MicroRNAs (miRNAs) represent a class of small, non-coding RNAs with the main roles of regulating mRNA through its degradation and adjusting protein levels. In recent years, extraordinary progress has been made in terms of identifying the origin and exact functions of miRNA, focusing on their potential use in both the research and the clinical field. This review aims at improving the current understanding of these molecules and their applicability in the medical field. A thorough analysis of the literature consulting resources available in online databases such as NCBI, PubMed, Medline, ScienceDirect, and UpToDate was performed. There is promising evidence that in spite of the lack of standardized protocols regarding the use of miRNAs in current clinical practice, they constitute a reliable tool for future use. These molecules meet most of the required criteria for being an ideal biomarker, such as accessibility, high specificity, and sensitivity. Despite present limitations, miRNAs as biomarkers for various conditions remain an impressive research field. As current techniques evolve, we anticipate that miRNAs will become a routine approach in the development of personalized patient profiles, thus permitting more specific therapeutic interventions.Biogenesis of miRNA begins in the nucleus, where the transcription of its precursor, primary miRNA or pri-miRNA takes place under the influence of RNA polymerases II and III [11,12]. The resulting molecule is a hairpin-like structure, which contains a loop at one end [11]. This primordial mi-RNA precursor that is usually made up of hundreds of nucleotides is then processed consecutively by two RNase III enzymes [13][14][15]. The first enzyme to act upon the pri-miRNA, which still resides in the nucleus, is called Drosha or DCGR8, and turns it into a new hairpin-like structure of approximately 70 nucleotides, the Precursor-miRNA or pre-miRNA. The latter is then transported to the cytoplasm, with the help of Exportin-5, where it is cleaved again by the Ago2/Dicer complex leading to the short, mature miRNA double strands [16].Further on, one of the strands, usually known as the guide strand, will be integrated into the RNA-induced silencing complex (RISC), while the other one, known as the passenger strand, is going to be degraded, even though in some occasions it has been found to be also functional [17]. In most cases, the strand that contains the less stable 5 end or a uracil at the beginning is more likely to be selected as the guide strand [18][19][20]. In those situations, where the passenger strand is not degraded and both get incorporated into the miRISC complex, the mature miRNA in the guide strand will be the dominant one [21,22].The main role of miRNA in the human body is gene regulation [23] by mediating the degradation of mRNA and also by regulating transcription and translation through canonical and non-canonical mechanisms [4]. The canonical mechanism means that the miRISC complex containing the miRNA guide strand is exerting its action by binding to the targ...

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[1] Darcy velocities for lognormal hydraulic conductivity with small variance and finite correlation length were approximated by periodic random fields. Accurate simulations of two-dimensional advection-dispersion processes were achieved with the global random walk algorithm, using 10 10 particles in every transport realization. Reliable statistical estimations were obtained by averaging over 256 realizations. The main result is a numerical evidence for the mean square convergence of the actual concentrations to the macrodispersion process predicted by a known limit theorem. For small initial plumes the ergodic behavior can be expected after thousands of advection timescales, when the deviation from the theoretical prediction of the cross-section space-averaged concentration monotonously decays and falls under 20%. The increase of the transverse dimension of the initial plume slows down the approach to the quasi-ergodic state and has a nonlinear effect on the variability of the actual concentrations and dispersivities.

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The North-West Inter Regional Female Cohort for Patients with Endometriosis (CIRENDO) is financed by the G4 Group (The University Hospitals of Rouen, Lille, Amiens and Caen). No financial support was specifically received for this study. The authors declare no conflict of interest.

Ovarian cancer has the highest mortality rate among gynecological cancers. Early clinical signs are missing and there is an urgent need to establish early diagnosis biomarkers. MicroRNAs are promising biomarkers in this respect. In this paper, we review the most recent advances regarding the alterations of microRNAs in ovarian cancer. We have briefly described the contribution of miRNAs in the mechanisms of ovarian cancer invasion, metastasis, and chemotherapy sensitivity. We have also summarized the alterations underwent by microRNAs in solid ovarian tumors, in animal models for ovarian cancer, and in various ovarian cancer cell lines as compared to previous reviews that were only focused the circulating microRNAs as biomarkers. In this context, we consider that the biomarker screening should not be limited to circulating microRNAs per se, but rather to the simultaneous detection of the same microRNA alteration in solid tumors, in order to understand the differences between the detection of nucleic acids in early vs. late stages of cancer. Moreover, in vitro and in vivo models should also validate these microRNAs, which could be very helpful as preclinical testing platforms for pharmacological and/or molecular genetic approaches targeting microRNAs. The enormous quantity of data produced by preclinical and clinical studies regarding the role of microRNAs that act synergistically in tumorigenesis mechanisms that are associated with ovarian cancer subtypes, should be gathered, integrated, and compared by adequate methods, including molecular clustering. In this respect, molecular clustering analysis should contribute to the discovery of best biomarkers-based microRNAs assays that will enable rapid, efficient, and cost-effective detection of ovarian cancer in early stages. In conclusion, identifying the appropriate microRNAs as clinical biomarkers in ovarian cancer might improve the life quality of patients.

A generalized form of the random walk algorithm to simulate diffusion processes is introduced. Unlike the usual approach, at a given time all the particles from a grid node are simultaneously scattered using the Bernoulli repartition. This procedure saves memory and computing time and no restrictions are imposed for the maximum number of particles to be used in simulations. We prove that for simple diffusion the method generalizes the finite difference scheme and gives the same precision for large enough number of particles. As an example, simulations of diffusion in random velocity field are performed and the main features of the stochastic mathematical model are numerically tested.Subject Classification: 65C35, 82C80, 82C70, 76S05