IntroductionBone marrow and organ transplantation are curative for an increasing number of diseases. The major barriers are graft-versushost disease (GVHD) and rejection, which currently are inhibited by toxic nonspecific immunosuppression. Induction of donorspecific tolerance without the requirement for immunosuppressive drugs would be highly desirable. Adoptive therapy with ex vivo-induced antigen (Ag)-specific T regulatory cells (Tregs) has considerable potential.CD4 ϩ CD25 high Foxp3 ϩ T cells are potent regulators of transplantation rejection 1-5 and GVHD. [6][7][8] Natural Tregs are produced as a separate lineage in the thymus that constitute 2% to 10% of peripheral CD4 ϩ T cells, 9 inhibit in a non-Ag-specific manner, and protect normal tissue from immune injury. 2,10 The CD4 ϩ CD25 ϩ T cells that mediate transplantation tolerance are Ag-specific, 1-4 but how they develop and differ to natural non-Ag-specific CD4 ϩ CD25 ϩ Tregs is poorly understood. 9 In fully allogeneic models, naive CD4 ϩ CD25 high T cells, if given at a ratio of 1:1 with naive CD4 ϩ T cells, can totally prevent rejection 5 and GVHD 7 but only partially block GVHD at a ratio of 1:2. 8 At a ratio of 1:10, naive CD4 ϩ CD25 high T cells do not block rejection 5 or GVHD. 7 Given the very low number of CD4 ϩ CD25 ϩ T cells in the T-cell population, it is impractical to prepare enough cells for therapeutic usage at a ratio of 1:1. Ex vivo polyclonal activation of CD4 ϩ CD25 ϩ T cells with interleukin-2 (IL-2) and anti-CD3 monoclonal antibody (mAb) 6 or IL-2, anti-CD3 and anti-CD28 11 results in 200-to 250-fold cell number expansion but no enhanced Ag-specific regulatory capacity. 12 Culture of CD4 ϩ CD25 ϩ Tregs with allo-Ag and IL-2 for a week or more also increases cell numbers but does not induce high potency Agspecific CD4 ϩ CD25 ϩ Tregs, in that a ratio of 2:1 13 or 5:1 14 with naive T cells is required to suppress skin graft rejection. Similarly, in GVHD, a 7:10 ratio of IL-2-and allo-Ag-cultured Tregs to naive cells is less effective than fresh naive CD4 ϩ CD25 ϩ T cells, in that they delay but do not fully prevent GVHD. 8 In contrast, CD4 ϩ CD25 ϩ T cells within CD4 ϩ T cells from hosts with allo-Ag-specific tolerance to a graft can transfer allo-Ag-specific tolerance at an effective ratio of less than 1:20. 2,3 These tolerant CD4 ϩ T cells, when cultured in vitro, lose the capacity to transfer tolerance unless stimulated by specific donor Ag in media supplemented with T-cell cytokines. 2,15,16 Which cytokines are most effective at maintaining specific Tregs is unknown, but IL-2 alone is insufficient. 16 This suggests that Ag-specific CD4 ϩ CD25 ϩ T cells may become dependent on cytokines other than IL-2. We have identified that interferon-␥ (IFN-␥) and IL-5, but not other T-helper 1 (Th1) and Th2 cytokines, promoted proliferation and survival of Agspecific tolerance mediating Tregs from rats tolerant to an allograft (B.M.H., M.N., K.M.P., N.D.V., G.T.T., S.J.H., unpublished data). 20 we examined whether Th1 and Th2 cytokines promote...

Abstract. Learning the governing equations in dynamical systems from time-varying measurements is of great interest across different scientific fields. This task becomes prohibitive when such data is moreover highly corrupted, for example, due to the recording mechanism failing over unknown intervals of time. When the underlying system exhibits chaotic behavior, such as sensitivity to initial conditions, it is crucial to recover the governing equations with high precision. In this work, we consider continuous time dynamical systemsẋ = f (x) where each component of f : R d → R d is a multivariate polynomial of maximal degree p; we aim to identify f exactly from possibly highly corrupted measurements x(t 1 ), x(t 2 ), . . . , x(tm). As our main theoretical result, we show that if the system is sufficiently ergodic that this data satisfies a strong central limit theorem (as is known to hold for chaotic Lorenz systems), then the governing equations f can be exactly recovered as the solution to an 1 minimization problem -even if a large percentage of the data is corrupted by outliers. Numerically, we apply the alternating minimization method to solve the corresponding constrained optimization problem. Through several examples of 3D chaotic systems and higher dimensional hyperchaotic systems, we illustrate the power, generality, and efficiency of the algorithm for recovering governing equations from noisy and highly corrupted measurement data.

