Chaos synchronization between two different fractional systems of Lorenz family

This work investigates chaos synchronization between two different fractional order chaotic systems of Lorenz family. The fractional order Lü system is controlled to be the fractional order Chen system, and the fractional order Chen system is controlled to be the fractional order Lorenzlike system. The analytical conditions for the synchronization of these pairs of different fractional order chaotic systems are derived by utilizing Laplace transform. Numerical simulations are used to verify the theoretical analysis using different values of the fractional order parameter

Chaos Synchronization between Two Different Fractional Systems of Lorenz Family

This work investigates chaos synchronization between two different fractional order chaotic systems of Lorenz family. The fractional order Lü system is controlled to be the fractional order Chen system, and the fractional order Chen system is controlled to be the fractional order Lorenz-like system. The analytical conditions for the synchronization of these pairs of different fractional order chaotic systems are derived by utilizing Laplace transform. Numerical simulations are used to verify the theoretical analysis using different values of the fractional order parameter

On New Generalized Ostrowski Type Integral Inequalities

The Ostrowski inequality expresses bounds on the deviation of a function from its integral mean. The aim of this paper is to establish some new inequalities similar to the Ostrowski's inequality. The current paper obtains bounds for the deviation of a function from a combination of integral means over the end intervals covering the entire interval in terms of the norms of the second derivative of the function. Some new perturbed results are obtained. Application for cumulative distribution function is also discussed

Routh-Hurwitz Stability and Quasiperiodic Attractors in a Fractional-Order Model for Awareness Programs: Applications to COVID-19 Pandemic

This work explores Routh-Hurwitz stability and complex dynamics in models for awareness programs to mitigate the spread of epidemics. Here, the investigated models are the integer-order model for awareness programs and their corresponding fractional form. A non-negative solution is shown to exist inside the globally attracting set (GAS) of the fractional model. It is also shown that the diseasefree steady state is locally asymptotically stable (LAS) given that R0 is less than one, where R0 is the basic reproduction number. However, as R0>1, an endemic steady state is created whose stability analysis is studied according to the extended fractional Routh-Hurwitz scheme, as the order lies in the interval (0,2]. Furthermore, the proposed awareness program models are numerically simulated based on the predictor-corrector algorithm and some clinical data of the COVID-19 pandemic in KSA. Besides, the model's basic reproduction number in KSA is calculated using the selected data R0=1.977828168. In conclusion, the findings indicate the effectiveness of fractional-order calculus to simulate, predict, and control the spread of epidemiological diseases. © 2022 Taher S. Hassan et al

Aerosolized BC-819 Inhibits Primary but Not Secondary Lung Cancer Growth

Despite numerous efforts, drug based treatments for patients suffering from lung cancer remains poor. As a promising alternative, we investigated the therapeutic potential of BC-819 for the treatment of lung cancer in mouse tumor models. BC-819 is a novel plasmid DNA which encodes for the A-fragment of Diphtheria toxin and has previously been shown to successfully inhibit tumor growth in human clinical study of bladder carcinoma. In a first set of experiments, we examined in vitro efficacy of BC-819 in human lung cancer cell-lines NCI-H460, NCI-H358 and A549, which revealed >90% reduction of cell growth. In vivo efficacy was examined in an orthotopic mouse xenograft lung cancer model and in a lung metastasis model using luminescent A549-C8-luc adenocarcinoma cells. These cells resulted in peri- and intra-bronchiolar tumors upon intrabronchial application and parenchymal tumors upon intravenous injection, respectively. Mice suffering from these lung tumors were treated with BC-819, complexed to branched polyethylenimine (PEI) and aerosolized to the mice once per week for a period of 10 weeks. Using this regimen, growth of intrabronchially induced lung tumors was significantly inhibited (p = 0.01), whereas no effect could be observed in mice suffering from lung metastasis. In summary, we suggest that aerosolized PEI/BC-819 is capable of reducing growth only in tumors arising from the luminal part of the airways and are therefore directly accessible for inhaled BC-819

The non-coding transcriptome as a dynamic regulator of cancer metastasis.

Since the discovery of microRNAs, non-coding RNAs (NC-RNAs) have increasingly attracted the attention of cancer investigators. Two classes of NC-RNAs are emerging as putative metastasis-related genes: long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs). LncRNAs orchestrate metastatic progression through several mechanisms, including the interaction with epigenetic effectors, splicing control and generation of microRNA-like molecules. In contrast, snoRNAs have been long considered "housekeeping" genes with no relevant function in cancer. However, recent evidence challenges this assumption, indicating that some snoRNAs are deregulated in cancer cells and may play a specific role in metastasis. Interestingly, snoRNAs and lncRNAs share several mechanisms of action, and might synergize with protein-coding genes to generate a specific cellular phenotype. This evidence suggests that the current paradigm of metastatic progression is incomplete. We propose that NC-RNAs are organized in complex interactive networks which orchestrate cellular phenotypic plasticity. Since plasticity is critical for cancer cell metastasis, we suggest that a molecular interactome composed by both NC-RNAs and proteins orchestrates cancer metastasis. Interestingly, expression of lncRNAs and snoRNAs can be detected in biological fluids, making them potentially useful biomarkers. NC-RNA expression profiles in human neoplasms have been associated with patients' prognosis. SnoRNA and lncRNA silencing in pre-clinical models leads to cancer cell death and/or metastasis prevention, suggesting they can be investigated as novel therapeutic targets. Based on the literature to date, we critically discuss how the NC-RNA interactome can be explored and manipulated to generate more effective diagnostic, prognostic, and therapeutic strategies for metastatic neoplasms

lncRNAdb: a reference database for long noncoding RNAs

Large numbers of long RNAs with little or no protein-coding potential [long noncoding RNAs (lncRNAs)] are being identified in eukaryotes. In parallel, increasing data describing the expression profiles, molecular features and functions of individual lncRNAs in a variety of systems are accumulating. To enable the systematic compilation and updating of this information, we have developed a database (lncRNAdb) containing a comprehensive list of lncRNAs that have been shown to have, or to be associated with, biological functions in eukaryotes, as well as messenger RNAs that have regulatory roles. Each entry contains referenced information about the RNA, including sequences, structural information, genomic context, expression, subcellular localization, conservation, functional evidence and other relevant information. lncRNAdb can be searched by querying published RNA names and aliases, sequences, species and associated protein-coding genes, as well as terms contained in the annotations, such as the tissues in which the transcripts are expressed and associated diseases. In addition, lncRNAdb is linked to the UCSC Genome Browser for visualization and Noncoding RNA Expression Database (NRED) for expression information from a variety of sources. lncRNAdb provides a platform for the ongoing collation of the literature pertaining to lncRNAs and their association with other genomic elements. lncRNAdb can be accessed at: http://www.lncrnadb.org/