The Effects of BACE and Its Targets on Age-related Seizures in \u3cem\u3eDrosophila\u3c/em\u3e

The presence of Beta-Amyloid (Aβ) containing plaques in the brain is one of the histological hallmarks of Alzheimer’s Disease. β-secretase (BACE) is the enzyme responsible for producing this Aβ cleavage product and has also been shown to affect myelination and general neuronal activity. Observations from geriatric medicine suggest that there may be an increase in seizure activity associated with Alzheimer’s Disease. Preliminary data suggests that both over- and under-expression of BACE contributes to mechanically stimulated seizures in Drosophila. In vertebrates, seizure activity has been correlated with many factors including Neuregulin production and Na+ Pump activity. Both of these proteins have also been shown to require BACE activity for proper function. However, their roles in BACE related seizures remains unknown. Here we are following up on this preliminary study and exploring the roles of Vein (the Drosophila homolog of Neuregulin) and Numb (a negative regulator of the Notch Pathway). We have confirmed that any perturbation in dBACE (Drosophila BACE) levels causes a significant increase in age related seizures, suggesting that that BACE levels must be tightly regulated. In addition an increase of Vein levels also cause a dramatic increase in seizure amounts and duration suggesting that BACE, at least in part, is acting through this signaling pathway. Understanding which BACE related signaling pathways are responsible for age related seizure activity can lead to new treatments which will hopefully slow the progression of Alzheimer’s and other related neurodegenerative diseases

Numerical Palindromes: The Next Generation

Several types of numerical palindromes have appeared in Word Ways (Susan Thorpe, Numerical Palindromes: Part 1 in Nov 1996 and Rex Gooch, Numerical Palindromes: Part 2 in Feb 1997). However, I believe the current exercise is the first to make two or more numerically-palindromic \u27offspring\u27 from the letters of a numerically-palindromic \u27parent\u27. In other words, numerical palindromes beget numerical palindromes

The Ill-Posed Problem in Growth Empirics

A problem encountered in growth empirics is that the number of explanatory variables is large compared to the number of observations. This makes it impossible to condition on all regressors when determining if a variable is important. We investigate methods used to resolve this problem: Extreme bounds, Sala-i-Martin’s test, BACE, general-to-specific, minimum t-statistics, BIC and AIC. We prove that the problem in general is ill-posed and that the existing methods are inconsistent. We propose a test and apply it to determine if "good policy" increases the effectiveness of foreign aid on growth. The test rejects inference regarding good policy.AIC; BACE; BIC; extreme bounds; general-to-specific; ill-posed inverse problem; robustness

Cost of capital, returns and leverage: empirical evidence from the S&P 500

Expected Returns, Actual Returns, and Leverage: Empirical Analysis of the S&P 500, 2006-2015 ABSTRACT Purpose The theoretical construct of the weighted average cost of capital (WACC), which uses an expected equity return, suggests that lower WACC, often facilitated by use of debt, should result in commensurate returns to shareholders, and higher shareholder value, that is if management is adept at investing in projects yielding returns at or above the WACC. In other words, finding good projects ought to be made easier by a lower hurdle rate on investment, thus translating into returns comparable to or above the WACC, and higher valuations. Is this actually the case? Does the relation between WACC, actual returns, and financial leverage also hold, as predicted, where higher leverage should result in lower WACC, and higher actual returns? Methodology This brief study looks at performance and valuation (total equity market returns to shareholders, and market values, on an annual basis) of S&P 500 companies over a recent ten year period (2006-2015), versus valuations implied by price to book ratios and WACC based on firm leverage. We compare theoretical valuations with the actual, and note variations year on year, but greater similarity over a longer time frame. Regression analysis is performed on these shareholder returns and valuations versus equity cost of these companies as computed using the Capital Asset Pricing Model (CAPM) and Bloomberg data. Another regression is run on WACC versus financial leverage (net debt to market capitalisation) for the same sample. Findings The study finds mixed evidence that expected return on equity, regarded as a benchmark for shareholder returns, was commensurate with actual returns and valuations on average over the time frame. R squared is low, but the analysis has significance. While the S&P 500 earned an annual total shareholder return of 11.8% over the period. and average cost of equity was 10.8%, there is a negative relation between values predicted by WACC and the actual ones. Implications This result leads us to look for other explanations as to why this should be. These include management capabilities, target capital structure and time horizon. We make suggestions for further research, encompassing different and wider samples

Three-Dimensionally Embedded Graph Convolutional Network (3DGCN) for Molecule Interpretation

We present a three-dimensional graph convolutional network (3DGCN), which predicts molecular properties and biochemical activities, based on 3D molecular graph. In the 3DGCN, graph convolution is unified with learning operations on the vector to handle the spatial information from molecular topology. The 3DGCN model exhibits significantly higher performance on various tasks compared with other deep-learning models, and has the ability of generalizing a given conformer to targeted features regardless of its rotations in the 3D space. More significantly, our model also can distinguish the 3D rotations of a molecule and predict the target value, depending upon the rotation degree, in the protein-ligand docking problem, when trained with orientation-dependent datasets. The rotation distinguishability of 3DGCN, along with rotation equivariance, provides a key milestone in the implementation of three-dimensionality to the field of deep-learning chemistry that solves challenging biochemical problems.Comment: 39 pages, 14 figures, 5 table

Influence of conformational fluctuations on enzymatic activity: modelling the functional motion of beta-secretase

Considerable insight into the functional activity of proteins and enzymes can be obtained by studying the low-energy conformational distortions that the biopolymer can sustain. We carry out the characterization of these large scale structural changes for a protein of considerable pharmaceutical interest, the human $\beta$-secretase. Starting from the crystallographic structure of the protein, we use the recently introduced beta-Gaussian model to identify, with negligible computational expenditure, the most significant distortion occurring in thermal equilibrium and the associated time scales. The application of this strategy allows to gain considerable insight into the putative functional movements and, furthermore, helps to identify a handful of key regions in the protein which have an important mechanical influence on the enzymatic activity despite being spatially distant from the active site. The results obtained within the Gaussian model are validated through an extensive comparison against an all-atom Molecular Dynamics simulation.Comment: To be published in a special issue of J. Phys.: Cond. Mat. (Bedlewo Workshop

Axonal amyloid precursor protein and its fragments undergo somatodendritic endocytosis and processing.

Deposition of potentially neurotoxic Aβ fragments derived from amyloid precursor protein (APP) at synapses may be a key contributor to Alzheimer's disease. However, the location(s) of proteolytic processing and subsequent secretion of APP fragments from highly compartmentalized, euploid neurons that express APP and processing enzymes at normal levels is not well understood. To probe the behavior of endogenous APP, particularly in human neurons, we developed a system using neurons differentiated from human embryonic stem cells, cultured in microfluidic devices, to enable direct biochemical measurements from axons. Using human or mouse neurons in these devices, we measured levels of Aβ, sAPPα, and sAPPβ secreted solely from axons. We found that a majority of the fragments secreted from axons were processed in the soma, and many were dependent on somatic endocytosis for axonal secretion. We also observed that APP and the β-site APP cleaving enzyme were, for the most part, not dependent on endocytosis for axonal entry. These data establish that axonal entry and secretion of APP and its proteolytic processing products traverse different pathways in the somatodendritic compartment before axonal entry