Aluminium in the human brain

Abstract  

An inevitable consequence of humans living in the Aluminium Age is the presence of aluminium in the brain. This non-essential, neurotoxic metal gains entry to the brain throughout all stages of human development, from the foetus through to old age. Human exposure to myriad forms of this ubiquitous and omnipresent metal makes its presence in the brain inevitable, while the structure and physiology of the brain makes it particularly susceptible to the accumulation of aluminium with age. In spite of aluminium’s complete lack of biological essentiality, it actually participates avidly in brain biochemistry and substitutes for essential metals in critical biochemical processes. The degree to which such substitutions are disruptive and are manifested as biological effects will depend upon the biological availability of aluminium in any particular physical or chemical compartment, and will under all circumstances be exerting an energy load on the brain. In short, the brain must expend energy in its ‘unconscious’ response to an exposure to biologically available aluminium. There are many examples where ‘biological effect’ has resulted in aluminium-induced neurotoxicity and most potently in conditions that have resulted in an aluminium-associated encephalopathy. However, since aluminium is non-essential and not required by the brain, its biological availability will only rarely achieve such levels of acuity, and it is more pertinent to consider and investigate the brain’s response to much lower though sustained levels of biologically reactive aluminium. This is the level of exposure that defines the putative role of aluminium in chronic neurodegenerative disease and, though thoroughly investigated in numerous animal models, the chronic toxicity of aluminium has yet to be addressed experimentally in humans. A feasible test of the ‘aluminium hypothesis’, whereby aluminium in the human brain is implicated in chronic neurodegenerative disease, would be to reduce the brain’s aluminium load to the lowest possible level by non-invasive means. The simplest way that this aim can be fulfilled in a significant and relevant population is by facilitating the urinary excretion of aluminium through the regular drinking of a silicic acid-rich mineral water over an extended time period. This will lower the body and brain burden of aluminium, and by doing so will test whether brain aluminium contributes significantly to chronic neurodegenerative diseases such as Alzheimer’s and Parkinson’s.     

Surface-amplified ligand disorder in CdSe quantum dots determined by electron and coherent vibrational spectroscopies

This Article reports measurements of the intra- and intermolecular ordering of tight-binding octylphosphonate ligands on the surface of colloidal CdSe quantum dots (QDs) within solid state films, and the dependence of this order on the size of the QDs. The order of the organic ligands, as probed by vibrational sum frequency generation (SFG) spectroscopy, decreases as the radius of the QDs decreases; this decrease is correlated with a decrease in the order of underlying Cd(2+), as detected by X-ray photoelectron spectroscopy (XPS) line width measurements, for radii of the QDs, R > 2.4 nm, and is independent of the disorder of the Cd(2+) for R < 2.4 nm. We believe that, for R < 2.4, the decreasing order of the ligands with decreasing size is due to an increase in the curvature of the QD surfaces. Disorder in the Cd(2+) results from the presence of a shell of Cd(2+)-surfactant complexes that form during synthesis, so this work demonstrates the possibility for chemical control over molecular order within films of colloidal QDs by changing the surfactant mixture.     

Extracting 2D IR frequency-frequency correlation functions from two component systems

The center line slope (CLS) method is often used to extract the frequency-frequency correlation function (FFCF) from 2D IR spectra to delineate dynamics and to identify homogeneous and inhomogeneous contributions to the absorption line shape of a system. While the CLS method is extremely efficient, quite accurate, and immune to many experimental artifacts, it has only been developed and properly applied to systems that have a single vibrational band, or to systems of two species that have spectrally resolved absorption bands. In many cases, the constituent spectra of multiple component systems overlap and cannot be distinguished from each other. This situation creates ambiguity when analyzing 2D IR spectra because dynamics for different species cannot be separated. Here a mathematical formulation is presented that extends the CLS method for a system consisting of two components (chemically distinct uncoupled oscillators). In a single component system, the CLS corresponds to the time-dependent portion of the normalized FFCF. This is not the case for a two component system, as a much more complicated expression arises. The CLS method yields a series of peak locations originating from slices taken through the 2D spectra. The slope through these peak locations yields the CLS value for the 2D spectra at a given T(w). We derive analytically that for two component systems, the peak location of the system can be decomposed into a weighted combination of the peak locations of the constituent spectra. The weighting depends upon the fractional contribution of each species at each wavelength and also on the vibrational lifetimes of both components. It is found that an unknown FFCF for one species can be determined as long as the peak locations (referred to as center line data) of one of the components are known, as well as the vibrational lifetimes, absorption spectra, and other spectral information for both components. This situation can arise when a second species is introduced into a well characterized single species system. An example is a system in which water exists in bulk form and also as water interacting with an interface. An algorithm is presented for back-calculating the unknown FFCF of the second component. The accuracy of the algorithm is tested with a variety of model cases in which all components are initially known. The algorithm successfully reproduces the FFCF for the second component within a reasonable degree of error.     

