Large Time-Varying Parameter VARs

In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

Free Mobility and Taste-Homogeneity of Jurisdiction Structures

We consider a population of agents distributed on the unit interval. Agents form jurisdictions in order to provide a public facility and share its costs equally. This creates an incentive to form large entities. Individuals also incur a transportation cost depending on their location and that of the facility which makes small jurisdictions advantageous. We consider a fairly general class of distributions of agents and generalize previous versions of this model by allowing for non-linear transportation costs. We show that, in general, jurisdictions are not necessarily homogeneous. However, they are if facilities are always intraterritory and transportation costs are superadditive. Superadditivity can be weakened to strictly increasing and strictly concave when agents are uniformly distributed. Keywords: Consecutiveness, stratification, local public goods, coalition formation, country formation. JEL Classification: C71 (Cooperative Games), D71 (Social Choice; Clubs; Committees; Associations), H73 (Interjurisdictional Differentials and Their Effects).

Immunopathology of american cutaneous leishmaniasis. Modulation of MHC class II gene products by Keratinocytes before and after glucantime therapy

Epidermal changes from 32 cutaneous and 3 mucosal American leishmaniasis (ACL) active lesions were studied for HLA-DR, -DP expression, Lanerhans cells and lymphocyte infiltration. In addition to a DR and DQ positivity at the surface of the cells of the inflammatory infiltrate, a strong reaction for DR antigens was detected on keratinocytes. Hyperplasia of Langerhans cells was present in al cutaneous lesions and epidermis was infiltrated by T lymphocytes. When healed lesions of 14 of these subjects were re-biopsied 1 to 12 months after the end of pentavalent antimonial therapy, MHC class antigens could no longer be seen on keratinocytes. Our data represrn evidence for hhe reversibility of the abnormal HLA-DR expression by keratinocytes in ACL after Glucantime therapy or spontaneous scar formation, demonstrating that this expresion is restricted to the period of active lesions. The present findings can be regarded as an indirect evidence that keratinocytes may be involved in the immunopathology of ACL.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

Large Bayesian VARMAs

Vector Autoregressive Moving Average (VARMA) models have many theoretical properties which should make them popular among empirical macroeconomists. However, they are rarely used in practice due to over-parameterization concerns, difficulties in ensuring identification and computational challenges. With the growing interest in multivariate time series models of high dimension, these problems with VARMAs become even more acute, accounting for the dominance of VARs in this field. In this paper, we develop a Bayesian approach for inference in VARMAs which surmounts these problems. It jointly ensures identification and parsimony in the context of an efficient Markov chain Monte Carlo (MCMC) algorithm. We use this approach in a macroeconomic application involving up to twelve dependent variables. We find our algorithm to work successfully and provide insights beyond those provided by VARs.

Revisiting the specificity of the MHC class II transactivator CIITA in vivo.

CIITA is a master regulatory factor for the expression of MHC class II (MHC-II) and accessory genes involved in Ag presentation. It has recently been suggested that CIITA also regulates numerous other genes having diverse functions within and outside the immune system. To determine whether these genes are indeed relevant targets of CIITA in vivo, we studied their expression in CIITA-transgenic and CIITA-deficient mice. In contrast to the decisive control of MHC-II and related genes by CIITA, nine putative non-MHC target genes (Eif3s2, Kpna6, Tap1, Yars, Col1a2, Ctse, Ptprr, Tnfsf6 and Plxna1) were found to be CIITA independent in all cell types examined. Two other target genes, encoding IL-4 and IFN-gamma, were indeed found to be up- and down-regulated, respectively, in CIITA-transgenic CD4(+) T cells. However, there was no correlation between MHC-II expression and this Th2 bias at the level of individual transgenic T cells, indicating an indirect control by CIITA. These results show that MHC-II-restricted Ag presentation, and its indirect influences on T cells, remains the only pathway under direct control by CIITA in vivo. They also imply that precisely regulated MHC-II expression is essential for maintaining a proper Th1-Th2 balance.

Large-scale imatinib dose-concentration-effect study in CML patients under routine care conditions.

