41 research outputs found

    Sleep oscillation-specific associations with Alzheimer’s disease CSF biomarkers : novel roles for sleep spindles and tau

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    Background: Based on associations between sleep spindles, cognition, and sleep-dependent memory processing, here we evaluated potential relationships between levels of CSF Aβ42, P-tau, and T-tau with sleep spindle density and other biophysical properties of sleep spindles in a sample of cognitively normal elderly individuals. Methods: One-night in-lab nocturnal polysomnography (NPSG) and morning to early afternoon CSF collection were performed to measure CSF Aβ42, P-tau and T-tau. Seven days of actigraphy were collected to assess habitual total sleep time. Results: Spindle density during NREM stage 2 (N2) sleep was negatively correlated with CSF Aβ42, P-tau and T-tau. From the three, CSF T-tau was the most significantly associated with spindle density, after adjusting for age, sex and ApoE4. Spindle duration, count and fast spindle density were also negatively correlated with T-tau levels. Sleep duration and other measures of sleep quality were not correlated with spindle characteristics and did not modify the associations between sleep spindle characteristics and the CSF biomarkers of AD. Conclusions: Reduced spindles during N2 sleep may represent an early dysfunction related to tau, possibly reflecting axonal damage or altered neuronal tau secretion, rendering it a potentially novel biomarker for early neuronal dysfunction. Given their putative role in memory consolidation and neuroplasticity, sleep spindles may represent a mechanism by which tau impairs memory consolidation, as well as a possible target for therapeutic interventions in cognitive decline

    Chicken caecal enterotypes in indigenous Kadaknath and commercial Cobb chicken lines are associated with Campylobacter abundance and influenced by farming practices

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    Identifying farming practices that decrease susceptibility to infectious diseases and optimise food conversion efficiency is valuable for chicken welfare and productivity, the environment, and public health. Enterotypes can be used to define microbial community phenotypes that have differential, potentially significant impacts on gut health. In this study, we delineated enterotypes by analysing the microbiomes of 300 indigenous Kadaknath and 300 commercial Cobb400 broiler chickens raised across 60 farms in western India. Using a compositional data approach, we identified three distinct enterotypes: PA1 (n=290), PA2 (n=142) and PA3 (n=67). PA1 and PA2 clustered more closely with each other than with PA3, however, PA2 had significantly lower alpha diversity than PA1. PA1 had a high Firmicutes: Bacteroides ratio, was dominated by Faecalibacterium and had a higher abundance of Prevotellamassilia than other enterotypes. PA2 was characterised by its low alpha diversity, a high abundance of the common taxa Phascolarctobacterium A and Phocaeicola dorei and a significantly higher Campylobacter abundance than PA1. PA3 had the highest Bacteroidota abundance of the three enterotypes and was defined by high prevalence of lower abundance taxa such as CAG-831 and Mucispirillum schaedleri. Network analysis showed that all enterotypes have different proportions of competing Firmicutes-dominant and Bacteroidota-dominant guilds. Random Forest Modelling using defined farm characteristics was predictive for enterotype. Factors affecting enterotype include whether farms were open, enclosed or caged, the location of farms, whether visitors were allowed inside, the number of people in contact with the chickens, chicken line, the presence of dogs and whether flock thinning took place. This study suggests that enterotypes are influenced by farming practices, hence modification of practices could potentially be used to reduce the burden of zoonotic pathogens such as Campylobacter

    Obstructive Sleep Apnea Severity Affects Amyloid Burden in Cognitively Normal Elderly. A Longitudinal Study

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    Rationale: Recent evidence suggests that obstructive sleep apnea (OSA) may be a risk factor for developing mild cognitive impairment and Alzheimer’s disease. However, how sleep apnea affects longitudinal risk for Alzheimer’s disease is less well understood. Objectives: To test the hypothesis that there is an association between severity of OSA and longitudinal increase in amyloid burden in cognitively normal elderly. Methods: Data were derived from a 2-year prospective longitudinal study that sampled community-dwelling healthy cognitively normal elderly. Subjects were healthy volunteers between the ages of 55 and 90, were nondepressed, and had a consensus clinical diagnosis of cognitively normal. Cerebrospinal fluid amyloid β was measured using ELISA. Subjects received Pittsburgh compound B positron emission tomography scans following standardized procedures. Monitoring of OSA was completed using a home sleep recording device. Measurements and Main Results: We found that severity of OSA indices (AHIall [F1,88 = 4.26; P < 0.05] and AHI4% [F1,87 = 4.36; P < 0.05]) were associated with annual rate of change of cerebrospinal fluid amyloid β42 using linear regression after adjusting for age, sex, body mass index, and apolipoprotein E4 status. AHIall and AHI4% were not associated with increases in ADPiB-mask (Alzheimer’s disease vulnerable regions of interest Pittsburg compound B positron emission tomography mask) most likely because of the small sample size, although there was a trend for AHIall (F1,28 = 2.96, P = 0.09; and F1,28 = 2.32, not significant, respectively). Conclusions: In a sample of cognitively normal elderly, OSA was associated with markers of increased amyloid burden over the 2-year follow-up. Sleep fragmentation and/or intermittent hypoxia from OSA are likely candidate mechanisms. If confirmed, clinical interventions for OSA may be useful in preventing amyloid build-up in cognitively normal elderly

    Convex Denoising using Non-Convex Tight Frame Regularization

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    Stable Principal Component Pursuit via Convex Analysis

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    Convex 1-D Total Variation Denoising with Non-convex Regularization

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