Sleep-Disordered Breathing in Michigan: A Practice Pattern Survey

Objectives: This survey sought to determine whether self-professed sleep specialists in the State of Michigan show practice variations in the diagnosis and management of sleep-disordered breathing (SDB), and whether such variations occur between pulmonologists and neurologists. Methods: Questionnaires on practice volume and patterns during the prior 12 months were mailed to physician members of the Michigan Sleep Disorders Association ( n = 119); 67 were completed and returned. Results: Respondents reported that they personally saw a median of 8 new patients each week for suspected SDB; estimates were that 86% of these patients were eventually confirmed to have SDB. Most patients (82%) had laboratory-based polysomnography after an initial clinic evaluation, and most (69%) of those treated for SDB received continuous positive airway pressure. However, practice patterns differed substantially among respondents, even when the analysis was limited to the 42 who reported board certification by the American Board of Sleep Medicine. For example, among all surveyed practices the likelihood that suspected SDB would be evaluated with a split-night diagnostic and treatment polysomnogram varied from 0 to 90%. The likelihood of SDB treatment with bilevel positive airway pressure varied from 0 to 50%, with automatically titrating devices from 0 to 100%, with surgery from 0 to 100% (0 to 50% among certified practitioners), and with oral appliances from 0 to 20%. The practice patterns of pulmonologists and neurologists did not differ significantly. Conclusion: Approaches to SDB vary widely in Michigan, though not according to clinician background in pulmonary medicine or neurology. A patient’s experience, in both assessment and treatment, could differ substantially based on which clinician is consulted.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47959/1/11325_2003_Article_95.pd

Heterogeneity assessment of functional T cell avidity.

The potency of cellular immune responses strongly depends on T cell avidity to antigen. Yet, functional avidity measurements are rarely performed in patients, mainly due to the technical challenges of characterizing heterogeneous T cells. The mean functional T cell avidity can be determined by the IFN-γ Elispot assay, with titrated amounts of peptide. Using this assay, we developed a method revealing the heterogeneity of functional avidity, represented by the steepness/hillslope of the peptide titration curve, documented by proof of principle experiments and mathematical modeling. Our data show that not only natural polyclonal CD8 T cell populations from cancer patients, but also monoclonal T cells differ strongly in their heterogeneity of functional avidity. Interestingly, clones and polyclonal cells displayed comparable ranges of heterogeneity. We conclude that besides the mean functional avidity, it is feasible and useful to determine its heterogeneity (hillslope) for characterizing T cell responses in basic research and patient investigation

Can Non-lytic CD8+T Cells Drive HIV-1 Escape?

The CD8+ T cell effector mechanisms that mediate control of HIV-1 and SIV infections remain poorly understood. Recent work suggests that the mechanism may be primarily non-lytic. This is in apparent conflict with the observation that SIV and HIV-1 variants that escape CD8+ T cell surveillance are frequently selected. Whilst it is clear that a variant that has escaped a lytic response can have a fitness advantage compared to the wild-type, it is less obvious that this holds in the face of non-lytic control where both wild-type and variant infected cells would be affected by soluble factors. In particular, the high motility of T cells in lymphoid tissue would be expected to rapidly destroy local effects making selection of escape variants by non-lytic responses unlikely. The observation of frequent HIV-1 and SIV escape poses a number of questions. Most importantly, is the consistent observation of viral escape proof that HIV-1- and SIV-specific CD8+ T cells lyse infected cells or can this also be the result of non-lytic control? Additionally, the rate at which a variant strain escapes a lytic CD8+ T cell response is related to the strength of the response. Is the same relationship true for a non-lytic response? Finally, the potential anti-viral control mediated by non-lytic mechanisms compared to lytic mechanisms is unknown. These questions cannot be addressed with current experimental techniques nor with the standard mathematical models. Instead we have developed a 3D cellular automaton model of HIV-1 which captures spatial and temporal dynamics. The model reproduces in vivo HIV-1 dynamics at the cellular and population level. Using this model we demonstrate that non-lytic effector mechanisms can select for escape variants but that outgrowth of the variant is slower and less frequent than from a lytic response so that non-lytic responses can potentially offer more durable control