Co-recovery of Mn and Fe from pyrolusite and copper slag with hydrometallurgy process: Kinetics and leaching mechanisms.

With the shortage of high-quality raw materials and increasingly strict environmental regulations, the recovery of metals from copper slag and pyrolusite has become a research hotspot. A novel method for simultaneously extracting Mn and Fe from pyrolusite and copper slag has been proposed. Under the optimal conditions (Copper slag / Pyrolusite = 2, H2SO4 = 2 M, liquid-solid ratio = 10, T = 90 ℃, holding time = 60 min), the leaching efficiencies of Mn and Fe can reach 98.28% and 99.04%, respectively. In addition, the treated residue containing 60.04 wt% SiO2 can be used as a raw building material. Through chemical kinetics and mineralogical transformation analyses, Fe2SiO4 in copper slag decomposes to release Fe2+, which can reduce and leach Mn from pyrolusite. The unreacted shrinkage nuclear reaction model under the control of the surface chemical reaction is the most suitable model to describe the process, and when the apparent activation energy is 35.50 kJ/mol, the apparent rate equation is: [Formula: see text].

Echinacoside, a promising sortase A inhibitor, combined with vancomycin against murine models of MRSA-induced pneumonia.

Methicillin-resistant Staphylococcus aureus (MRSA) is a pathogenic bacterium responsible for a range of severe infections, such as skin infections, bacteremia, and pneumonia. Due to its antibiotic-resistant nature, current research focuses on targeting its virulence factors. Sortase A (SrtA) is a transpeptidase that anchors surface proteins to the bacterial cell wall and is involved in adhesion and invasion to host cells. Through fluorescence resonance energy transfer (FRET), we identified echinacoside (ECH), a natural polyphenol, as a potential SrtA inhibitor with an IC50 of 38.42 µM in vitro. It was demonstrated that ECH inhibited SrtA-mediated S. aureus fibrinogen binding, surface protein A anchoring, and biofilm formation. The fluorescence quenching assay determined the binding mode of ECH to SrtA and calculated the KA-binding constant of 3.09 × 105 L/mol, demonstrating the direct interaction between the two molecules. Molecular dynamics simulations revealed that ECH-SrtA interactions occurred primarily at the binding sites of A92G, A104G, V168A, G192A, and R197A. Importantly, the combination of ECH and vancomycin offered protection against murine models of MRSA-induced pneumonia. Therefore, ECH may serve as a potential antivirulence agent against S. aureus infections, either alone or in combination with vancomycin.

Inhibitory effect of bilobalide on Staphylococcus aureus von Willebrand factor-binding protein and its therapeutic effect in mice with pneumonia.

AIMS: Disabling bacterial virulence with small molecules has been proposed as a potential strategy to prevent bacterial pathogenicity. The von Willebrand factor-binding protein of Staphylococcus aureus was identified previously as a key virulence determinant. Our objective was to discover a von Willebrand-factor binding protein (vWbp) inhibitor distinct from the antibiotics used to prevent infections resulting from S. aureus. METHODS AND RESULTS: Using coagulation assays, we found that the sesquiterpene trilactone bilobalide blocks coagulation mediated by vWbp, but has no impact on the growth of S. aureus at a concentration of 128 µg ml-1. Moreover, a mouse model of pneumonia caused by S. aureus indicated that bilobalide could attenuate S. aureus virulence in vivo. This effect is achieved not by interfering with the expression of vWbp but by binding to vWbp, as demonstrated by western blotting, thermal shift assays, and fluorescence quenching assays. Using molecular dynamic simulations and point mutagenesis analysis, we identified that the Q17A and R453A residues are key residues for the binding of bilobalide to vWbp. CONCLUSIONS: Overall, we tested the ability of bilobalide to inhibit S. aureus infections by targeting vWbp and explored the potential mechanism of this activity.

Inhibitory Effect of Salicin on Staphylococcus aureus Coagulase.

