The phenanthroimidazole-based dizinc(II) complex as a fluorescent probe for the pyrophosphate ion as generated in polymerase chain reactions and pyrosequencing

A highly selective and sensitive phenanthroimidazole tagged Mannich base type dizinc(II) fluorescent probe (R-Zn2+) has been developed for the pyrophosphate ion (PPi) with a very low limit of detection (LOD) of 0.25 ppm; this also assesses PPi from DNA polymerization chain reaction (PCR).

Novel triethylamine mediated thermal reactions of 3-aryl-2-cyanoprop-2-enoic acid derivatives-demethylation, reduction and vinylogation

3-Aryl-2-propenoic acid derivatives undergo interesting reactions with hot triethylamine. Substrates like 6 having a methoxyl with a nitro in the ortho and cyanoacrylic derivatives in the para positions give O-demethylated products, for example, entacapone 7. On the other hand compounds like 16 having the NO2 in the para and cyanoacrylic in the ortho position undergo reduction and vinylogation. The latter phenomenon is observed in the absence of the NO2 group also. (C) 2015 Elsevier Ltd. All rights reserved.

Regioselective Synthesis of Nitrofuran Containing Novel Spiropyrrolidine Library through 1,3-Dipolar Cycloaddition Reactions

A novel series of nitrofuran containing spiropyrrolidines has been synthesized with high regioselectivity in moderate to excellent yields via 1,3-dipolar cycloaddition reaction of azomethine ylides with various substituted chalcones.

CROSS-SECTIONAL ANALYSIS OF PRE-TWISTED THICK BEAMS USING VARIATIONAL ASYMPTOTIC METHOD

An asymptotically-exact methodology is presented for obtaining the cross-sectional stiffness matrix of a pre-twisted moderately-thick beam having rectangular cross sections and made of transversely isotropic materials. The anisotropic beam is modeled from 3-D elasticity, without any further assumptions. The beam is allowed to have large displacements and rotations, but small strain is assumed. The strain energy of the beam is computed making use of the constitutive law and the kinematical relations derived with the inclusion of geometrical nonlinearities and initial twist. Large displacements and rotations are allowed, but small strain is assumed. The Variational Asymptotic Method is used to minimize the energy functional, thereby reducing the cross section to a point on the reference line with appropriate properties, yielding a 1-D constitutive law. In this method as applied herein, the 2-D cross-sectional analysis is performed asymptotically by taking advantage of a material small parameter and two geometric small parameters. 3-D strain components are derived using kinematics and arranged as orders of the small parameters. Warping functions are obtained by the minimization of strain energy subject to certain set of constraints that renders the 1-D strain measures well-defined. Closed-form expressions are derived for the 3-D non-linear warping and stress fields. The model is capable of predicting interlaminar and transverse shear stresses accurately up to first order.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Controlled Release of Salicylic Acid from Biodegradable Cross-Linked Polyesters

The purpose of this work was to develop a family of crosslinked poly(xylitol adipate salicylate)s with a wide range of tunable release properties for delivering pharmacologically active salicylic acid. The synthesis parameters and release conditions were varied to modulate polyester properties and to understand the mechanism of release. Varying release rates were obtained upon longer curing (35% in the noncured polymer to 10% in the cured polymer in 7 days). Differential salicylic acid loading led to the synthesis of polymers with variable cross-linking and the release could be tuned (100% release for the lowest loading to 30% in the highest loading). Controlled release was monitored by changing various factors, and the release profiles were dependent on the stoichiometric composition, pH, curing time, and presence of enzyme. The polymer released a combination of salicylic acid and disalicylic acid, and the released products were found to be nontoxic. Minimal hemolysis and platelet activation indicated good blood compatibility. These polymers qualify as ``bioactive'' and ``resorbable'' and can, therefore, find applications as immunomodulatory resorbable biomaterials with tunable release properties.

