EX VIVO ANTICOAGULANT ACTIVITY OF 1, 3, 4-OXADIAZOLE DERIVATIVES

Objective: The present medication for the management of arterial thromboembolism (ATE) disorders by anticoagulant therapy highlights its lacunae due to recurrent ATE episodes and indicates the need for better anticoagulant agents with clinical advantage.Methods: The anticoagulant study was performed for increase in prothrombin time (PT) and activated partial thromboplastin time (aPTT) at a test dose of 25 mg kg-1.Results: The results of ex vivo anticoagulant evaluation revealed that the tested compounds 3a-3q did not exhibit a significant increase in PT with respect to acenocoumarol (1 mg kg-1) employed as the reference drug for increase in PT. While the compounds, 3a-3q exhibited minimal increase in aPTT in comparison to unfractionated heparin (500 IU kg-1) employed as the reference drug for increase in aPTT. Among all the tested compounds, only compound 3q exhibited moderate anticoagulant activity with an increase in PT (33 ± 0.4 s) to that of the reference drug acenocoumarol (48 ± 0.5 s).Conclusion: The anticoagulant efficacy investigation highlights that the synthesized compound 3q could be considered for further clinical studies to ascertain its possible hit as anticoagulant agents.Â

DESIGN, SYNTHESIS, IN VITRO ANTIOXIDANT AND IN VIVO ANTI-INFLAMMATORY ACTIVITIES OF NOVEL OXADIAZOLE DERIVATIVES

Objective: In the present study, a series of novel 1,3,4-oxadiazole derivatives (3a-3q) were designed, synthesized and evaluated for antioxidant and anti-inflammatory activities.Methods: The title compounds were designed and docked onto the COX-2 enzyme (3LN1) protein using SYBYLX 2.1. 2-substituted-5-(5-nitrobenzofuran-2-yl)-1,3,4-oxadiazole derivatives (3a-3p) were synthesized from acid catalyzed dehydrative cyclization of 5-nitrobenzofuran-2-carbohydrazide (2) with various heteroaryl/aryl/aliphatic carboxylic acid derivatives. And 5-(5-nitrobenzofuran-2-yl)-1,3,4-oxadiazole-2-thiol (3q) was synthesized on reacting the hydrazide derivative 2 with carbon disulfide. The synthesized compounds were evaluated for in vitro antioxidant property by DPPH radical scavenging assay method and in vivo anti-inflammatory activity by carrageenan induced paw edema method.Results: The synthesized 1,3,4-oxadiazole derivatives (3a-3q) were characterized on the basis of LCMS, 1HNMR [13]CNMR, IR and elemental analysis. The title compounds 3a-3q exhibited significant antioxidant efficacy ranging from 34 to 86%and the results of anti-inflammatory evaluation revealed that compounds 3c, 3e and 3d exhibited substantial anti-inflammatory activity of 72, 68 and 65%, respectively, at a dose of 50 mg kg-1.Conclusion: A significant correlation was observed between the in silico study and the anti-inflammatory results. The anti-inflammatory results highlight the synthesized compounds 3c, 3e and 3d could be considered as possible hit as therapeutic agents.Â

DETERMINATION OF OCTANOL-WATER PARTITION COEFFICIENT OF NOVEL COUMARIN BASED ANTICANCER COMPOUNDS BY REVERSED-PHASE ULTRA-FAST LIQUID CHROMATOGRAPHY

Objective: The present study aims at the development of a reversed phase ultra-fast liquid chromatography (RP-UFLC) method for measurement of the lipophilicity (log P) between n-octanol and water for the newly synthesized coumarin derivatives in our laboratory.Methods: The synthesized compounds were dissolved in methanol and analyzed using XTerra RP18 column as the stationary phase and a mixture of methanol (0.25% v/v octanol) and buffer as the mobile phase with isocratic elution.Results: In this study we concentrated on the relationship between a reversed-phase ultra-fast liquid chromatography (RP-UFLC) retention parameters and log P of our synthesized compounds. Furthermore, a good correlation and very close values were obtained between the experimentally determined log P values and values obtained from Chemdraw.Conclusion: The developed method was found to be insensitive to any of the impurities present and moreover it requires very little sample for analysis

