Microfluidic Continuous Synthesis of Size- and Facet-Controlled Porous Bi2O3 Nanospheres for Efficient CO2 to Formate Catalysis.

Bismuth-based catalysts are effective in converting carbon dioxide into formate via electrocatalysis. Precise control of the morphology, size, and facets of bismuth-based catalysts is crucial for achieving high selectivity and activity. In this work, an efficient, large-scale continuous production strategy is developed for achieving a porous nanospheres Bi2O3-FDCA material. First-principles simulations conducted in advance indicate that the Bi2O3 (111)/(200) facets help reduce the overpotential for formate production in electrocatalytic carbon dioxide reduction reaction (ECO2RR). Subsequently, using microfluidic technology and molecular control to precisely adjust the amount of 2, 5-furandicarboxylic acid, nanomaterials rich in (111)/(200) facets are successfully synthesized. Additionally, the morphology of the porous nanospheres significantly increases the adsorption capacity and active sites for carbon dioxide. These synergistic effects allow the porous Bi2O3-FDCA nanospheres to stably operate for 90 h in a flow cell at a current density of ≈250 mA cm- 2, with an average Faradaic efficiency for formate exceeding 90%. The approach of theoretically guided microfluidic technology for the large-scale synthesis of finely structured, efficient bismuth-based materials for ECO2RR may provide valuable references for the chemical engineering of intelligent nanocatalysts.

[Investigation of the mechanism of action and identification of candidate traditional Chinese medicines for the treatment of ischemic stroke in the Danshen-Jiangxiang pair based on drug-target-disease association network].

The therapeutic efficacy of Danshen and Jiangxiang in the treatment of ischemic stroke (IS) is relatively significant. Studying the mechanism of action of Danshen and Jiangxiang in the treatment of IS can effectively identify candidate traditional Chinese medicines (TCM) with efficacy. However, it is challenging to analyze the effector substances and explain the mechanism of action of Danshen-Jiangxiang from a systematic perspective using traditional pharmacological approaches. In this study, a systematic study was conducted based on the drug-target-symptom-disease association network using complex network theory. On the basis of the association information about Danshen, Jiangxiang and IS, the protein-protein interaction (PPI) network and the "drug pair-pharmacodynamic ingredient-target-IS" network were constructed. The different topological features of the networks were analyzed to identify the core pharmacodynamic ingredients including formononetin in Jiangxiang, cryptotanshinone and tanshinone IIA in Danshen as well as core target proteins such as prostaglandin G/H synthase 2, retinoic acid receptor RXR-alpha, sodium channel protein type 5 subunit alpha, prostaglandin G/H synthase 1 and beta-2 adrenergic receptor. Further, a method for screening IS candidates based on TCM symptoms was proposed to identify key TCM symptoms and syndromes using the "drug pair-TCM symptom-syndrome-IS" network. The results showed that three TCMs, namely Puhuang, Sanleng and Zelan, might be potential therapeutic candidates for IS, which provided a theoretical reference for the development of drugs for the treatment of IS.

DeepPPThermo: A Deep Learning Framework for Predicting Protein Thermostability Combining Protein-Level and Amino Acid-Level Features.

Using wet experimental methods to discover new thermophilic proteins or improve protein thermostability is time-consuming and expensive. Machine learning methods have shown powerful performance in the study of protein thermostability in recent years. However, how to make full use of multiview sequence information to predict thermostability effectively is still a challenge. In this study, we proposed a deep learning-based classifier named DeepPPThermo that fuses features of classical sequence features and deep learning representation features for classifying thermophilic and mesophilic proteins. In this model, deep neural network (DNN) and bi-long short-term memory (Bi-LSTM) are used to mine hidden features. Furthermore, local attention and global attention mechanisms give different importance to multiview features. The fused features are fed to a fully connected network classifier to distinguish thermophilic and mesophilic proteins. Our model is comprehensively compared with advanced machine learning algorithms and deep learning algorithms, proving that our model performs better. We further compare the effects of removing different features on the classification results, demonstrating the importance of each feature and the robustness of the model. Our DeepPPThermo model can be further used to explore protein diversity, identify new thermophilic proteins, and guide directed mutations of mesophilic proteins.