Trapping a labile adduct formed between an ortho-quinone methide and 2'-deoxycytidine

Selective oxidation by bis[(trifluoroacetoxy)iodo]benzene (BTI) provides an effective trap for quenching adducts formed reversibly between dC and an ortho-quinone methide (QM) under physiological conditions. A model adduct generated by 4-methyl-o-QM and 2'-deoxycytidine is rapidly converted by intramolecular cyclization and loss of aromaticity to a characteristic product for quantifying QM alkylation. However, BTI induces a surprising rearrangement driven by overoxidation of a derivative lacking an alkyl substituent at the 4-position of the QM.     

New candidaspongiolides, tedanolide analogues that selectively inhibit melanoma cell growth

Extracts of the sponge genus Candidaspongia showed selective cytotoxicity toward melanoma cells in the NCI 60-cell-line screen. Continued investigation of the Candidaspongia sp. extracts led to the isolation of three new tedanolide analogues, precandidaspongiolides A (1) and B (2) and candidaspongiolide B (4), as well as candidaspongiolide A (3) and tedanolide (5). Semisynthetic derivatives were also generated to develop SAR. Candidaspongiolides A/B were the most potent and showed low nanomolar activity against several melanoma cell lines.     

Optimization of silver nanoparticles for surface enhanced Raman spectroscopy of structurally diverse analytes using visible and near-infrared excitation

Several experimental parameters affecting surface enhanced Raman (SER) signals using 488, 785 and 1064 nm excitation for eight diverse analytes are reported. Citrate reduced silver colloids having average diameters ranging from 40 ± 10 to 100 ± 20 nm were synthesized. The nanoparticles were characterized by transmission electron microscopy, dynamic light scattering and absorbance spectrophotometry before and after inducing nanoparticle aggregation with 0.99% v/v 0.5 M magnesium chloride. The nanoparticle aggregates and SERS signal were stable between 30 and 90 minutes after inducing aggregation. For the analytes 4-mercaptopyridine, 4-methylthiobenzoic acid and the dipeptide phenylalanine-cysteine using all three excitation wavelengths, the highest surface area adjusted SER signal was obtained using 70 ± 20 nm nanoparticles, which generated 290 ± 40 nm aggregates with the addition of magnesium chloride. The decrease in the SER signal using non-optimum colloids was 12 to 42% using 488 nm excitation and larger decreases in signal, up to 92%, were observed using near infrared excitation wavelengths. In contrast, pyridine, benzoic acid, and phenylalanine required 220 ± 30 nm aggregates for the highest SER signal with 785 or 1064 nm excitation, but larger aggregates (290 ± 40 nm) were required with 488 nm excitation. The optimum experimental conditions measured with the small molecule analytes held for a 10 amino acid peptide and hemoglobin. Reproducible SERS measurements with 2 to 9% RSD have been obtained by considering nanoparticle size, aggregation conditions, excitation wavelength and the nature of the analyte-silver interaction.     

