Browsing by Author "Chen, Z"
Now showing 1 - 5 of 5
- Results Per Page
- Sort Options
Item Open Access Complement C4 inhibits systemic autoimmunity through a mechanism independent of complement receptors CR1 and CR2.(J Exp Med, 2000-11-06) Chen, Z; Koralov, SB; Kelsoe, GThe complement system enhances antibody responses to T-dependent antigens, but paradoxically, deficiencies in C1 and C4 are strongly linked to autoantibody production in humans. In mice, disruption of the C1qa gene also results in spontaneous autoimmunity. Moreover, deficiencies in C4 or complement receptors 1 and 2 (CR1/CR2) lead to reduced selection against autoreactive B cells and impaired humoral responses. These observations suggest that C1 and C4 act through CR1/CR2 to enhance humoral immunity and somehow suppress autoimmunity. Here we report high titers of spontaneous antinuclear antibody (ANA) in C4(-/)- mice. This systemic lupus erythematosus-like autoimmunity is highly penetrant; by 10 mo of age, all C4(-)(/)- females and most males produced ANA. In contrast, titers and frequencies of ANA in Cr2(-)(/)- mice, which are deficient in CR1 and CR2, never rose significantly above those in normal controls. Glomerular deposition of immune complexes (ICs), glomerulonephritis, and splenomegaly were observed in C4(-)(/)- but not Cr2(-)(/)- mice. C4(-)(/)-, but not Cr2(-)(/)-, mice accumulate activated T and B cells. Clearance of circulating ICs is impaired in preautoimmune C4(-)(/)-, but not Cr2(-)(/)-, mice. C4 deficiency causes spontaneous, lupus-like autoimmunity through a mechanism that is independent of CR1/CR2.Item Open Access Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass.(Nat Commun, 2017-11-07) Zillikens, MC; Demissie, S; Hsu, Y - H; Yerges-Armstrong, LM; Chou, W - C; Stolk, L; Livshits, G; Broer, L; Johnson, T; Koller, DL; Kutalik, Z; Luan, J; Malkin, I; Ried, JS; Smith, AV; Thorleifsson, G; Vandenput, L; Hua Zhao, J; Zhang, W; Aghdassi, A; Åkesson, K; Amin, N; Baier, LJ; Barroso, I; Bennett, DA; Bertram, L; Biffar, R; Bochud, M; Boehnke, M; Borecki, IB; Buchman, AS; Byberg, L; Campbell, H; Campos Obanda, N; Cauley, JA; Cawthon, PM; Cederberg, H; Chen, Z; Cho, NH; Jin Choi, H; Claussnitzer, M; Collins, F; Cummings, SR; De Jager, PL; Demuth, I; Dhonukshe-Rutten, RAM; Diatchenko, L; Eiriksdottir, G; Enneman, AW; Erdos, M; Eriksson, JG; Eriksson, J; Estrada, K; Evans, DS; Feitosa, MF; Fu, M; Garcia, M; Gieger, C; Girke, T; Glazer, NL; Grallert, H; Grewal, J; Han, B - G; Hanson, RL; Hayward, C; Hofman, A; Hoffman, EP; Homuth, G; Hsueh, W - C; Hubal, MJ; Hubbard, A; Huffman, KM; Husted, LB; Illig, T; Ingelsson, E; Ittermann, T; Jansson, J - O; Jordan, JM; Jula, A; Karlsson, M; Khaw, K - T; Kilpeläinen, TO; Klopp, N; Kloth, JSL; Koistinen, HA; Kraus, WE; Kritchevsky, S; Kuulasmaa, T; Kuusisto, J; Laakso, M; Lahti, J; Lang, T; Langdahl, BL; Launer, LJ; Lee, J - Y; Lerch, MM; Lewis, JR; Lind, L; Lindgren, C; Liu, Y; Liu, T; Liu, Y; Ljunggren, Ö; Lorentzon, M; Luben, RN; Maixner, W; McGuigan, FE; Medina-Gomez, C; Meitinger, T; Melhus, H; Mellström, D; Melov, S; Michaëlsson, K; Mitchell, BD; Morris, AP; Mosekilde, L; Newman, A; Nielson, CM; O'Connell, JR; Oostra, BA; Orwoll, ES; Palotie, A; Parker, SCJ; Peacock, M; Perola, M; Peters, A; Polasek, O; Prince, RL; Räikkönen, K; Ralston, SH; Ripatti, S; Robbins, JA; Rotter, JI; Rudan, I; Salomaa, V; Satterfield, S; Schadt, EE; Schipf, S; Scott, L; Sehmi, J; Shen, J; Soo Shin, C; Sigurdsson, G; Smith, S; Soranzo, N; Stančáková, A; Steinhagen-Thiessen, E; Streeten, EA; Styrkarsdottir, U; Swart, KMA; Tan, S - T; Tarnopolsky, MA; Thompson, P; Thomson, CA; Thorsteinsdottir, U; Tikkanen, E; Tranah, GJ; Tuomilehto, J; van Schoor, NM; Verma, A; Vollenweider, P; Völzke, H; Wactawski-Wende, J; Walker, M; Weedon, MN; Welch, R; Wichmann, H - E; Widen, E; Williams, FMK; Wilson, JF; Wright, NC; Xie, W; Yu, L; Zhou, Y; Chambers, JC; Döring, A; van