Brain-derived neurotrophic factor modulation of Kv1.3 channel is disregulated by adaptor proteins Grb10 and nShc

Background

Developmental dyslexia is a specific cognitive disorder in reading acquisition that has genetic and neurological origins. Despite histological evidence for brain differences in dyslexia, we recently demonstrated that in large cohort of subjects, no differences between control and dyslexic readers can be found at the macroscopic level (MRI voxel), because of large variances in brain local volumes. In the present study, we aimed at finding brain areas that most discriminate dyslexic from control normal readers despite the large variance across subjects. After segmenting brain grey matter, normalizing brain size and shape and modulating the voxels' content, normal readers' brains were used to build a 'typical' brain via bootstrapped confidence intervals. Each dyslexic reader's brain was then classified independently at each voxel as being within or outside the normal range. We used this simple strategy to build a brain map showing regional percentages of differences between groups. The significance of this map was then assessed using a randomization technique.

Results

The right cerebellar declive and the right lentiform nucleus were the two areas that significantly differed the most between groups with 100% of the dyslexic subjects (N = 38) falling outside of the control group (N = 39) 95% confidence interval boundaries. The clinical relevance of this result was assessed by inquiring cognitive brain-based differences among dyslexic brain subgroups in comparison to normal readers' performances. The strongest difference between dyslexic subgroups was observed between subjects with lower cerebellar declive (LCD) grey matter volumes than controls and subjects with higher cerebellar declive (HCD) grey matter volumes than controls. Dyslexic subjects with LCD volumes performed worse than subjects with HCD volumes in phonologically and lexicon related tasks. Furthermore, cerebellar and lentiform grey matter volumes interacted in dyslexic subjects, so that lower and higher lentiform grey matter volumes compared to controls differently modulated the phonological and lexical performances. Best performances (observed in controls) corresponded to an optimal value of grey matter and they dropped for higher or lower volumes.

Conclusion

These results provide evidence for the existence of various subtypes of dyslexia characterized by different brain phenotypes. In addition, behavioural analyses suggest that these brain phenotypes relate to different deficits of automatization of language-based processes such as grapheme/phoneme correspondence and/or rapid access to lexicon entries.     

Synthesis of 3,5-Bis(trifluoromethyl)phenyl-Substituted Pyrazole Derivatives as Potent Growth Inhibitors of Drug-Resistant Bacteria

Enterococci and methicillin-resistant S. aureus (MRSA) are among the menacing bacterial pathogens. Novel antibiotics are urgently needed to tackle these antibiotic-resistant bacterial infections. This article reports the design, synthesis, and antimicrobial studies of 30 novel pyrazole derivatives. Most of the synthesized compounds are potent growth inhibitors of planktonic Gram-positive bacteria with minimum inhibitory concertation (MIC) values as low as 0.25 µg/mL. Further studies led to the discovery of several lead compounds, which are bactericidal and potent against MRSA persisters. Compounds 11, 28, and 29 are potent against S. aureus biofilms with minimum biofilm eradication concentration (MBEC) values as low as 1 µg/mL.     

Fullerene derived molecularly imprinted polymer for chemosensing of adenosine-5′-triphosphate (ATP)

For molecular imprinting of oxidatively electroactive analytes by electropolymerization, we used herein reductively electroactive functional monomers. As a proof of concept, we applied C₆₀ fullerene adducts as such for the first time. For that, we derivatized C₆₀ to bear either an uracil or an amide, or a carboxy addend for recognition of the adenosine-5′-triphosphate (ATP) oxidizable analyte with the ATP-templated molecularly imprinted polymer (MIP-ATP). Accordingly, the ATP complex with all of the functional monomers formed in solution was potentiodynamically electropolymerized to deposit an MIP-ATP film either on an Au electrode of the quartz crystal resonator or on a Pt disk electrode for the piezoelectric microgravimetry (PM) or capacitive impedimetry (CI) determination of ATP, respectively, under the flow-injection analysis (FIA) conditions. The apparent imprinting factor for ATP was ∼4.0. After extraction of the ATP template, analytical performance of the resulting chemosensors, including detectability, sensitivity, and selectivity, was characterized. The limit of detection was 0.3 and 0.03 mM ATP for the PM and CI chemosensor, respectively. The MIP-ATP film discriminated structural analogues of ATP quite well. The Langmuir, Freundlich, and Langmuir–Freundlich isotherms were fitted to the experimental data of the ATP sorption and sorption stability constants appeared to be nearly independent of the adopted sorption model.     

Assessment of Five SGS Models for Low-Rem MHD Turbulence

Assessment of three regularization-based and two eddy-viscosity-based subgrid-scale (SGS) turbulence models for large eddy simulations (LES) are carried out in the context of magnetohydrodynamic (MHD) decaying homogeneous turbulence (DHT) with a Taylor scale Reynolds number (Re_λ) of 120 and a MHD transition-to-turbulence Taylor-Green vortex (TGV) problems with a Reynolds number of 3000, through direct comparisons to direct numerical simulations (DNS). Simulations are conducted using the low-magnetic Reynolds number approximation (Re_m<<1). LES predictions using the regularization-based Leray- α,LANS- α, and Clark- α SGS models, along with the eddy viscosity-based non-dynamic Smagorinsky and the dynamic Smagorinsky models are compared to in-house DNS for DHT and previous results for TGV. With regard to the regularization models, this work represents their first application to MHD turbulence. Analyses of turbulent kinetic energy decay rates, energy spectra, and vorticity fields made between the varying magnetic field cases demonstrated that the regularization models performed poorly compared to the eddy-viscosity models for all MHD cases, but the comparisons improved with increase in magnitude of magnetic field, due to a decrease in the population of SGS eddies within the flow field.     

