841 research outputs found
sj-tif-2-tct-10.1177_15330338241248573 - Supplemental material for Impact of Anti-angiogenic Drugs on Severity of COVID-19 in Patients with Non-Small Cell Lung Cancer
No full textSupplemental material, sj-tif-2-tct-10.1177_15330338241248573 for Impact of Anti-angiogenic Drugs on Severity
of COVID-19 in Patients with Non-Small
Cell Lung Cancer by Sujuan Peng, Hongxiang Huang, Jinhong Chen, Xinjing Ding, Xie Zhu, Yangyang Liu, Li Chen, and Zhihui Lu in Technology in Cancer Research & Treatment</p
sj-tif-1-tct-10.1177_15330338241248573 - Supplemental material for Impact of Anti-angiogenic Drugs on Severity of COVID-19 in Patients with Non-Small Cell Lung Cancer
No full textSupplemental material, sj-tif-1-tct-10.1177_15330338241248573 for Impact of Anti-angiogenic Drugs on Severity
of COVID-19 in Patients with Non-Small
Cell Lung Cancer by Sujuan Peng, Hongxiang Huang, Jinhong Chen, Xinjing Ding, Xie Zhu, Yangyang Liu, Li Chen, and Zhihui Lu in Technology in Cancer Research & Treatment</p
Interleukin-1 mediated cell-type specific signaling in hippocampal neurons and astrocytes
No full textInterleukin-1β (IL-1β) is a pro-inflammatory cytokine that is implicated in immune and inflammatory responses. In the central nervous system (CNS), IL-1β is synthesized and released during injury, infection, and many neurodegenerative diseases, but also under physiological conditions. Several IL-1-mediated signaling pathways and effects have been identified in hippocampal neurons and astrocytes, but their mechanisms have not been fully defined. IL-1 signaling requires the type one IL-1 receptor (IL-1RI) as well as IL-1 receptor accessory protein (IL-1RAcP) as a receptor partner. A novel isoform of the IL-1 receptor accessory protein, AcPb, has also been found in the CNS, but its role remains unclear. This thesis examined AcPb function in regulating IL-1β signaling. The results showed that IL-1β activated p38 MAPK but not NFκB in neurons. In astrocytes, IL-1β induced both p38 and NFκB pathways in regulating inflammatory responses. AcPb was not involved in mediating either p38 or NFκB in either cell type. In contrast, a physiological level of IL-1β treatment (0.01ng/ml) activated p-Src in neurons via AcPb in vitro. In addition, overexpression of AcPb in astrocytes was sufficient to induce p-Src mediated by IL-1β. Taken together, these results suggest that the restricted expression of AcPb in CNS neurons may mediate neuronal specific IL-1 pathways and outcomes, and that physiological and pathophysiological levels of IL-1β mediate particular neuronal functions via separate pathways.Ph. D.Includes abstractIncludes bibliographical referencesby Yangyang Huan
Molecular simulations of rheological, mechanical and transport properties of solid-fluid systems:
No full textIn this dissertation, two distinct but relevant systems are chosen as representatives of interesting solid-fluid systems. Molecular dynamics (MD) and Monte Carlo techniques are applied to investigate the rheological, mechanical and transport properties of these systems.
Firstly, polyethylene melt embedded with silica nanoparticles is examined to be of our interest. Since it is computationally impractical to model a complex system with a molecular description, a multiscale modeling approach, which combines both atomistic and mesoscale simulations, is employed to efficiently represent and study the polymer nanoparticle systems. Based on a coarse-grained force field for polyethylene, a novel method is developed for determining the solid-fluid interaction at the spherical interface. Our coarse grained model is designed to mimic 4 nm silica nanoparticles in polyethylene melt at 423K. A series of MD simulations are performed to investigate the factors that control the homogeneity of nanofillers inside polymer matrix, also in the presence of nonionic surfactants (short chain alcohols). The effects of nanoparticle filling fraction, polymer chain length, and relative sizes between nanoparticles and polymer chains on the particle dispersion are explored. In addition, a fundamental relationship is pursued between the microstructure and macroscopic properties (transport and rheological) of polymer nanoparticle composites.
In this work another method for determining the solid-fluid interaction parameter is presented: the experimental adsorption isotherms are used to validate the potential parameters. The rapid expansion of silica nanoparticle agglomerates in supercritical carbon dioxide (RESS process) is chosen to be the system of interest. The simulations show that the effective attraction between two identical nanoparticles is most prominent for densely hydroxylated particle surfaces that interact strongly with CO2 via hydrogen bonds, while it is significantly weaker for dehydroxylated particles. We also explore the shearing forces necessary to break an agglomerate in supercritical fluid. The agglomerate experiences deformation followed by elongation, and finally break-up. The calculated diffusion coefficient of CO2 is expected to be smaller than the experimental value, because the nanoparticle agglomerate hinders fluid movement. In the direction of shearing forces, the diffusion of CO2 shows a steep increase after the breakup, confirming the rupture of the agglomerate.Ph.D.Includes bibliographical references (p. 136-142)by Yangyang She
Towards robust malware detection
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 45-48).A central challenge of malware detection using machine learning methods is the presence of adversarial variants, small changes to detectable malware that allow it to evade a model (i.e. be classified as benign). We take inspiration from adversarial variant generation methods in the continuous-valued image domain to introduce methods for malware in the binary domain. We incorporate these methods in the training of hardened models towards the goal of robustness against adversarial variants. Additionally, we provide visualization tools for analysis of hardened models. Our tools illustrate the difference in loss behavior between models trained with different methods, the effect of adversarial learning on the loss landscape of a model, and the effect of adversarial learning on the decision map of a model. The adversarial learning framework and the visualization tools in combination allow for the creation and understanding of robust models.by Alex Yangyang Huang.M. Eng
Lectures on Brill-Noether theory
No full textThese notes are the summary of lectures given by the author, in the framework of Joint Lectures of F. Flamini and E. Sernesi, at the Workshop
”Curves and Jacobians”, organized by the Korean Institute of Advanced Study (Seoul) and held on October 18-21, 2010, at Sol Beach Resort, Yangyang (Korea
Validation of goose liver fat measurement by QCT and CSE-MRI with biochemical extraction and pathology as reference
No full textObjectives: This study aimed to validate the accuracy and reliability of quantitative computed tomography (QCT) and chemical shift encoded magnetic resonance imaging (CSE-MRI) to assess hepatic steatosis. Methods: Twenty-two geese with a wide range of hepatic steatosis were collected. After QCT and CSE-MRI examinations, the liver of each goose was removed and samples were taken from the left lobe, upper and lower half of the right lobe for biochemical measurement and histology. Fat percentages by QCT and proton density fat fraction by MRI (MRI-PDFF) were measured within the sample regions of biochemical measurement and histology. The accuracy of QCT and MR measurements were assessed through Spearman correlation coefficients (r) and Passing and Bablok regression equations using biochemical measurement as the "gold standard". Results: Both QCT and MRI correlated highly with chemical extraction [r = 0.922 (p < 0.001) and r = 0.949 (p < 0.001) respectively]. Chemically extracted triglyceride was accurately predicted by both QCT liver fat percentages (Y = 0.6 + 0.866 à X) and by MRI-PDFF (Y = -1.8 + 0.773 à X). Conclusions: QCT and CSE-MRI measurements of goose liver fat were accurate and reliable compared with biochemical measurement. Key Points: ⢠QCT and CSE-MRI can measure liver fat content accurately and reliably⢠Histological grading of hepatic steatosis has larger sampling variability⢠QCT and CSE-MRI have potential in the clinical settin
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