DeepWalk: Online Learning of Social Representations

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs. DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi-label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide $F_1$ scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data. DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.Comment: 10 pages, 5 figures, 4 table

Visibility graphs of random scalar fields and spatial data

The family of visibility algorithms were recently introduced as mappings between time series and graphs. Here we extend this method to characterize spatially extended data structures by mapping scalar fields of arbitrary dimension into graphs. After introducing several possible extensions, we provide analytical results on some topological properties of these graphs associated to some types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension, extending a well known result in one-dimensional time series. As this result holds independently of the field's marginal distribution, we show that it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatio-temporal chaos. We finally discuss the range of potential applications of this combinatorial framework, which include image processing in engineering, the description of surface growth in material science, soft matter or medicine and the characterization of potential energy surfaces in chemistry, disordered systems and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed

Modeling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India

Does Indian sovereign yield volatility reflect economic fundamentals, or whether it is a self-generated force flowing through markets with little connection to such fundamentals? To answer the question, this research explores the volatility dynamics and measures the persistence of shocks to the sovereign bond yield volatility in India from 1 January 2016, to 18 May 2022, using a family of GARCH models. The empirical results indicate the high volatility persistence across the maturity spectrum in the sample period. However, upon decomposing the markets into bull and bear phases, our results support the existence of weak volatility persistence and rapid mean reversion in the bear market. This shows that the economic response policies implemented by the government during the pandemic, including fiscal measures, have a restraining effect on sovereign yield volatility. For a positive γ, the results suggest the possibility of a “leverage effect” that is markedly different from that frequently seen in stock markets. Results further indicate that the fluctuations in Indian sovereign yields cannot be dissociated from inflation and money market volatility. Our findings herein provide valuable information and implications for policymakers and financial investors worldwide

Encapsulation of olanzapine into beeswax microspheres: preparation, characterization and release kinetics

The objective of the present study was to minimise the unwanted side effects of olanzapine (OZ) drug by kinetic control of drug release by entrapping into gastro resistant, biodegradable waxes such as beeswax (BW) microspheres using meltable emulsified dispersion cooling induced solidification technique utilizing a wetting agent. Solid, discrete, reproducible free flowing microspheres were obtained. The yield of the microspheres was up to 94.0 %. The microspheres had smooth surfaces, with free flowing and good packing properties, indicating that the obtained angle of repose, % Carr’s index and tapped density values were well within the limit. More than 97.0 % of the isolated spherical microspheres were in the particle size range of 312-330 μm were confirmed by scanning electron microscopy (SEM) photographs. The drug loaded in microspheres was stable and compatible, as confirmed by DSC and FTIR studies. The release of drug was controlled for more than 8 h. Intestinal drug release from microspheres was studied and compared with the release behaviour of commercially available formulation Olanex®. The release kinetics followed different transport mechanisms. The drug release from the bees wax microspheres was found sufficient for oral delivery and the drug release profile was significantly affected by the properties of wax used in the preparation of microspheres. These results demonstrate the potential use of wax for the fabrication of controlled delivery devices for many water soluble drugs.Colegio de Farmacéuticos de la Provincia de Buenos Aire

The complexity of the Pk partition problem and related problems in bipartite graphs

International audienceIn this paper, we continue the investigation made in [MT05] about the approximability of Pk partition problems, but focusing here on their complexity. Precisely, we aim at designing the frontier between polynomial and NP-complete versions of the Pk partition problem in bipartite graphs, according to both the constant k and the maximum degree of the input graph. We actually extend the obtained results to more general classes of problems, namely, the minimum k-path partition problem and the maximum Pk packing problem. Moreover, we propose some simple approximation algorithms for those problems

Hierarchies and Ranks for Persistence Pairs

We develop a novel hierarchy for zero-dimensional persistence pairs, i.e., connected components, which is capable of capturing more fine-grained spatial relations between persistence pairs. Our work is motivated by a lack of spatial relationships between features in persistence diagrams, leading to a limited expressive power. We build upon a recently-introduced hierarchy of pairs in persistence diagrams that augments the pairing stored in persistence diagrams with information about which components merge. Our proposed hierarchy captures differences in branching structure. Moreover, we show how to use our hierarchy to measure the spatial stability of a pairing and we define a rank function for persistence pairs and demonstrate different applications.Comment: Topology-based Methods in Visualization 201