Pharmacophore mapping of flavone derivatives for aromatase inhibition

Aromatase, which catalyses the final step in the steroidogenesis pathway of estrogen, has been target for the design of inhibitor in the treatment of hormone dependent breast cancer for postmenopausal women. The extensive SAR studies performed in the last 30 years to search for potent, selective and less toxic compounds, have led to the development of second and third generation of non-steroidal aromatase inhibitors (AI). Besides the development of synthetic compounds, several naturally occurring and synthetic flavonoids, which are ubiquitous natural phenolic compounds and mediate the host of biological activities, are found to demonstrate inhibitory effects on aromatase. The present study explores the pharmacophores, i.e., the structural requirements of flavones (Fig. 1) for inhibition of aromatase activity, using quantitative structure activity relationship (QSAR) and space modeling approaches. The classical QSAR studies generate the model (R (2) = 0.924, Q (2) = 0.895, s = 0.233) that shows the importance of aromatic rings A and C, along with substitutional requirements in meta and para positions of ring C for the activity. 3D QSAR of Comparative Molecular Field Analysis (CoMFA, R (2) = 0.996, [Formula: see text]) and Comparative Molecular Similarity Analysis (CoMSIA, R (2) = 0.992, [Formula: see text]) studies show contour maps of steric and hydrophobic properties and contribution of acceptor and donor of the molecule, suggesting the presence of steric hindrance due to ring C and R'-substituent, bulky hydrophobic substitution in ring A, along with acceptors at positions 11, and alpha and gamma of imidazole ring, and donor in ring C favor the inhibitory activity. Further space modeling (CATALYST) study (R = 0.941, Delta( cost ) = 96.96, rmsd = 0.876) adjudge the presence of hydrogen bond acceptor (keto functional group), hydrophobic (ring A) and aromatic rings (steric hindrance) along with critical distance among features are important for the inhibitory activity.     

Exploring the cause of the dual allosteric targeted inhibition attaching to allosteric sites enhancing SHP2 inhibition

Molecular Diversity - SHP2 is a protein tyrosine phosphatase (PTP) that can regulate the tyrosine phosphorylation level. Overexpression of SHP2 will promote the development of cancer diseases, so...     

Diffusion abnormality in the posterior cingulum and hippocampal volume: correlation with disease progression in Alzheimer's disease

The purpose of this study was to determine correlations among disease progression, diffusion abnormalities in the posterior cingulum and hippocampal volume in patients with Alzheimer's disease (AD). We studied 25 AD patients by neuropsychological testing, including the Mini-Mental State Examination (MMSE), and by magnetic resonance imaging, including diffusion tensor imaging (DTI) and high-resolution three-dimensional T1-weighted imaging. The MMSE score was used as an indicator of disease progression. Diffusion tensor tractography of the posterior cingulum was generated from the DTI; mean diffusivity (MD) and fractional anisotropy (FA) were measured in co-registered voxels along the posterior cingulum. Hippocampal volume was measured using automated voxel-based morphometry. The relationships among MMSE score, hippocampal volume and MD and FA of the posterior cingulum were evaluated by bivariate correlation analysis. MD in the posterior cingulum correlated significantly with the MMSE score. No significant correlation was seen between FA and MMSE score and between hippocampal volume and MMSE score, FA or MD. Our results suggest that MD in the posterior cingulum is a more sensitive indicator of progression of AD than FA of the posterior cingulum and hippocampal volume.     

Individual identification using multi-metric of DTI in Alzheimer's disease and mild cognitive impairment

Accurate identification of Alzheimer's disease(AD) and mild cognitive impairment(MCI) is crucial so as to improve diagnosis techniques and to better understand the neurodegenerative process. In this work, we aim to apply the machine learning method to individual identification and identify the discriminate features associated with AD and MCI. Diffusion tensor imaging scans of 48 patients with AD, 39 patients with late MCI, 75 patients with early MCI, and 51 age-matched healthy controls(HCs) are acquired from the Alzheimer's Disease Neuroimaging Initiative database. In addition to the common fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity metrics, there are two novel metrics,named local diffusion homogeneity that used Spearman's rank correlation coefficient and Kendall's coefficient concordance,which are taken as classification metrics. The recursive feature elimination method for support vector machine(SVM)and logistic regression(LR) combined with leave-one-out cross validation are applied to determine the optimal feature dimensions. Then the SVM and LR methods perform the classification process and compare the classification performance.The results show that not only can the multi-type combined metrics obtain higher accuracy than the single metric, but also the SVM classifier with multi-type combined metrics has better classification performance than the LR classifier.Statistically, the average accuracy of the combined metric is more than 92% for all between-group comparisons of SVM classifier. In addition to the high recognition rate, significant differences are found in the statistical analysis of cognitive scores between groups. We further execute the permutation test, receiver operating characteristic curves, and area under the curve to validate the robustness of the classifiers, and indicate that the SVM classifier is more stable and efficient than the LR classifier. Finally, the uncinated fasciculus, cingulum, corpus callosum, corona radiate, external capsule, and internal capsule have been regarded as the most important white matter tracts to identify AD, MCI, and HC. Our findings reveal a guidance role for machine-learning based image analysis on clinical diagnosis.     

