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Abstract Background Biochemistry is a core subject in clinical medical education. The traditional classroom teaching model led by teachers is often limited to the knowledge transfer of teachers and the passive acceptance of students. It lacks interactive and efficient teaching methods and is not enough to meet the learning needs and educational goals of modern students. The combination of WeChat public platform, flipped classroom and TBL teaching model is closer to the needs of real life and workplace, helping students to cultivate comprehensive literacy and the ability to solve practical problems. At the same time, this teaching model has yet to be used in biochemistry courses. Objective To explore the influence of the mixed teaching model of flipped classroom and combining TBL based on WeChat public platform upon undergraduates in biochemistry. Methods Using the mixed research method of quasi-experimental research design and descriptive qualitative research, 68 students were selected into the traditional and the blended teaching groups. Among them, the blended teaching group adopts the blended teaching model of flipped classroom combined with TBL based on the WeChat platform to learn biochemical courses. In this study, an independent sample t-test was intended to analyze the differences in final scores, a chi-square test was served to analyze the differences in satisfaction questionnaires, and thematic analysis was used to analyze semi-structured interview data. Results Compared with the traditional teaching model, the mixed teaching model significantly improved students' final exam scores (P

In scenarios where the global navigation satellite system is unavailable, unmanned aerial vehicles (UAVs) can employ visual algorithms to process aerial images. These images are integrated with satellite maps and digital elevation models (DEMs) to achieve global localization. To address the localization challenge in unfamiliar areas devoid of prior data, an iterative computation-based localization framework is commonly used. This framework iteratively refines its calculations using multiple observations from a downward-facing camera to determine an accurate global location. To improve the rate of convergence for localization, we introduced an innovative observation model. We derived a terrain descriptor from the images captured by a forward-facing camera and integrated it as supplementary observation into a point-mass filter (PMF) framework to enhance the confidence of the observation likelihood distribution. Furthermore, within this framework, the methods for the truncation of the convolution kernel and that of the probability distribution were developed, thereby enhancing the computational efficiency and convergence rate, respectively. The performance of the algorithm was evaluated using real UAV flight sequences, a satellite map, and a DEM in an area measuring 7.7 km × 8 km. The results demonstrate that this method significantly accelerates the localization convergence during both takeoff and ascent phases as well as during cruise flight. Additionally, it increases localization accuracy and robustness in complex environments, such as areas with uneven terrain and ambiguous scenes. The method is applicable to the localization of UAVs in large-scale unknown scenarios, thereby enhancing the flight safety and mission execution capabilities of UAVs.

In recent years, transition-metal oxides (TMOs) have been long employed for aerobic oxidative desulfurization. However, the inherent bottlenecks, such as the low explosion of active sites, limit the application of bulk TMOs catalyst. In this study, V2O5 nanoparticles with oxygen vacancies were prepared in large-scale via facile ball milling strategy with adding oxalic acid as a reducing agent. The as-prepared catalysts exhibit remarkable sulfur removal for oils with different initial S-concentrations and different substrates. Sulfur removal could reach up to 99.7% (< 2 ppm) under the optimized reaction conditions. This work provides a feasible desulfurization strategy for fuel oils.

The photoreduction of CO2 to chemical fuels represents a promising technology to mitigate the current energy dilemma and global warming problems. Unfortunately, the original photocatalysts suffer from many side reactions and a poor CO2 conversion efficiency. The rational combination of active co-catalyst with pristine photocatalysts for promoting the adsorption and activation of CO2 is of vital importance to tackle this grand challenge. Herein, we rationally designed a SnIn4S8 nanosheet photocatalyst simultaneously equipped with CuAu alloys. The experimental results proved that the CuAu alloy can trap the electrons and enhance the separation and transport efficiency of the photogenerated carrier in the photocatalyst, alleviating the kinetical difficulty of the charge transfer process because of the preferable localized surface plasmon resonance (LSPR). Furthermore, the CuAu alloy works as the synergistic site to increase the CO2 adsorption and activation capacity. The optimized CuAu-SnIn4S8 photocatalyst exhibited a superior performance with CO generation rates of 27.87 μmol g−1 h−1 and CH4 of 7.21 μmol g−1 h−1, which are about 7.6 and 2.5 folds compared with SnIn4S8. This work highlights the critical role of alloy cocatalysts in boosting a CO2 activation and an efficient CO2 reduction, thus contributing to the development of more outstanding photocatalytic systems.

