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BACKGROUND: Cardiovascular disease is a global health concern and reducing plasma LDL-C levels is a major goal in cardiovascular prevention. Our study aimed to evaluate the effectiveness of a nutraceutical formulation including leucoselect® phytosome®, red yeast rice, policosanol and folic acid on LDL-c levels in patients at low cardiovascular risk with dyslipidemia. MATERIALS AND METHODS: We prospectively enrolled all consecutive patients with dyslipidemia at low cardiovascular risk who were unresponsive to diet and physical activity. Clinical assessments and laboratory analyses, encompassing lipid profile, hepatic function, and CPK levels, were performed at baseline prior to initiating treatment and repeated at the 12-week mark following administration of the study nutraceutical. RESULTS: Sixty (60) consecutive patients (mean age 48.02 ± 10.1 years; 60% male) were included. At the 12-week follow-up, a statistically significant reduction in Total Cholesterol (13.1%) and LDL-c serum level (20.4%) was observed. Hepatic and muscular function remain stable over the time. The adherence to therapy was 99% and the persistence was maximum. CONCLUSIONS: The nutraceutical formulation including leucoselect® phytosome® red yeast rice, policosanol and folic acid significantly reduced the LDL-c plasma levels, consistent with previous research showing that the bioactive component in red yeast rice-lovastatin-is effective in addressing problems with lipid metabolism. Importantly, it was safe and well-tolerated among patients with dyslipidemia in a real-world setting.
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In the context of upcoming large-scale surveys like Euclid, the necessity for the automation of strong lens detection is essential. While existing machine learning pipelines heavily rely on the classification probability (P), this study intends to address the importance of integrating additional metrics, such as Information Content (IC) and the number of pixels above the segmentation threshold ([Formula: see text]), to alleviate the false positive rate in unbalanced data-sets. In this work, we introduce a segmentation algorithm (U-Net) as a supplementary step in the established strong gravitational lens identification pipeline (Denselens), which primarily utilizes [Formula: see text] and [Formula: see text] parameters for the detection and ranking. The results demonstrate that the inclusion of segmentation enables significant reduction of false positives by approximately 25 per cent in the final sample extracted from DenseLens, without compromising the identification of strong lenses. The main objective of this study is to automate the strong lens detection process by integrating these three metrics. To achieve this, a decision tree-based selection process is introduced, applied to the Kilo Degree Survey (KiDS) data. This process involves rank-ordering based on classification scores ([Formula: see text]), filtering based on Information Content ([Formula: see text]), and segmentation score ([Formula: see text]). Additionally, the study presents 14 newly discovered strong lensing candidates identified by the U-Denselens network using the KiDS DR4 data.
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Optimizing the anticoagulation therapy is of pivotal importance in patients with a malignant tumor, as venous thromboembolism (VTE) has become the second-leading cause of death in this population. Cancer can highly increase the risk of thrombosis and bleeding. Consequently, the management of cancer-associated VTE is complex. In recent years, translational research has intensified, and several studies have highlighted the role of inflammatory cytokines in cancer growth and progression. Simultaneously, the pleiotropic effects of anticoagulants currently recommended for VTE have emerged. In this review, we describe the anti-inflammatory and anticancer effects of both direct oral anticoagulants (DOACs) and low-molecular-weight heparins (LWMHs).
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Identifying coastal tracts suitable for sea turtle reproduction is crucial for sea turtle conservation in a context of fast coastal development and climate change. In contrast to nesting aggregations, diffuse nesting is elusive and assessing nesting levels is challenging. A total of 323 nesting events by the loggerhead sea turtle Caretta caretta have been reported in Sicily, the largest Mediterranean island, in the 1944-2021 period, mostly in the last decade. Specific monitoring efforts are the most likely explanation for such an increase and shows that sea turtle nesting may be underestimated or completely ignored in many areas with scattered nesting. The real nesting level along the 464 km sandy shores of Sicily is still unknown and more research is needed. The observed incubation period was relatively long (57 d) suggesting that a majority of males are produced in Sicily, in contrast to the typical female-biased sex ratio of sea turtles. In a context of climate warming producing sex ratios more skewed towards females, the potential of Sicily as a male-producing area should be further investigated. Other reproductive parameters are provided, such as clutch size and hatching and emergence success. A negative effect of relocation on the latter two was observed.
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The kinematics of the outer parts of three intermediate-luminosity elliptical galaxies were studied with the Planetary Nebula Spectrograph. The galaxies' velocity-dispersion profiles were found to decline with the radius, and dynamical modeling of the data indicates the presence of little if any dark matter in these galaxies' halos. This unexpected result conflicts with findings in other galaxy types and poses a challenge to current galaxy formation theories.