Initial assessment of α-synuclein structure in platelets

Journal of Thrombosis and Thrombolysis - Over the last few years data from our group have indicated that α-synuclein is important in development of immune cells as well as potentially...     

Analysis of relative effectiveness of high-dose versus standard-dose influenza vaccines using an instrumental variable method

Background

Observational studies of the relative effectiveness of influenza vaccines are essential for public health decision making. Their estimates, however, are subject to bias due to unmeasured confounders. Instrumental variable (IV) methods can control for observed and unobserved confounders.

Impact of sampling rate on statistical significance for single subject fMRI connectivity analysis

A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity.     

Traumatic Cerebral Microbleeds in the Subacute Phase Are Practical and Early Predictors of Abnormality of the Normal-Appearing White Matter in the Chronic Phase

BACKGROUND AND PURPOSE:In the chronic phase after traumatic brain injury, DTI findings reflect WM integrity. DTI interpretation in the subacute phase is less straightforward. Microbleed evaluation with SWI is straightforward in both phases. We evaluated whether the microbleed concentration in the subacute phase is associated with the integrity of normal-appearing WM in the chronic phase.MATERIALS AND METHODS:Sixty of 211 consecutive patients 18 years of age or older admitted to our emergency department ≤24 hours after moderate to severe traumatic brain injury matched the selection criteria. Standardized 3T SWI, DTI, and T1WI were obtained 3 and 26 weeks after traumatic brain injury in 31 patients and 24 healthy volunteers. At baseline, microbleed concentrations were calculated. At follow-up, mean diffusivity (MD) was calculated in the normal-appearing WM in reference to the healthy volunteers (MD_z). Through linear regression, we evaluated the relation between microbleed concentration and MD_z in predefined structures.RESULTS:In the cerebral hemispheres, MD_z at follow-up was independently associated with the microbleed concentration at baseline (left: B = 38.4 [95% CI 7.5–69.3], P = .017; right: B = 26.3 [95% CI 5.7–47.0], P = .014). No such relation was demonstrated in the central brain. MD_z in the corpus callosum was independently associated with the microbleed concentration in the structures connected by WM tracts running through the corpus callosum (B = 20.0 [95% CI 24.8–75.2], P < .000). MD_z in the central brain was independently associated with the microbleed concentration in the cerebral hemispheres (B = 25.7 [95% CI 3.9–47.5], P = .023).CONCLUSIONS:SWI-assessed microbleeds in the subacute phase are associated with DTI-based WM integrity in the chronic phase. These associations are found both within regions and between functionally connected regions.

The yearly incidence of traumatic brain injury (TBI) is around 300 per 100,000 persons.^1,2 Almost three-quarters of patients with moderate to severe TBI have traumatic axonal injury (TAI).³ TAI is a major predictor of functional outcome,^4,5 but it is mostly invisible on CT and conventional MR imaging.^6,7DTI provides direct information on WM integrity and axonal injury.^5,8 However, DTI abnormalities are neither specific for TAI nor stable over time. Possibly because of the release of mass effect and edema and resorption of blood products, the effects of concomitant (non-TAI) injury on DTI are larger in the subacute than in the chronic phase (>3 months).^4,9,10 Therefore, DTI findings are expected to reflect TAI more specifically in the chronic than in the subacute phase (1 week–3 months).⁴ Even in regions without concomitant injury, the effects of TAI on DTI are dynamic, possibly caused by degeneration and neuroplastic changes.^6,11,12 These ongoing pathophysiological processes possibly contribute to the emerging evidence that DTI findings in the chronic phase are most closely associated with the eventual functional outcome.^12,13Although DTI provides valuable information, its acquisition, postprocessing, and interpretation in individual patients are demanding. SWI, with which microbleeds can be assessed with high sensitivity, is easier to interpret and implement in clinical practice. In contrast to DTI, SWI-detected traumatic microbleeds are more stable¹ except in the hyperacute^14,15 and the late chronic phases.¹⁶ Traumatic cerebral microbleeds are commonly interpreted as signs of TAI. However, the relation is not straightforward. On the one hand, nontraumatic microbleeds may be pre-existing. On the other hand, even if traumatic in origin, microbleeds represent traumatic vascular rather than axonal injury.¹⁷ Indeed, TAI is not invariably hemorrhagic.¹⁸ Additionally, microbleeds may secondarily develop after trauma through mechanisms unrelated to axonal injury, such as secondary ischemia.¹⁸DTI is not only affected by pathophysiological changes but also by susceptibility.¹⁹ The important susceptibility-effect generated by microbleeds renders the interpretation of DTI findings at the location of microbleeds complex. In the chronic phase, mean diffusivity (MD) is the most robust marker of WM integrity.^4,6 For these reasons, we evaluated MD in the normal-appearing WM.Much TAI research focuses on the corpus callosum because it is commonly involved in TAI^5,18,20 and it can reliably be evaluated with DTI,^5,21 and TAI in the corpus callosum is related to clinical prognosis.^6,20 The corpus callosum consists of densely packed WM tracts that structurally and functionally connect left- and right-sided brain structures.²² The integrity of the corpus callosum is associated with the integrity of the brain structures it connects.²³ Therefore, microbleeds in brain structures that are connected through the corpus callosum may affect callosal DTI findings. Analogous to this, microbleeds in the cerebral hemispheres, which exert their function through WM tracts traveling through the deep brain structures and brain stem,^24,25 may affect DTI findings in the WM of the latter.Our purpose was to evaluate whether the microbleed concentration in the subacute phase is associated with the integrity of normal-appearing WM in the chronic phase. We investigated this relation within the cerebral hemispheres and the central brain and between regions that are functionally connected by WM tracts.     

Pump Speed Optimization in Patients Implanted With the HeartMate 3 Device

Background

Pump speed optimization in patients implanted with a ventricular assist device represents a major challenge during the follow-up period. We present our findings on whether combined invasive hemodynamic ramp tests and cardiopulmonary exercise testing (CPX) can help optimize patient management.

Trade-offs between acquired and innate immune defenses in humans

Immune defenses provide resistance against infectious disease that is critical to survival. But immune defenses are costly, and limited resources allocated to immunity are not available for other physiological or developmental processes. We propose a framework for explaining variation in patterns of investment in two important subsystems of anti-pathogen defense: innate (non-specific) and acquired (specific) immunity. The developmental costs of acquired immunity are high, but the costs of maintenance and activation are relatively low. Innate immunity imposes lower upfront developmental costs, but higher operating costs. Innate defenses are mobilized quickly and are effective against novel pathogens. Acquired responses are less effective against novel exposures, but more effective against secondary exposures due to immunological memory. Based on their distinct profiles of costs and effectiveness, we propose that the balance of investment in innate versus acquired immunity is variable, and that this balance is optimized in response to local ecological conditions early in development. Nutritional abundance, high pathogen exposure and low signals of extrinsic mortality risk during sensitive periods of immune development should all favor relatively higher levels of investment in acquired immunity. Undernutrition, low pathogen exposure, and high mortality risk should favor innate immune defenses. The hypothesis provides a framework for organizing prior empirical research on the impact of developmental environments on innate and acquired immunity, and suggests promising directions for future research in human ecological immunology.