1,721,141 research outputs found
Evolutionary adaptations to risk of cancer: Evidence from cancer resistance in elephants
No full textParadoxes can be intellectually challenging and illuminating. The eponymous Peto paradox originated approximately 40 years ago when Peto, along with his colleagues Doll and Cairns, highlighted the observation that cancer risk does not appear to scale with size in the animal kingdom.1,2 The underlying premise was that more cell division (to make and sustain a larger animal) along with longer life span might be expected to carry a proportionally greater mutational and malignancy risk
Un enigma difficile da risolvere: come identificare il paziente a rischio cardiovascolare.
No full textSantuari martiriali e centri di pellegrinaggio in Italia fra tarda antichità e alto medioevo
No full textCancer progression: a single cell perspective
Full text linkTumor tissues are constituted by a dynamic diversity of malignant and non-malignant cells, which shape a puzzling biological ecosystem affecting cancer biology and response to treatments. Over the course of the tumoral disease, cancer cells acquire genotypic and phenotypic changes, allowing them to improve cellular fitness and overcome environmental and treatment constraints. This progression is depicted by an evolutionary process in which single cells expand as a result of an interaction between single-cell changes and the lovelopments have made it possible to depict the development of cancer at the single-cell level, offering a novel method for understanding the biology of this complex disease. Here, we review those complex interactions from the perspective of single cells and introduce the concept of omics for single-cell studies. This review emphasizes the evolutionary dynamics that control cancer progression and the capacity of single cells to escape the local environment and colonize distant sites. We are assisting a rapid progression of studies carried out at the single-cell level, and we survey relevant single-cell technologies looking at multi-omics studies. These path for precision medicine in cancer
Statins, mevalonate pathway and its intermediate products in placental development and preeclampsia
No full textThe mevalonate pathway synthesizes intermediates and products such as cholesterol and non-sterol isoprenoids that are crucial for cell survival and function. In the human placenta, the prenylation of proteins, rather than cholesterol synthesis, represents the main "metabolic target" of mevalonate metabolism. Major cellular functions depend on isoprenylation including proliferation, migration, metabolism and protein glycosylation that are all crucial for proper development of the embryo and the placenta. Statins are inhibitors of HMG-CoA reductase, the enzyme that catalyzes the reduction of HMG-CoA to mevalonic acid by NADPH. In vitro experiments using human placental explants suggest that statins elicit a detrimental effect on placental growth. However, animal and epidemiologic studies show no increase of fetal malformations after exposure to statins during pregnancy. Moreover, emerging evidence from mouse studies suggest that statins may be useful in preventing serious pregnancy complications like preeclampsia
Artificial Neural Networks applied to landslide susceptibility assessment
No full textLandslide hazard mapping is often performed through the identification and analysis of hillslope instability factors, usually managed as thematic data within geographic information systems (GIS). In heuristic approaches, these factors are rated by the attribution of scores based on the assumed role played by each of them in controlling the development of a sliding process. Other more refined methods, based on the principle that the present and the past are keys to the future, have also been developed, thus allowing less subjective analyses in which landslide susceptibility is assessed by statistical relationships between past landslide events and hillslope instability factors. The objective of this research is to define a method with the ability to forecast landslide susceptibility through the application of Artificial Neural Networks (ANNs). The Riomaggiore catchment, a subwatershed of the Reno River basin located in the Northern Apennines (Italy), was chosen as an ideal test site, as it is representative of many of the geomorphological settings within this region. In the present application, two different ANNs, used in classification problems, were set up and applied: one belonging to the category of Multi-Layered Perceptron (MLP) and the other to the Probabilistic Neural Network (PNN) family. The hillslope factors that have been taken into account in the analysis were the following: (a) lithology, (b) slope angle, (c), profile curvature, (d) land cover and (e) upslope contributing area. These factors have been classified on nominal scales, and their intersection allowed 