Highly active anti-retroviral therapy (HAART) cannot clear infected cells harboring HIV-1 proviral DNA from HIV-1-infected patients. We previously demonstrated that zinc-finger nucleases (ZFNs) can specifically and efficiently excise HIV-1 proviral DNA from latently infected human T cells by targeting long terminal repeats (LTRs), a novel and alternative antiretroviral strategy for eradicating HIV-1 infection. To prevent unwanted off-target effects from constantly expressed ZFNs, in this study, we engineered the expression of ZFNs under the control of HIV-1 LTR, by which ZFN expression can be activated by the HIV-1 (Trans-Activator of Transcription) Tat protein. Our results show that functional expression of ZFNs induced by Tat excise the integrated proviral DNA of HIV-NL4-3-eGFP in approximately 30% of the population of HIV-1-infected cells. The results from HIV-1-infected human primary T cells and latently infected T cells treated with the inducible ZFNs further validated that proviral DNA can be excised. Taken together, positively regulated expression of ZFNs in the presence of HIV-1 Tat may provide a safer and novel implementation of genome-editing technology for eradicating HIV-1 proviral DNA from infected host cells. Keywords: zinc-finger nuclease, genome editing, genomic excision, inducible, Tat, HIV-1, gene therapy

HIV-1 inserts its proviral DNA into the infected host cells, by which HIV proviral DNA can then be duplicated along with each cell division. Thus, provirus cannot be eradicated completely by current antiretroviral therapy. We have developed an innovative strategy to silence the HIV provirus by targeted DNA methylation on the HIV promoter region. We genetically engineered a chimeric DNA methyltransferase 1 composed of designed zinc-finger proteins to become ZF2 DNMT1. After transient transfection of the molecular clone encoding this chimeric protein into HIV-1 infected or latently infected cells, efficient suppression of HIV-1 expression by the methylation of CpG islands in 5′-LTR was observed and quantified. The effective suppression of HIV in latently infected cells by ZF2-DNMT1 is stable and can last through about 40 cell passages. Cytotoxic caused by ZF2-DNMT1 was only observed during cellular proliferation. Taken together, our results demonstrate the potential of this novel approach for anti-HIV-1 therapy. Keywords: HIV-1, methylation, zinc finger, chimeric protein, DNMT1, gene therapy

Systemic lupus erythematosus (SLE) is a chronic, autoimmune disorder that affects nearly all organs and tissues. As knowledge about the mechanism of SLE has increased, some immunosuppressive agents have become routinely used in clinical care, and infections have become one of the direct causes of mortality in SLE patients. To identify the risk factors indicative of infection in SLE patients, a case control study of our hospital's medical records between 2011 and 2013 was performed. We reviewed the records of 117 SLE patients with infection and 61 SLE patients without infection. Changes in the levels of T cell subsets, immunoglobulin G (IgG), complement C3, complement C4, globulin, and anti-double-stranded DNA (anti-ds-DNA) were detected. CD4+ and CD4+/CD8+ T cell levels were significantly lower and CD8+ T cell levels were significantly greater in SLE patients with infection than in SLE patients without infection. Additionally, the concentrations of IgG in SLE patients with infection were significantly lower than those in SLE patients without infection. However, complement C3, complement C4, globulin, and anti-ds-DNA levels were not significantly different in SLE patients with and without infection. Therefore, clinical testing for T cell subsets and IgG is potentially useful for identifying the presence of infection in SLE patients and for distinguishing a lupus flare from an acute infection.