Nickel-Catalyzed α-Carbonylalkylarylation of Vinylarenes: Expedient Access to γ,γ-Diarylcarbonyl and Aryltetralone Derivatives

We report a Ni-catalyzed regioselective α-carbonylalkylarylation of vinylarenes with α-halocarbonyl compounds and arylzinc reagents. The reaction works with primary, secondary, and tertiary α-halocarbonyl molecules, and electronically varied arylzinc reagents. The reaction generates γ,γ-diarylcarbonyl derivatives with α-secondary, tertiary, and quaternary carbon centers. The products can be readily converted to aryltetralones, including a precursor to Zoloft, an antidepressant drug.     

DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction

Protein N-linked glycosylation is a post-translational modification that plays an important role in a myriad of biological processes. Computational prediction approaches serve as complementary methods for the characterization of glycosylation sites. Most of the existing predictors for N-linked glycosylation utilize the information that the glycosylation site occurs at the N-X-[S/T] sequon, where X is any amino acid except proline. Not all N-X-[S/T] sequons are glycosylated, thus the N-X-[S/T] sequon is a necessary but not sufficient determinant for protein glycosylation. In that regard, computational prediction of N-linked glycosylation sites confined to N-X-[S/T] sequons is an important problem. Here, we report DeepNGlyPred a deep learning-based approach that encodes the positive and negative sequences in the human proteome dataset (extracted from N-GlycositeAtlas) using sequence-based features (gapped-dipeptide), predicted structural features, and evolutionary information. DeepNGlyPred produces SN, SP, MCC, and ACC of 88.62%, 73.92%, 0.60, and 79.41%, respectively on N-GlyDE independent test set, which is better than the compared approaches. These results demonstrate that DeepNGlyPred is a robust computational technique to predict N-Linked glycosylation sites confined to N-X-[S/T] sequon. DeepNGlyPred will be a useful resource for the glycobiology community.     

Pricing vulnerable European options with stochastic default barriers

CF Lo and KC Ku Institute of Theoretical Physics and Department of Physics, The Chinese University of Hong Kong, Shatin, Hong Kong, China Email: cho-hoi_hui{at}hkma.gov.hk Received on 31 July 2006. Accepted on 15 March 2007. This paper develops a valuation model of European options incorporatinga stochastic default barrier, which extends a constant defaultbarrier proposed in the Hull–White model. The defaultbarrier is considered as an option writer's liability. Closed-formsolutions of vulnerable European option values based on themodel are derived to study the impact of the stochastic defaultbarriers on option values. The numerical results show that negativecorrelation between the firm values and the stochastic defaultbarriers of option writers gives material reductions in optionvalues where the options are written by firms with leverageratios corresponding to BBB or BB ratings.     

Chlorophosphonates: inexpensive precursors for stereodefined chloro-substituted olefins and unsymmetrical disubstituted acetylenes

New chlorophosphonates bearing a 1,3,2-dioxaphosphorinane ring which are useful for the stereospecific synthesis of 5-chlorofurfuryl substituted olefins and chloro-substituted dienes have been obtained by an easy, inexpensive route. The utility of some of these in the synthesis of ferrocenyl- and anthracenyl-substituted unsymmetrical acetylenes has been explored. The structures of the phosphonates (OCH(2)CMe(2)CH(2)O)P(O)CH(2)(C(4)H(2)ClO) (4) and (OCH(2)CMe(2)CH(2)O)P(O)(CH=CHCH(Cl)Ph (7) have been determined; in addition, the stereochemistry of (5-chlorofurfuryl)CH=CH(4-ClC(6)H(4)) (13b) and 2, 4-Cl(2)C(6)H(3)-CH=CH-CH=C(Ph)Cl (14a) is unambiguously proved by the X-ray structure determination.     

A carrier protein strategy yields the structure of dalbavancin

Many large natural product antibiotics act by specifically binding and sequestering target molecules found on bacterial cells. We have developed a new strategy to expedite the structural analysis of such antibiotic-target complexes, in which we covalently link the target molecules to carrier proteins, and then crystallize the entire carrier-target-antibiotic complex. Using native chemical ligation, we have linked the Lys-D-Ala-D-Ala binding epitope for glycopeptide antibiotics to three different carrier proteins. We show that recognition of this peptide by multiple antibiotics is not compromised by the presence of the carrier protein partner, and use this approach to determine the first-ever crystal structure for the new therapeutic dalbavancin. We also report the first crystal structure of an asymmetric ristocetin antibiotic dimer, as well as the structure of vancomycin bound to a carrier-target fusion. The dalbavancin structure reveals an antibiotic molecule that has closed around its binding partner; it also suggests mechanisms by which the drug can enhance its half-life by binding to serum proteins, and be targeted to bacterial membranes. Notably, the carrier protein approach is not limited to peptide ligands such as Lys-D-Ala-D-Ala, but is applicable to a diverse range of targets. This strategy is likely to yield structural insights that accelerate new therapeutic development.