Dimerization of the transmembrane domain of amyloid precursor proteins and familial Alzheimer's disease mutants

Background  

Amyloid precursor protein (APP) is enzymatically cleaved by γ-secretase to form two peptide products, either Aβ40 or the more neurotoxic Aβ42. The Aβ42/40 ratio is increased in many cases of familial Alzheimer's disease (FAD). The transmembrane domain (TM) of APP contains the known dimerization motif GXXXA. We have investigated the dimerization of both wild type and FAD mutant APP transmembrane domains.     

Increased glucose concentration in the hippocampus in early Alzheimer's disease following oral glucose ingestion

Glucose is the primary source of energy for brain cells. Because energy storage in the brain is limited, an uninterrupted supply of glucose and its rapid metabolism are essential for normal cognitive function. This study utilized an oral glucose load to examine hippocampal glucose metabolism in early Alzheimer's disease (AD) - a disease characterized by progressive deterioration of cognitive function and glucose hypometabolism. Short echo time 1H MR spectra (20 ms) from the right hippocampus of 8 patients with probable AD, 14 healthy elderly and 14 healthy young adults were compared pre- and post-glucose loading. In contrast to the healthy adults, the AD patients exhibited significantly elevated hippocampal glucose concentrations post-glucose ingestion relative to baseline (P < .01). These results suggest that cerebral glucose hypometabolism in AD leads to an increased steady-state concentration of cerebral glucose. This research demonstrates the feasibility of studying cerebral glucose metabolism in AD with 1H MR spectroscopy.     

The modular systems biology approach to investigate the control of apoptosis in Alzheimer's disease neurodegeneration

Apoptosis is a programmed cell death that plays a critical role during the development of the nervous system and in many chronic neurodegenerative diseases, including Alzheimer's disease (AD). This pathology, characterized by a progressive degeneration of cholinergic function resulting in a remarkable cognitive decline, is the most common form of dementia with high social and economic impact. Current therapies of AD are only symptomatic, therefore the need to elucidate the mechanisms underlying the onset and progression of the disease is surely needed in order to develop effective pharmacological therapies. Because of its pivotal role in neuronal cell death, apoptosis has been considered one of the most appealing therapeutic targets, however, due to the complexity of the molecular mechanisms involving the various triggering events and the many signaling cascades leading to cell death, a comprehensive understanding of this process is still lacking. Modular systems biology is a very effective strategy in organizing information about complex biological processes and deriving modular and mathematical models that greatly simplify the identification of key steps of a given process. This review aims at describing the main steps underlying the strategy of modular systems biology and briefly summarizes how this approach has been successfully applied for cell cycle studies. Moreover, after giving an overview of the many molecular mechanisms underlying apoptosis in AD, we present both a modular and a molecular model of neuronal apoptosis that suggest new insights on neuroprotection for this disease.     

Magnetic resonance elastography of the brain in a mouse model of Alzheimer's disease: initial results

The increasing prevalence of Alzheimer's disease (AD) has provided motivation for developing novel methods for assessing the disease and the effects of potential treatments. Magnetic resonance elastography (MRE) is an MRI-based method for quantitatively imaging the shear tissue stiffness in vivo. The objective of this research was to determine whether this new imaging biomarker has potential for characterizing neurodegenerative disease. Methods were developed and tested for applying MRE to evaluate the mouse brain, using a conventional large bore 3.0T MRI system. The technique was then applied to study APP-PS1 mice, a well-characterized model of AD. Five APP-PS1 mice and 8 age-matched wild-type mice were imaged immediately following sacrifice. Brain shear stiffness measurements in APP-PS1 mice averaged 22.5% lower than those for wild-type mice (P = .0031). The results indicate that mouse brain MRE is feasible at 3.0T, and brain shear stiffness has merit for further investigation as a potential new biomarker for Alzheimer's disease.     

Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory

Background  

Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL), a measure of functional connectivity, was calculated for each sensor pair in 0.5–4 Hz, 4–8 Hz, 8–10 Hz, 10–13 Hz, 13–30 Hz and 30–45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity), characteristic path length (global connectivity) and degree correlation (network 'assortativity'). All results were normalized for network size and compared with random control networks.     