Zwitterionic-type hydrophilic interaction nano-liquid chromatography of complex and high mannose glycans coupled with electrospray ionisation high resolution time of flight mass spectrometry

In this study we describe a new method for rapid and sensitive analysis of reduced high mannose and complex glycans using zwitterionic-type hydrophilic interaction nano-liquid chromatography (nano ZIC-HILIC, 75 μm I.D.×150 mm) coupled with high resolution nanoelectrospray ionisation time of flight mass spectrometry (nano ESI-TOF-MS). The retention of neutral glycans increases with increasing molecular weight and is higher for high mannose glycans than for complex-type glycans. The selectivity of ZIC-HILIC for sialylated glycans differs from that for the neutral glycans and is believed to involve electrostatic repulsion; therefore, charged glycans are eluted earlier than neutral glycans with comparable molecular weight. Due to the improved sensitivity achieved by employing a ZIC-HILIC nano-column, a range of less common complex glycans has been studied and the high resolution mass spectrometry enabled confirmation of glycan composition for the proposed structures. Good sensitivity for glycans was achieved without prior fluorescent labelling, and the time of the analysis was significantly reduced compared to the separation of glycans on a conventional-size column. The proposed method offers a fast and sensitive approach for glycan profiling applied to analysis of biopharmaceuticals.     

Quantum mechanical embedding theory based on a unique embedding potential

We remove the nonuniqueness of the embedding potential that exists in most previous quantum mechanical embedding schemes by letting the environment and embedded region share a common embedding (interaction) potential. To efficiently solve for the embedding potential, an optimized effective potential method is derived. This embedding potential, which eschews use of approximate kinetic energy density functionals, is then used to describe the environment while a correlated wavefunction (CW) treatment of the embedded region is employed. We first demonstrate the accuracy of this new embedded CW (ECW) method by calculating the van der Waals binding energy curve between a hydrogen molecule and a hydrogen chain. We then examine the prototypical adsorption of CO on a metal surface, here the Cu(111) surface. In addition to obtaining proper site ordering (top site most stable) and binding energies within this theory, the ECW exhibits dramatic changes in the p-character of the CO 4σ and 5σ orbitals upon adsorption that agree very well with x-ray emission spectra, providing further validation of the theory. Finally, we generalize our embedding theory to spin-polarized quantum systems and discuss the connection between our theory and partition density functional theory.     

Prospect for characterizing interacting soft colloidal structures using spin-echo small angle neutron scattering

Spin-echo small angle neutron scattering (SESANS) provides a new experimental tool for structural investigation. Due to the action of spin-echo encoding, SESANS measures a spatial correlation function in real space, as opposed to the structure factor S(Q), I(Q), in momentum (Q) space measured by conventional small angle neutron scattering. To establish the usefulness of SESANS in structural characterization, particularly for interacting colloidal suspensions, we have previously conducted a theoretical study of the SESANS correlation functions for model systems consisting of particles with uniform density profiles [X. Li, C.-Y. Shew, Y. Liu, R. Pynn, E. Liu, K. W. Herwig, G. S. Smith, J. L. Robertson, and W.-R. Chen J. Chem. Phys. 132, 174509 (2010)]. Within the same framework, we explore in the present paper the prospect of using SESANS to investigate the structural characteristics of colloidal systems consisting of particles with nonuniform intraparticle mass distribution. As an example, a Gaussian model of interacting soft colloids is used to investigate the manifestation of structural softness in a SESANS measurement. The exploration shows a characteristically different SESANS correlation function for interacting soft colloids, in comparison to that of a uniform hard sphere system. The difference arises from the Abel transform imbedded in the mathematical formalism bridging the SESANS spectra and the spatial autocorrelation function.     

Testing variations of the GW approximation on strongly correlated transition metal oxides: hematite (α-Fe2O3) as a benchmark

Quantitative characterization of low-lying excited electronic states in materials is critical for the development of solar energy conversion materials. The many-body Green's function method known as the GW approximation (GWA) directly probes states corresponding to photoemission and inverse photoemission experiments, thereby determining the associated band structure. Several versions of the GW approximation with different levels of self-consistency exist in the field. While the GWA based on density functional theory (DFT) works well for conventional semiconductors, less is known about its reliability for strongly correlated semiconducting materials. Here we present a systematic study of the GWA using hematite (α-Fe(2)O(3)) as the benchmark material. We analyze its performance in terms of the calculated photoemission/inverse photoemission band gaps, densities of states, and dielectric functions. Overall, a non-self-consistent G(0)W(0) using input from DFT+U theory produces physical observables in best agreement with experiments.