468 research outputs found
Factor analysis of predictive markers of response and resistance to primary chemo-endocrine treatment in elderly breast cancer (BC) patients
No full textFUNDAMENTAL RADIOBIOLOGY AND ITS APPLICATION TO RADIATION ONCOLOGY
No full textA brief overview of fundamental concepts in radiobiology is provided. The concept of cell survival as ability to retain reproductive integrity is introduced, and critical variables influencing the cell survival curve as a function of absorbed radiation dose are discussed. Application of these concepts to radiation oncology and radiotherapy is then outlined. Examples are provided of clinical studies that can be performed with current high-throughput molecular biology and imaging technology. The type of information derived from these studies and its potential are discussed in the context of radiotherapy trial design, radiotherapy schedule and modality tailoring, and planning of treatment dose. © 2009 Springer Science + Business Media B.V
Backscatter and dose perturbations for low- to medium-energy electron point sources at the interface between materials with different atomic numbers
No full text: Electron backscatter at interfaces between dissimilar media can affect dosimetry and should be taken into consideration in radiotherapy and in radiobiology experiments. Backscatter dose perturbations depend upon factors such as electron energy, medium atomic number (Z), and distance from the interface. This study quantifies the backscatter dose factor (BSDF) for electron point sources of energy between 0.1 to 3 MeV in water at the interface with scattering materials ranging in Z from (13)Al to (79)Au. A Monte Carlo code that performs dose calculations for monoenergetic and continuous-spectrum electron sources was developed using EGSnrc transport routines. The BSDF was quantified in a parallel layers geometry (BSDF(1D)) and three-dimensional voxel geometry (BSDF(3D)). The BSDF(1D) near the interface increased up to 52% with decreasing energy from 3 to 0.1 MeV and increasing Z from 13 to 79. The analysis of the BSDF(3D) showed a significant dependence of the scattered electron angular distribution on Z and energy, with a decrease in isotropy going from high to low Z. This effect proves the importance of considering the correct geometry when quantifying the BSDF for electron sources, especially when the dimensions of the relevant dose-collecting volume are comparable with the CSDA range of the source
New perspectives in liquid biopsy for glioma patients
No full textReview.
Gliomas are the most common primary tumors of the central nervous system. They are characterized by a disappointing prognosis and ineffective therapy that has shown no substantial improvements in the past 20 years. The lack of progress in treating gliomas is linked with the inadequacy of suitable tumor samples to plan translational studies and support laboratory developments. To overcome the use of tumor tissue, this commentary review aims to highlight the potential for the clinical application of liquid biopsy (intended as the study of circulating biomarkers in the blood), focusing on circulating tumor cells, circulating DNA and circulating noncoding RNA.
Recent findings
Thanks to the increasing sensitivity of sequencing techniques, it is now possible to analyze circulating nucleic acids and tumor cells (liquid biopsy).
Summary
Although studies on the use of liquid biopsy are still at an early stage, the potential clinical applications of liquid biopsy in the study of primary brain cancer are many and have the potential to revolutionize the approach to neuro-oncology, and importantly, they offer the possibility of gathering information on the disease at any time during its history
Moment equations for the mixed formulation of the Hodge Laplacian with stochastic data
No full textWe study the mixed formulation of the stochastic Hodge-Laplace problem defined on a n-dimensional domain D (n ≥ 1), with random forcing term. In particular, we focus on the magnetostatic problem and on the Darcy problem in the three dimensional case. We derive and analyze the moment equations, that is the deterministic equations solved by the m-th moment (m ≥ 1) of the unique stochastic solution of the stochastic problem. We find stable tensor product finite element discretizations, both full and sparse, and provide optimal order of convergence estimates. In particular,
we prove the inf-sup condition for sparse tensor product finite element spaces
From alternative representations to prospective visions. The administrative subdivisions in Palermo (Italy)
No full textAlternative representations of the city are not only a useful analysis tool, but they also provide elements of a conceived new version of lived space that can contribute to ameliorate the spatial justice of the city. This is even truer for intra-local spaces that are the reference scale for many public participation policies, grass-root projects and activists.
In this paper, we present the case of Palermo where the administrative subdivisions of the urban space have been imposed – because of legislation about administrative decentralisation – on the historical and perceived ones.
Alternative mapping shows intra-local spaces as places of identity definition and civic engagement. In our paper we present some examples of how local stakeholders represent their prospective visions for the neighbourhoods they live or act in
Machine learning using Gene-Sets to infer miRNA function
No full textmiRNA are regulators of cell phenotype, and there is clear evidence that these small posttranscriptional modifiers of gene expression are involved in defining a cellular response across states of development and disease. Classical methods for elucidating the repressive effect of a miRNA on its targets involve controlling for the many factors influencing miRNA action, and this can be achieved in cell lines, but misses tissue and organism level context which are key to a miRNA function. Also, current technology to carry out this validation is limited in both generalizability and throughput. Methodologies with greater scalability and rapidity are required to better understand the function of these important species of RNA. To this end, there is an increasing store of RNA expression level data incorporating both miRNA and mRNA, and in this chapter, we describe how to use machine learning and gene-sets to translate the knowledge of phenotype defined by mRNA to putative roles for miRNA. We outline our approach to this process and highlight how it was done for our miRNA annotation of the hallmarks of cancer using the Cancer Genome Atlas (TCGA) dataset. The concepts we present are applicable across datasets and phenotypes, and we highlight potential pitfalls and challenges that may be faced as they are used
A new tool to process forecast meteorological data for atmospheric pollution dispersion simulations of accident scenarios: A Sicily-based case study
No full textEmergency response plans to mitigate the severity of the accidental release of hazardous compounds in the air have become a primary concern in view of the many adverse events occurred over the years in high-risk plants. To do this, an accurate estimate of forecast meteorological data to be used in dispersion models can be very useful to respond in advance to emergency situations. In this field, FORCALM is a new tool developed to elaborate European Centre for Medium-Range Weather Forecasts data on a 3D computational domain with a high-resolution grid. FORCALM data can be used to perform predictive simulations of impacts on local and regional levels by using CALPUFF modelling system. A case study relevant to an accident, occurred in the “Mediterranea” Refinery at Milazzo (Italy) in 2014, has been also examined for validation purposes. A comparison with results obtained by using CALMET modelling system and observed meteorological data, covering the area under study, is also described. The validation work has allowed confirming that predictive assessments, carried out with the help of FORCALM, lead to information regarding potential environmental impacts with a good degree of accuracy
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