Gradients of delay of reinforcement and discriminative stimuli during the delay interval.

Thesis (Ph.D.)--Boston UniversityThis experiment was designed to investigate the relationship of delay interval behavior, food panel pressing, on the performance of an antecedent response, lever pressing. Albino rats were trained in a modified Skinner box with a hinged food cup panel and a removable lever. The delay of reinforcement gradient for lever pressing at 4, 10, 30, and 50 seconds delay was determined under two different delay conditions. In Condition 1, the stimulus conditions, sDl (light on), remained constant throughout the delay interval. Under Condition 11, the stimulus conditions sDl remained constant up to the end of the presented delay interval, and a discrete auditory stimulus, sD2 , signalled the end of this interval. Under both conditions 1 and 11, the presentation of the terminal primary reinforcement was contingent on a panel press response. The animals of both groups were initially trained on a discrimination in which panel responses were reinforced at the end of the delay interval in the presence of sDl, Condition 1, or sD and the stimulus trace of sD2 (Condition 11). Panel responses were never reinforced in the absence of these stimuli, a condition which prevailed on an average of 3 minutes (VI3) between trials. Following this training, the onset of the delay interval sD1 was made contingent on the occurrence of a lever press response. Several predictions were made employing primarily the concepts of the relationship of the discriminative sD and secondary reinforcing (sR) properties of a stimulus, and also the relationship of panel pressing behavior during the delay interval and lever pressing. [TRUNCATED

Attachment and Entry of Chlamydia Have Distinct Requirements for Host Protein Disulfide Isomerase

Chlamydia is an obligate intracellular pathogen that causes a wide range of diseases in humans. Attachment and entry are key processes in infectivity and subsequent pathogenesis of Chlamydia, yet the mechanisms governing these interactions are unknown. It was recently shown that a cell line, CHO6, that is resistant to attachment, and thus infectivity, of multiple Chlamydia species has a defect in protein disulfide isomerase (PDI) N–terminal signal sequence processing. Ectopic expression of PDI in CHO6 cells led to restoration of Chlamydia attachment and infectivity; however, the mechanism leading to this recovery was not ascertained. To advance our understanding of the role of PDI in Chlamydia infection, we used RNA interference to establish that cellular PDI is essential for bacterial attachment to cells, making PDI the only host protein identified as necessary for attachment of multiple species of Chlamydia. Genetic complementation and PDI-specific inhibitors were used to determine that cell surface PDI enzymatic activity is required for bacterial entry into cells, but enzymatic function was not required for bacterial attachment. We further determined that it is a PDI-mediated reduction at the cell surface that triggers bacterial uptake. While PDI is necessary for Chlamydia attachment to cells, the bacteria do not appear to utilize plasma membrane–associated PDI as a receptor, suggesting that Chlamydia binds a cell surface protein that requires structural association with PDI. Our findings demonstrate that PDI has two essential and independent roles in the process of chlamydial infectivity: it is structurally required for chlamydial attachment, and the thiol-mediated oxido-reductive function of PDI is necessary for entry

Brief history of agricultural systems modeling

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the “next generation” models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure thatwe avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statisticalmodels based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for themajor advances in agricultural systems science that are needed for the next generation ofmodels, databases, knowledge products and decision support systems. The lessons fromhistory should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models