Diffusion MRI detects basal forebrain cholinergic abnormalities in the 3xTg-AD mouse model of Alzheimer's disease

Degeneration of the basal forebrain (BF) is detected early in the course of Alzheimer's disease (AD). Reduction in the number of BF cholinergic (ChAT) neurons associated with age-related hippocampal cholinergic neuritic dystrophy is described in the 3xTg-AD mouse model; however, no prior diffusion MRI (dMRI) study has explored the presence of BF alterations in this model. Here we investigated the ability of diffusion MRI (dMRI) to detect abnormalities in BF microstructure for the 3xTg-AD mouse model, along with related pathology in the hippocampus (HP) and white matter (WM) tracks comprising the septo-hippocampal pathway. 3xTg-AD and normal control (NC) mice were imaged in vivo using the specific dMRI technique known as diffusional kurtosis imaging (DKI) at 2, 8, and 15 months of age, and 8 dMRI parameters were measured at each time point. Our results revealed significant lower dMRI values in the BF of 2 months-old 3xTg-AD mice compared with NC mice, most likely related to the increased number of ChAT neurons seen in this AD mouse model at this age. They also showed significant age-related dMRI changes in the BF of both groups between 2 and 8 months of age, mainly a decrease in fractional anisotropy and axial diffusivity, and an increase in radial kurtosis. These dMRI changes in the BF may be reflecting the complex aging and pathological microstructural changes described in this region. Group differences and age-related changes were also observed in the HP, fimbria (Fi) and fornix (Fx). In the HP, diffusivity values were significantly higher in the 2 months-old 3xTg-AD mice, and the HP of NC mice showed a significant increase in axial kurtosis after 8 months, reflecting a normal pattern of increased fiber density complexity, which was not seen in the 3xTg-AD mice. In the Fi, mean and radial diffusivity values were significantly higher, and fractional anisotropy, radial kurtosis and kurtosis fractional anisotropy were significantly lower in the 2 months-old 3xTg-AD mice. The age trajectories for both NC and TG mice in the Fi and Fx were similar between 2 and 8 months, but after 8 months there was a significant decrease in diffusivity metrics associated with an increase in kurtosis metrics in the 3xTg-AD mice. These later HP, Fi and Fx dMRI changes probably reflect the growing number of dystrophic neurites and AD pathology progression in the HP, accompanied by WM disruption in the septo-hippocampal pathway. Our results demonstrate that dMRI can detect early cytoarchitectural abnormalities in the BF, as well as related aging and neurodegenerative changes in the HP, Fi and Fx of the 3xTg-AD mice. Since DKI is widely available on clinical scanners, these results also support the potential of the considered dMRI parameters as in vivo biomarkers for AD disease progression.     

Longitudinal stability of resting-state networks in normal aging,mild cognitive impairment,and Alzheimer's disease

Test–retest reliability is essential for using resting-state functional magnetic resonance imaging (rs-fMRI) as a potential biomarker for Alzheimer's disease (AD), especially when monitoring longitudinal changes and treatment effects. In addition, test–retest variability itself might represent a feature of AD. Using 3.0 T rs-fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we examined the long-term (1-year) test–retest reliability of resting-state networks (RSNs) in 31 healthy elderly subjects, 63 patients with mild cognitive impairment (MCI), and 17 patients with AD by applying temporal concatenation group independent component analysis and dual regression. The intraclass correlation coefficient estimates of RSN amplitudes ranged from 0.44 to 0.77 in healthy elderly subjects, from 0.31 to 0.62 in patients with MCI, and from −0.06 to 0.44 in patients with AD. The overall test–retest reliability of RSNs was lower in patients with MCI than in healthy elderly subjects, and was lower in patients with AD than in patients with MCI. The differences in the test–retest reliabilities were due to the RSN amplitudes rather than the RSN shapes. Head motion was not significantly different among the three groups of subjects. The results indicate that the test–retest stability of RSNs generally declines with progression to MCI and AD, mainly due to the RSN amplitudes rather than the RSN shapes. The test–retest instability in MCI and AD may reflect progressive neurofunctional alterations related to the pathology of AD.     

Novel tacrine-based acetylcholinesterase inhibitors as potential agents for the treatment of Alzheimer’s disease: Quinolotacrine hybrids

A new series of quinolotacrine hybrids including cyclopenta- and cyclohexa-quinolotacrine derivatives were designed, synthesized, and assessed as anti-cholinesterase (ChE) agents. The designed derivatives indicated higher inhibitory effect on the acetylcholinesterase (AChE) with IC₅₀ values of 0.285–100 µM compared to butyrylcholinesterase (BChE) with IC₅₀ values of?>?100 µM. Of these compounds, cyclohexa-quinolotacrine hybrids displayed a little better anti-AChE activity than cyclopenta-quinolotacrine hybrids. Compound 8-amino-7-(3-hydroxyphenyl)-5,7,9,10,11,12-hexahydro-6H-pyrano[2,3-b:5,6-c'] diquinolin-6-one (6m) including 3-hydroxyphenyl and cyclohexane ring moieties exhibited the best AChE inhibitory activity with IC₅₀ value of 0.285 µM. The kinetic and molecular docking studies indicated that compound 6m occupied both the catalytic anionic site (CAS) and peripheral anionic site (PAS) of AChE as a mixed inhibitor. Using neuroprotective assay against H₂O₂-induced cell death in PC12 cells, the compound 6h illustrated significant protection among the assessed compounds. In silico ADME studies estimated good drug-likeness for the designed compounds. As a result, these quinolotacrine hybrids can be very encouraging AChE inhibitors to treat Alzheimer’s disease.