CDCS-TCM: A framework based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine, with the feature of synergistic effects of multi-component, multi-pathway and multi-target, plays an important role in the treatment of cancer, cardiovascular and cerebrovascular diseases, etc. However, chemical components in traditional Chinese medicine are complex and most of the pharmacological mechanisms remain unclear, especially the relationships of chemical components change during the metabolic process. AIM OF STUDY: Our aim is to provide a method based on complex network theory to analyze the causality and dynamic correlation of substances in the metabolic process of traditional Chinese medicine. MATERIALS AND METHODS: We proposed a framework named CDCS-TCM to analyze the causality and dynamic correlation between substances in the metabolic process of traditional Chinese medicine. Our method mainly consists two parts. The first part is to discover the local and global causality by the causality network. The second part is to investigate the dynamic correlations and identify the essential substance by dynamic substance correlation network. RESULTS: We developed a CDCS-TCM method to analyze the causality and dynamic correlation of substances. Using the XiangDan Injection for ischemic stroke as an example, we have identified the important substances in the metabolic process including substance pairs with strong causality and the dynamic changes of the core effector substance clusters. CONCLUSION: The proposed framework will be useful for exploring the correlations of active ingredients in traditional Chinese medicine more effectively and will provide a new perspective for the elucidation of drug action mechanisms and the new drug discovery.

Optimal scheduling study of cascade hydropower stations to ensure ecological flow requirements-A case study of the Gorge Section of the Yongding River, China.

In order to maintain the ecological health of rivers and balance ecological and economic benefits, the study focuses on the Gorge Section of the Yongding River. The Lyon method was utilized to determine suitable ecological flow values. An optimized scheduling model for cascade hydropower stations was established to meet ecological flow requirements. Various scheduling scenarios were established to derive the optimized dispatching schemes for cascade hydropower stations. The results show that the appropriate natural ecological flow for the Gorge Section of the Yongding River, ranges from 4.05 to 9.86 m3/s. Under Scenario 1 (outbound flow from Guanting Reservoir: 40.5 m3/s, ecological flow: 4.50 m3/s), Scenario 2 (40.5 m3/s, 6.68 m3/s), Scenario 3 (80.0 m3/s, 4.50 m3/s), and Scenario 4 (80.0 m3/s, 6.68 m3/s), the optimized scheduling schemes resulted in comprehensive system electricity generation of 10.4132 million kW.h, 9.1727 million kW.h, 18.6214 million kW.h, and 18.4660 million kW.h, respectively.

Impact of joint dispatch of reservoir group on water pollution incident in drinking water source area.

To reduce the harm of water contamination incidents in drinking water source areas (DWSAs) and explore feasible approaches, the research developed a hydrodynamic water quality model for DWSAs based on two dimensional water quality and quantity equations, Geographic Information System (GIS), and Digital Elevation Model (DEM). The Heshangshan Drinking Water Source Area (HDWSA) in the Three Gorges Reservoir Area (TGRA) was selected as the research area, with total phosphorus (TP) as the representative pollutant in the water. The research investigated the changes in TP content during various hydrological phase under pollution incident, compared the duration and trends of TP concentration exceeding standard value before and after joint reservoir group dispatch. The results showed that the migration speed of TP pollutants varied from slowest to fastest in the following order: dry phase, recession phase, storage phase, and flood phase. Under pollution incident condition, the time demanded for TP content to meet standard value in each water phase was 36 min (dry phase), 33 min (recession phase), 30 min (storage phase), and 27 min (flood phase). The joint dispatch group 1-3 shortened the time required to meet standard value by 6-13 min (dry phase), 5-11 min (recession phase), 4-9 min (storage phase), and 3-7 min (flood phase). The trend of TP concentration before and after joint dispatch showed four stages: significant increase, sharp decrease, rapid decrease, and slow decrease. Joint dispatch of reservoir group can effectively reduced the TP concentration in DWSA under pollution incident.

Toxicological mechanisms and molecular impacts of tire particles and antibiotics on zebrafish.