Duijn, CM; Econs, MJ; Gudnason, V; Kooner, JS; Psaty, BM; Spector, TD; Stefansson, K; Rivadeneira, F; Uitterlinden, AG; Wareham, NJ; Ossowski, V; Waterworth, D; Loos, RJF; Karasik, D; Harris, TB; Ohlsson, C; Kiel, DPA correction to this article has been published and is linked from the HTML version of this article.Item Open Access Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning(Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2023-02-28) Zhang, Y; Qu, G; Xu, P; Lin, Y; Chen, Z; Wierman, AWe study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of their entropy-regularized long-term rewards. To overcome the curse of dimensionality and to reduce communication, we propose a Localized Policy Iteration (LPI) algorithm that provably learns a near-globally-optimal policy using only local information. In particular, we show that, despite restricting each agent's attention to only its κ-hop neighborhood, the agents are able to learn a policy with an optimality gap that decays polynomially in κ. In addition, we show the finite-sample convergence of LPI to the global optimal policy, which explicitly captures the trade-off between optimality and computational complexity in choosing κ. Numerical simulations demonstrate the effectiveness of LPI.Item Open Access Notching R&D Investment with Corporate Income Tax Cuts in China(American Economic Review, 2021-07-01) Suarez Serrato, JC; Chen, Z; Liu, Z; Xu, DYWe analyze the effects of a large fiscal incentive for R&D investment in China that awards a lower average corporate income tax rate to qualifying firms. The sharp incentives of the program generate notches, or jumps, in firm values, and vary over time and across firm characteristics. We exploit a novel link between survey and administrative tax data of Chinese firms to estimate investment responses, the potential for evasion, as well as effects on productivity and tax payments. We find large responses of reported R&D using a cross-sectional “bunching” estimators that is new in the R&D literature. We also find evidence that firms relabel administrative expenses as R&D to qualify for the program. We estimate an intent-to-treat effect of the policy on R&D investment of 18.8%, and find that 45% of this response is due to evasion. These effects imply user-cost-elasticities of 2 for the reported response, and 1.14 for the real response. We utilize the panel structure of the data to estimate the effect of the program on firm productivity, and find an increase of 1.6% for targeted firms. These estimates are crucial ingredients for designing policies that trade-off corporate tax revenue with future productivity growth.Item Open Access Scaffold-free, Human Mesenchymal Stem Cell-Based Tissue Engineered Blood Vessels.(Sci Rep, 2015-10-12) Jung, Y; Ji, H; Chen, Z; Fai Chan, H; Atchison, L; Klitzman, B; Truskey, G; Leong, KWTissue-engineered blood vessels (TEBV) can serve as vascular grafts and may also play an important role in the development of organs-on-a-chip. Most TEBV construction involves scaffolding with biomaterials such as collagen gel or electrospun fibrous mesh. Hypothesizing that a scaffold-free TEBV may be advantageous, we constructed a tubular structure (1 mm i.d.) from aligned human mesenchymal cell sheets (hMSC) as the wall and human endothelial progenitor cell (hEPC) coating as the lumen. The burst pressure of the scaffold-free TEBV was above 200 mmHg after three weeks of sequential culture in a rotating wall bioreactor and perfusion at 6.8 dynes/cm(2). The interwoven organization of the cell layers and extensive extracellular matrix (ECM) formation of the hMSC-based TEBV resembled that of native blood vessels. The TEBV exhibited flow-mediated vasodilation, vasoconstriction after exposure to 1 μM phenylephrine and released nitric oxide in a manner similar to that of porcine femoral vein. HL-60 cells attached to the TEBV lumen after TNF-α activation to suggest a functional endothelium. This study demonstrates the potential of a hEPC endothelialized hMSC-based TEBV for drug screening.