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"Ren, Ming"
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مصائر عشر نساء : رواية /
مجموعة مترادفات قصصية للأديب الصيني «ما تشونغ جينغ» ضمن سلسلة إبداعات أدب الأقليات الصينية، وتضم قصصا قصيرة لعادات الأقليات الصينية، وسلوكيات العائلات في المناسبات الدينية والاحتفالات الأخرى المختلفة، وتتباين فيها الشخصيات والزمان والمكان، لتضع القارئ أمام رسم أدبي يشرح حياة الأقليات الصينية المليئة بالتناص.
Book
Commensal Bacteria Control Cancer Response to Therapy by Modulating the Tumor Microenvironment
The gut microbiota influences both local and systemic inflammation. Inflammation contributes to development, progression, and treatment of cancer, but it remains unclear whether commensal bacteria affect inflammation in the sterile tumor microenvironment. Here, we show that disruption of the microbiota impairs the response of subcutaneous tumors to CpG-oligonucleotide immunotherapy and platinum chemotherapy. In antibiotics-treated or germ-free mice, tumor-infiltrating myeloid-derived cells responded poorly to therapy, resulting in lower cytokine production and tumor necrosis after CpG-oligonucleotide treatment and deficient production of reactive oxygen species and cytotoxicity after chemotherapy. Thus, optimal responses to cancer therapy require an intact commensal microbiota that mediates its effects by modulating myeloid-derived cell functions in the tumor microenvironment. These findings underscore the importance of the microbiota in the outcome of disease treatment.
Journal Article
Enhancing predictions of antimicrobial resistance of pathogens by expanding the potential resistance gene repertoire using a pan-genome-based feature selection approach
Background
Predicting which pathogens might exhibit antimicrobial resistance (AMR) based on genomics data is one of the promising ways to swiftly and precisely identify AMR pathogens. Currently, the most widely used genomics approach is through identifying known AMR genes from genomic information in order to predict whether a pathogen might be resistant to certain antibiotic drugs. The list of known AMR genes, however, is still far from comprehensive and may result in inaccurate AMR pathogen predictions. We thus felt the need to expand the AMR gene set and proposed a pan-genome-based feature selection method to identify potential gene sets for AMR prediction purposes.
Results
By building pan-genome datasets and extracting gene presence/absence patterns from four bacterial species, each with more than 2000 strains, we showed that machine learning models built from pan-genome data can be very promising for predicting AMR pathogens. The gene set selected by the eXtreme Gradient Boosting (XGBoost) feature selection approach further improved prediction outcomes, and an incremental approach selecting subsets of XGBoost-selected features brought the machine learning model performance to the next level. Investigating selected gene sets revealed that on average about 50% of genes had no known function and very few of them were known AMR genes, indicating the potential of the selected gene sets to expand resistance gene repertoires.
Conclusions
We demonstrated that a pan-genome-based feature selection approach is suitable for building machine learning models for predicting AMR pathogens. The extracted gene sets may provide future clues to expand our knowledge of known AMR genes and provide novel hypotheses for inferring bacterial AMR mechanisms.
Journal Article
Investigation of hydrodynamics of water impact and tail slamming of high-speed water entry with a novel immersed boundary method
High-speed water entry is a transient hydrodynamic process that is accompanied by strongly compressible flow, free surface splash, cavity evolution and other nonlinear hydrodynamic phenomena. To address these problems, a novel fluid–structure interaction (FSI) scheme based on the immersed boundary method is proposed which is suitable for strongly compressible multiphase flows. In this scheme, considering the multiphase interfaces at the immersed boundary, an improved immersed boundary method for effectively suppressing the non-physical force oscillation is proposed. Additionally, a quaternion-based six degrees of freedom motion system is used to describe rigid body motion, and the multiphase flow Eulerian finite element method is applied as the fluid solver. Using analytical solutions, experimental data and literature data, the accuracy and robustness of the FSI scheme are validated. Finally, the high-speed water entry of the slender body with different noses is investigated, and the hydrodynamic loads including the axial and normal drag forces and the bending moment are extensively discussed. The hydrodynamic load and motion trajectory are determined by the nose configuration. The tail slamming phenomenon is the primary focus, and it is revealed that its formation is primarily related to the pitch moment formed at the stage of crossing the free surface. Tail slamming also causes violent impact loads, especially bending moments, which may cause slender projectiles to break off. Finally, to combine the features of the flat and hemispherical noses, the water entry of the projectile with a truncated hemispherical nose is simulated and discussed.
Journal Article
H2S Alleviates Salinity Stress in Cucumber by Maintaining the Na+/K+ Balance and Regulating H2S Metabolism and Oxidative Stress Response
Salinity stress from soil or irrigation water can significantly limit the growth and development of plants. Emerging evidence suggests that hydrogen sulfide (H2S), as a versatile signal molecule, can ameliorate salt stress-induced adverse effects. However, the possible physiological mechanism underlying H2S-alleviated salt stress in cucumber remains unclear. Here, a pot experiment was conducted with an aim to examine the possible mechanism of H2S in enhancement of cucumber salt stress tolerance. The results showed that H2S ameliorated salt-induced growth inhibition and alleviated the reduction in photosynthetic attributes, chlorophyll fluorescence and stomatal parameters. Meanwhile H2S increased the endogenous H2S level concomitant with increased activities of D/L-cysteine desulfhydrase and β-cyanoalanine synthase and decreased activities of O-acetyl-L-serine(thiol)lyase under excess NaCl. Notably, H2S maintained Na+ and K+ homeostasis via regulation of the expression of PM H+-ATPase , SOS1 and SKOR at the transcriptional level under excess NaCl. Moreover, H2S alleviated salt-induced oxidative stress as indicated by lowered lipid peroxidation and reactive oxygen species accumulation through an enhanced antioxidant system. Altogether, these results demonstrated that application of H2S could protect cucumber seedlings against salinity stress, likely by keeping the Na+/K+ balance, controlling the endogenous H2S level by regulating the H2S synthetic and decomposition enzymes, and preventing oxidative stress by enhancing the antioxidant system under salinity stress.