In this study, a hyperspectral imaging system of 866.4−1701.0 nm was selected and combined with multivariate methods to identify wheat kernels with different concentrations of omethoate on the surface. In order to obtain the optimal model combination, three preprocessing methods (standard normal variate (SNV), Savitzky−Golay first derivative (SG1), and multivariate scatter correction (MSC)), three feature extraction algorithms (successive projections algorithm (SPA), random frog (RF), and neighborhood component analysis (NCA)), and three classifier models (decision tree (DT), k-nearest neighbor (KNN), and support vector machine (SVM)) were applied to make a comparison. Firstly, based on the full wavelengths modeling analysis, it was found that the spectral data after MSC processing performed best in the three classifier models. Secondly, three feature extraction algorithms were used to extract the feature wavelength of MSC processed data and based on feature wavelengths modeling analysis. As a result, the MSC−NCA−SVM model performed best and was selected as the best model. Finally, in order to verify the reliability of the selected model, the hyperspectral image was substituted into the MSC−NCA−SVM model and the object-wise method was used to visualize the image classification. The overall classification accuracy of the four types of wheat kernels reached 98.75%, which indicates that the selected model is reliable.

ZFN technology is a powerful research tool and has been used for genome editing in cells lines, animals and plants. The generation of functional ZFNs for particular targets in mammalian genome is still challenging for an average research group. The modular-assembly method is relatively fast, easy-to-practice but has a high failure rate. Some recent studies suggested that a ZFP with low binding activity might be able to form a working ZFN pair with another binding active half-ZFP. In order to unveil the potential ZFP candidates among those with low binding activities, this paper established a highly sensitive mammalian cell-based transcriptional reporter system to assess the DNA binding activities of ZFPs by inserting multiple copies of ZFN target sequence fragment (TSF) of an interested gene (e. g., hPGRN or hVEGF). Our results showed that this system increased the screening sensitivity up to 50-fold and markedly amplified the differences in the binding activities between different ZFPs. We also found that the targeted chromosomal gene repair efficiency of each hPGRN or hVEGF ZFN pair was in proportion with the combination of the binding activities of the ZFL (Left zinc finger) and ZFR (Right zinc finger). A hPGRN ZFR with low binding ability was able to form a biological active ZFN if combined with a hPGRN ZFL with relatively high binding ability. Lastly, site-specific genome editing by hPGRN ZFNs generated by this system was confirmed by sequencing, and the PGRN knock-out cell line showed significantly decreased cell growth compared with the control. Our system will provide a valuable tool for further optimizing the nucleases with regard to specificity and cytotoxicity.

Abstract The coal-gangue recognition technology plays an important role in the intelligent realization of fully mechanized caving face and the improvement of coal quality. Although great progress has been made for the coal-gangue recognition in recent years, most of them have not taken into account the impact of the complex environment of top coal caving on recognition performance. Herein, a hybrid multi-branch convolutional neural network (HMBCNN) is proposed for coal-gangue recognition, which based on improved Mel Frequency Cepstral Coefficient (MFCC) as well as Mel spectrogram, and attention mechanism. Firstly, the MFCC and its smooth feature matrix are input into each branch of one-dimensional multi-branch convolutional neural network, and the spliced features are extracted adaptively through multi-head attention mechanism. Secondly, the Mel spectrogram and its first-order derivative are input into each branch of the two-dimensional multi-branch convolutional neural network respectively, and the effective time-frequency information is paid attention to through the soft attention mechanism. Finally, at the decision-making level, the two networks are fused to establish a model for feature fusion and classification, obtaining optimal fusion strategies for different features and networks. A database of sound pressure signals under different signal-to-noise ratios and equipment operations is constructed based on a large amount of data collected in the laboratory and on-site. Comparative experiments and discussions are conducted on this database with advanced algorithms and different neural network structures. The results show that the proposed method achieves higher recognition accuracy and better robustness in noisy environments.

