- Important Dates
- ConferenceMay 27-29, 2021
- Submission Extended to Apr. 20, 2021
- Notification20-40 days after the submission
- Publication15-20 days after the final edition
The information about the Keynote Speakers of ICPHMS2021 is as follows, which will be updated regularly.
Biography: Dr. Xuesong Cao received his Ph.D. degree in botany from Beijing University, Beijing, China. He is currently a Professor in the College of Life Sciences, Liaocheng University. He has published many academic papers with SCI-indexed (the total Impact Factor is over 25). His major research areas include the molecular diagnosis of SARS-COV-2, plant virus and genome editing.
Topic: A Novel Rapid, Simple Fluorescent Bioprobe Based Diagnosis of SARS-cov-2 Virion
Abstract: The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to more than fourteen million confirmed cases, with over three million deaths globally, as of April 20, 2021. To date, almost all diagnostic testing for the virus occurs in centralized laboratories, and involves expensive laboratory equipment, lengthy assays, and trained laboratory technicians. Developing rapid, simple, sensitive and specific and cheap to mass produce diagnostic assays remains an urgent need. We have developed a novel technique of fluorescent bioprobe based diagnosis for SARS-CoV-2 virion. The features of this method are rapid, simple, sensitive and suitably applied for point-of-care (POC) and high-throughput tests. The development of test kid by this novel diagnostic platform may provide fruitful diagnosis for SARS-CoV-2 based on its accurate, specific and easy to run, producing results in a short time, and cheap to mass produce.
Biography: Dr. Tiefu Liu has completed his MD education in Hengyang Medical College, Master education in China Medical University, PhD education in University of Hong Kong, and Postdoctoral studies in University of South California and Wake Forest University. He is currently the Professor and Foreign Expert of Shanghai Public Health Clinical Center, Fudan University，Adjunct Faculty Member of Wake Forest Unversity School of Medicine, Scientific Counselor of Chinese Society for Cancer Metabolism. He is expertized in Molecular Immunology, Sirtuin biology, the mutual actions of immunometabolism in regulation of acute inflammatory response, infectious diseases, inflammation to cancer transition, and molecularly targeted therapies of severe inflammation and cancers. His recent works have proposed sepsis as an immunometabolic disease and the key role of energy sensing-based energistic modifications in promting restoration of immunometabolism homeostasis during inflammation resolution, and have emphasized the sigificance of inflammatory phase-specific targeted therapies to improve sepsis outcomes. His previous works had produced a panel of immunotoxins for molecularly targeted therapies for glioblastoma and acute leukemia, and demonstrated APPL serves as a molecular link between extro- and intro-cellular signalings.
Topic: Chronic HIV Infection Primes Hyper Inflammatory Response to Subsequent Infections in AIDS Patients by Disturbing Immunometabolic Homeostasis
Abstract: Despite the successful control of HIV replication by antiretroviral therapy, the consequent hyper-inflammatory sepsis upon subsequent infection becomes a leading cause of AIDS-associated death. It has been attributed to the hyper inflammatory priming by persistent immune activation and GLUT1-dependent hyper-glycolytic activity, however, the underlying knowledge is still incomplete. We have recently revealed that the imbalance of pro- and anti-inflammatory signaling is responsible for the immunometabolic modifications of AIDS patients. Upon activation of TLR4 signaling, AIDS immune cells expressed significantly higher pro-inflammatory cytokines and GLUT1-dependent glycolysis than healthy immune cells did, which was contrary to the repressed expression of the anti-inflammatory genes. Stimulating anti-inflammatory signaling reversed inflammatory imbalance by restricting nuclear translocation of pro-inflammatory gene transactivator but prompting nuclear translocation of pro-inflammatory gene repressors. Thus, restoring homeostasis of pro- and anti-inflammatory signaling of AIDS immune cells by activation of anti-inflammatory signaling promises prevention and effective therapy of AIDS-related sepsis.
Biography: Dr. Xi Chen received his Ph.D. degree in fermentation engineering from Tianjin university of science and technology, Tianjin, China and finished the research of Ph.D. project in Nankai university, China. He is currently an Associate Professor in the College of Pharmaceutical Engineering of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine. He has published many academic papers with SCI-indexed (the total Impact Factor is over 35). He is also a guest reviewer in the Journal of International Immunopharmacology. His major research areas include the immunopharmacology of traditional Chinese medicine, drug screening, tumor & allergic immune response and clinical transformation of basic immunology.
Topic: Astragaloside III Enhance the Tumor Response of NK Cells by Elevating NKG2D and IFN-γ
Abstract: Natural killer (NK) cells play an irreplaceable role in the development of colon cancer, in which antitumor function of NK cells was impaired. Astragaloside III is a natural compound from Astragalus that has been shown to have immunomodulatory effects in various systems. However, few studies have evaluated the antitumor effects of Astragaloside III through stimulating systemic immunity and regulating NK cells. In this study, flow cytometry, immunohistochemical analysis, and immunofunctional assays were performed to elucidate the functions of Astragaloside III in restoring antitumor function of NK cells. We demonstrated that Astragaloside III significantly elevated the expression of natural killer group 2D (NKG2D), Fas, and interferon-γ (IFN-γ) production in NK cells, leading to increased tumor-killing ability. Experiments in cell co-culture assays and CT26-bearing mice model further confirmed that Astragaloside III could effectively impede tumor growth by increasing infiltration of NK cells into tumor and upregulating the antitumor response of NK cells. We further revealed that Astragaloside III increased IFN-γ secretion of NK cells by enhancing the expression of transcription factor T-bet. In conclusion, the effective anti-tumor function of Astragaloside III was achieved through up-regulation of the immune response of NK cells and elevation of NKG2D, Fas, and IFN-γ production.
Biography: Dr. Fang Hu received the Ph.D. degree in Complex Network from School of Computer, Central China Normal University, Wuhan, China. Dr. Hu worked at the University of West Florida as a postdoctoral researcher in the department of Mathematics and Statistics. She is currently an Associate Professor with the College of Information Engineering, Hubei University of Chinese Medicine, Wuhan, China. She has published over 30 papers in SCI, EI journals, etc. She is the guest editor or reviewer for SCI journals. Her main research interests include complex networks, machine learning, optimization algorithms, and data modeling in various research fields.
Topic: Clinical Knowledge Discovery Based on Graph Embedding
Abstract: Exploring the complicated relationships underlying the clinical information is essential for the diagnosis and treatment of various diseases. Based on the real-world electronic medical records (EMRs) of the Coronavirus Disease 2019 (COVID-19) and Chronic Insomnia, an AI-based model of diagnosis and treatment is proposed for the clinical knowledge discovery. This model constructs the heterogeneous information network to exploit the complex relationships among the syndromes, symptoms, and medicines. Then, it generates the numerical symptom (medicine) embeddings and divides them into seven communities (syndromes) using the combination of the Skip-Gram model and Spectral Clustering (SC) algorithm. It identifies the key factors in symptom and medicine networks using six evaluation metrics of node centrality. The experimental results indicate that the proposed model is capable of discovering the critical symptoms and symptom distribution for diagnosis; the key medicines and medicine combinations for treatment. Furthermore, this model can provide tremendously valuable guidance and help physicians to combat the COVID-19 or other diseases.