125 research outputs found

    Research on Higher Vocational Classroom revolution under the background of improving quality and cultivating excellence

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    with the change of social environment and the change of information technology, promoting classroom revolution has become an important path for the reform and development of higher vocational education. Since the “action plan for improving the quality of Vocational Education (2020-2023)” was put forward, in order to adapt to the characteristics of students’ diversity, higher vocational colleges should implement reform actions from the perspectives of teaching content, classroom organization, curriculum evaluation, faculty, curriculum resources, curriculum ideology and politics, so as to create an effi cient, personalized and intelligent classroom environment for students. This paper analyzes the research status and objectives of classroom revolution, summarizes the problems existing in Higher Vocational Classroom Teaching at the present stage, thinks about the basic motivation of classroom revolution, and then puts forward the implementation strategies of higher vocational classroom revolution under the background of quality improvement

    A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics

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    Graph neural networks (GNNs) have demonstrated a significant boost in prediction performance on graph data. At the same time, the predictions made by these models are often hard to interpret. In that regard, many efforts have been made to explain the prediction mechanisms of these models from perspectives such as GNNExplainer, XGNN and PGExplainer. Although such works present systematic frameworks to interpret GNNs, a holistic review for explainable GNNs is unavailable. In this survey, we present a comprehensive review of explainability techniques developed for GNNs. We focus on explainable graph neural networks and categorize them based on the use of explainable methods. We further provide the common performance metrics for GNNs explanations and point out several future research directions

    In vitro and in vivo antitumor properties of 7-epidocetaxel, a major impurity of docetaxel

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    Purpose: To investigate the antitumor properties and toxicity of 7-epi docetaxel (7-epi DTX) as an active pharmaceutical ingredient, and in formulations.Methods: Docetaxel-loaded albumin nanoparticles (DTX NPs) were prepared by freeze-drying, while 7- epi DTX was detected and isolated by high performance liquid chromatography (HPLC). Their antitumor properties were evaluated in vitro in CT26 cells and in vivo in BALB/c sk-ov-3 xenograft nude mice model. The tissues were histological examined.Results: The in vivo antitumor effects of DTX NPs at different doses of 7-epi DTX were similar. Moreover, the in vitro anti-cancer effect of 7-epi DTX was comparable to that of DTX. However, the in vivo antitumor effectiveness of 7-epi DTX was inferior to that of DTX. In toxicity studies, 7-epi DTX did not elicit any acute toxic effects both as active pharmaceutical ingredients, and as a component of formulations.Conclusion: The results indicate that 7-epi DTX does not elicit acute toxic effects both as an active pharmaceutical ingredient and in bulk formulations. The antitumor property of 7-epi DTX is less than that of DTX.Keywords: 7-Epidocetaxel, Impurity, Antitumor properties, Toxicit

    Modeling Occupant Window Behavior in Hospitals—A Case Study in a Maternity Hospital in Beijing, China

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    Nowadays, relevant data collected from hospital buildings remain insufficient because hospital buildings often have stricter environmental requirements resulting in more limited data access than other building types. Additionally, existing window-opening behavior models were mostly developed and validated using data measured from the experimental building itself. Hence, their accuracy is only assessed by the algorithm’s evaluation index, which limits the model’s applicability, given that it is not tested by the actual cases nor cross-verified with other buildings. Based on the aforementioned issues, this study analyzes the window-opening behavior of doctors and patients in spring in a maternity hospital in Beijing and develops behavioral models using logistic regression. The results show that the room often has opened windows in spring when the outdoor temperature exceeds 20 °C. Moreover, the ward windows’ use frequency is more than 10 times higher than those of doctors’ office. The window-opening behavior in wards is more susceptible to the influence of outdoor temperature, while in the doctors’ office, more attention is paid to indoor air quality. Finally, by embedding the logistic regression model of each room into the EnergyPlus software to simulate the CO2 concentration of the room, it was found that the model has better applicability than the fixed schedule model. However, by performing cross-validation with different building types, it was found that, due to the particularity of doctors’ offices, the models developed for other building types cannot accurately reproduce the window-opening behavior of doctors. Therefore, more data are still needed to better understand window usage in hospital buildings and support the future building performance simulations of hospital buildings

    Changes in the Expression of miR-381 and miR-495 Are Inversely Associated with the Expression of the MDR1 Gene and Development of Multi-Drug Resistance