The two-component signalling networks of Mycobacterium tuberculosis display extensive cross-talk in vitro

Two-component systems (TCSs), which contain paired sensor kinase and response regulator proteins, form the primary apparatus for sensing and responding to environmental cues in bacteria. TCSs are thought to be highly specific, displaying minimal cross-talk, primarily due to the co-evolution of the participating proteins. To assess the level of cross-talk between the TCSs of Mycobacterium tuberculosis, we mapped the complete interactome of the M. tuberculosis TCSs using phosphotransfer profiling. Surprisingly, we found extensive crosstalk among the M. tuberculosis TCSs, significantly more than that in the TCSs in Escherichia coli or Caulobacter crescentus, thereby offering an alternate to specificity paradigm in TCS signalling. Nearly half of the interactions we detected were significant novel cross-interactions, unravelling a potentially complex signalling landscape. We classified the TCSs into specific `one-to-one' and promiscuous `one-to-many' and `many-to-one' circuits. Using mathematical modelling, we deduced that the promiscuous signalling observed can explain several currently confounding observations about M. tuberculosis TCSs. Our findings suggest an alternative paradigm of bacterial signalling with significant cross-talk between TCSs yielding potentially complex signalling landscapes.

Optimal input cross-power spectra in shake table testing of asymmetric structures

The study considers earthquake shake table testing of bending-torsion coupled structures under multi-component stationary random earthquake excitations. An experimental procedure to arrive at the optimal excitation cross-power spectral density (psd) functions which maximize/minimize the steady state variance of a chosen response variable is proposed. These optimal functions are shown to be derivable in terms of a set of system frequency response functions which could be measured experimentally without necessitating an idealized mathematical model to be postulated for the structure under study. The relationship between these optimized cross-psd functions to the most favourable/least favourable angle of incidence of seismic waves on the structure is noted. The optimal functions are also shown to be system dependent, mathematically the sharpest, and correspond to neither fully correlated motions nor independent motions. The proposed experimental procedure is demonstrated through shake table studies on two laboratory scale building frame models.

Hidden role of anion exchange reactions in nucleation of colloidal nanocrystals

We investigate the processes involved in the nucleation of colloidal lead selenide nanoparticles. Our studies show that an unusual pathway - an anion exchange reaction, causes the nucleation of lead selenide nanocrystals. In this process, one quantum dot is transformed into another due to a substitution of its constituent anions. The existence of this pathway was never anticipated perhaps due to its unusually rapid kinetics. The nucleation and growth kinetics of colloidal lead selenide quantum dots are found to fit well to a two-step process. The rate constant associated with the anion exchange process is found to be four orders of magnitude greater than that of the nanocrystal growth. The complete consumption of the initial oxide nanoparticle thus provides a sharp, temporally well-defined nucleation event.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

Three-dimensional plotted hydroxyapatite scaffolds with predefined architecture: comparison of stabilization by alginate cross-linking versus sintering

Scaffolds for bone tissue engineering are essentially characterized by porous three-dimensional structures with interconnected pores to facilitate the exchange of nutrients and removal of waste products from cells, thereby promoting cell proliferation in such engineered scaffolds. Although hydroxyapatite is widely being considered for bone tissue engineering applications due to its occurrence in the natural extracellular matrix of this tissue, limited reports are available on additive manufacturing of hydroxyapatite-based materials. In this perspective, hydroxyapatite-based three-dimensional porous scaffolds with two different binders (maltodextrin and sodium alginate) were fabricated using the extrusion method of three-dimensional plotting and the results were compared in reference to the structural properties of scaffolds processed via chemical stabilization and sintering routes, respectively. With the optimal processing conditions regarding to pH and viscosity of binder-loaded hydroxyapatite pastes, scaffolds with parallelepiped porous architecture having up to 74% porosity were fabricated. Interestingly, sintering of the as-plotted hydroxyapatite-sodium alginate (cross-linked with CaCl2 solution) scaffolds led to the formation of chlorapatite (Ca9.54P5.98O23.8Cl1.60(OH)(2.74)). Both the sintered scaffolds displayed progressive deformation and delayed fracture under compressive loading, with hydroxyapatite-alginate scaffolds exhibiting a higher compressive strength (9.5 +/- 0.5MPa) than hydroxyapatite-maltodextrin scaffolds (7.0 +/- 0.6MPa). The difference in properties is explained in terms of the phase assemblage and microstructure.