Dayaolingzhiols A−E,AchE inhibitory meroterpenoids from Ganoderma lucidum

Ganoderma mushrooms are widely used as effective medicines for treating and preventing chronic diseases. In this study, five new meroterpenoids, dayaolingzhiols A (1) and B (2) featuring a 6/6/6 ring system, dayaolingzhiols C?E (3–5) harboring a γ-lactone motif, along with eight known ones (6–13), were purified from G. lucidum. To clarify their chemical structures, spectroscopic and ECD and OR computational methods were used. In addition, the inhibition of all the new meroterpenoids against AChE was evaluated, disclosing that (+)-4 and (±)-5 possess potent AChE inhibitory activities with respective IC₅₀ values of 8.52?±?1.90?μM and 7.37?±?0.52?μM.     

Central Sets Theorem along filters and some combinatorial consequences

The Central Sets Theorem was introduced by H. Furstenberg and then afterwards several mathematicians have provided various versions and extensions of this theorem. All of these theorems deal with central sets, and its origin from the algebra of Stone–?ech compactification of arbitrary semigroup, say $\beta S$. It can be proved that every closed subsemigroup of $\beta S$ is generated by a filter. We will show that, under some restrictions, one can derive the Central Sets Theorem for any closed subsemigroup of $\beta S$. We will derive this theorem using the corresponding filter and its algebra. Later we will also deal with how the notions of largeness along filters are preserved under some well behaved homomorphisms and give some consequences.     

Nanoproteomic Approach for Isolation and Identification of Potential Biomarkers in Human Urine from Adults with Normal Weight,Overweight and Obesity

In this work, previously synthesized and characterized core-shell silica nanoparticles (FCSNP) functionalized with immobilized molecular bait, Cibacron blue, and a porous polymeric bis-acrylamide shell were incubated with pooled urine samples from adult women or men with normal weight, overweight or obesity for the isolation of potential biomarkers. A total of 30 individuals (15 woman and 15 men) were included. FCSNP allowed the capture of a variety of low molecular weight (LMW) proteins as evidenced by mass spectrometry (MS) and the exclusion of high molecular weight (HMW) proteins (>34 kDa) as demonstrated by SDS-PAGE and 2D SDS-PAGE. A total of 36 proteins were successfully identified by MS and homology database searching against the Homo sapiens subset of the Swiss-Prot database. Identified proteins were grouped into different clusters according to their abundance patterns. Four proteins were found only in women and five only in men, whereas 27 proteins were in urine from both genders with different abundance patterns. Based on these results, this new approach represents an alternative tool for isolation and identification of urinary biomarkers.     

Functional analysis of repositioned anilide derivatives as anticancer compounds

Off the different types cancers 40% of the population have been observed to be affected by leukemia. Contemporary therapeutics is focusing on generation of new synthetic analogues that can exert maximum positive physiological effect with minimum dosage and negligible deleterious side effects. New generation pharmacists are focusing on such promising effects of Imatinib (a potential anti-cancer drug molecule), Dasatinib, Pelitinib and Nilotinib. The present research study focuses on novel synthesized anilides derivative against BCR-ABL kinase as potential anti-leukemic agent. Validation of the compounds by molecular docking with specific BCR-ABL kinase confirmed their activity. Toxicity prediction of these compounds helped to identify sustainability as therapeutic molecules. The IC₅₀ values were calculated (211 ug, 175 ug, 272ug for compounds A, B, C resp.) and the mode of cell death was gauged by DNA laddering assay. The cells were observed to be induced for programmed cell death. By validating and in-vivo testing of three synthesized compounds, the compound B was observed to be more stable thermodynamically with a potentially vital active site and appears to be a promising anti-leukemic factor. The present research thus lays a preliminary platform in world of pharmaceutics, where these new analogues appear to be efficient, target specific and less toxic molecules.     

On a Lyapunov-type inequality and the zeros of a certain Mittag–Leffler function

In this work, a Lyapunov-type inequality is obtained for the case when one is dealing with a fractional differential boundary value problem. We then use that result to obtain an interval where a certain Mittag–Leffler function has no real zeros.     

Network-based ranking methods for prediction of novel disease associated microRNAs

BackgroundMany studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a “disease module” principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the “disease module” principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction.MethodsWe constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm.ResultsAnalyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In addition, the performance of PRINCE, PRP and KSM was comparable with that of RWR, whereas it was worst for the neighborhood-based algorithm. Moreover, all the algorithms were stable with the change of parameters. Final, using the integrated network, we predicted six novel miRNAs (i.e., hsa-miR-101, hsa-miR-181d, hsa-miR-192, hsa-miR-423-3p, hsa-miR-484 and hsa-miR-98) associated with breast cancer.ConclusionsNetwork-based ranking algorithms, which were successfully applied for either disease gene prediction or for studying social/web networks, can be also used effectively for disease microRNA prediction.     

A canonical module characterization of Serre’s (R1)

In this short note, we give a characterization of domains satisfying Serre’s condition (R₁) in terms of their canonical modules. In the special case of toric rings, this generalizes a result of the second author [9 Yanagawa, K. (2015). Dualizing complexes of seminormal a?ne semigroup rings and toric face rings. J. Algebra 425:367–391.[Crossref], [Web of Science ®] , [Google Scholar]] where the normality is described in terms of the “shape” of the canonical module.     

Constructing affine Lie algebras

The ?-grading determined by a long simple root of a rank n+1 a?ne Lie algebra over ? arises from a representation of a rank n semi-simple complex Lie algebra. Analysis of the relationship between the grading and the representation yields constructions that generalize the minuscule and adjoint algorithms as well as Kac’s construction of nontwisted a?ne Lie algebras.     

Necessary and Sufficient Conditions for Weak Quasi Efficiency in Nonsmooth Multiobjective Problems

In this article, a multiobjective problem with a feasible set defined by inequality, equality and set constraints is considered, where the objective and constraint functions are locally Lipschitz. Several constraint qualifications are given and the relations between them are analyzed. We establish Kuhn-Tucker and strong Kuhn-Tucker necessary optimality conditions for (weak) quasi e?ciency in terms of the Clarke subdifferential. By using two new classes of generalized convex functions, su?cient conditions for local (weak) quasi e?cient are also provided. Furthermore, we study the Mond-Weir type dual problem and establish weak, strong and converse duality results.     

Proximal-gradient algorithms for fractional programming

In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a proximal step with respect to the nonsmooth numerator and a gradient step with respect to the smooth denominator. The algorithm in case of a concave denominator has the particularity that it generates sequences which approach both the (global) optimal solutions set and the optimal objective value of the underlying fractional programming problem. In case of a convex denominator the numerical scheme approaches the set of critical points of the objective function, provided the latter satisfies the Kurdyka-?ojasiewicz property.