Biochar has been developed in recent years for the removal of contaminants such as Cr (VI) in water. The enhancement of the adsorption capacity of biochar and its recyclable use are still challenges. ...In this study, magnetic biochar derived from corncobs and peanut hulls was synthesized under different pyrolysis temperatures after pretreating the biomass with a low concentration of 0.5 M FeCl
solution. The morphology, specific surface area, saturation magnetization and Fourier transform infrared spectroscopy (FT-IR) spectra were characterized for biochar. The magnetic biochar performed well in combining adsorption and separation recycle for the removal of Cr (VI) in water. The Cr (VI) adsorbance of the biochar was increased with the increase in pyrolysis temperature, and the magnetic biochar derived from corncobs showed better performance for both magnetization and removal of Cr (VI) than that from peanut hulls. The Langmuir model was used for the isothermal adsorption and the maximum Cr (VI) adsorption capacity of corncob magnetic biochar pyrolyzed at 650 °C reached 61.97 mg/g. An alkaline solution (0.1 M NaOH) favored the desorption of Cr (VI) from the magnetic biochar, and the removal of Cr (VI) still remained around 77.6% after four cycles of adsorption-desorption. The results showed that corncob derived magnetic biochar is a potentially efficient and recoverable adsorbent for remediation of heavy metals in water.
Efficient upgrading of inferior agro-industrial resources and production of bio-based chemicals through a simple and environmentally friendly biotechnological approach is interesting Lactobionic acid ...is a versatile aldonic acid obtained from the oxidation of lactose. Several microorganisms have been used to produce lactobionic acid from lactose and whey. However, the lactobionic acid production titer and productivity should be further improved to compete with other methods. In this study, a new strain, Pseudomonas fragi NL20W, was screened as an outstanding biocatalyst for efficient utilization of waste whey to produce lactobionic acid. After systematic optimization of biocatalytic reactions, the lactobionic acid productivity from lactose increased from 3.01 g/L/h to 6.38 g/L/h in the flask. In batch fermentation using a 3 L bioreactor, the lactobionic acid productivity from whey powder containing 300 g/L lactose reached 3.09 g/L/h with the yield of 100%. Based on whole genome sequencing, a novel glucose dehydrogenase (GDH1) was determined as a lactose-oxidizing enzyme. Heterologous expression the enzyme GDH1 into P. putida KT2440 increased the lactobionic acid yield by 486.1%. This study made significant progress both in improving lactobionic acid titer and productivity, and the lactobionic acid productivity from waste whey is superior to the ever reports. This study also revealed a new kind of aldose-oxidizing enzyme for lactose oxidation using P. fragi NL20W for the first time, which laid the foundation for further enhance lactobionic acid production by metabolic engineering.
Abstract
Motivation
Protein kinases have been the focus of drug discovery research for many years because they play a causal role in many human diseases. Understanding the binding profile of kinase ...inhibitors is a prerequisite for drug discovery, and traditional methods of predicting kinase inhibitors are time-consuming and inefficient. Calculation-based predictive methods provide a relatively low-cost and high-efficiency approach to the rapid development and effective understanding of the binding profile of kinase inhibitors. Particularly, the continuous improvement of network pharmacology methods provides unprecedented opportunities for drug discovery, network-based computational methods could be employed to aggregate the effective information from heterogeneous sources, which have become a new way for predicting the binding profile of kinase inhibitors.
Results
In this study, we proposed a network-based influence deep diffusion model, named IDDkin, for enhancing the prediction of kinase inhibitors. IDDkin uses deep graph convolutional networks, graph attention networks and adaptive weighting methods to diffuse the effective information of heterogeneous networks. The updated kinase and compound representations are used to predict potential compound-kinase pairs. The experimental results show that the performance of IDDkin is superior to the comparison methods, including the state-of-the-art kinase inhibitor prediction method and the classic model widely used in relationship prediction. In experiments conducted to verify its generalizability and in case studies, the IDDkin model also shows excellent performance. All of these results demonstrate the powerful predictive ability of the IDDkin model in the field of kinase inhibitors.
Availability and implementation
Source code and data can be downloaded from https://github.com/CS-BIO/IDDkin.
Supplementary information
Supplementary data are available at Bioinformatics online.