Pulmonary fibrosis (PF) is a chronic progressive end-stage lung disease. However, the mechanisms underlying the progression of this disease remain elusive. Presently, clinically employed drugs are scarce for the treatment of PF. Hence, there is an urgent need for developing novel drugs to address such diseases. Our study found for the first time that a natural source of Prismatomeris connata Y. Z. Ruan (Huang Gen, HG) ethyl acetate extract (HG-2) had a significant anti-PF effect by inhibiting the expression of the transforming growth factor beta 1/suppressor of mothers against decapentaplegic (TGF-β1/Smad) pathway. Network pharmacological analysis suggested that HG-2 had effects on tyrosine kinase phosphorylation, cellular response to reactive oxygen species, and extracellular matrix (ECM) disassembly. Moreover, mass spectrometry imaging (MSI) was used to visualize the heterogeneous distribution of endogenous metabolites in lung tissue and reveal the anti-PF metabolic mechanism of HG-2, which was related to arginine biosynthesis and alanine, asparate and glutamate metabolism, the downregulation of arachidonic acid metabolism, and the upregulation of glycerophospholipid metabolism. In conclusion, we elaborated on the relationship between metabolite distribution and the progression of PF, constructed the regulatory metabolic network of HG-2, and discovered the multi-target therapeutic effect of HG-2, which might be conducive to the development of new drugs for PF.

In this work, FeCrB-based composites modified by in-situ ceramic particles (TiB2 and TiC) were synthesized, and the effects of ceramic particles on their microstructure evolution and the corrosion-resistant behavior in liquid aluminum were systematically investigated. Results indicate that the introduction of in-situ ceramic particles can significantly improve the size, morphology and distribution of borides, thus leading to a remarkable enhancement of the corrosion resistance. Based on the growth-dissolution kinetic relationship of intermetallic compounds (IMCs) at the corrosion interface, a theoretical numerical model was established to quantitatively describe the corrosion behavior of ferrous alloys in liquid aluminum, and the multi-scale corrosion-resistance mechanism is proposed to elucidate the excellent performance of FeCrB-based composites in liquid aluminum.

Effect of in-situ nanoparticles (NPs) induced by Ti addition on the microstructure and tribological properties of FeCrB alloys has been investigated systematically by various advanced techniques. The results reveal that the TiC and TiB2 nanoparticles can be in-situ formed when adding Ti into the FeCrB alloys and they show great contribution to the microstructure refinement and tribological performance improvement of FerCrB alloys. With the gradual addition of Ti, the improvement effect of in-situ NPs increases initially and subsequently decreases. The JDF2 alloy (refers to FeCrB alloy containing 1.17 wt % Ti) shows the finest microstructure and the exceptional wear resistance. The average size and fracture toughness of primary borides are only 11.8 % of that in FeCrB matrix alloy (without Ti addition) and increase to 22.7 MPa∙m1/2, respectively. Moreover, the wear rate measures at 3.38 × 10−5 mm3/N·m, which is only 48.8% compared to that of FeCrB matrix alloy. The underlying wear mechanisms of FeCrB alloys have been discussed by unraveling the role of in-situ nanoparticles in the microstructure evolution, which belongs to adhesive wear and abrasive wear.

Abstract Background Venous thromboembolism (VTE) is most prevalent among parturients following a cesarean section (CS). The objective of this study was to assess the practical utility of bilateral compression ultrasonography (CUS) of the lower limbs, coupled with D-dimer monitoring, in the early diagnosis of VTE within the Han Chinese population. Methods Our prospective observational study included 742 women who underwent CUS and D-dimer testing on the first day post-CS. Subsequently, telephone or outpatient follow-ups were conducted until 42 days postpartum. States of hypercoagulation and thrombosis, as indicated by CUS, were classified as CUS abnormal. A D-dimer level ≥ 3 mg/l was considered the D-dimer warning value. Early ambulation and mechanical prophylaxis were universally recommended for all parturients post-CS. A sequential diagnostic strategy, based on the 2015 RCOG VTE risk-assessment tool, was employed. Therapeutic doses of low-molecular-weight heparin (LMWH) were administered for the treatment of thromboembolic disease. Prophylactic doses of LMWH were given for VTE prophylaxis in parturients with hypercoagulative status accompanied by D-dimer levels ≥ 3 mg/l. All high-risk women (RCOG score ≥ 4 points) were additionally treated with preventive LMWH. Statistical analyses were conducted using the R statistical software, with a two-sided P value