Graphic abstract

A novel series of quinolotacrine hybrids were designed, synthesized, and evaluated against AChE and BChE enzymes as potential agents for the treatment of AD. The hybrids showed good to significant inhibitory activity against AChE (0.285–100 μM) compared to butyrylcholinesterase (BChE) with IC₅₀ values of?>?100 μM. Among them, compound 8-amino-7-(3-hydroxyphenyl)-5,7,9,10,11,12-hexahydro-6H-pyrano[2,3-b:5,6-c′] diquinolin-6-one (6 m) bearing 3-hydroxyphenyl moiety and cyclohexane ring exhibited the highest anti-AChE activity with IC₅₀ value of 0.285 μM. The kinetic and molecular docking studies illustrated that compound 6 m is a mixed inhibitor and binds to both the catalytic anionic site (CAS) and peripheral anionic site (PAS) of AChE.

     

Absence of ghost in the dual pomeron

We show that the ghost state found recently by Cremmer and Scherk in the dual pomeron is due to an incorrect treatment of massless spin-two states.     

Polymer-population mapping and localization in the space of phenotypes

We present a mapping between the thermodynamics of an ideal heteropolymer in an external field and the dynamics of structured populations in fluctuating environments. We employ a population model in which individuals may adopt different phenotypes, each of which may be optimal in a different environment. Using this mapping, we develop a path integral formulation for populations and predict the existence of a biological counterpart for the well-known heteropolymer localization phase transition.     

Cancellation of the leading divergence in dual loops

We show that the leading divergence of the single meson loop of the dual pion model is cancelled by a similar divergence of the fermion loop in the model with no ghosts. There is still one remaining divergence at the one-loop level.     

Commuting conformal and dual conformal symmetries in the Regge limit

In this paper we continue our study of the dual SL(2,C)$\mathit{SL}(2,C)$ symmetry of the BFKL equation, analogous to the dual conformal symmetry of N=4$N=4$ super-Yang–Mills. We find that the ordinary and dual SL(2,C)$\mathit{SL}(2,C)$ symmetries do not generate a Yangian, in contrast to the ordinary and dual conformal symmetries in the four-dimensional gauge theory. The algebraic structure is still reminiscent of that of N=4$N=4$ SYM, however, and one can extract a generator from the dual SL(2,C)$\mathit{SL}(2,C)$ close to the bi-local form associated with Yangian algebras. We also discuss the issue of whether the dual SL(2,C)$\mathit{SL}(2,C)$ symmetry, which in its original form is broken by IR effects, is broken in a controlled way, similar to the way the dual conformal symmetry of N=4$N=4$ satisfies an anomalous Ward identity. At least for the lowest orders it seems possible to recover the dual SL(2,C)$\mathit{SL}(2,C)$ by deforming its representation, keeping open the possibility that it is an exact symmetry of BFKL. Independently of a possible relation to N=4$N=4$ scattering amplitudes, this opens an avenue for explaining the integrability of BFKL in terms of two finite-dimensional subalgebras.     

Berberine chloride can ameliorate the spatial memory impairment and increase the expression of interleukin-1beta and inducible nitric oxide synthase in the rat model of Alzheimer's disease

Background  

Berberine is the major alkaloidal component of Rhizoma coptidis, and has multiple pharmacological effects including inhibiting acetylcholinesterase, reducing cholesterol and glucose, lowering mortality in patients with chronic congestive heart failure and anti-inflammation etc. Thus berberine is a promising drug for diabetes, hyperlipemia, coronary artery disease and ischemic stroke etc. The present study was carried out to investigate the effect of berberine chloride on the spatial memory, inflammation factors interleukin-1 beta (IL-1beta) and inducible nitric oxide synthase (iNOS) expression in the rat model of Alzheimer's disease (AD) which was established by injecting Abeta (1–40) (5 microgram) into the rats hippocampuses bilaterally.     

Sequential convergence in the dual of aW*-algebra

The present paper is the result of the author's attempt to extend Theorem 9 of [5] to the case of a non-abelianW*-algebra. In [5]Grothendieck proves that weak and weak* convergence are equivalent for sequences in the dual space of an abelianW*-algebra. Theorem 4 of the present paper is only a partial result in that direction, but it is presented here because of its possible worth as a technical tool.