Immune responses to foreign and selfAgs can be controlled by regulatory T cells (Tregs) expressing CD4 and IL-2R␣ chain (CD25). Defects in Tregs lead IntroductionBoth Ag-specific 1 and naive regulatory T cells (Tregs) 2-4 that control immune responses are mainly CD4 ϩ CD25 ϩ T cells 5 expressing transcription factor FOXP3. 6 Autoimmunity occurs with the breakdown in immune tolerance to self-Ag and can be because of a failure of natural Tregs (nTregs) produced by the thymus which prevent spontaneous autoimmune activation of CD4 ϩ CD25 Ϫ T effector cells by inhibiting APCs. 5 nTregs maintain immune homeostasis and are polyclonally expanded by IL-2. nTregs can suppress all immune responses, because they are not Ag specific. To fully suppress high ratios to effector lineage, CD4 ϩ CD25 Ϫ T cells are required, usually Ͼ 1:1; whereas the natural ratio of these cells in peripheral lymphoid tissues is tightly regulated to Ͻ 1:10. 7,8 There is ample evidence for Ag-specific Treg induction in vivo, including T-cell transfer of tolerance to specific autoantigen induced by immunization with autoantigen without complete Freund adjuvant (CFA), 9 the parabiosis of tolerance to autoimmunity from normal hosts, 10 and the epitope specificity of tolerance induction with an autoantigen. 11 Ag-specific CD4 ϩ CD25 ϩ Tregs have phenotypic and functional differences from the nTreg, recently reviewed by Hall et al. 12 Activated Tregs do not migrate from blood to lymph but express chemokine receptors and other ligands that promote their migration to sites of inflammation, where they control local inflammation. 12 Further, their action is not to inhibit APCs via CTLA4, but to inhibit or eliminate activated effector T cells and macrophages, by a variety of mechanisms. 12 To date, most studies focused on nTregs that suppress in a non-Ag-specific manner and must be present at high ratios with effector T cells to fully suppress an immune response. In autoimmune disease it would be desirable to induce Ag-specific Tregs that can suppress only the specific immune response at low ratios (Ͻ 1:10) to effector cells. 13 Specific immune tolerance, as occurs in adult rodents that accept an allograft long term, is mediated by Ag-specific CD4 ϩ CD25 ϩ Tregs that suppress at ratios Ͻ 1:10. 1,14,15 These alloantigen-specific Tregs are difficult to identify, because their survival depends on stimulation by both Ag 1,16 and T cell-derived cytokines. 17 IL-2 17 or IL-4 do not fully maintain activated Agspecific Tregs, but other cytokines such as IL-5 can. 3 In our studies, the initial activation of nTregs to alloantigenspecific Tregs occurred when they were cultured with specific alloantigens and either the T helper type 1 (Th1) cytokine IL-2 or the Th2 cytokine IL-4, but not other Th1 or Th2 cytokines. 3 Alloactivation of nTregs with IL-2 induces the receptor for the late Th1 cytokine IFN-␥ (Ifn␥r) but not the receptor for the Th2 cytokine ␤, Ifn␥r. 3 The selective induction of Il-5r␣ on Ag-activated Tregs that have been stimulated by IL-4, not IL-2, ra...