Journal Article
Design of magnetic flux leakage detector for mine wire rope
At present, the online detection technology of wire rope damage in coal mine hoisting needs to be improved. Given the large number of detection elements and high detection cost in the wire rope detection device, the magnetic flux leakage detection device of the wire rope damage detection system is designed. The magnetic sensor is selected. At the same time, in order to improve the strength of the magnetic leakage field at the defect and reduce the number of magnetic sensors, a magnetic focusing device is designed. The finite element simulation shows that the magnetic focusing device can effectively improve the sensitivity of defect detection. The above research provides the basis for the design of steel wire rope damage detection systems and is of great significance to ensure the safe and efficient operation of mine hoisting equipment.
Journal Article
The Tumor Microenvironment in Neuroblastoma: New Players, New Mechanisms of Interaction and New Perspectives
The contribution of the tumor microenvironment (TME) to cancer progression has been well recognized in recent decades. As cancer therapeutic strategies are increasingly precise and include immunotherapies, knowledge of the nature and function of the TME in a tumor becomes essential. Our understanding of the TME in neuroblastoma (NB), the second most common solid tumor in children, has significantly progressed from an initial focus on its Schwannian component to a better awareness of its complex nature, which includes not only immune but also non-immune cells such as cancer-associated fibroblasts (CAFs), the contribution of which to inflammation and interaction with tumor-associated macrophages (TAMs) is now recognized. Recent studies on the TME landscape of NB tumors also suggest significant differences between MYCN-amplified (MYCN-A) and non-amplified (MYCN-NA) tumors, in their content in stromal and inflammatory cells and their immunosuppressive activity. Extracellular vesicles (EVs) released by cells in the TME and microRNAs (miRs) present in their cargo could play important roles in the communication between NB cells and the TME. This review article discusses these new aspects of the TME in NB and the impact that information on the TME landscape in NB will have in the design of precise, biomarker-integrated clinical trials.
Journal Article
Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach
O6-Methylguanine-DNA-methyltransferase (MGMT) promoter methylation was shown in many studies to be an important predictive biomarker for temozolomide (TMZ) resistance and poor progression-free survival in glioblastoma multiforme (GBM) patients. However, identifying the MGMT methylation status using molecular techniques remains challenging due to technical limitations, such as the inability to obtain tumor specimens, high prices for detection, and the high complexity of intralesional heterogeneity. To overcome these difficulties, we aimed to test the feasibility of using a novel radiomics-based machine learning (ML) model to preoperatively and noninvasively predict the MGMT methylation status. In this study, radiomics features extracted from multimodal images of GBM patients with annotated MGMT methylation status were downloaded from The Cancer Imaging Archive (TCIA) public database for retrospective analysis. The radiomics features extracted from multimodal images from magnetic resonance imaging (MRI) had undergone a two-stage feature selection method, including an eXtreme Gradient Boosting (XGBoost) feature selection model followed by a genetic algorithm (GA)-based wrapper model for extracting the most meaningful radiomics features for predictive purposes. The cross-validation results suggested that the GA-based wrapper model achieved the high performance with a sensitivity of 0.894, specificity of 0.966, and accuracy of 0.925 for predicting the MGMT methylation status in GBM. Application of the extracted GBM radiomics features on a low-grade glioma (LGG) dataset also achieved a sensitivity 0.780, specificity 0.620, and accuracy 0.750, indicating the potential of the selected radiomics features to be applied more widely on both low- and high-grade gliomas. The performance indicated that our model may potentially confer significant improvements in prognosis and treatment responses in GBM patients.
Journal Article
Investigation of free surface effect on the cavity expansion and contraction in high-speed water entry
The evolution of the water-entry cavity affects the impact load and the motion of the body. This paper adopts the Eulerian finite element method for multiphase flow for simulations of the high-speed water-entry process. The accuracy and convergence of the numerical method are verified by comparing it with the experimental data and the results of the transient cavity dynamics theory. Based on the results, the representative characteristics of the cavity are discussed from the perspective of the cavity cross-section. It is found that the asymmetry of the cavity expansion and contraction durations is related to the motion of the free surface and the closure of the cavity. The uplift of the free surface suppresses cavity expansion, while the jet generated from free surface closure accelerates cavity contraction. The duration of the contraction of the cavity near the free surface is shorter than the expansion duration due to the change in the velocity distribution caused by the free surface motion. The necking phenomenon during deep closure leads to an increase in the internal pressure of the cavity, prolonging cavity contraction near the deep closure area. This work provides new insights into the cavity dynamics in high-speed water entry.
Journal Article
Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi
Secondary metabolites (SM) produced by fungi and bacteria have long been of exceptional interest owing to their unique biomedical ramifications. The traditional discovery of new natural products that was mainly driven by bioactivity screening has now experienced a fresh new approach in the form of genome mining. Several bioinformatics tools have been continuously developed to detect potential biosynthetic gene clusters (BGCs) that are responsible for the production of SM. Although the principles underlying the computation of these tools have been discussed, the biological background is left underrated and ambiguous. In this review, we emphasize the biological hypotheses in BGC formation driven from the observations across genomes in bacteria and fungi, and provide a comprehensive list of updated algorithms/tools exclusively for BGC detection. Our review points to a direction that the biological hypotheses should be systematically incorporated into the BGC prediction and assist the prioritization of candidate BGC.
Journal Article