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    Multidrug resistance (MDR) frequently develops in cancer patients exposed to chemotherapeutic agents and is usually brought about by over-expression of P-glycoprotein (P-gp) which acts as a drug efflux pump to reduce the intracellular concentration of the drug(s). Thus, inhibiting P-gp expression might assist in overcoming MDR in cancer chemotherapy. MiRNAome profiling using next-generation sequencing identified differentially expressed microRNAs (miRs) between parental K562 cells and MDR K562 cells (K562/ADM) induced by adriamycin treatment. Two miRs, miR-381 and miR-495, that were strongly down-regulated in K562/ADM cells, are validated to target the 3'-UTR of the MDR1 gene. These miRs are located within a miR cluster located at chromosome region 14q32.31, and all miRs in this cluster appear to be down-regulated in K562/ADM cells. Functional analysis indicated that restoring expression of miR-381 or miR-495 in K562/ADM cells was correlated with reduced expression of the MDR1 gene and its protein product, P-gp, and increased drug uptake by the cells. Thus, we have demonstrated that changing the levels of certain miR species modulates the MDR phenotype in leukemia cells, and propose further exploration of the use of miR-based therapies to overcome MDR.The authors would like to declare that we received funding from a commercial source, i.e. Bioplatforms Australia. This does not alter the authors' adherence to all PLOS ONE policies on sharing data and materials

    ELM of ELM-WD: An extremely low mass hot donor star discovered in LAMOST survey

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    The Extremely Low Mass White Dwarfs (ELM WDs) and pre-ELM WDs are helium core white dwarfs with mass <0.3M<\sim 0.3M_{\odot}. They are formed in close binaries and have lost over half of their initial masses via Common Envelope (CE) ejection or stable Roche Lobe Over Flow (RLOF). Both evolution simulations and observations show that a lower mass limit for ELM WDs exists at 0.14M\approx0.14M_{\odot}. Here we report the discovery of an extremely low mass ELM WD, ID70904216 in LAMOST survey, that may be lower than the ELM WD mass limit. Based on LAMOST and P200 spectroscopic observations, ID70904216 shows orbital period Porb=P_{orb} = 0.219658 days and radial velocity semi-amplitude K1=317.33km/sK1=317.33km/s, which gives the mass function of 0.73MM_{\odot}, indicating the companion is a compact star. The low resolution spectra shows a F type star with Teff7361KT_{\rm eff} \sim 7361K without emission features. The temperature is consistent with that derived from SED fitting(7440K7440K) and multi-color light curve solution(7400K7400K). The optical light curves, in ZTF g, r and i bands and Catalina V band, show ellipsoidal variability with amplitudes 30%\approx30\%, suggesting that the visible companion is heavily tidal distorted. Combining with the distance from Gaia survey, the WD code modeling estimates that the mass of the visible star is M1=0.080.03+0.06MM1=0.08^{+0.06}_{-0.03}M_{\odot}, and the mass of the invisible star is M2=0.940.10+0.45MM2=0.94^{+0.45}_{-0.10}M_{\odot}. The radius of the visible donor is R=0.29±0.01RR=0.29\pm0.01R_{\odot}. The inclination angle is constrained between 60^{\circ} and 90^{\circ}. The observations indicate the system is a pre-ELM WD + WD/NS binary system with an extremely low mass hot donor below the 0.14M0.14M_{\odot} theoretical limit.Comment: 16 pages, 10 figure

    Single-cell multiomics of the human retina reveals hierarchical transcription factor collaboration in mediating cell type-specific effects of genetic variants on gene regulation

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    BACKGROUND: Systematic characterization of how genetic variation modulates gene regulation in a cell type-specific context is essential for understanding complex traits. To address this question, we profile gene expression and chromatin accessibility in cells from healthy retinae of 20 human donors through single-cell multiomics and genomic sequencing. RESULTS: We map eQTL, caQTL, allelic-specific expression, and allelic-specific chromatin accessibility in major retinal cell types. By integrating these results, we identify and characterize regulatory elements and genetic variants effective on gene regulation in individual cell types. The majority of identified sc-eQTLs and sc-caQTLs display cell type-specific effects, while the cis-elements containing genetic variants with cell type-specific effects are often accessible in multiple cell types. Furthermore, the transcription factors whose binding sites are perturbed by genetic variants tend to have higher expression levels in the cell types where the variants exert their effects, compared to the cell types where the variants have no impact. We further validate our findings with high-throughput reporter assays. Lastly, we identify the enriched cell types, candidate causal variants and genes, and cell type-specific regulatory mechanism underlying GWAS loci. CONCLUSIONS: Overall, genetic effects on gene regulation are highly context dependent. Our results suggest that cell type-dependent genetic effect is driven by precise modulation of both trans-factor expression and chromatin accessibility of cis-elements. Our findings indicate hierarchical collaboration among transcription factors plays a crucial role in mediating cell type-specific effects of genetic variants on gene regulation
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