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Abstract Background and aim Galectins have been recently tackled by many researchers in the field of cancer due to their role in tumorigenesis, disease progression, and metastasis. Thus, they are currently involved in biomarkers research on several types of cancer. In ovarian cancers, few studies were carried out to evaluate galectins expression profiling. Hence, our present study was executed to evaluate the mRNA expression of galectins -1, -3, -4, -8, and -9 in epithelial ovarian cancers. Methods Fifty-six tumor samples of ovarian carcinomas were analyzed for mRNA expression using qRT-PCR, and fold-changes were calculated in comparison to tissue samples of 26 women with normal ovaries. Results The results of the present paper emphasize the importance of galectins as predictors for targeted therapy. LGALS1, LGALS3, LGALS4, LGALS8, and LGALS9 were found to be mostly overexpressed in ovarian carcinoma patients with the following percentage: 78.6%, 92.9%, 66.1%, 87.5%, and 85.7% respectively. Moreover, galectins -3 and -9 were found to be significantly elevated with lymph node metastasis (p = 0.044 and p = 0.011). Also, upregulation of galectin-1 and -9 were statistically significant in stages IIB, IIC, and IIIB (p = 0.002) in FIGO staging. CA19.9 is positively correlated to galectin-4 expression (p = 0.039). Conclusion Our findings strengthen the role of galectins in carcinogenesis, disease progression, and lymphnode metastasis in ovarian carcinomas. And since these galectins are mostly overexpressed, they could be promising markers for targeted therapy to reduce disease progression and metastasis process.

The paper explores the Kullback-Leibler divergence formalism (KLDF) applied to stable queue manifold. More potentially, both service time probability and cumulative functions, which make KLDF exact, are obtained. The credibility of KLDF is justified through consistency axioms. In other words, the current work provides a cutting-edge unification of information theory, combined with applied probability and divergence theory. Accordingly, this paper adds new knowledge, which extends a novel contemporary information theoretic link to some other different mathematical disciplines. The significance of Kullback-Leibler divergence (KLD) is highlighted through references to some potential applications of KLD to biometry. [ABSTRACT FROM AUTHOR]

This study of text discusses the analysis of the CDFs of service time in the stable M/G/1 queueing system with 'longrange interactions' of order q (where 0.5 < q < 1). This letter makes a significant contribution since it uses a novel methodology to show how the order q and the Lagrangian multiplier τs affect the increasability and decreasability themes of T-R CDFs. Additionally, the numerical data sets to show the validity of our analytical proofs are introduced. Some Tsallisian and Rényian Entropic applications to SIs are provided. Closing remarks entailed with the next phase of research are given. [ABSTRACT FROM AUTHOR]

A theoretical approach for creating power law behaviour in broadband communication networks with GeoM or SGeoM specifications utilizing the Rényian maximum entropy functional formalism is undertaken. When specifying the SGeoM, the special case of M/M/1 queue's equilibrium distribution emerges. The suggested method simplifies closed-form equations for a queueing distribution, and the service time density and cumulative distribution functions reduce to the appropriate Rényian, Tsallisian, and Shannonian situations. The concept works well in power law activated - communication networks. Some influential applications of GeoM to WSNs are provided. [ABSTRACT FROM AUTHOR]

An exposition is undertaken for the threshold of both Rényian and Tsallisian steady-state probabilities of the stable queueing system with 'long-range interactions' (LRIs). The current work is pivotal for developing revolutionary queueing theory and providing ground-breaking queueingtheoretic unifications with other scientific disciplines. The significance of the novel results of the current letter is based on the novelty of employing a mathematical approach to reveal the impact of the queueing parameters on the decidability procedure on the regions of increasability (decreasability). The numerical data sets to show the validity of our analytical proofs are introduced. Some influential applications of the probability density function (PDF) are presented. Finally, conclusions combined with some challenging open problems combined with the next phase of research are provided. [ABSTRACT FROM AUTHOR]

An exposition is undertaken to solve the open problem of finding the exact analytic closed form solution for GI/M/1 PSFFA model of the D/M/1 queueing system. This paper reveals the general revolutionary analytic solution to this open problem. Moreover, the closed form representation of the root parameter, σ(t), 1 > σ(t) > 0 is devised. Another contribution of this paper is determining the thresholds of the root parameter with respect to both time and the timedependent mean arrival rate, λ(t) are determined. Moreover, the thresholds of the derived analytic solution with respect to time-dependent mean arrival rate, λ(t) is devised. Typical numerical experiments to evidence the significant impact of time, time dependent mean arrival rate of the underlying time varying GI/M/1 queueing system as well as the time dependent root parameter, σ(t), 1 > σ(t) > 0, of the geometric distribution of the new arrival of the GI/M/1 model is given. Some potential applications of PSFFA theory to computer science, engineering and technology works are given. Closing remarks with proposed next research phases are provided. [ABSTRACT FROM AUTHOR]

An exposition is undertaken for the linearity of both stable M/G/1 queue's non-extensive (Rényian)and (Tsallisian) solutions. This current letter provides the mathematical validity for the experimental setup of the information theoretic unification with queueing theory manifested by the Rényian, and Tsallisian linearity profile attained, which is a consequence of the progressive increase of the Shannonian squared coefficient of variation, through the provision of the mathematical proof. Potential applications of Queueing Theory (QT) to Cloud Computing (CC) and Internet of Things(IoT) are given. Closing remarks combined with open problems and future next phase research are provided. [ABSTRACT FROM AUTHOR]

An explanation is made for the stable M/G/1 queueing system's threshold of Rényian and Tsallisian squared coefficient of variation (SCV) with "long-range interactions" of order, q (0.5

Information geometry, (IG), is an ever-growing area with a great scope of applications ranging from Probability & Statistics, Machine Learning (ML), Artificial Intelligence (AI), Signal Processing, Mathematical Programming, etc., There is always a great race to distil information from data to models. Since its inception, IG as a concept has been known under a variety of guises and been used in numerous contexts, establishing an almost rock-star status in both sciences and popular culture. The three most prominent "styles" which IG has been (re)told in and which have determined its popularity are Deep Learning, Statistical learning, and Machine Learning. Following the footsteps of the relentless hunt for the core of the concept that kindled this underlying development, connections with emergence of time combined with irreversibility, the elegant nature of probability and the generated information which add to its illusiveness as much as simulating its cross-contextual adoption and proliferation. In this review, we search and retrace through the five main perspectives from which IG has been regarded, emphasizing the motivations behind each application, their ramifications as well as the bridges that have been constructed to justify them. Consequently, this analysis of the foundations provides a beautiful panorama of several characteristic traits of the concept that underline its significance and exceptionality as an engine of conceptual progress [ABSTRACT FROM AUTHOR]