3342 homogeneous domains (Unique Condition Unit, UCU) to be singled out, which correspond to the terrain units utilized in this analysis. The model vector used to train the ANNs is a subset of that derived from the production of Unique Condition Units and consists of 3342 records organized in input and output variable vectors. In particular, the hillslope factors, once classified on nominal scales as binary numbers, represent the 19 input variables, while the presence/ absence of a landslide in a given terrain unit is assumed to be the output variable. The comparison between the most up-to-date landslide inventory of the Riomaggiore catchment and the hazardous areas, as predicted by the ANNs, showed satisfactory results (with a slight preference for the MLP). For this reason, this is an encouraging preliminary approach towards a systematic introduction of ANN-based statistical methods in landslide hazard assessment and mapping. © 2004 Elsevier B.V. All rights reserved
The Application of Long-Read Sequencing to Cancer
Full text linkCancer is a multifaceted disease arising from numerous genomic aberrations that have been identified as a result of advancements in sequencing technologies. While next-generation sequencing (NGS), which uses short reads, has transformed cancer research and diagnostics, it is limited by read length. Third-generation sequencing (TGS), led by the Pacific Biosciences and Oxford Nanopore Technologies platforms, employs long-read sequences, which have marked a paradigm shift in cancer research. Cancer genomes often harbour complex events, and TGS, with its ability to span large genomic regions, has facilitated their characterisation, providing a better understanding of how complex rearrangements affect cancer initiation and progression. TGS has also characterised the entire transcriptome of various cancers, revealing cancer-associated isoforms that could serve as biomarkers or therapeutic targets. Furthermore, TGS has advanced cancer research by improving genome assemblies, detecting complex variants, and providing a more complete picture of transcriptomes and epigenomes. This review focuses on TGS and its growing role in cancer research. We investigate its advantages and limitations, providing a rigorous scientific analysis of its use in detecting previously hidden aberrations missed by NGS. This promising technology holds immense potential for both research and clinical applications, with far-reaching implications for cancer diagnosis and treatment
Defects in lysosomal degradation contribute to impaired fibronectin matrix assembly in preeclampsia
No full textObjectives: The glycoprotein,fibronectin (FN), is a fundamentalcomponent of the extracellular matrix (ECM), driving trophoblast inva-sion and angiogenesis in the developing placenta. These events arecompromised in preeclampsia (PE), a pathology typified by impairedangiogenesis. FN undergoes extensive intracellular processing, from itsdimerization and secretion, to signalling, endocytosis and lysosomaldegradation. To date, the mechanisms controlling FN trafficking anddeposition in PE remain unknown, prompting us to investigate FN ma-trix assembly in the human placenta in physiological and pathologicalconditions.Methods: Placentae were collected fromfirst trimester, preeclamptic(n1⁄417), pre-term (n1⁄414) and term (n1⁄415) pregnancies. Placental mesen-chymal cells (pMCs) were isolated and characterized by FACS. Organelleswere isolated using sucrose density gradients and ultracentrifugation.pMCs were exposed to either cycloheximide (protein synthesis inhibitor),Brefeldin A (ER-Golgi transport inhibitor), or the lysosomal inhibitors,NH4Cl and Bafilomycin. Concanavalin A lectin-binding was used to assessFN glycosylation.Results: FN monomers and dimers accumulated in the Golgi and lyso-somal compartments in PE placentae and in PE pMCs relative to age-matched controls, whileFN1mRNA was unchanged. FN intracellularglycosylation was markedly reduced in PE pMCs, accompanied by aberrantER-Golgi transit and secretion. Assessment of protein half-life by cyclo-heximide revealed distinct impairments in FN matrix turnover in PE, whilein controls, FN was sequentially processed from cell-associated solubledimers to matrix-associated insolublefibrils. Confirming impairments inits clearance, lysosomal inhibition by NH4Cl or Bafilomycin in control pMCsstabilized intracellular FN and attenuated integrin-mediated signalling,while in PE, FN failed to be stabilized and continued to aberrantly signaldownstream.Conclusion: This study highlights profound disruptions in key stages offibronectin matrix assembly in preeclampsia, particularly its depositionand lysosomal degradation. Given the importance of pMC-derived ECM intriggering villous angiogenesis, this work sheds new light on the mecha-nisms contributing to abnormal vascular development in P
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