This observational study analyzed imatinib pharmacokinetics and response in 2478 chronic myeloid leukemia (CML) patients. Data were obtained through centralized therapeutic drug monitoring (TDM) at median treatment duration of ≥2 years. First, individual initial trough concentrations under 400mg/day imatinib starting dose were estimated. Second, their correlation (C^min(400mg)) with reported treatment response was verified. Low imatinib levels were predicted in young male patients and those receiving P-gp/CYP3A4 inducers. These patients had also lower response rates (7% lower 18-months MMR in male, 17% lower 1-year CCyR in young patients, Kaplan-Meier estimates). Time-point independent multivariate regression confirmed a correlation of individual C^min(400mg) with response and adverse events. Possibly due to confounding factors (e.g. dose modifications, patient selection bias), the relationship seemed however flatter than previously reported from prospective controlled studies. Nonetheless, these observational results strongly suggest that a subgroup of patients could benefit from early dosage optimization assisted by TDM, because of lower imatinib concentrations and lower response rates.

Selective abrogation of major histocompatibility complex class II expression on extrahematopoietic cells in mice lacking promoter IV of the class II transactivator gene.

MHC class II (MHCII) molecules play a pivotal role in the induction and regulation of immune responses. The transcriptional coactivator class II transactivator (CIITA) controls MHCII expression. The CIITA gene is regulated by three independent promoters (pI, pIII, pIV). We have generated pIV knockout mice. These mice exhibit selective abrogation of interferon (IFN)-gamma-induced MHCII expression on a wide variety of non-bone marrow-derived cells, including endothelia, epithelia, astrocytes, and fibroblasts. Constitutive MHCII expression on cortical thymic epithelial cells, and thus positive selection of CD4(+) T cells, is also abolished. In contrast, constitutive and inducible MHCII expression is unaffected on professional antigen-presenting cells, including B cells, dendritic cells, and IFN-gamma-activated cells of the macrophage lineage. pIV(-/-) mice have thus allowed precise definition of CIITA pIV usage in vivo. Moreover, they represent a unique animal model for studying the significance and contribution of MHCII-mediated antigen presentation by nonprofessional antigen-presenting cells in health and disease.

Stochastic demography and the neutral substitution rate in class-structured populations.

The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Mini-review: Specificity and expression of CIITA, the master regulator of MHC class II genes.

The class II transactivator (CIITA) has been referred to as the "master control factor" for the expression of MHC class II (MHCII) genes. As our knowledge on the specificity and function of CIITA grows, it is becoming increasingly evident that this sobriquet is entirely justified. First, despite extensive investigations, the major target genes of CIITA remain those implicated in the presentation of antigenic peptides by MHCII molecules. Although other putative target genes have been reported, the contribution of CIITA to their expression remains indirect, controversial or comparatively minor relative to its decisive role as a regulator of MHCII and related genes. Second, the most important parameter dictating MHCII expression is by far the expression pattern of the gene encoding CIITA (MHC2TA). The vast majority of signals that activate or repress MHCII expression under physiological and pathological situations converge on one or more of the three alternative promoters that drive transcription of the MHC2TA gene. In short, with respect to its specificity and its exquisitely controlled pattern of expression, CIITA is by a long stretch the single most important transcription factor for the regulation of genes required for MHCII-restricted antigen-presentation.

Direct analysis of peptide binding to cell-associated MHC class I molecules.

Exogenously added synthetic peptides can mimic endogenously produced antigenic peptides recognized on target cells by MHC class I-restricted cytolytic T lymphocytes. While it is assumed that exogenous peptides associate with class I molecules on the target cell surface, direct binding of peptides to cell-associated class I molecules has been difficult to demonstrate. Using a newly developed binding assay based on photoaffinity labeling, we have investigated the interaction of two antigenic peptides, known to be recognized in the context of H-2Kd or H-2Db, respectively, with 20 distinct class I alleles on living cells. None of the class I alleles tested, with the exception of H-2Kd or H-2Db, bound either of the peptides, thus demonstrating the exquisite specificity of peptide binding to class I molecules. Moreover, peptide binding to cell-associated H-2Kd was drastically reduced when metabolic energy, de novo protein synthesis or protein egress from the endoplasmic reticulum was inhibited. It is thus likely that exogenously added peptides do not associate with the bulk of class I molecules expressed at the cell surface, but rather bind to short-lived molecules devoid of endogenous peptides.