The transcriptional landscape of αβ T cell differentiation

αβT cell differentiation from thymic precursors is a complex process, explored here with the breadth of ImmGen expression datasets, analyzing how differentiation of thymic precursors gives rise to transcriptomes. After surprisingly gradual changes though early T commitment, transit through the CD4+CD8+ stage involves a shutdown or rare breadth, and correlating tightly with MYC. MHC-driven selection promotes a large-scale transcriptional reactivation. We identify distinct signatures that mark cells destined for positive selection versus apoptotic deletion. Differential expression of surprisingly few genes accompany CD4 or CD8 commitment, a similarity that carries through to peripheral T cells and their activation, revealed by mass cytometry phosphoproteomics. The novel transcripts identified as candidate mediators of key transitions help define the “known unknown” of thymocyte differentiation

A Systematic Literature Review Approach to Estimate the Therapeutic Index of Selected Immunosuppressant Drugs After Renal Transplantation:

Drugs that exhibit close margins between therapeutic and toxic blood concentrations are considered to have a narrow therapeutic index (NTI). The Food and Drug Administration has proposed that NTI drugs should have more stringent bioequivalence standards for approval of generic formulations. However, many immunosuppressant drugs do not have a well-defined therapeutic index (TI)

Simple Markov-Perfect Industry Dynamics

This paper develops a tractable model for the computational and empirical analysis of infinite-horizon oligopoly dynamics. It features aggregate demand uncertainty, sunk entry costs, stochastic idiosyncratic technological progress, and irreversible exit. We develop an algorithm for computing a symmetric Markov-perfect equilibrium quickly by finding the fixed points to a finite sequence of low-dimensional contraction mappings. If at most two heterogenous firms serve the industry, the result is the unique natural equilibrium in which a high profitability firm never exits leaving behind a low profitability competitor. With more than two firms, the algorithm always finds a natural equilibrium. We present a simple rule for checking ex post whether the calculated equilibrium is unique, and we illustrate the model's application by assessing how price collusion impacts consumer and total surplus in a market for a new product that requires costly development. The results confirm Fershtman and Pakes' (2000) finding that collusive pricing can increase consumer surplus by stimulating product development. A distinguishing feature of our analysis is that we are able to assess the results' robustness across hundreds of parameter values in only a few minutes on an off-the-shelf laptop computer

Total Factor Productivity Estimation: A Practical Review

This paper aims to provide empirical researchers with an overview of the methodological issues that arise when estimating total factor productivity at the establishment level, as well as of the existing techniques designed to overcome them. Apart from the well-known simultaneity and selection bias; attention is given to methodological issues that have emerged more recently and that are related to the use of deflated values of inputs and outputs (as opposed to quantities) in estimating productivity at the firm level, as well as to the endogeneity of product choice. Using data on single-product firms active in the Belgian food and beverages sector, I illustrate the biases introduced in traditional TFP estimates and discuss the perfirmance of a number of alternative estimators that have been proposed in the literature

The Local Role in Homeland Security

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73848/1/j.1540-5893.2005.00236.x.pd

Gene Expression during the Generation and Activation of Mouse Neutrophils: Implication of Novel Functional and Regulatory Pathways

As part of the Immunological Genome Project (ImmGen), gene expression was determined in unstimulated (circulating) mouse neutrophils and three populations of neutrophils activated in vivo, with comparison among these populations and to other leukocytes. Activation conditions included serum-transfer arthritis (mediated by immune complexes), thioglycollate-induced peritonitis, and uric acid-induced peritonitis. Neutrophils expressed fewer genes than any other leukocyte population studied in ImmGen, and down-regulation of genes related to translation was particularly striking. However, genes with expression relatively specific to neutrophils were also identified, particularly three genes of unknown function: Stfa2l1, Mrgpr2a and Mrgpr2b. Comparison of genes up-regulated in activated neutrophils led to several novel findings: increased expression of genes related to synthesis and use of glutathione and of genes related to uptake and metabolism of modified lipoproteins, particularly in neutrophils elicited by thioglycollate; increased expression of genes for transcription factors in the Nr4a family, only in neutrophils elicited by serum-transfer arthritis; and increased expression of genes important in synthesis of prostaglandins and response to leukotrienes, particularly in neutrophils elicited by uric acid. Up-regulation of genes related to apoptosis, response to microbial products, NFkB family members and their regulators, and MHC class II expression was also seen, in agreement with previous studies. A regulatory model developed from the ImmGen data was used to infer regulatory genes involved in the changes in gene expression during neutrophil activation. Among 64, mostly novel, regulatory genes predicted to influence these changes in gene expression, Irf5 was shown to be important for optimal secretion of IL-10, IP-10, MIP-1α, MIP-1β, and TNF-α by mouse neutrophils in vitro after stimulation through TLR9. This data-set and its analysis using the ImmGen regulatory model provide a basis for additional hypothesis-based research on the importance of changes in gene expression in neutrophils in different conditions

Gene expression during the generation and activation of mouse neutrophils: implication of novel functional and regulatory pathways.

As part of the Immunological Genome Project (ImmGen), gene expression was determined in unstimulated (circulating) mouse neutrophils and three populations of neutrophils activated in vivo, with comparison among these populations and to other leukocytes. Activation conditions included serum-transfer arthritis (mediated by immune complexes), thioglycollate-induced peritonitis, and uric acid-induced peritonitis. Neutrophils expressed fewer genes than any other leukocyte population studied in ImmGen, and down-regulation of genes related to translation was particularly striking. However, genes with expression relatively specific to neutrophils were also identified, particularly three genes of unknown function: Stfa2l1, Mrgpr2a and Mrgpr2b. Comparison of genes up-regulated in activated neutrophils led to several novel findings: increased expression of genes related to synthesis and use of glutathione and of genes related to uptake and metabolism of modified lipoproteins, particularly in neutrophils elicited by thioglycollate; increased expression of genes for transcription factors in the Nr4a family, only in neutrophils elicited by serum-transfer arthritis; and increased expression of genes important in synthesis of prostaglandins and response to leukotrienes, particularly in neutrophils elicited by uric acid. Up-regulation of genes related to apoptosis, response to microbial products, NFkB family members and their regulators, and MHC class II expression was also seen, in agreement with previous studies. A regulatory model developed from the ImmGen data was used to infer regulatory genes involved in the changes in gene expression during neutrophil activation. Among 64, mostly novel, regulatory genes predicted to influence these changes in gene expression, Irf5 was shown to be important for optimal secretion of IL-10, IP-10, MIP-1α, MIP-1β, and TNF-α by mouse neutrophils in vitro after stimulation through TLR9. This data-set and its analysis using the ImmGen regulatory model provide a basis for additional hypothesis-based research on the importance of changes in gene expression in neutrophils in different conditions