Tire microplastics (TMPs) and antibiotics are emerging pollutants that widely exist in water environments. The coexistence of these pollutants poses severe threats to aquatic organisms. However, the toxicity characteristics and key molecular factors of the combined exposure to TMPs in aquatic organisms remain unknown. Therefore, the joint toxicity of styrene-butadiene rubber TMPs (SBR-TMPs) and 32 antibiotics (macrolides, fluoroquinolones, ß-lactams, sulfonamides, tetracyclines, nitroimidazoles, highly toxic antibiotics, high-content antibiotics, and common antibiotics) in zebrafish was investigated using a full factorial design, molecular docking, and molecular dynamics simulation. Sixty-four combinations of antibiotics were designed to investigate the hepatotoxicity of the coexistence of SBR-TMPs additives and antibiotics in zebrafish. Results indicated that low-order effects of antibiotics (e.g., enoxacin-lomefloxacin and ofloxacin-enoxacin-lomefloxacin) had relatively notable toxicity. The van der Waals interaction between additives and zebrafish cytochrome P450 enzymes primarily affected zebrafish hepatotoxicity. Zebrafish hepatotoxicity was also affected by the ability of SBR-TMPs to adsorb antibiotics, the relation between antibiotics, the affinity of antibiotics docking to zebrafish cytochrome P450 enzymes, electronegativity, atomic mass, and the hydrophobicity of the antibiotic molecules. This study aimed to eliminate the joint toxicity of TMPs and antibiotics and provide more environmentally friendly instructions for using different chemicals.

Improved microbial-plant soil bioremediation of PAHs and heavy metal through in silico methods.

The combined pollution of polycyclic aromatic hydrocarbons (PAHs) and organic cadmium (Cd) in farmland soils, and the field controlling strategy need to be studied urgently. In this study, 5 PAHs, 5 Cd and 11 soil conditioners were selected to explore the co-exposure risk and remediation efficiency. Firstly, a significant combination Fl-alkylalkoxy cadmium was obtained using forward and reverse methods coupling variation coefficient methods (the combined pollution value was 0.173). Secondly, the interaction energy of microbial degradation / plant absorption of Fl under Cd stress, and microbial mineralization / plant absorption of alkylalkoxy cadmium under PAHs stress were characterized using factorial experimental design, molecular docking and molecular dynamics simulation. The combined pollution of alkylalkoxy cadmium and dialkyl cadmium, phenanthrene and Benzo [a] pyrene was significant (synergistic contribution rates were 17.58 % and 19.22 %, respectively). In addition, 6 soil conditioners with significant efficiency were selected to design Taguchi orthogonal experimental schemes, indicating the microbial degradation / mineralization and plant absorption were significantly effective (the maximum increase of remediation efficiency was 93.81 %) under the combinations (i.e., trratone, coumarol, fulvamic acid, potassium fertilizer and others, etc.). Finally, it was found that the soil conditioners affected the hydrophobic groups and forces, and the efficiency was proportional to the highest peak value and minimum distance in the RDF curve. This study identifies the risk characteristics of co-exposure of PAHs and Cd and screens effective soil conditioners, providing theoretical guidance for risk controlling.

Mechanism analysis and improved molecular modification: Design of high efficiency and environmentally friendly triazole fungicide substitutes.

The adverse effects of triazole fungicides (TFs) on the soil and the environmental damage caused by their residues have attracted the attention of the international community. To effectively prevent and control the above problems, this paper designed 72 substitutes of TFs with significantly better molecular functionality (>40%) using Paclobutrazol (PBZ) as the template molecule. Then, the comprehensive scores for environmental effects calculated after normalization by "extreme value method-entropy weight method-weighted average method" was the dependent variable, the structural parameters of TFs molecules was the independent variable (PBZ-214 was the template molecule) to construct the 3D-QSAR model of integrated environmental effects of TFs with high degradability, low bioenrichment, low endocrine disruption effects, and low hepatotoxicity and designed 46 substitutes of TFs with significantly better comprehensive environmental effects (>20%). After confirming the above effects of TFs and assessing human health risk and the universality of biodegradation and endocrine disruption, we screened PBZ-319-175 as the eco-friendly substitute of TF, which had high efficiency (improved functionality) and better environmental effects than those of the target molecule by 51.63% and 36.09%, respectively. Finally, the results of the molecular docking analysis showed that non-bonding interactions (hydrogen bonding, electrostatic, or polar force) predominantly affected the association between PBZ-319-175 and its biodegradable protein, and the hydrophobic effect of the amino acids distributed around PBZ-319-175 played a significant role. Additionally, we determined the microbial degradation path of PBZ-319-175 and found that the steric hindrance of the substituent group after molecular modification promoted its biodegradability. In this study, we enhanced molecular functionality twice and also reduce the major damage of TFs to the environment by performing iterative modifications. This paper provided theoretical support for the development and application of high-performance, eco-friendly substitutes of TFs.

WITHDRAWN: The WHO and the ICTV rename viruses such as monkeypox.

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