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Abstract Myocardial infarction (MI) induces neuroinflammation indirectly, chronic neuroinflammation may cause neurodegenerative diseases. Changes in the proteomics of heart and brain tissue after MI may shed new light on the mechanisms involved in neuroinflammation. This study explored brain and heart protein changes after MI with a data-independent acquisition (DIA) mode proteomics approach. Permanent ligation of the left anterior descending coronary artery (LAD) was performed in the heart of rats, and the immunofluorescence of microglia in the brain cortex was performed at 1d, 3d, 5d, and 7d after MI to detect the neuroinflammation. Then proteomics was accomplished to obtain the vital proteins in the heart and brain post-MI. The results show that the number of microglia was significantly increased in the Model-1d group, the Model-3d group, the Model-5d group, and the Model-7d group compared to the Sham group. Various proteins were obtained through DIA proteomics. Linking to key targets of brain disease, 14 proteins were obtained in the brain cortex. Among them, elongation of very long chain fatty acids protein 5 (ELOVL5) and ATP-binding cassette subfamily G member 4 (ABCG4) were verified through western blotting (WB). The results of WB were consistent with the proteomics results. Therefore, these proteins may be related to the pathogenesis of neuroinflammation after MI.

Abstract Chromium (Cr(VI)) pollution has attracted wide attention due to its high toxicity and carcinogenicity. Modified biochar has been widely used in the removal of Cr(VI) in water as an efficient and green adsorbent. However, the existing biochar prepared by chemical modification is usually complicated in process, high in cost, and has secondary pollution, which limits its application. It is urgent to explore modified biochar with simple process, low cost and environmental friendliness. Therefore, ball milling wheat straw biochar (BM-WB) was prepared by ball milling technology in this paper. The adsorption characteristics and mechanism of Cr(VI) removal by BM-WB were analyzed by functional group characterization, adsorption model and response surface method. The results showed that ball milling effectively reduced the particle size of biochar, increased the specific surface area, and more importantly, enhanced the content of oxygen-containing functional groups on the surface of biochar. After ball milling, the adsorption capacity of Cr(VI) increased by 3.5–9.1 times, and the adsorption capacity reached 52.21 mg/g. The adsorption behavior of Cr(VI) follows the pseudo-second-order kinetics and Langmuir isotherm adsorption model rate. Moreover, the Cr(VI) adsorption process of BM-WB is endothermic and spontaneous. Under the optimized conditions of pH 2, temperature 45 °C, and adsorbent dosage 0.1 g, the removal rate of Cr(VI) in the solution can reach 100%. The mechanism of Cr(VI) adsorption by BM-WB is mainly based on electrostatic attraction, redox and complexation. Therefore, ball milled biochar is a cheap, simple and efficient Cr(VI) removal material, which has a good application prospect in the field of remediation of Cr(VI) pollution in water.

Abstract In this study, modified biochar (BRB) was prepared from rice straw by ball milling technique and used for the adsorption of methylene blue (MB) in wastewater. The BRB was characterized by SEM, FTIR and XPS, and the adsorption model and Box–Behnken design were used to optimize the five influencing factors. The results showed that the ball milling technique could increase the content of functional groups (–OH, C=C and C–O, etc.) and aromatic structures on the surface of biochar, thus facilitating the removal of MB. The isotherm model was consistent with the Langmuir adsorption model (R2 = 0.947) and the maximum adsorption capacity was 50.27 mg/g. The adsorption kinetics was consistent with the pseudo-second-order kinetic model (R2 = 1) and the adsorption rate was mainly controlled by chemisorption. The thermodynamic model confirmed that the adsorption process was a spontaneous heat absorption reaction. The maximum adsorption efficiency was 99.78% under the optimal conditions (40℃, pH 8, reaction time = 90 min, dosing amount = 0.1 mg), and the adsorption efficiency could be improved by increasing the pH and BRB dosing amount. The surface functional groups and crystal structure properties of BRB were the main determinants of adsorption, and it was clarified that physical adsorption, electrostatic attraction and π-π interaction were the main mechanisms for the adsorption of MB by BRB. The main mechanisms were clarified. Therefore, BRB is an economic, efficient and green adsorption material with good potential for the removal of dye pollutants in the aqueous environment.

Abstract During the continuous charge and discharge process in lithium-sulfur batteries, one of the next-generation batteries, polysulfides are generated in the battery’s electrolyte, and impact its performance in terms of power and capacity by involving the process. The amount of polysulfides in the electrolyte could be estimated by the change of the Gibbs free energy of the electrolyte, $$\Delta _{mix}\textrm{G}$$ Δ mix G in the presence of polysulfide. However, obtaining $$\Delta _{mix}\textrm{G}$$ Δ mix G of the diverse mixtures of components in the electrolyte is a complex and expensive task that shows itself as a bottleneck in optimization of electrolytes. In this work, we present a machine-learning approach for predicting $$\Delta _{mix}\textrm{G}$$ Δ mix G of electrolytes. The proposed architecture utilizes (1) an attention-based model (Attentive FP), a contrastive learning model (MolCLR) or morgan fingerprints to represent chemical components, and (2) transformers to account for the interactions between chemicals in the electrolyte. This architecture was not only capable of predicting electrolyte properties, including those of chemicals not used during training, but also providing insights into chemical interactions within electrolytes. It revealed that interactions with other chemicals relate to the logP and molecular weight of the chemicals.

Abstract Functional dyspepsia (FD) is one of the most prevalent functional gastrointestinal disorders, and more and more multicomponent drugs represented by traditional Chinese medicines have provided a favorable therapeutic effect in its treatment. However, their precise localization in the clinic, as well as corresponding mechanism, is ambiguous, thus hindering their widespread use. To meet this requirement, a precise and systematic approach based on a restriction of special disease-related molecules and the following network pharmacology analysis was developed and applied to a multicomponent conventional drug, XiaoErFuPi (XEFP) granules. Experimental verification of the results indicates that this approach can facilitate the prediction, and the precise and systematic efficacy of XEFP could be easily revealed, which shows that XEFP has an advantage over the positive control drug on lactate, gastrin, interleukin 4 and calcitonin gene-related peptide. Moreover, by the proteomics analysis, its superposition of multi-target effects was revealed and a new candidate target for the treatment of FD, striatin, was obtained and verified. This study provides a practicable precise approach for the investigation of the efficacy of multicomponent drugs against FD and offers a promising alternative for the systematical management of FD.

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