Altered Heparan Sulfate in Ageing and Dementia: a Potential Axis for the Dysregulation of BACE-1 in Alzheimer's disease

Alzheimer’s disease (AD) is characterised by amyloid plaques composed of amyloid-beta (Aβ), the cleavage product of the amyloid precursor protein (APP) by the protease beta-secretase (BACE- 1). Heparan sulfate (HS) inhibits BACE-1 and holds potential as a new drug discovery target; in vivo HS may act as a brake on the generation of Aß via regulation of BACE-1. Previous work has identified the sulfate moieties in HS as key determinants in the efficacy of BACE-1 inhibition. Structural changes in HS are known to occur with ageing and we hypothesised that these changes could result in reduced BACE-1 inhibition and ultimately elevated production of Aβ. Strong anion exchange chromatography was used to assess disaccharide composition of HS from AD (n=20) and age-matched control (n=15) brain tissue. TaqMan® array profiling of HS-related genes was also carried out to explore expression levels of HS-related genes that may be responsible for downstream HS structural changes. HS purified from AD and age-matched control samples was assessed for its ability to inhibit BACE-1 using FRET-based BACE-1 activity assays and finally, manipulation of endogenous HS in HEKSweAPP cells with RNAi was carried out to explore the possibility of modulating generation of the toxic Aβ species. HS from AD tissue was found to carry a significantly decreased proportion of the di-sulfated ΔUA-GlcNS(6S) disaccharide vs. controls (p<0.01) and increased levels of the lesser-sulfated ΔUAGlcNAc( 6S) unit vs. controls (p<0.05). Furthermore, significantly more total HS was present within control brain tissue (122.3μg/100mg) vs. AD (78.6μg/100mg) (p<0.01). TaqMan® array analysis revealed significant alteration in expression of HS biosynthetic genes with AD including upregulation of HS6ST1 (p<0.05) and a strong trend for down regulation of HS6ST3, coupled with up regulation of SULF1. These changes may go some way to explain changes in the level of sulfation of HS particularly, 6-O sulfation, as observed by structural analysis. Most noticeably, BACE-1 activity assays revealed a significant reduction of BACE-1 inhibition efficacy by HS from AD patients (p<0.05). In addition, knockdown of SULF1 in HEKSweAPP cells, which would be expected to elevate 6-O sulfation, generated a significant reduction in Aß. Our observation that AD brain HS contains fewer di-sulfated ΔUA-GlcNS(6S) disaccharides, alongside observed upstream gene expression changes, would be consistent with a less sulfated HS chain with reduced ability to inhibit BACE-1 thus generating more Aß as observed in AD. The observed reduction in BACE-1 inhibition efficacy by HS with AD confirms our hypothesis that structural changes in HS may contribute to modulating AD pathogenesis in patients. Finally, these studies support the idea that HS-based therapeutics might provide the basis for novel disease modifying drugs that could prove beneficial in future efforts to treat an underlying cause of AD

The Core of the Participatory Budgeting Problem

In participatory budgeting, communities collectively decide on the allocation of public tax dollars for local public projects. In this work, we consider the question of fairly aggregating the preferences of community members to determine an allocation of funds to projects. This problem is different from standard fair resource allocation because of public goods: The allocated goods benefit all users simultaneously. Fairness is crucial in participatory decision making, since generating equitable outcomes is an important goal of these processes. We argue that the classic game theoretic notion of core captures fairness in the setting. To compute the core, we first develop a novel characterization of a public goods market equilibrium called the Lindahl equilibrium, which is always a core solution. We then provide the first (to our knowledge) polynomial time algorithm for computing such an equilibrium for a broad set of utility functions; our algorithm also generalizes (in a non-trivial way) the well-known concept of proportional fairness. We use our theoretical insights to perform experiments on real participatory budgeting voting data. We empirically show that the core can be efficiently computed for utility functions that naturally model our practical setting, and examine the relation of the core with the familiar welfare objective. Finally, we address concerns of incentives and mechanism design by developing a randomized approximately dominant-strategy truthful mechanism building on the exponential mechanism from differential privacy

A general approach to physical realization of unambiguous quantum-state discrimination

We present a general scheme to realize the POVMs for the unambiguous discrimination of quantum states. For any set of pure states it enables us to set up a feasible linear optical circuit to perform their optimal discrimination, if they are prepared as single-photon states. An example of unknown states discrimination is discussed as the illustration of the general scheme.Comment: 9 pages, Latex fil

Human COQ9 Rescues a coq9 Yeast Mutant by Enhancing Coenzyme Q Biosynthesis from 4-Hydroxybenzoic Acid and Stabilizing the CoQ-Synthome

