Epigenetics in Canine Mammary Tumors: Upregulation of miR-18a and miR-18b Oncogenes Is Associated with Decreased ERS1 Target mRNA Expression and ERα Immunoexpression in Highly Proliferating Carcinomas

The expression of miRNAs is one of the main epigenetic mechanisms responsible for the regulation of gene expression in mammals, and in cancer, miRNAs participate by regulating the expression of protein-coding cancer-associated genes. In canine mammary tumors (CMTs), the ESR1 gene encodes for ERa, and represents a major target gene for miR-18a and miR-18b, previously found to be overexpressed in mammary carcinomas. A loss in ERa expression in CMTs is commonly associated with poor prognosis, and it is noteworthy that the downregulation of the ESR1 would appear to be more epigenetic than genetic in nature. In this study, the expression of ESR1 mRNA in formalin-fixed, paraffin-embedded (FFPE) canine mammary tumors (CMTs) was evaluated and compared with the expression levels of miR18a and miR18b, both assessed via RT-qPCR. Furthermore, the possible correlation between the miRNA expression data and the immunohistochemical prognostic factors (ERa immunoexpression; Ki67 proliferative index) was explored. A total of twenty-six FFPE mammary samples were used, including 22 CMTs (7 benign; 15 malignant) and four control samples (three normal mammary glands and one case of lobular hyperplasia). The obtained results demonstrate that miR-18a and miR-18b are upregulated in malignant CMTs, negatively correlating with the expression of target ESR1 mRNA. Of note, the upregulation of miRNAs strictly reflects the progressive loss of ERa immunoexpression and increased tumor cell proliferation as measured using the Ki67 index. The results suggest a central role of miR-18a and miR-18b in the pathophysiology of canine mammary tumors as potential epigenetic mechanisms involved in ERa downregulation. Moreover, as miRNA expression reflects ERa protein status and a high proliferative index, miR-18a and miR-18b may represent promising biomarkers with prognostic value. More detailed investigations on a larger number of cases are needed to better understand the influence of these miRNAs in canine mammary tumors

Nondestructive Evaluation of Coatings

Bulk and Rayleigh (or surface wave) velocities of ultrasonic waves in chromium coatings on steel were measured and an experimental correlation was found between the surface velocity and the hardness. Since qualitative coating evaluation is commonly made using hardnesses as a guideline, the possibility is herewith presented of using the sound velocities of surface ultrasonic waves for this purpose. This provides the advantage of using a nondestructive technique over one that is destructive and more qualitative

Soft tissue regeneration using leukocyte-platelet rich fibrin after exeresis of hyperplastic gingival lesions: Two case reports

Introduction The Leukocyte-PRF (Leukocyte-Platelet Rich Fibrin) belongs to a second generation of platelet concentrates which doesn’t need a biochemical blood manipulation. It is used for tissue healing and regeneration in periodontal and oral-maxillofacial surgery. We report two cases of hyperplastic gingival lesions treated by exeresis and application of PRF membranes in order to improve and accelerate tissue healing. Case Presentation Two patients (one Caucasian female, 78-year-old, and one Caucasian male, 30-year-old) were treated for hyperplastic gingival lesions. They underwent to exeresis of lesions and application of PRF membranes. Tissue healing was clinically evaluated after one, three, seven, fourteen and thirty post-operative days. No recurrences were observed after two years of semiannual follow up. Conclusion We obtained rapid and good healing of soft tissues probably due to the elevated content of leukocytes, platelets and growth factors in the leukocyte-platelet rich fibrin. According to our results we suggest L-PRF employment for wounds covering after exeresis of oral neoformations such as hyperplastic gingival lesions

PICKING THE BEST NOVEL ORAL ANTICOAGULANT FOR ATRIAL FIBRILLATION: EVIDENCE FROM A WARFARIN-CONTROLLED NETWORK META-ANALYSIS

Warfarin is a mainstay atrial ibrillation (AF) treatment, yet it has a narrow therapeutic window. Novel agents have been successfully tested against warfarin, yet no direct comparison among them is available. We thus performed a pair-wise and warfarin-adjusted network metaanalyses of novel oral anticoagulants for AF

Influence of eNOS Gene Polymorphisms on Carotid Atherosclerosis

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Structural Analysis of the Western Afar Margin, East Africa: Evidence for Multiphase Rotational Rifting

The Afar region in East Africa represents a key location to study continental breakup. We present an integrated structural analysis of the Western Afar Margin (WAM) aiming to better understand rifted margin development and the role of plate rotation during rifting. New structural information from remote sensing, fieldwork, and earthquake data sets reveals that the N-S striking WAM is still actively deforming and is characterized by NNW-SSE normal faulting as well as a series of marginal grabens. Seismicity distribution analysis and the first-ever borehole-calibrated sections of this developing passive margin show recent slip concentrated along antithetic faults. Tectonic stress parameters derived from earthquake focal mechanisms reveal different extension directions along the WAM (82°N), in Afar (66°N) and in the Main Ethiopian Rift (108°N). Fault slip analysis along the WAM yields the same extension direction. Combined with GPS data, this shows that current tectonics in Afar is dominated by the local rotation of the Danakil Block, considered to have occurred since 11 Ma. Earlier stages of Afar development (since 31–25 Ma) were most likely related to the large-scale rotation of the Arabian plate. Various authors have proposed scenarios for the evolution of the WAM. Any complete model should consider, among other factors, the multiphase tectonic history and antithetic fault activity of the margin. The findings of this study are not only relevant for a better understanding of the WAM but also provide insights into the role of multiphase rotational extension during rifting and passive margin formation in general.</p

Strategies to develop radiomics and machine learning models for lung cancer stage and histology prediction using small data samples

Predictive models based on radiomics and machine-learning (ML) need large and annotated datasets for training, often difficult to collect. We designed an operative pipeline for model training to exploit data already available to the scientific community. The aim of this work was to explore the capability of radiomic features in predicting tumor histology and stage in patients with non-small cell lung cancer (NSCLC). We analyzed the radiotherapy planning thoracic CT scans of a proprietary sample of 47 subjects (L-RT) and integrated this dataset with a publicly available set of 130 patients from the MAASTRO NSCLC collection (Lung1). We implemented intra- and inter-sample cross-validation strategies (CV) for evaluating the ML predictive model performances with not so large datasets. We carried out two classification tasks: histology classification (3 classes) and overall stage classification (two classes: stage I and II). In the first task, the best performance was obtained by a Random Forest classifier, once the analysis has been restricted to stage I and II tumors of the Lung1 and L-RT merged dataset (AUC = 0.72 ± 0.11). For the overall stage classification, the best results were obtained when training on Lung1 and testing of L-RT dataset (AUC = 0.72 ± 0.04 for Random Forest and AUC = 0.84 ± 0.03 for linear-kernel Support Vector Machine). According to the classification task to be accomplished and to the heterogeneity of the available dataset(s), different CV strategies have to be explored and compared to make a robust assessment of the potential of a predictive model based on radiomics and ML