The massive use of antibiotics has resulted in an alarming increase in antibiotic resistance in Staphylococcus aureus (S. aureus). This study aimed to identify the inhibitory effect of salicin on S. aureus. Coagulase (Coa) activity was assessed using in vitro Coa assays and Western blot, thermal shift assay (TSA), fluorescence quenching and molecular docking experiments were conducted to verify the interaction between salicin and Coa. An in vivo mouse pneumonia model demonstrated that salicin can reduce the virulence of S. aureus. In vitro Coa assays elucidated that salicin directly inhibited Coa activity. The Western blot and TSA results suggested that salicin did not block the expression of Coa but affected the thermal stability of the protein by binding to Coa. The fluorescence quenching, molecular docking and molecular dynamics assays have found that the most promising binding site between salicin and Coa was GLN-97. The pneumonia model of mice infected with S. aureus revealed that salicin could not only reduce the content of lung bacteria in mice but also prolong their survival. Salicin was identified as a novel anti-infective candidate compound with the potential to target Coa and inhibit its activity by binding to it, which would facilitate the development of roadmaps for future research.

A Practical CEUS Thyroid Reporting System for Thyroid Nodules.

Background The role of contrast-enhanced US (CEUS) in reducing unnecessary biopsies of thyroid nodules has received little attention. Purpose To construct and externally validate a thyroid imaging reporting and data system (TI-RADS) based on nonenhanced US and CEUS to stratify the malignancy risk of thyroid nodules. Materials and Methods This retrospective study evaluated 756 patients with 801 thyroid nodules who underwent nonenhanced US, CEUS, and fine-needle aspiration and received a final diagnosis from January 2018 to December 2019. Qualitative US features of the thyroid nodules were analyzed with univariable and multivariable logistic regression to construct a CEUS TI-RADS. The CEUS TI-RADS was validated with use of internal cross-validation and external validation. Results A total of 801 thyroid nodules in 590 female (mean age, 44 years ± 13) and 166 male (mean age, 47 years ± 13 [SD]) patients were included. Independent predictive US features included nodule composition at CEUS, echogenicity, nodule shape, nodule margin, echogenic foci, extrathyroidal extension, enhancement direction, peak intensity, and ring enhancement. The CEUS TI-RADS showed a higher area under the receiver operating characteristic curve of 0.93 (95% CI: 0.92, 0.95; P < .001 in comparison with all other systems), a biopsy yield of malignancy of 66% (157 of 239 nodules), and an unnecessary biopsy rate of 34% (82 of 239 nodules). In the external validation, the area under the receiver operating characteristic curve, biopsy yield of malignancy, and unnecessary biopsy rate of CEUS TI-RADS were 0.89 (95% CI: 0.84, 0.92), 61% (65 of 106 nodules), and 39% (41 of 106 nodules) for the first external validation set and 0.90 (95% CI: 0.85, 0.94), 57% (56 of 99 nodules), and 43% (43 of 99 nodules) for the second external validation set. Conclusion A contrast-enhanced US (CEUS) thyroid imaging reporting and data system was created with thyroid nodule malignancy risk stratification according to the simplified regression coefficients of nonenhanced US and qualitative features of CEUS. Clinical trials registration no. ChiCTR2000028712 Published under a CC BY 4.0 license. Online supplemental material is available for this article.

Deep Multi-Scale Residual Connected Neural Network Model for Intelligent Athlete Balance Control Ability Evaluation.

Athlete balance control ability plays an important role in different types of sports. Accurate and efficient evaluations of the balance control abilities can significantly improve the athlete management performance. With the rapid development of the athlete training field, intelligent and automatic evaluations have been highly demanded in the past years. This study proposes a deep learning-based athlete balance control ability evaluation method through processing the time-series movement pressure measurement data. An end-to-end model structure is proposed, which directly analyzes the raw data and provides the evaluation results, which largely facilitates practical utilization. A multi-scale feature extraction scheme is employed, by exploring the learned features in different scales. A residual connected neural network architecture is further proposed. By using the short-cut connection, the deep neural network model can be more efficiently trained. Experiments on the real athlete balance control ability tests are carried out for validations. Through comparisons with different related methods, the results show the proposed deep multi-scale residual connected neural network model is well suited for the athlete balance control ability evaluation problem, and promising for actual applications in the real scenarios.