Photothermocatalytic CO2 reduction as the channel of the energy and environmental issues resolution has captured persistent attention in recent years. In2O3 has been prompted to be a potential ...photothermal catalyst in this sector on account of its unique physicochemical properties. However, different from the metal‐based photothermal catalyst with the nature of efficient light‐to‐thermal conversion and H2 dissociation, the wide‐bandgap semiconductor needs to be modified to possess wide‐wavelength‐range absorption and the active surface. It remains a challenge to achieve the two aims simultaneously via a single material modulation approach. In this study, one strategy of carbon doping can empower In2O3 with two advantageous modifications. Carbon doping can reduce the formation energy of oxygen vacancy, which induces the generation of oxygen‐vacancy‐riched material. The introduction of oxygen defect levels and carbon doping levels in the bandgap of In2O3 significantly reduces this bandgap, which endows it full‐spectral and intensive solar light absorption. Therefore, the carbon doped In2O3 achieves effective light‐to‐thermal conversion and delivers a 123.6 mmol g–1 h–1 of CO generation rate with near‐unity selectivity, as well as prominent stability in photothermocatalytic CO2 reduction.
The dual functional carbon doping can extend In2O3 absorption to the full range of the UV–vis–NIR spectrum and, therefore, forcefully drive photothermal conversion and reduce the formation energy of oxygen vacancy to create high concentration active sites. The C‐In2O3−x delivers a 123.6 mmol g−1 h−1 CO generation rate with near‐unity selectivity, as well as prominent stability.
Owing to their powerful feature extraction capabilities, deep learning-based methods have achieved significant progress in hyperspectral remote sensing classification. However, several issues still ...exist in these methods, including a lack of hyperspectral datasets for specific complicated scenarios and the need to improve the classification accuracy of land cover with limited samples. Thus, to highlight and distinguish effective features, we propose a hyperspectral classification framework based on a joint channel-space attention mechanism and generative adversarial network (JAGAN). To relearn feature-based weights, a higher priority was assigned to important features, which was developed by integrating a two-joint channel-space attention model to obtain the most valuable feature via the attention weight map. Additionally, two classifiers were designed in JAGAN: sigmoid was used to determine whether the input data were real or fake samples produced by the generator, while Softmax was adopted as a land cover classifier to yield the prediction type labels of the input samples. To test the classification performance of the JAGAN model, we used a self-constructed complex land cover dataset based on GaoFen-5 AHSI images, which consists of mixed landscapes of mining and agricultural areas from the urban-rural fringe. Compared with other methods, the proposed model achieved the highest overall classification accuracy of 86.09%, the highest kappa amount of 79.41%, the highest F1 score of 85.86%, and the highest average accuracy of 82.30%, indicating the JAGAN can effectively improve the classification accuracy for limited samples in complex regional environments using GF-5 AHSI images.
Abstract A positive feedback magnetic-coupled piezoelectric energy harvester (PFM) is proposed to address the limitations of current piezoelectric energy collectors, including restricted acquisition ...direction, limited acquisition bandwidth, and low energy output. Firstly, the dynamic theoretical model of the energy harvester was established, and the optimization factors were explored, providing a solid theoretical foundation for subsequent research endeavors. The energy capture characteristics of rectangular beam and compound trapezoidal beam were compared through finite element simulation analysis. Subsequently, an experimental platform was constructed and an optimized experimental methodology was devised to analyze the energy capture characteristics and enhance the performance of the energy harvester. The results demonstrate that the positive feedback magnetic-coupled PFM with a trapezoidal beam exhibits superior energy capture efficiency. Furthermore, it is observed that the optimized energy harvester possesses wide frequency coverage, multi-directional capabilities, low-frequency adaptability, and facilitates easy vibration. When the 45 kΩ resistor is connected in series and subjected to a longitudinal external excitation amplitude of 0.5 g, it is capable of generating an average voltage and power output of 4.20 V and 0.39 mW respectively at a vibration frequency of 9 Hz. Similarly, when exposed to a transverse external excitation amplitude of 1 g, it can produce an average voltage output of 6.2 V and power output of 0.85 mW at a vibration frequency of 19 Hz. When the inclination angle of the energy harvester is set to 35 degrees, the maximum voltage output occurs at a frequency of 18 Hz and the Z -axis to X -axis force ratio of the energy harvester is 1.428. These research findings can serve as valuable references for piezoelectric energy harvesting applications in self-powered microelectronic systems.
