Putting the coke in coke

The story of cocaine: from royalty to popular refresher... Surprising as it sounds, Coca Cola gets its name from one of its original ingredients - cocaine. And although the drug's now illegal, this wasn't always the case. But how did it become popular, what led to its downfall, and how does Coca Cola come in to it?

Magnetic coupling in trinuclear partial cubane copper(II) complexes with a hydroxo bridging core and peripheral phenoxo bridges from NNO donor Schiff base ligands

Three new trinuclear copper(II) complexes, [(CuL1)(3)(mu(3)-OH)](ClO4)(2)center dot 3.75H(2)O (1), [(CuL2)(3)(mu(3)-OH)](ClO4)(2) (2) and [(CuL3)(3)(mu(3)-OH)](BF4)(2)center dot 0.5CH(3)CN (3) have been synthesized from three tridentate Schiff bases HL1, HL2, and HL3 (HL1 = 2-[(2-amino-ethylimino)-methyl]-phenol, HL2 = 2-[(2-methylamino-ethylimino)-methyl]-phenol and HL3 = 2-[1-(2-dimethylamino-ethylimino)-ethyl]-phenol). The complexes are characterized by single-crystal X-ray diffraction analyses, IR, UV-vis and EPR spectroscopy, and variable-temperature magnetic measurements. All the compounds contain a partial cubane [Cu3O4] core consisting of the trinuclear unit [(CuL)(3)(mu(3)-OH)](2+) together with perchlorate or fluoroborate anions. In each of the complexes, the three copper atoms are five-coordinated with a distorted square-pyramidal geometry except in complex 1, in which one of the Cu-II ions of the trinuclear unit is six-coordinate being in addition weakly coordinated to one of the perchlorate anions. Variable-temperature magnetic measurements and EPR spectra indicate an antiferromagnetic exchange coupling between the CuII ions of complexes 1 and 2, while this turned out to be ferromagnetic for complex 3. Experimental values have been fitted according to an isotropic exchange Hamiltonian. Calculations based on Density Functional Theory have also been performed in order to estimate the exchange coupling constants in these three complexes. Both sets of values indicate similar trends and specially calculated J values establish a magneto-structural correlation between them and the Cu-O-Cu bond angle, in that the coupling is more ferromagnetic for smaller bond angle values.

A dynamic model of neurovascular coupling: Implications for blood vessel dilation and constriction

Neurovascular coupling in response to stimulation of the rat barrel cortex was investigated using concurrent multichannel electrophysiology and laser Doppler flowmetry. The data were used to build a linear dynamic model relating neural activity to blood flow. Local field potential time series were subject to current source density analysis, and the time series of a layer IV sink of the barrel cortex was used as the input to the model. The model output was the time series of the changes in regional cerebral blood flow (CBF). We show that this model can provide excellent fit of the CBF responses for stimulus durations of up to 16 s. The structure of the model consisted of two coupled components representing vascular dilation and constriction. The complex temporal characteristics of the CBF time series were reproduced by the relatively simple balance of these two components. We show that the impulse response obtained under the 16-s duration stimulation condition generalised to provide a good prediction to the data from the shorter duration stimulation conditions. Furthermore, by optimising three out of the total of nine model parameters, the variability in the data can be well accounted for over a wide range of stimulus conditions. By establishing linearity, classic system analysis methods can be used to generate and explore a range of equivalent model structures (e.g., feed-forward or feedback) to guide the experimental investigation of the control of vascular dilation and constriction following stimulation.

Model estimation of cerebral hemodynamics between blood flow and volume changes: A data-based modeling approach

It is well known that there is a dynamic relationship between cerebral blood flow (CBF) and cerebral blood volume (CBV). With increasing applications of functional MRI, where the blood oxygen-level-dependent signals are recorded, the understanding and accurate modeling of the hemodynamic relationship between CBF and CBV becomes increasingly important. This study presents an empirical and data-based modeling framework for model identification from CBF and CBV experimental data. It is shown that the relationship between the changes in CBF and CBV can be described using a parsimonious autoregressive with exogenous input model structure. It is observed that neither the ordinary least-squares (LS) method nor the classical total least-squares (TLS) method can produce accurate estimates from the original noisy CBF and CBV data. A regularized total least-squares (RTLS) method is thus introduced and extended to solve such an error-in-the-variables problem. Quantitative results show that the RTLS method works very well on the noisy CBF and CBV data. Finally, a combination of RTLS with a filtering method can lead to a parsimonious but very effective model that can characterize the relationship between the changes in CBF and CBV.

Reduced-order modeling of light transport in tissue for real-time monitoring of brain hemodynamics using diffuse optical tomography

This paper proposes a new reconstruction method for diffuse optical tomography using reduced-order models of light transport in tissue. The models, which directly map optical tissue parameters to optical flux measurements at the detector locations, are derived based on data generated by numerical simulation of a reference model. The reconstruction algorithm based on the reduced-order models is a few orders of magnitude faster than the one based on a finite element approximation on a fine mesh incorporating a priori anatomical information acquired by magnetic resonance imaging. We demonstrate the accuracy and speed of the approach using a phantom experiment and through numerical simulation of brain activation in a rat's head. The applicability of the approach for real-time monitoring of brain hemodynamics is demonstrated through a hypercapnic experiment. We show that our results agree with the expected physiological changes and with results of a similar experimental study. However, by using our approach, a three-dimensional tomographic reconstruction can be performed in ∼3  s per time point instead of the 1 to 2 h it takes when using the conventional finite element modeling approach