B7-H1 Blockade Increases Survival of Dysfunctional CD8+ T Cells and Confers Protection against Leishmania donovani Infections

Experimental visceral leishmaniasis (VL) represents an exquisite model to study CD8+ T cell responses in a context of chronic inflammation and antigen persistence, since it is characterized by chronic infection in the spleen and CD8+ T cells are required for the development of protective immunity. However, antigen-specific CD8+ T cell responses in VL have so far not been studied, due to the absence of any defined Leishmania-specific CD8+ T cell epitopes. In this study, transgenic Leishmania donovani parasites expressing ovalbumin were used to characterize the development, function, and fate of Leishmania-specific CD8+ T cell responses. Here we show that L. donovani parasites evade CD8+ T cell responses by limiting their expansion and inducing functional exhaustion and cell death. Dysfunctional CD8+ T cells could be partially rescued by in vivo B7-H1 blockade, which increased CD8+ T cell survival but failed to restore cytokine production. Nevertheless, B7-H1 blockade significantly reduced the splenic parasite burden. These findings could be exploited for the design of new strategies for immunotherapeutic interventions against VL

Searching for stochastic gravitational waves using data from the two colocated LIGO Hanford detectors

Searches for a stochastic gravitational-wave background (SGWB) using terrestrial detectors typically involve cross-correlating data from pairs of detectors. The sensitivity of such cross-correlation analyses depends, among other things, on the separation between the two detectors: the smaller the separation, the better the sensitivity. Hence, a colocated detector pair is more sensitive to a gravitational-wave background than a noncolocated detector pair. However, colocated detectors are also expected to suffer from correlated noise from instrumental and environmental effects that could contaminate the measurement of the background. Hence, methods to identify and mitigate the effects of correlated noise are necessary to achieve the potential increase in sensitivity of colocated detectors. Here we report on the first SGWB analysis using the two LIGO Hanford detectors and address the complications arising from correlated environmental noise. We apply correlated noise identification and mitigation techniques to data taken by the two LIGO Hanford detectors, H1 and H2, during LIGO’s fifth science run. At low frequencies, 40–460 Hz, we are unable to sufficiently mitigate the correlated noise to a level where we may confidently measure or bound the stochastic gravitational-wave signal. However, at high frequencies, 460–1000 Hz, these techniques are sufficient to set a 95% confidence level upper limit on the gravitational-wave energy density of Ω(f) < 7.7 × 10[superscript -4](f/900  Hz)[superscript 3], which improves on the previous upper limit by a factor of ~180. In doing so, we demonstrate techniques that will be useful for future searches using advanced detectors, where correlated noise (e.g., from global magnetic fields) may affect even widely separated detectors.National Science Foundation (U.S.)United States. National Aeronautics and Space AdministrationCarnegie TrustDavid & Lucile Packard FoundationAlfred P. Sloan Foundatio

Incidental Findings on Brain Magnetic Resonance Imaging From 1000 Asymptomatic Volunteers

CONTEXT Previous reports have discussed incidental disease found on brain magnetic resonance imaging (MRI) scans that had been requested for an unrelated clinical concern or symptom, resulting in a selection bias for disease. However, the prevalence of unexpected abnormalities has not been studied in a healthy population. OBJECTIVE To evaluate the prevalence of incidental findings on brain MRI scans obtained for a healthy, asymptomatic population without selection bias. DESIGN, SETTING, AND PARTICIPANTS Retrospective analysis of brain MRI scans obtained between May 17, 1996, and July 25, 1997, from 1000 volunteers who participated as control subjects for various research protocols at the National Institutes of Health. All participants (age range, 3-83 years; 54.6% male) were determined to be healthy and asymptomatic by physician examination and participant history. MAIN OUTCOME MEASURE Prevalence of abnormalities on brain MRI by category of finding (no referral necessary, routine referral, urgent referral [within 1 week of study], and immediate referral [within 1 to several days of study]). RESULTS Eighty-two percent of the MRI results were normal. Of the 18% demonstrating incidental abnormal findings, 15.1% required no referral; 1.8%, routine referral; 1.1%, urgent referral; and 0%, immediate referral. In subjects grouped for urgent referral, 2 confirmed primary brain tumors (and a possible but unconfirmed third) were found, demonstrating a prevalence of at least 0.2%. CONCLUSION Asymptomatic subjects present with a variety of abnormalities, providing valuable information on disease prevalence in a presumed healthy population. A small percentage of these findings require urgent medical attention and/or additional studies

A Methodology and Implementation for Annotating Digital Images for Context-appropriate Use in an Academic Health Care Environment

Use of digital medical images has become common over the last several years, coincident with the release of inexpensive, mega-pixel quality digital cameras and the transition to digital radiology operation by hospitals. One problem that clinicians, medical educators, and basic scientists encounter when handling images is the difficulty of using business and graphic arts commercial-off-the-shelf (COTS) software in multicontext authoring and interactive teaching environments. The authors investigated and developed software-supported methodologies to help clinicians, medical educators, and basic scientists become more efficient and effective in their digital imaging environments. The software that the authors developed provides the ability to annotate images based on a multispecialty methodology for annotation and visual knowledge representation. This annotation methodology is designed by consensus, with contributions from the authors and physicians, medical educators, and basic scientists in the Departments of Radiology, Neurobiology and Anatomy, Dermatology, and Ophthalmology at the University of Utah. The annotation methodology functions as a foundation for creating, using, reusing, and extending dynamic annotations in a context-appropriate, interactive digital environment. The annotation methodology supports the authoring process as well as output and presentation mechanisms. The annotation methodology is the foundation for a Windows implementation that allows annotated elements to be represented as structured eXtensible Markup Language and stored separate from the image(s)