Organic small-molecule contrast agents have attracted considerable attention in the field of multispectral optoacoustic imaging, but their weak optoacoustic performance resulted from relatively low ...extinction coefficient and poor water solubility restrains their widespread applications. Herein, we address these limitations by constructing supramolecular assemblies based on cucurbit8uril (CB8). Two dixanthene-based chromophores (DXP and DXBTZ) are synthesized as the model guest compounds, and then included in CB8 to prepare host-guest complexes. The obtained DXP-CB8 and DXBTZ-CB8 display red-shifted and increased absorption as well as decreased fluorescence, thereby leading to a substantial enhancement in optoacoustic performance. Biological application potential of DXBTZ-CB8 is investigated after co-assembly with chondroitin sulfate A (CSA). Benefiting from the excellent optoacoustic property of DXBTZ-CB8 and the CD44-targeting feature of CSA, the formulated DXBTZ-CB8/CSA can effectively detect and diagnose subcutaneous tumors, orthotopic bladder tumors, lymphatic metastasis of tumors and ischemia/reperfusion-induced acute kidney injury in mouse models with multispectral optoacoustic imaging.
Most β-galactosidases reported are sensitive to the end product (galactose), making it the rate-limiting component for the efficient degradation of lactose through the enzymatic route. Therefore, ...there is ongoing interest in searching for galactose-tolerant β-galactosidases. In the present study, the predicted galactose-binding residues of β-galactosidase from Bacillus coagulans, which were determined by molecular docking, were selected for alanine substitution. The asparagine residue at position 148 (N148) is correlated with the reduction of galactose inhibition. Saturation mutations revealed that the N148C, N148D, N148S, and N148G mutants exhibited weaker galactose inhibition effects. The N148D mutant was used for lactose hydrolysis and exhibited a higher hydrolytic rate. Molecular dynamics revealed that the root mean square deviation and gyration radius of the N148D-galactose complex were higher than those of wild-type enzyme-galactose complex. In addition, the N148D mutant had a higher absolute binding free-energy value. All these factors may lead to a lower affinity between galactose and the mutant enzyme. The use of mutant enzyme may have potential value in lactose hydrolysis.
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MicroRNAs (miRNAs) are significant regulators of post-transcriptional levels and have been confirmed to be targeted by small molecule (SM) drugs. It is a novel insight to treat human diseases and ...accelerate drug discovery by targeting miRNA with small molecules. Computational approaches for discovering novel small molecule–miRNA associations by integrating more heterogeneous network information provide a new idea for the multiple node association prediction between small molecule–miRNA and small molecule–disease associations at a system level. In this study, we proposed a new computational model based on graph regularization techniques in heterogeneous networks, called identification of small molecule–miRNA associations with graph regularization techniques (SMMARTs), to discover potential small molecule–miRNA associations. The novelty of the model lies in the fact that the association score of a small molecule–miRNA pair is calculated by an iterative method in heterogeneous networks that incorporates small molecule–disease associations and miRNA–disease associations. The experimental results indicate that SMMART has better performance than several state-of-the-art methods in inferring small molecule–miRNA associations. Case studies further illustrate the effectiveness of SMMART for small molecule–miRNA association prediction.
To cope effectively with the world’s energy shortage and environmental pollution, a fuel cell combined with waste heat recovery technology has gradually become the best option for large ship power ...generation equipment. In this investigation, a combined system comprising a solid-oxide-fuel-cell-gas-turbine subsystem, supercritical carbon dioxide cycle, organic Rankine cycle, ammonia-water absorption refrigeration cycle, and high-pressure reverse osmosis desalination plant is introduced and analysed. Not only the power output of the system is calculated, but also the contribution of cold energy is considered by calculating its equivalent power. The results illustrate that the equivalent net output and thermal efficiency of the system are 278.82 kW and 67.03%, respectively. Compared with the solid oxide fuel cell, the power output increases by 86.35 kW and the fuel efficiency increases by 20.7%. Additionally, the system can provide 5.95 kW of cold energy and 0.94 m3/h of fresh water for the crew under the condition of maximum power output. To summarize, the proposed novel system design can realize the combined production of cold energy, electric energy, and fresh water, and it exhibits the characteristics of high efficiency and cleanliness.
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•A novel combined cooling, cascaded power and desalination systems is proposed.•Power density, temperature distribution and afterburner temperature are simulated.•The utilization of heat source from high temperature to low temperature is realized.•The equivalent power output and thermal efficiency reach 278.82 kW and 67.03%.
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