Search results for "ASIS"
showing 10 items of 4190 documents
EFFICACY OF ZOLEDRONIC ACID IN PATIENTS WITH COLORECTAL CANCER METASTATIC TO BONE
2010
Introduction. Bone metastases are an emerging clinical problem in colorectal cancer patients probably related to survival increase. There are no data in literature about the role of BPs in the treatment of bone disease from colorectal cancer. We present the final data of a large Italian multicenter retrospective analysis. Methods. 264 colorectal cancer patients with occurrence of bone metastases have been included in the study. All patients were dead due to cancer at the moment of the study inclusion. Patients characteristics, Skeletal Related Events (SRE) data and median survival after bone metastases appearance have been collected in a master data base and statistically analyzed. The prim…
Nab-paclitaxel in pretreated metastatic breast cancer: evaluation of activity, safety, and quality of life
2019
Rossella De Luca,1 Giuseppe Profita,2 Giuseppe Cicero1 1Department of Surgical, Oncological and Oral Sciences, Section of Medical Oncology, University of Palermo, Palermo, Italy; 2Department of Surgical, Oncological and Oral Sciences, Section of Surgical, University of Palermo, Palermo, Italy Objective: Metastatic breast cancer (MBC) is an incurable disease; the treatment of this disease prolongs survival, improving the quality of life (QoL) with a balance between efficacy and toxicity of the treatment. In recent years, treatment with nab-paclitaxel has improved the already known antitumor activity of conventional paclitaxel, in terms of increased efficacy and better tolerability. The aim o…
The C-X-C Motif Chemokine Ligand 1 Sustains Breast Cancer Stem Cell Self-Renewal and Promotes Tumor Progression and Immune Escape Programs
2021
Breast cancer (BC) mortality is mainly due to metastatic disease, which is primarily driven by cancer stem cells (CSC). The chemokine C-X-C motif ligand-1 (CXCL1) is involved in BC metastasis, but the question of whether it regulates breast cancer stem cell (BCSC) behavior is yet to be explored. Here, we demonstrate that BCSCs express CXCR2 and produce CXCL1, which stimulates their proliferation and self-renewal, and that CXCL1 blockade inhibits both BCSC proliferation and mammosphere formation efficiency. CXCL1 amplifies its own production and remarkably induces both tumor-promoting and immunosuppressive factors, includingSPP1/OPN,ACKR3/CXCR7,TLR4,TNFSF10/TRAILandCCL18and, to a lesser exte…
Long-Term Domiciliary High-Flow Nasal Therapy in Patients with Bronchiectasis: A Preliminary Retrospective Observational Case-Control Study
2022
High-flow nasal therapy (HFNT) provides several pathophysiological benefits in chronic respiratory disorders. We aimed to evaluate the effectiveness of long-term HFNT in patients with bronchiectasis (BE). Methods: This is a retrospective bicentric case-control study of outpatients with BE on optimized medical treatment with a severe exacerbation requiring hospitalization in the previous year. Patients on long-term home HFNT (cases) and patients on optimized medical treatment alone (controls) were matched by age, sex, bronchiectasis severity index, and exacerbations in the previous year. Data on BE exacerbations, hospitalizations/year, mucus features, respiratory symptoms, and pulmonary func…
Cancer Stem Cells: From Birth to Death
2019
Abstract Conspicuous investigations have proven the role of cancer stem cells (CSCs) in the onset and progression of a plethora of liquid and solid neoplasms. CSCs are endowed with the capability of initiating tumor growth and becoming dormant at distant organ sites just waiting for optimal conditions amenable for metastatic outgrowth. This cancer subpopulation is inherently resistant to anticancer therapeutics, and its targeting could avoid metastatic disease, which is largely incurable, and clinical relapses. CSCs are considered the Achilles heel of cancer. However, many efforts are necessary to identify univocal CSC markers as well as specific CSC biomarkers of therapeutic response. Here…
Spectral clustering with the probabilistic cluster kernel
2015
Abstract This letter introduces a probabilistic cluster kernel for data clustering. The proposed kernel is computed with the composition of dot products between the posterior probabilities obtained via GMM clustering. The kernel is directly learned from the data, is parameter-free, and captures the data manifold structure at different scales. The projections in the kernel space induced by this kernel are useful for general feature extraction purposes and are here exploited in spectral clustering with the canonical k-means. The kernel structure, informative content and optimality are studied. Analysis and performance are illustrated in several real datasets.
Fuzzy sigmoid kernel for support vector classifiers
2004
This Letter proposes the use of the fuzzy sigmoid function presented in (IEEE Trans. Neural Networks 14(6) (2003) 1576) as non-positive semi-definite kernel in the support vector machines framework. The fuzzy sigmoid kernel allows lower computational cost, and higher rate of positive eigenvalues of the kernel matrix, which alleviates current limitations of the sigmoid kernel.
Feature extraction from remote sensing data using Kernel Orthonormalized PLS
2007
This paper presents the study of a sparse kernel-based method for non-linear feature extraction in the context of remote sensing classification and regression problems. The so-called kernel orthonormalized PLS algorithm with reduced complexity (rKOPLS) has two core parts: (i) a kernel version of OPLS (called KOPLS), and (ii) a sparse (reduced) approximation for large scale data sets, which ultimately leads to rKOPLS. The method demonstrates good capabilities in terms of expressive power of the extracted features and scalability.
Three-dimensional object detection under arbitrary lighting conditions
2006
A novel method of 3D object recognition independent of lighting conditions is presented. The recognition model is based on a vector space representation using an orthonormal basis generated by the Lambertian reflectance functions obtained with distant light sources. Changing the lighting conditions corresponds to multiplying the elementary images by a constant factor and because of that, all possible lighting views will be elements that belong to that vector space. The recognition method proposed is based on the calculation of the angle between the vector associated with a certain illuminated 3D object and that subspace. We define the angle in terms of linear correlations to get shift and i…
A novel method for network intrusion detection based on nonlinear SNE and SVM
2017
In the case of network intrusion detection data, pre-processing techniques have been extensively used to enhance the accuracy of the model. An ideal intrusion detection system (IDS) is one that has appreciable detection capability overall the group of attacks. An open research problem of this area is the lower detection rate for less frequent attacks, which result from the curse of dimensionality and imbalanced class distribution of the benchmark datasets. This work attempts to minimise the effects of imbalanced class distribution by applying random under-sampling of the majority classes and SMOTE-based oversampling of minority classes. In order to alleviate the issue arising from the curse…