Density and cross-sectional areas of axons in the olfactory tract in control subjects and Alzheimer's disease:an image analysis study

Objective. Using an image analysis system to determine whether there is loss of axons in the olfactory tract (OT) in Alzheimer’s disease (AD). Design. A retrospective neuropathological study. Patients Nine control patients and eight clinically and pathologically verified AD cases. Measurements and Results. There was a reduction in axon density in AD compared with control subjects in the central and peripheral regions of the tract. Axonal loss was mainly of axons with smaller (<2.99 µm2) myelinated cross-sectional areas. Conclusions. The data suggest significant degeneration of axons within the OT involving the smaller sized axons. Loss of axons in the OT is likely to be secondary to pathological changes originating within the parahippocampal gyrus rather than to a pathogen spreading into the brain via the olfactory pathways.

Mixture density networks

Minimization of a sum-of-squares or cross-entropy error function leads to network outputs which approximate the conditional averages of the target data, conditioned on the input vector. For classifications problems, with a suitably chosen target coding scheme, these averages represent the posterior probabilities of class membership, and so can be regarded as optimal. For problems involving the prediction of continuous variables, however, the conditional averages provide only a very limited description of the properties of the target variables. This is particularly true for problems in which the mapping to be learned is multi-valued, as often arises in the solution of inverse problems, since the average of several correct target values is not necessarily itself a correct value. In order to obtain a complete description of the data, for the purposes of predicting the outputs corresponding to new input vectors, we must model the conditional probability distribution of the target data, again conditioned on the input vector. In this paper we introduce a new class of network models obtained by combining a conventional neural network with a mixture density model. The complete system is called a Mixture Density Network, and can in principle represent arbitrary conditional probability distributions in the same way that a conventional neural network can represent arbitrary functions. We demonstrate the effectiveness of Mixture Density Networks using both a toy problem and a problem involving robot inverse kinematics.

Comparison of estimates and calculations of risk of coronary heart disease by doctors and nurses using different calculation tools in general practice: cross sectional study

OBJECTIVE: To assess the effect of using different risk calculation tools on how general practitioners and practice nurses evaluate the risk of coronary heart disease with clinical data routinely available in patients' records. DESIGN: Subjective estimates of the risk of coronary heart disease and results of four different methods of calculation of risk were compared with each other and a reference standard that had been calculated with the Framingham equation; calculations were based on a sample of patients' records, randomly selected from groups at risk of coronary heart disease. SETTING: General practices in central England. PARTICIPANTS: 18 general practitioners and 18 practice nurses. MAIN OUTCOME MEASURES: Agreement of results of risk estimation and risk calculation with reference calculation; agreement of general practitioners with practice nurses; sensitivity and specificity of the different methods of risk calculation to detect patients at high or low risk of coronary heart disease. RESULTS: Only a minority of patients' records contained all of the risk factors required for the formal calculation of the risk of coronary heart disease (concentrations of high density lipoprotein (HDL) cholesterol were present in only 21%). Agreement of risk calculations with the reference standard was moderate (kappa=0.33-0.65 for practice nurses and 0.33 to 0.65 for general practitioners, depending on calculation tool), showing a trend for underestimation of risk. Moderate agreement was seen between the risks calculated by general practitioners and practice nurses for the same patients (kappa=0.47 to 0.58). The British charts gave the most sensitive results for risk of coronary heart disease (practice nurses 79%, general practitioners 80%), and it also gave the most specific results for practice nurses (100%), whereas the Sheffield table was the most specific method for general practitioners (89%). CONCLUSIONS: Routine calculation of the risk of coronary heart disease in primary care is hampered by poor availability of data on risk factors. General practitioners and practice nurses are able to evaluate the risk of coronary heart disease with only moderate accuracy. Data about risk factors need to be collected systematically, to allow the use of the most appropriate calculation tools.

Towards a unified understanding of event-related changes in the EEG:the Firefly model of synchronization through cross-frequency phase modulation

Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing.

Surface catalysed Suzuki-Miyaura cross-coupling by Pd nanoparticles:an operando XAS study

Size-controlled, catalytically active PVP-stabilised Pd nanoparticles have been studied by operando liquid phase XAS during the Suzuki cross-coupling of iodonanisole and phenylboronic acid in MeOH-toluene using KOMe base. XAS reveals nanoparticles are stable to metal leaching throughout the reaction, with surface density Pd defect sites directly implicated in the catalytic cycle. The efficacy of popular selective chemical and structural poisons for distinguishing heterogeneous and homogeneous contributions in Pd catalysed cross-couplings is also explored. © 2010 The Royal Society of Chemistry.

Sonogashira cross-coupling and homocoupling on a silver surface:chlorobenzene and phenylacetylene on Ag(100)

Scanning tunneling microscopy, temperature-programmed reaction, near-edge X-ray absorption fine structure spectroscopy, and density functional theory calculations were used to study the adsorption and reactions of phenylacetylene and chlorobenzene on Ag(100). In the absence of solvent molecules and additives, these molecules underwent homocoupling and Sonogashira cross-coupling in an unambiguously heterogeneous mode. Of particular interest is the use of silver, previously unexplored, and chlorobenzene—normally regarded as relatively inert in such reactions. Both molecules adopt an essentially flat-lying conformation for which the observed and calculated adsorption energies are in reasonable agreement. Their magnitudes indicate that in both cases adsorption is predominantly due to dispersion forces for which interaction nevertheless leads to chemical activation and reaction. Both adsorbates exhibited pronounced island formation, thought to limit chemical activity under the conditions used and posited to occur at island boundaries, as was indeed observed in the case of phenylacetylene. The implications of these findings for the development of practical catalytic systems are considered.