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Because of its anabolic effects on muscle, testosterone is being explored as a function-promoting anabolic therapy for functional limitations associated with aging; however, concerns about testosterone's adverse effects on prostate have inspired efforts to develop strategies that selectively increase muscle mass while sparing the prostate. Testosterone's promyogenic effects are mediated through upregulation of follistatin. We show here that the administration of recombinant follistatin (rFst) increased muscle mass in mice, but had no effect on prostate mass. Consistent with the results of rFst administration, follistatin transgenic mice with constitutively elevated follistatin levels displayed greater muscle mass than controls, but had similar prostate weights. To elucidate signaling pathways regulated differentially by testosterone and rFst in prostate and muscle, we performed microarray analysis of mRNAs from prostate and levator ani of castrated male mice treated with vehicle, testosterone, or rFst. Testosterone and rFst shared the regulation of many transcripts in levator ani; however, in prostate, 593 transcripts in several growth-promoting pathways were differentially expressed after testosterone treatment, while rFst showed a negligible effect with only 9 transcripts differentially expressed. Among pathways that were differentially responsive to testosterone in prostate, we identified ornithine decarboxylase (Odc1), an enzyme in polyamine biosynthesis, as a testosterone-responsive gene that is unresponsive to rFst. Accordingly, we administered testosterone with and without α-difluoromethylornithine (DFMO), an Odc1 inhibitor, to castrated mice. DFMO selectively blocked testosterone's effects on prostate, but did not affect testosterone's anabolic effects on muscle. Co-administration of testosterone and Odc1 inhibitor presents a novel therapeutic strategy for prostate-sparing anabolic therapy.

Alternative splicing (AS) allows increased diversity and orthogonal regulation of the transcriptional products of mammalian genomes. To assess the distribution and variation of alternative splicing across cell lineages of the immune system, we comprehensively analyzed RNA sequencing and microarray data generated by the Immunological Genome Project Consortium. AS is pervasive: 60% of genes showed frequent AS isoforms in T or B lymphocytes, with 7,599 previously unreported isoforms. Distinct cell specificity was observed, with differential exon skipping in 5% of genes otherwise coexpressed in both B and T cells. The distribution of isoforms was mostly all or none, suggesting on/off switching as a frequent mode of AS regulation in lymphocytes. From the identification of differential exon use in the microarray data, clustering of exon inclusion/exclusion patterns across all Immunological Genome Project cell types showed that ∼70% of AS exons are distributed along a common pattern linked to lineage differentiation and cell cycling. Other AS events distinguished myeloid from lymphoid cells or affected only a small set of exons without clear lineage specificity (e.g., Ptprc). Computational analysis predicted specific associations between AS exons and splicing regulators, which were verified by detection of the hnRPLL/Ptprc connection.

The stochastic state point process filter (SSPPF) and steepest descent point process filter (SDPPF) are adaptive filter algorithms for state estimation from point process observations that have been used to track neural receptive field plasticity and to decode the representations of biological signals in ensemble neural spiking activity. The SSPPF and SDPPF are constructed using, respectively, Gaussian and steepest descent approximations to the standard Bayes and Chapman-Kolmogorov (BCK) system of filter equations. To extend these approaches for constructing point process adaptive filters, we develop sequential Monte Carlo (SMC) approximations to the BCK equations in which the SSPPF and SDPPF serve as the proposal densities. We term the two new SMC point process filters SMC-PPFs and SMC-PPFD, respectively. We illustrate the new filter algorithms by decoding the wind stimulus magnitude from simulated neural spiking activity in the cricket cercal system. The SMC-PPFs and SMC-PPFD provide more accurate state estimates at low number of particles than a conventional bootstrap SMC filter algorithm in which the state transition probability density is the proposal density. We also use the SMC-PPFs algorithm to track the temporal evolution of a spatial receptive field of a rat hippocampal neuron recorded while the animal foraged in an open environment. Our results suggest an approach for constructing point process adaptive filters using SMC methods. Index Terms--Adaptive filtering, hidden Markov models, point processes, sequential Monte Carlo, state estimation.

