Browsing by Author "Li, H."

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    Absence of human T-cell lymphotropic virus type I and human foamy virus in thymoma
    (Springer, 2004-06) Li, H.; Loehrer, P. J.; Hisada, M.; Henley, J.; Whitby, D.; Engels, E. A.; Medicine, School of Medicine
    The cause of thymoma, a rare malignancy of thymic epithelial cells, is unknown. Recent studies have reported the detection of DNA from human T-cell lymphotropic virus type I (HTLV-I) and human foamy virus (HFV) in small numbers of thymoma tumours, suggesting an aetiologic role for these retroviruses. In the present study, we evaluated 21 US thymoma patients and 20 patients with other cancers for evidence of infection with these viruses. We used the polymerase chain reaction to attempt to amplify viral DNA from tumour tissues, using primers from the pol and tax (HTLV-I) and gag and bel1 (HFV) regions. In these experiments, we did not detect HTLV-I or HFV DNA sequences in any thymoma or control tissues, despite adequate sensitivity of our assays (one HTLV-I copy per 25 000 cells, one HFV copy per 7500 cells). Additionally, none of 14 thymoma patients evaluated serologically for HTLV I/II infection was positive by enzyme-linked immunoassay (ELISA), while five (36%) had indeterminate Western blot reactivity. In comparison, one of 20 US blood donors was HTLV-I/II ELISA positive, and nine (45%) donors, including the ELISA-positive donor, had indeterminate Western blot reactivity. Western blot patterns varied across individuals and consisted mostly of weak reactivity. In conclusion, we did not find evidence for the presence of HTLV-I or HFV in US thymoma patients.
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    CD29 of human umbilical cord mesenchymal stem cells is required for expansion of CD34+ cells
    (Wiley, 2014-12) Yang, Y.; Hu, M.; Zhang, Y.; Li, H.; Miao, Z.; Medical and Molecular Genetics, School of Medicine
    Objectives: Human umbilical cord mesenchymal stem cells (hUCMSCs) play a critical role in expanding haematopoietic stem cells (HSCs) by providing the essential microenvironment for haematopoiesis. In this study, we sought to investigate whether CD29 of hUCMSCs would play a key role in the ability of hUCMSCs to help expand HSCs in vivo and in vitro. Material and methods: To investigate whether CD29 of hUCMSCs would play a key role for the ability of hUCMSCs to expand HSCs, soluble anti-CD29 antibody was added to co-cultures of hUCMSCs and cord blood (CB) CD34(+) cells. It significantly blocked expansion of CB CD34(+) cells induced by hUCMSCs. Using CD29-deficient hUCMSCs models, long-term culture-initiating cell and non-obese diabetic/severe combined immunodeficient disease mouse repopulating cell assay, revealed that CB CD34(+) cells co-cultured with CD29-deficient hUCMSCs only retained the capacity of multipotent differentiation for 5 weeks at the most. Results: Soluble anti-CD29 antibody significantly blocked expansion of CB CD34(+) cells induced by hUCMSCs. CB CD34(+) cells co-cultured with CD29-deficient hUCMSCs only retained the capacity of multipotent differentiation for 5 weeks at the most. Conclusions: CB CD34(+) cells co-cultured with CD29-deficient hUCMSCs gave rise to all major haematopoietic lineages, but failed to engraft long term.
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    Immune signatures underlying post-acute COVID-19 lung sequelae
    (AAAS, 2021-11) Cheon, I. S.; Li, C.; Son, Y. M.; Goplen, N. P.; Wu, Y.; Cassmann, T.; Wang, Z.; Wei, X.; Tang, J.; Li, Y.; Marlow, H.; Hughes, S.; Hammel, L.; Cox, T. M.; Goddery, E.; Ayasoufi, K.; Weiskopf, D.; Boonyaratanakornkit, J.; Dong, H.; Li, H.; Chakraborty, R.; Johnson, A. J.; Edell, E.; Taylor, J. J.; Kaplan, M. H.; Sette, A.; Bartholmai, B. J.; Kern, R.; Vassallo, R.; Sun, J.; Microbiology and Immunology, School of Medicine
    Severe coronavirus disease 2019 (COVID-19) pneumonia survivors often exhibit long-term pulmonary sequelae, but the underlying mechanisms or associated local and systemic immune correlates are not known. Here, we have performed high-dimensional characterization of the pathophysiological and immune traits of aged COVID-19 convalescents, and correlated the local and systemic immune profiles with pulmonary function and lung imaging. We found that chronic lung impairment was accompanied by persistent respiratory immune alterations. We showed that functional severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)–specific memory T and B cells were enriched at the site of infection compared with those of blood. Detailed evaluation of the lung immune compartment revealed that dysregulated respiratory CD8+ T cell responses were associated with the impaired lung function after acute COVID-19. Single-cell transcriptomic analysis identified the potential pathogenic subsets of respiratory CD8+ T cells contributing to persistent tissue conditions after COVID-19. Our results have revealed pathophysiological and immune traits that may support the development of lung sequelae after SARS-CoV-2 pneumonia in older individuals, with implications for the treatment of chronic COVID-19 symptoms.
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    Physics-Based Regression vs. CFD for Hagen-Poiseuille and Womersley Flows and Uncertainty Quantification
    (NSF, 2022-07-01) Li, H.; Islam, M.; Yu, H.; Du, X.; Mechanical and Energy Engineering, School of Engineering and Technology
    Computational fluid dynamics (CFD) and its uncertainty quantification are computationally expensive. We use Gaussian Process (GP) methods to demonstrate that machine learning can build efficient and accurate surrogate models to replace CFD simulations with significantly reduced computational cost without compromising the physical accuracy. We also demonstrate that both epistemic uncertainty (machine learning model uncertainty) and aleatory uncertainty (randomness in the inputs of CFD) can be accommodated when the machine learning model is used to reveal fluid dynamics. The demonstration is performed by applying simulation of Hagen-Poiseuille and Womersley flows that involve spatial and spatial-tempo responses, respectively. Training points are generated by using the analytical solutions with evenly discretized spatial or spatial-temporal variables. Then GP surrogate models are built using supervised machine learning regression. The error of the GP model is quantified by the estimated epistemic uncertainty. The results are compared with those from GPU-accelerated volumetric lattice Boltzmann simulations. The results indicate that surrogate models can produce accurate fluid dynamics (without CFD simulations) with quantified uncertainty when both epistemic and aleatory uncertainties exist.