorting genetic algorithm-II (NSGA-II) was designed as technical support for designing the circular symbiosis network while quantitatively assessing the economic and environmental benefits of the network. The results show that the designed circular symbiosis option has better resource saving and carbon footprint reduction potential than both the business as usual option and circular symbiosis option without service collaboration. In practice, the proposed circular symbiosis network can save EPW recycling costs and reduce carbon footprint. This study provides a practical guideline for the application of urban symbiosis strategies to help urban green governance and the sustainable development of express companies.

TMT-based quantitative proteomics analysis of the effects of Jiawei Danshen decoction myocardial ischemia-reperfusion injury.

BACKGROUND: Every year, approximately 17 million people worldwide die due to coronary heart disease, with China ranking second in terms of the death toll. Myocardial ischemia-reperfusion injury (MIRI) significantly influences cardiac function and prognosis in cardiac surgery patients. Jiawei Danshen Decoction (JWDSD) is a traditional Chinese herbal prescription that has been used clinically for many years in China to treat MIRI. The underlying molecular mechanisms, however, remain unknown. To investigate the proteomic changes in myocardial tissue of rats given JWDSD for MIRI therapy-based proteomics. METHODS: MIRI rat model was created by ligating/releasing the left anterior descending coronary artery. For seven days, the drugs were administered twice daily. The model was created following the last drug administration. JWDSD's efficacy in improving MIRI was evaluated using biochemical markers and cardiac histology. Tandem mass tag-based quantitative proteomics (TMT) technology was also used to detect proteins in the extracted heart tissue. To analyze differentially expressed proteins (DEPs), bioinformatics analysis, including gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathways, were employed. Furthermore, western blotting confirmed the potential targets regulated by JWDSD. RESULTS: The histopathologic characteristics and biochemical data showed JWDSD's protective effects on MIRI rats. A total of 4549 proteins were identified with FDR (false discovery rate) ≤1%. Twenty overlapping were identified (162 DEPs and 45 DEPs in Model/Control or JWDSD/Model group, respectively). Of these DEPs, 16 were regulated by JWDSD. GO analysis provided a summary of the deregulated protein expression in the categories of biological process (BP), cell component (CC), and molecular function (MF). KEGG enrichment analysis revealed that the signaling pathways of neutrophil extracellular trap formation, RNA polymerase, serotonergic synapse, and linoleic acid metabolism are all closely related to JWDSD effects in MIRI rats. Furthermore, T-cell lymphoma invasion and metastasis 1 (TIAM1) was validated using western blotting, and the results were consistent with proteomics data. CONCLUSIONS: Our study suggests that JWDSD may exert therapeutic effects through multi-pathways regulation in MIRI treatment. This work may provide proteomics clues for continuing research on JWDSD in treating MIRI.

A bi-objective optimization model for the medical supplies' simultaneous pickup and delivery with drones.

In the COVID-19 pandemic, it is essential to transport medical supplies to specific locations accurately, safely, and promptly on time. The application of drones for medical supplies delivery can break ground traffic restrictions, shorten delivery time, and achieve the goal of contactless delivery to reduce the likelihood of contacting COVID-19 patients. However, the existing optimization model for drone delivery is cannot meet the requirements of medical supplies delivery in public health emergencies. Therefore, this paper proposes a bi-objective mixed integer programming model for the multi-trip drone location routing problem, which allows simultaneous pick-up and delivery, and shorten the time to deliver medical supplies in the right place. Then, a modified NSGA-II (Non-dominated Sorting Genetic Algorithm II) which includes double-layer coding, is designed to solve the model. This paper also conducts multiple sets of data experiments to verify the performance of modified NSGA-II. Comparing with separate pickup and delivery modes, this study demonstrates that the proposed optimization model with simultaneous pickup and delivery mode achieves a shorter time, is safer, and saves more resources. Finally, the sensitivity analysis is conducted by changing some parameters, and providing some reference suggestions for medical supplies delivery management via drones.

Administration of a mixture of triterpenoids from yeyachun and phenolic acids from danshen ameliorates carbon tetrachloride-induced liver fibrosis in mice by the regulation of intestinal flora.

yeyachun and danshen exist as Chinese patent medicine, Xuemai Tong, and are clearly effective at alleviating liver fibrosis (LF). Previous studies have indicated that triterpenoids from yeyachun (EFT), and phenolic acids from danshen (SMP) are effective in the treatment of LF. The regulation of intestinal flora is an effective method for treating LF. The aim of this study was to investigate the effect of a mixture of EFT and SMP on carbon tetrachloride (CCl4) induced LF. Our results showed the mixture significantly decreased liver damage and fibrosis index, and maintained liver tissue composition, compared to the model group. Moreover, the imbalance of symptoms of intestinal flora was improved. The mixture also caused changes to metabolites of gut flora. Furthermore, the expression of CD68 in liver tissues from the treated groups was significantly decreased when compared to the model group. However, no significant difference was observed from microstructure of gut tissues and LPS concentrations in the serum between mixture treated mice and model mice. This study suggests that the mixture of EFT and SMP had a significant effect on CCl4 induced LF, and the mechanism of this action, at least in part, involved the regulation of intestinal flora and their metabolites.

Optimization of Location-Routing Problem in Emergency Logistics Considering Carbon Emissions.

In order to solve the optimization problem of emergency logistics system, this paper provides an environmental protection point of view and combines with the overall optimization idea of emergency logistics system, where a fuzzy low-carbon open location-routing problem (FLCOLRP) model in emergency logistics is constructed with the multi-objective function, which includes the minimum delivery time, total costs and carbon emissions. Taking into account the uncertainty of the needs of the disaster area, this article illustrates a triangular fuzzy function to gain fuzzy requirements. This model is tackled by a hybrid two-stage algorithm: Particle swarm optimization is adopted to obtain the initial optimal solution, which is further optimized by tabu search, due to its global optimization capability. The effectiveness of the proposed algorithm is verified by the classic database in LRP. What's more, an example of a post-earthquake rescue is used in the model for acquiring reliable conclusions, and the application of the model is tested by setting different target weight values. According to these results, some constructive proposals are propounded for the government to manage emergency logistics and for the public to aware and measure environmental emergency after disasters.

Decision Analysis of Disturbance Management in the Process of Medical Supplies Transportation after Natural Disasters.

Public health emergencies, such as casualties and epidemic spread caused by natural disasters, have become important factors that seriously affect social development. Special medical supplies, such as blood and vaccines, are important public health medical resources, and the cold-chain distribution of medical supplies is in a highly unstable environment after a natural disaster that is easily affected by disturbance events. This paper innovatively studies the distribution optimization of medical supplies after natural disasters from the perspective of disturbance management. A disturbance management model for medical supplies distribution is established from two dimensions: time and cost. In addition, a hybrid genetic algorithm is introduced to solve the model. Disturbance recovery schemes with different weight coefficients are obtained through the actual numerical experiments, and experimental results show the effectiveness of the proposed model and algorithm. Finally, we discuss the formulation of weight coefficients in the case of emergency distribution and general distribution, which provide a reference for emergency decisions in disturbance events.

Optimization of Location-Routing Problem for Cold Chain Logistics Considering Carbon Footprint.

In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location-routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network.