FoxP3+ T regulatory (Treg) cells are central elements of immunologic tolerance. They are abundant in many tumors, where they restrict potentially favorable antitumor responses. We used a three-pronged strategy to identify genes related to the presence and function of Tregs in the tumor microenvironment. Gene expression profiles were generated from tumor-infiltrating Tregs (TITRs) of both human and mouse tumors and were compared with those of Tregs of lymphoid organs or normal tissues from the same individuals. A computational deconvolution of wholetumor datasets from the Cancer Genome Atlas (TCGA) was performed to identify transcripts specifically associated with Tregs across thousands of tumors from different stages and locations. We identified a set of TITR-differential transcripts with striking reproducibility between tumor types in mice, between mice and humans, and between different human patients spanning tumor stages. Many of the TITR-preferential transcripts were shared with "tissue Tregs" residing in nonlymphoid tissues, but a tumorpreferential segment could be identified. Many of these TITR signature transcripts were confirmed by mining of TCGA datasets, which also brought forth transcript modules likely representing the parenchymal attraction of, or response to, tumor Tregs. Importantly, the TITR signature included several genes encoding effective targets of tumor immunotherapy. A number of other targets were validated by CRISPR-based gene inactivation in mouse Tregs. These results confirm the validity of the signature, generating a wealth of leads for understanding the role of Tregs in tumor progression and identifying potential targets for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Retinoic acid receptor-related orphan nuclear receptor γ (RORγ) orchestrates a pro-inflammatory gene expression programme in multiple lymphocyte lineages including T helper type 17 (Th17) cells, γδ T cells, innate lymphoid cells and lymphoid tissue inducer cells. There is compelling evidence that RORγ-expressing cells are relevant targets for therapeutic intervention in the treatment of autoimmune and inflammatory diseases. Unlike Th17 cells, where RORγ expression is induced under specific pro-inflammatory conditions, γδ T cells and other innate-like immune cells express RORγ in the steady state. Small molecule mediated disruption of RORγ function in cells with pre-existing RORγ transcriptional complexes represents a significant and challenging pharmacological hurdle. We present data demonstrating that a novel, selective and potent small molecule RORγ inhibitor can block the RORγ-dependent gene expression programme in both Th17 cells and RORγ-expressing γδ T cells as well as a disease-relevant subset of human RORγ-expressing memory T cells. Importantly, systemic administration of this inhibitor in vivo limits pathology in an innate lymphocyte-driven mouse model of psoriasis. [ABSTRACT FROM AUTHOR]

Foxp3+ regulatory T cells (Tregs) originate in the thymus, but the Treg phenotype can also be induced in peripheral lymphoid organs or in vitro by stimulation of conventional CD4+ T cells with IL-2 and TGF-β. There have been divergent reports on the suppressive capacity of these TGF-Treg cells. We find that TGF-Tregs derived from diabetes-prone NOD mice, although expressing normal Foxp3 levels, are uniquely defective in suppressive activity, whereas TGF-Tregs from control strains (B6g7) or ex vivo Tregs from NOD mice all function normally. Most Treg-typical transcripts were shared by NOD or B6g7 TGF-Tregs, except for a small group of differentially expressed genes, including genes relevant for suppressive activity (Lrrc32, Ctla4, and Cd73). Many of these transcripts form a coregulated cluster in a broader analysis of T-cell differentiation. The defect does not map to idd3 or idd5 regions. Whereas Treg cells from NOD mice are normal in spleen and lymph nodes, the NOD defect is observed in locations that have been tied to pathogenesis of diabetes (small intestine lamina propria and pancreatic lymph node). Thus, a genetic defect uniquely affects a specific Treg subpopulation in NOD mice, in a manner consistent with a role in determining diabetes susceptibility. [ABSTRACT FROM AUTHOR]