In rat models, CD4+CD25+ T regulatory cells (Treg) play a key role in the induction and maintenance of antigen-specific transplant tolerance, especially in DA rats with PVG cardiac allografts (1, 2). We have previously described generation of alloantigen-specific Treg (Ts1), by culture of naïve natural CD4+CD25+ Treg (nTreg) with specific alloantigen and IL-2 for 4 days. These cells express mRNA for IFN-γ receptor (ifngr) and suppress donor but not third party cardiac allograft rejection mediated by alloreactive CD4+ T cells at ratios of <1:10. Here, we show that Ts1 also expressed the IL-12p70 specific receptor (il-12rβ2) and that rIL-12p70 can induce their proliferation. Ts1 cells re-cultured with rIL-12p70 alone or rIL-12p70 and recombinant interleukin-2 (rIL-2), suppressed proliferation of CD4+ T cells in mixed lymphocyte culture at <1:1024, whereas Ts1 cells re-cultured with rIL-2 and alloantigen only suppressed at 1:32–64. The rIL-12p70 alloactivated Ts1 cells markedly delayed PVG, but not third party Lewis, cardiac allograft rejection in normal DA recipients. Ts1 cells re-cultured for 4 days with rIL-12p70 alone, but not those re-cultured with rIL-12p70 and rIL-2, expressed more il-12rβ2, t-bet, and ifn-γ, and continued to express the markers of Ts1 cells, foxp3, ifngr, and il-5 indicating Th1-like Treg were induced. Ts1 cells re-cultured with rIL-2 and alloantigen remained of the Ts1 phenotype and did not suppress cardiac graft rejection in normal DA rats. We induced highly suppressive Th1-like Treg from naïve nTreg in 7 days by culture with alloantigen, first with rIL-2 then with rIL-12p70. These Th1-like Treg delayed specific donor allograft rejection demonstrating therapeutic potential.

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Extracting governing equations from dynamic data is an essential task in model selection and parameter estimation. The form of the governing equation is rarely known a priori; however, based on the sparsity-of-effect principle one may assume that the number of candidate functions needed to represent the dynamics is very small. In this work, we leverage the sparse structure of the governing equations along with recent results from random sampling theory to develop methods for selecting dynamical systems from under-sampled data. In particular, we detail three sampling strategies that lead to the exact recovery of first-order dynamical systems when we are given fewer samples than unknowns. The first method makes no assumptions on the behavior of the data, and requires a certain number of random initial samples. The second method utilizes the structure of the governing equation to limit the number of random initializations needed. The third method leverages chaotic behavior in the data to construct a nearly deterministic sampling strategy. Using results from compressive sensing, we show that the strategies lead to exact recovery, which is stable to the sparse structure of the governing equations and robust to noise in the estimation of the velocity. Computational results validate each of the sampling strategies and highlight potential applications.

Carboranethiol molecules self-assemble into upright molecular monolayers on Au{111} with aligned dipoles in two dimensions. The positions and offsets of each molecule's geometric apex and local dipole moment are measured and correlated with sub-Ångström precision. Juxtaposing simultaneously acquired images, we observe monodirectional offsets between the molecular apexes and dipole extrema. We determine dipole orientations using efficient new image analysis techniques and find aligned dipoles to be highly defect tolerant, crossing molecular domain boundaries and substrate step edges. The alignment observed, consistent with Monte Carlo simulations, forms through favorable intermolecular dipoleÀdipole interactions.

Diffusion MRI offers the unique opportunity of assessing the structural connections of human brains in vivo. With the advance of diffusion MRI technology, multi-shell imaging methods are becoming increasingly practical for large scale studies and clinical application. In this work, we propose a novel method for the analysis of multi-shell diffusion imaging data by incorporating compartment models into a spherical deconvolution framework for fiber orientation distribution (FOD) reconstruction. For numerical implementation, we develop an adaptively constrained energy minimization approach to efficiently compute the solution. On simulated and real data from Human Connectome Project (HCP), we show that our method not only reconstructs sharp and clean FODs for the modeling of fiber crossings, but also generates reliable estimation of compartment parameters with great potential for clinical research of neurological diseases. In comparisons with publicly available DSI-Studio and BEDPOSTX of FSL, we demonstrate that our method reconstructs sharper FODs with more precise estimation of fiber directions. By applying probabilistic tractography to the FODs computed by our method, we show that more complete reconstruction of the corpus callosum bundle can be achieved. On a clinical, two-shell diffusion imaging data, we also demonstrate the feasibility of our method in analyzing white matter lesions.