Coq9 is required for the stability of a mitochondrial multi-subunit complex, termed the CoQ-synthome, and the deamination step of Q intermediates that derive from para-aminobenzoic acid (pABA) in yeast. In human, mutations in the COQ9 gene cause neonatal-onset primary Q10 deficiency. In this study, we determined whether expression of human COQ9 could complement yeast coq9 point or null mutants. We found that expression of human COQ9 rescues the growth of the temperature-sensitive yeast mutant, coq9-ts19, on a non-fermentable carbon source and increases the content of Q6, by enhancing Q biosynthesis from 4-hydroxybenzoic acid (4HB). To study the mechanism for the rescue by human COQ9, we determined the steady-state levels of yeast Coq polypeptides in the mitochondria of the temperature-sensitive yeast coq9 mutant expressing human COQ9. We show that the expression of human COQ9 significantly increased steady-state levels of yeast Coq4, Coq6, Coq7, and Coq9 at permissive temperature. Human COQ9 polypeptide levels persisted at non-permissive temperature. A small amount of the human COQ9 co-purified with tagged Coq6, Coq6-CNAP, indicating that human COQ9 interacts with the yeast Q-biosynthetic complex. These findings suggest that human COQ9 rescues the yeast coq9 temperature-sensitive mutant by stabilizing the CoQ-synthome and increasing Q biosynthesis from 4HB. This finding provides a powerful approach to studying the function of human COQ9 using yeast as a model

Processing Spatial Keyword Query as a Top-k Aggregation Query

We examine the spatial keyword search problem to retrieve objects of interest that are ranked based on both their spatial proximity to the query location as well as the textual relevance of the object’s keywords. Existing solutions for the problem are based on either using a combination of textual and spatial indexes or using specialized hybrid indexes that integrate the indexing of both textual and spatial attribute values. In this paper, we propose a new approach that is based on modeling the problem as a top-k aggregation problem which enables the design of a scalable and efficient solution that is based on the ubiquitous inverted list index. Our performance study demonstrates that our approach outperforms the state-of-theart hybrid methods by a wide margin

Deep Learning Discovery of Demographic Biomarkers in Echocardiography

Deep learning has been shown to accurately assess 'hidden' phenotypes and predict biomarkers from medical imaging beyond traditional clinician interpretation of medical imaging. Given the black box nature of artificial intelligence (AI) models, caution should be exercised in applying models to healthcare as prediction tasks might be short-cut by differences in demographics across disease and patient populations. Using large echocardiography datasets from two healthcare systems, we test whether it is possible to predict age, race, and sex from cardiac ultrasound images using deep learning algorithms and assess the impact of varying confounding variables. We trained video-based convolutional neural networks to predict age, sex, and race. We found that deep learning models were able to identify age and sex, while unable to reliably predict race. Without considering confounding differences between categories, the AI model predicted sex with an AUC of 0.85 (95% CI 0.84 - 0.86), age with a mean absolute error of 9.12 years (95% CI 9.00 - 9.25), and race with AUCs ranging from 0.63 - 0.71. When predicting race, we show that tuning the proportion of a confounding variable (sex) in the training data significantly impacts model AUC (ranging from 0.57 to 0.84), while in training a sex prediction model, tuning a confounder (race) did not substantially change AUC (0.81 - 0.83). This suggests a significant proportion of the model's performance on predicting race could come from confounding features being detected by AI. Further work remains to identify the particular imaging features that associate with demographic information and to better understand the risks of demographic identification in medical AI as it pertains to potentially perpetuating bias and disparities.Comment: 2450 words, 2 figure, 3 table

The impact of nutritional quality and gut bacteria on the fitness of Bactrocera minax (Diptera: Tephritidae)

To examine how nutritional quality and resident gut bacteria interplay in improving the fitness of an oligophagous fruit fly, Bactrocera minax, artificial sucrose diets and full diets (sucrose, tryptone and yeast extract) were fed to flies with and without antibiotic supplementation. Furthermore, Klebsiella oxytoca and Citrobacter freundii were supplemented to sucroseonly diets. Flies were maintained in the laboratory and the fitness parameters, male and female longevity, number of copulations and female fecundity, were recorded. Full diet without bacterial depletion significantly increased fecundity and copulation. In the absence of gut bacteria, flies fed with full diets had significantly decreased mean fecundity and copulation rate. Flies that were fed with sucrose diet had a very low copulation rate and produced no eggs. Diet type and the presence of bacteria did not have any effect on the average longevity ofmale and female flies. Bacterial supplementation in sucrose diets did not improve any of the measured parameters. The results demonstrate that gut bacteria interact with diet to influence mating and reproduction in B. minax. Symbiotic bacteria significantly and positively impact reproduction in B. minax; however, their impact can only be fully realized when the flies are fed with a nutritionally complete diet

Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically "learn" models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? In this work, we investigate existing algorithms for learning probabilistic models for model checking, propose an evolution-based approach for better controlling the degree of generalization and conduct an empirical study in order to answer the questions. One of our findings is that the effectiveness of learning may sometimes be limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP