Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Generation of the primary hair follicle pattern.

Hair follicles are spaced apart from one another at regular intervals through the skin. Although follicles are predominantly epidermal structures, classical tissue recombination experiments indicated that the underlying dermis defines their location during development. Although many molecules involved in hair follicle formation have been identified, the molecular interactions that determine the emergent property of pattern formation have remained elusive. We have used embryonic skin cultures to dissect signaling responses and patterning outcomes as the skin spatially organizes itself. We find that ectodysplasin receptor (Edar)-bone morphogenetic protein (BMP) signaling and transcriptional interactions are central to generation of the primary hair follicle pattern, with restriction of responsiveness, rather than localization of an inducing ligand, being the key driver in this process. The crux of this patterning mechanism is rapid Edar-positive feedback in the epidermis coupled with induction of dermal BMP4/7. The BMPs in turn repress epidermal Edar and hence follicle fate. Edar activation also induces connective tissue growth factor, an inhibitor of BMP signaling, allowing BMP action only at a distance from their site of synthesis. Consistent with this model, transgenic hyperactivation of Edar signaling leads to widespread overproduction of hair follicles. This Edar-BMP activation-inhibition mechanism appears to operate alongside a labile prepattern, suggesting that Edar-mediated stabilization of beta-catenin active foci is a key event in determining definitive follicle locations.

SwissParam: a fast force field generation tool for small organic molecules.

The drug discovery process has been deeply transformed recently by the use of computational ligand-based or structure-based methods, helping the lead compounds identification and optimization, and finally the delivery of new drug candidates more quickly and at lower cost. Structure-based computational methods for drug discovery mainly involve ligand-protein docking and rapid binding free energy estimation, both of which require force field parameterization for many drug candidates. Here, we present a fast force field generation tool, called SwissParam, able to generate, for arbitrary small organic molecule, topologies, and parameters based on the Merck molecular force field, but in a functional form that is compatible with the CHARMM force field. Output files can be used with CHARMM or GROMACS. The topologies and parameters generated by SwissParam are used by the docking software EADock2 and EADock DSS to describe the small molecules to be docked, whereas the protein is described by the CHARMM force field, and allow them to reach success rates ranging from 56 to 78%. We have also developed a rapid binding free energy estimation approach, using SwissParam for ligands and CHARMM22/27 for proteins, which requires only a short minimization to reproduce the experimental binding free energy of 214 ligand-protein complexes involving 62 different proteins, with a standard error of 2.0 kcal mol(-1), and a correlation coefficient of 0.74. Together, these results demonstrate the relevance of using SwissParam topologies and parameters to describe small organic molecules in computer-aided drug design applications, together with a CHARMM22/27 description of the target protein. SwissParam is available free of charge for academic users at www.swissparam.ch.

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2008

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2008

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2007

Report on applying agreed-upon procedures to the City of Protivin’s certification of compliance with Chapter 388.10 of the Code of Iowa for the year ended June 30, 2007

Iowa Department of Transportation Fiscal Year 2008 Report of Savings by Using Video Conferencing Through Iowa Communications Network to the Iowa General Assembly Pursuant to Iowa Code § II 84 Acts and Joint Resolutions Enacted at the 1994 Regular Session of the 75th General Assembly of the State of Iowa Iowa Code §8D.10 Report of Savings by State Agencies

Iowa Code § 8D.10 requires certain state agencies prepare an annual report to the General Assembly certifying the identified savings associated with that state agency’s use of the Iowa Communications Network (ICN). This report covers estimated cost savings related to video conferencing via ICN for the Iowa Department of Transportation (DOT). In FY 2008, the DOT did not conduct any sessions utilizing ICN’s video conferencing system. Therefore, no cost savings were calculated for this report.

A glutathione precursor, N-acetyl-cysteine, modulates mismatch negativity generation in schizophrenia patients

Schizophrenia patients exhibit deficits in low-level processing, including pitch discrimination. This deficiency manifests in auditory evoked potentials (AEPs) as an impaired mismatch negativity (MMN), an electrophysiological response to infrequent target stimuli interspersed among frequent standard stimuli that typically peaks ~100ms post-stimulus onset. NMDA receptor antagonists have been shown to block MMN generation in both animals and humans, and NMDA dysfunction has been linked to the underlying pathophysiology of schizophrenia. A parallel line of evidence indicates that glutathione (GSH) regulation is perturbed in schizophrenia patients at the gene, protein and functional levels (Tosic et al., 2006). This GSH dysregulation leads to NMDA receptors' hypofunction through interaction with their redox site (Steullet et al., 2006). The present study aimed to modulate GSH levels in schizophrenia patients and assessed the effects of such a modulation on MMN generation mechanisms. N-acetyl-cysteine (NAC), a GSH precursor, was administered to schizophrenia patients, using a double-blind cross-over protocol. One group received NAC (2g/day) for 60 days and then placebo for another 60 days, and vice-versa for the second group. AEPs from patients were recorded at the onset of the protocol, at the point of cross-over, and at the end of the study. Participants were instructed to manually respond to target stimuli (2kHz pure tones occurring 20% of the time among 1kHz pure tones). Analyses of AEPs recorded at protocol onset indicated that patients (n=11) were significantly impaired in generating the MMN relative to age-matched controls (n=11). Specifically, the global field power (GFP), an index of AEP magnitude, was measured over the 70- 155ms post-stimulus interval and submitted to an analysis of variance (ANOVA). There was a significant interaction between population and stimulus frequency, indicating impaired MMN generation in patients at protocol onset. Analyses of AEPs recorded during administration of NAC (n=7) versus placebo (n=7) revealed the efficacy of this GSH precursor in modulating MMN generation mechanisms. ANOVA of GFP over the 70- 155ms post-stimulus interval, using stimulus frequency and treatment as within-participants variables, revealed a significant interaction and indicated that NAC can ameliorate MMN generation. We discuss these results in terms of potential therapeutic strategies for schizophrenia.