Water Exchange Rate across the Blood-Brain Barrier Is Associated with CSF Amyloid-β 42 in Healthy Older Adults

INTRODUCTION: We tested if water exchange across the blood-brain barrier (BBB), estimated with a noninvasive magnetic resonance imaging (MRI) technique, is associated with cerebrospinal fluid (CSF) biomarkers of Alzheimer\u27s disease (AD) and neuropsychological function. METHODS: Forty cognitively normal older adults (67–86 years old) were scanned with diffusion‐prepared, arterial spin labeling (DP‐ASL), which estimates water exchange rate across the BBB (kw). Participants also underwent CSF draw and neuropsychological testing. Multiple linear regression models were run with kw as a predictor of CSF concentrations and neuropsychological scores. RESULTS: In multiple brain regions, BBB kw was positively associated with CSF amyloid beta (Aβ)42 concentration levels. BBB kw was only moderately associated with neuropsychological performance. DISCUSSION: Our results suggest that low water exchange rate across the BBB is associated with low CSF Aβ42 concentration. These findings suggest that kw may be a promising noninvasive indicator of BBB Aβ clearance functions, a possibility which should be further tested in future research

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative.

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients’ predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm’s pa- rameters and data-related modeling choices are also both crucial and challenging

Kynurenine 3-Monooxygenase Inhibition in Blood Ameliorates Neurodegeneration

SummaryMetabolites in the kynurenine pathway, generated by tryptophan degradation, are thought to play an important role in neurodegenerative disorders, including Alzheimer's and Huntington's diseases. In these disorders, glutamate receptor-mediated excitotoxicity and free radical formation have been correlated with decreased levels of the neuroprotective metabolite kynurenic acid. Here, we describe the synthesis and characterization of JM6, a small-molecule prodrug inhibitor of kynurenine 3-monooxygenase (KMO). Chronic oral administration of JM6 inhibits KMO in the blood, increasing kynurenic acid levels and reducing extracellular glutamate in the brain. In a transgenic mouse model of Alzheimer's disease, JM6 prevents spatial memory deficits, anxiety-related behavior, and synaptic loss. JM6 also extends life span, prevents synaptic loss, and decreases microglial activation in a mouse model of Huntington's disease. These findings support a critical link between tryptophan metabolism in the blood and neurodegeneration, and they provide a foundation for treatment of neurodegenerative diseases

Burden of disease attributable to suboptimal diet, metabolic risks, and low physical activity in Ethiopia and comparison with Eastern sub-Saharan African countries, 1990-2015: findings from the Global Burden of Disease Study 2015

Background: Twelve of the 17 Sustainable Development Goals (SDGs) are related to malnutrition (both under- and overnutrition), other behavioral, and metabolic risk factors. However, comparative evidence on the impact of behavioral and metabolic risk factors on disease burden is limited in sub-Saharan Africa (SSA), including Ethiopia. Using data from the Global Burden of Disease (GBD) Study, we assessed mortality and disability-adjusted life years (DALYs) attributable to child and maternal undernutrition (CMU), dietary risks, metabolic risks and low physical activity for Ethiopia. The results were compared with 14 other Eastern SSA countries. Methods: Databases from GBD 2015, that consist of data from 1990 to 2015, were used. A comparative risk assessment approach was utilized to estimate the burden of disease attributable to CMU, dietary risks, metabolic risks and low physical activity. Exposure levels of the risk factors were estimated using spatiotemporal Gaussian process regression (ST-GPR) and Bayesian meta-regression models. Results: In 2015, there were 58,783 [95% uncertainty interval (UI): 43,653-76,020] or 8.9% [95% UI: 6.1-12.5] estimated all-cause deaths attributable to CMU, 66,269 [95% UI: 39,367-106,512] or 9.7% [95% UI: 7.4-12.3] to dietary risks, 105,057 [95% UI: 66,167-157,071] or 15.4% [95% UI: 12.8-17.6] to metabolic risks and 5808 [95% UI: 3449-9359] or 0.9% [95% UI: 0.6-1.1]to low physical activity in Ethiopia. While the age-adjusted proportion of all-cause mortality attributable to CMU decreased significantly between 1990 and 2015, it increased from 10.8% [95% UI: 8.8-13.3] to 14.5% [95% UI: 11.7-18.0] for dietary risks and from 17.0% [95% UI: 15.4-18.7] to 24.2% [95% UI: 22.2-26.1] for metabolic risks. In 2015, Ethiopia ranked among the top four countries (of 15 Eastern SSA countries) in terms of mortality and DALYs based on the age-standardized proportion of disease attributable to dietary risks and metabolic risks. Conclusions: In Ethiopia, while there was a decline in mortality and DALYs attributable to CMU over the last two and half decades, the burden attributable to dietary and metabolic risks have increased during the same period. Lifestyle and metabolic risks of NCDs require more attention by the primary health care system of in the country

Terrestrial Very-Long-Baseline Atom Interferometry:Workshop Summary

This document presents a summary of the 2023 Terrestrial Very-Long-Baseline Atom Interferometry Workshop hosted by CERN. The workshop brought together experts from around the world to discuss the exciting developments in large-scale atom interferometer (AI) prototypes and their potential for detecting ultralight dark matter and gravitational waves. The primary objective of the workshop was to lay the groundwork for an international TVLBAI proto-collaboration. This collaboration aims to unite researchers from different institutions to strategize and secure funding for terrestrial large-scale AI projects. The ultimate goal is to create a roadmap detailing the design and technology choices for one or more km-scale detectors, which will be operational in the mid-2030s. The key sections of this report present the physics case and technical challenges, together with a comprehensive overview of the discussions at the workshop together with the main conclusions

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level