Graduate Recital:Yalin Song, Cello

Kemp Recital Hall Saturday Evening April 25, 1998 9:30p.m

Miniaturized-Element Frequency-Selective Rasorber Design Using Characteristic Modes Analysis

A dual-polarization frequency-selective rasorber with two absorptive bands at both sides of a passband is presented. Based on the characteristic mode analysis, a circuit analog absorber is designed using a lossy FSS that consists of miniaturized meander lines and lumped resistors. The positions and values of resistors are determined according to the analysis of modal significances and modal current. After that, the presented rasorber is designed by cascading of the lossy FSS and a lossless bandpass FSS. Equivalent circuits of the frequency-selective rasorber are modelled, and surface current distributions of both FSSs are illustrated to explain the operation mechanism. Measurement results show that, under the normal incidence, a minimum insertion loss of 0.27 dB is achieved at a passband around 6 GHz, and the absorption bands with an absorption rate higher than 80% are 2.5 to 4.6 GHz in the lower band and 7.7 to 12 GHz in the higher band, respectively. Our results exhibit good agreements between measurements and simulations

Application of Data Architecture Model in Enterprise Management

Today is in the era of rapid development of information, data volume of high-speed expansion, it is difficult in the previous system for communication, sharing and integration. In order to integrate data resources, eliminate the “information island”, build enterprise development blueprints, people gradually realize the importance of top design. Many enterprises for their own development to establish their own enterprise architecture of the top design, and as its core data architecture model is also reflected in different industries according to different development. This paper mainly studies the data architecture model, expounds the role of data architecture model and its relationship

Faculty Recital:Faculty String Quartet

Kemp Recital Hall Monday Evening November 24, 1997 8:00 p.m

Observation of Viruses, Bacteria, and Fungi in Clinical Skin Samples under Transmission Electron Microscopy

The highlight of this chapter is the description of the clinical manifestation and its pathogen and the host tissue damage observed under the transmission electron microscopy, which helps the clinician understand the pathogen’s ultrastructure, the change of host sub-cell structure, and helps the laboratory workers understand the pathogen-induced human skin lesions’ clinical characteristics, to establish a two-way learning exchange database with vivid images

Possible Mechanisms of SARS-CoV2-Mediated Myocardial Injury

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has rapidly become a global health emergency. In addition to causing respiratory effects, SARS-CoV-2 can result in cardiac involvement leading to myocardial damage, which is increasingly being explored in the literature. Myocardial injury is an important pathogenic feature of COVID-19. The angiotensin-converting enzyme-2 receptor plays a key role in the pathogenesis of the virus, serving as a “bridge” allowing SARS-CoV-2 to invade the body. However, the exact mechanism underlying how SARS-CoV-2 causes myocardial injury remains unclear. This review summarizes the main possible mechanisms of myocardial injury in patients with COVID-19, including direct myocardial cell injury, microvascular dysfunction, cytokine responses and systemic inflammation, hypoxemia, stress responses, and drug-induced myocardial injury. Understanding of the underlying mechanisms would aid in proper identification and treatment of myocardial injury in patients with COVID-19

FAM20A: a potential diagnostic biomarker for lung squamous cell carcinoma

BackgroundLung squamous cell carcinoma (LUSC) ranks among the carcinomas with the highest incidence and dismal survival rates, suffering from a lack of effective therapeutic strategies. Consequently, biomarkers facilitating early diagnosis of LUSC could significantly enhance patient survival. This study aims to identify novel biomarkers for LUSC.MethodsUtilizing the TCGA, GTEx, and CGGA databases, we focused on the gene encoding Family with Sequence Similarity 20, Member A (FAM20A) across various cancers. We then corroborated these bioinformatic predictions with clinical samples. A range of analytical tools, including Kaplan-Meier, MethSurv database, Wilcoxon rank-sum, Kruskal-Wallis tests, Gene Set Enrichment Analysis, and TIMER database, were employed to assess the diagnostic and prognostic value of FAM20A in LUSC. These tools also helped evaluate immune cell infiltration, immune checkpoint genes, DNA repair-related genes, DNA methylation, and tumor-related pathways.ResultsFAM20A expression was found to be significantly reduced in LUSC, correlating with lower survival rates. It exhibited a negative correlation with key proteins in DNA repair signaling pathways, potentially contributing to LUSC’s radiotherapy resistance. Additionally, FAM20A showed a positive correlation with immune checkpoints like CTLA-4, indicating potential heightened sensitivity to immunotherapies targeting these checkpoints.ConclusionFAM20A emerges as a promising diagnostic and prognostic biomarker for LUSC, offering potential clinical applications

CHD7 and Runx1 interaction provides a braking mechanism for hematopoietic differentiation.

Hematopoietic stem and progenitor cell (HSPC) formation and lineage differentiation involve gene expression programs orchestrated by transcription factors and epigenetic regulators. Genetic disruption of the chromatin remodeler chromodomain-helicase-DNA-binding protein 7 (CHD7) expanded phenotypic HSPCs, erythroid, and myeloid lineages in zebrafish and mouse embryos. CHD7 acts to suppress hematopoietic differentiation. Binding motifs for RUNX and other hematopoietic transcription factors are enriched at sites occupied by CHD7, and decreased RUNX1 occupancy correlated with loss of CHD7 localization. CHD7 physically interacts with RUNX1 and suppresses RUNX1-induced expansion of HSPCs during development through modulation of RUNX1 activity. Consequently, the RUNX1:CHD7 axis provides proper timing and function of HSPCs as they emerge during hematopoietic development or mature in adults, representing a distinct and evolutionarily conserved control mechanism to ensure accurate hematopoietic lineage differentiation.Bloodwise, CRUK, MRC, Wellcome Trust, NIH, Leukemia and Lymphoma Societ

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking