Learning Graph Cut Energy Functions for Image Segmentation

In this paper we address the task of learning how to segment a particular class of objects, by means of a training set of images and their segmentations. In particular we propose a method to overcome the extremely high training time of a previously proposed solution to this problem, Kernelized Structural Support Vector Machines. We employ a one-class SVM working with joint kernels to robustly learn significant support vectors (representative image-mask pairs) and accordingly weight them to build a suitable energy function for the graph cut framework. We report results obtained on two public datasets and a comparison of training times on different training set sizes

A complete system for garment segmentation and color classification

In this paper, we propose a general approach for automatic segmentation, color-based retrieval and classification of garments in fashion store databases, exploiting shape and color information. The garment segmentation is automatically initialized by learning geometric constraints and shape cues, then it is performed by modeling both skin and accessory colors with Gaussian Mixture Models. For color similarity retrieval and classification, to adapt the color description to the users’ perception and the company marketing directives, a color histogram with an optimized binning strategy, learned on the given color classes, is introduced and combined with HOG features for garment classification. Experiments validating the proposed strategy, and a free-to-use dataset publicly available for scientific purposes, are finally detailed

GOLD: Gaussians of Local Descriptors for Image Representation

The Bag of Words paradigm has been the baseline from which several successful image classification solutions were developed in the last decade. These represent images by quantizing local descriptors and summarizing their distribution. The quantization step introduces a dependency on the dataset, that even if in some contexts significantly boosts the performance, severely limits its generalization capabilities. Differently, in this paper, we propose to model the local features distribution with a multivariate Gaussian, without any quantization. The full rank covariance matrix, which lies on a Riemannian manifold, is projected on the tangent Euclidean space and concatenated to the mean vector. The resulting representation, a Gaussian of local descriptors (GOLD), allows to use the dot product to closely approximate a distance between distributions without the need for expensive kernel computations. We describe an image by an improved spatial pyramid, which avoids boundary effects with soft assignment: local descriptors contribute to neighboring Gaussians, forming a weighted spatial pyramid of GOLD descriptors. In addition, we extend the model leveraging dataset characteristics in a mixture of Gaussian formulation further improving the classification accuracy. To deal with large scale datasets and high dimensional feature spaces the Stochastic Gradient Descent solver is adopted. Experimental results on several publicly available datasets show that the proposed method obtains state-of-the-art performance

A pesquisa em enfermagem na América Latina: 1988-1998

The purpose of this article is to provide an overview of nursing research in Latin America during the decade from 1988 to 1998. Data from the bi-annual Pan American Colloquia in Nursing Research from 1988 to 1998 were subject to secondary analysis. Findings indicate that most of the research emanated from Brazil, the only country with a doctoral program in nursing in the 1990's. Research topics included: public health issues, clinical studies (usually of adults), nursing care studies of process, therapeutic communication, and administrative issues such as standards of care and quality. The most common design was descriptive quantitative, although there were several qualitative studies. The analysis provides directions for future research and indicates areas of concern, especially the need for theory based nursing research.El propósito de este artículo es ofrecer un panorama sobre la investigación en enfermería en América Latina durante la década de 1988 a 1998. La información reunida en los Coloquios Panamericanos de Investigación en Enfermería, que se celebran cada dos años, fue sometida a análisis secundario. Descubrimos que la mayor parte de las investigaciones emana del Brasil, el único país con un programa de doctorado en enfermería en los años noventa. Los tópicos de investigación incluyen asuntos de salud pública, estudios clínicos (normalmente de adultos), estudios del proceso de atención de enfermería, comunicación terapéutica y asuntos administrativos tales como normas de atención y calidad. El diseño más común fue el estudio cuantitativo descriptivo, aunque también encontramos varios estudios cualitativos. El análisis ofrece direcciones para futuras investigaciones e indica áreas de preocupación, especialmente la necesidad de una investigación en enfermería con base teórica.O objetivo do presente artigo é oferecer um panorama da pesquisa em enfermagem na América Latina realizada durante a década de 1988 a 1998. A informação reunida nos Colóquios Pan-Americanos de Pesquisa em Enfermagem, organizados a cada dois anos, foi submetida à análise secundária. Descobrimos que a maior parte das pesquisas foi produzida no Brasil, o único país com um programa de doutorado em enfermagem nos anos noventa. Os temas de pesquisa incluem tópicos de saúde pública, estudos clínicos (normalmente de adultos), estudos do processo de assistência de enfermagem, comunicação terapêutica e assuntos administrativos, tais como normas de cuidado e qualidade. O desenho mais comum foi o estudo quantitativo descritivo, mas também encontramos vários estudos qualitativos. A análise oferece direções para futuras pesquisas e indica áreas de preocupação, especialmente a necessidade de pesquisas de enfermagem com fundamentação teórica

<i>Echinococcus granulosus</i> in the Lombardy region

Cystic echinococcosis (Echinococcus granulosus) is a significant public health problem in the Mediterranean basin. In Italy, there are few epidemiological studies on echinococcosis in animals and humans mainly on southern regions, even if echinoccocosis is included in the list of zoonoses that need an epidemiological surveillance (2003/99/EEC of 17 November 2003). The results confirm that echinococcosis is hypoendemic in Lombardy, but data collected at the slaughterhouse could underestimate the prevalence of the infection, because old sheep are not always slaughtered under veterinary control

The mutant p53-driven secretome has oncogenic functions in pancreatic ductal adenocarcinoma cells

The cancer secretome is a rich repository of useful information for both cancer biology and clinical oncology. A better understanding of cancer secretome is particularly relevant for pancreatic ductal adenocarcinoma (PDAC), whose extremely high mortality rate is mainly due to early metastasis, resistance to conventional treatments, lack of recognizable symptoms, and assays for early detection. TP53 gene is a master transcriptional regulator controlling several key cellular pathways and it is mutated in ~75% of PDACs. We report the functional effect of the hot-spot p53 mutant isoforms R175H and R273H on cancer cell secretome, showing their influence on proliferation, chemoresistance, apoptosis, and autophagy, as well as cell migration and epithelial-mesenchymal transition. We compared the secretome of p53-null AsPC-1 PDAC cells after ectopic over-expression of R175H-mutp53 or R273H-mutp53 to identify the differentially secreted proteins by mutant p53. By using high-resolution SWATH-MS technology, we found a great number of differentially secreted proteins by the two p53 mutants, 15 of which are common to both mutants. Most of these secreted proteins are reported to promote cancer progression and epithelial-mesenchymal transition and might constitute a biomarker secreted signature that is driven by the hot-spot p53 mutants in PDAC

Plant Signals Anticipate the Induction of the Type III Secretion System in Pseudomonas syringae pv. actinidiae, Facilitating Efficient Temperature-Dependent Effector Translocation

Disease resistance in plants depends on a molecular dialogue with microbes that involves many known chemical effectors, but the time course of the interaction and the influence of the environment are largely unknown. The outcome of host-pathogen interactions is thought to reflect the offensive and defensive capabilities of both players. When plants interact with Pseudomonas syringae, several well-characterized virulence factors contribute to early bacterial pathogenicity, including the type III secretion system (T3SS), which must be activated by signals from the plant and environment to allow the secretion of virulence effectors. The manner in which these signals regulate T3SS activity is still unclear. Here, we strengthen the paradigm of the plant-pathogen molecular dialogue by addressing overlooked details concerning the timing of interactions, specifically the role of plant signals and temperature on the regulation of bacterial virulence during the first few hours of the interaction. Whole-genome expression profiling after 1 h revealed that the perception of plant signals from kiwifruit or tomato extracts anticipated T3SS expression in P. syringae pv. actinidiae compared to apoplast-like conditions, facilitating more efficient effector transport in planta, as revealed by the induction of a temperature-dependent hypersensitive response in the nonhost plant Arabidopsis thaliana Columbia-0 (Col-0). Our results show that in the arms race between plants and bacteria, the temperature-dependent timing of bacterial virulence versus the induction of plant defenses is probably one of the fundamental parameters governing the outcome of the interaction. IMPORTANCE Plant diseases-their occurrence and severity-result from the impact of three factors: the host, the pathogen, and the environmental conditions, interconnected in the disease triangle. Time was further included as a fourth factor accounting for plant disease, leading to a more realistic three-dimensional disease pyramid to represent the evolution of disease over time. However, this representation still considers time only as a parameter determining when and to what extent a disease will occur, at a scale from days to months. Here, we show that time is a factor regulating the arms race between plants and pathogens, at a scale from minutes to hours, and strictly depends on environmental factors. Thus, besides the arms possessed by pathogens and plants per se, the opportunity and the timing of arms mobilization make the difference in determining the outcome of an interaction and thus the occurrence of plant disease

Chemotherapy effects on brain glucose metabolism at rest

Background: A growing number of studies reports that chemotherapy may impair brain functions inducing cognitive changes which can persist in a subset of cancer survivors. Aims: To investigate the neural basis of the chemotherapy-induced neurobehavioral changes by means of metabolic imaging and voxel-based statistical parametric mapping analyses. Methods: We studied the resting brain [18]FDG-PET/CT images of 43 adult cancer patients with solid (n=12, 28%) or hematologic malignancies (n=31, 72%); 12 patients were studied prior to chemotherapy (No chemotherapy) while treated patients were divided into two matched subgroups: Early High (6 chemotherapy cycles, n=10), and Late Low (>9 months after chemotherapy, <6 chemotherapy cycles, n=21). Findings: Compared to No chemotherapy, the Early High subgroup showed a significant bilateral (p<0.05) lower regional cerebral metabolic rate of glucose metabolism in both the prefrontal cortices and white matter, cerebellum, posterior medial cortices and limbic regions. A similar pattern emerged in the Early High versus Low Late comparison, while no significant result was obtained in the Low Late versus No chemotherapy comparison. The number of cycles and the post-chemotherapy time were negatively and positively correlated, respectively, with a set of these same brain regions. Interpretation: The present study shows that chemotherapy induces significant transient changes in the glucose metabolism of multiple cerebral cortical and white matter regions with a prevailing involvement of the prefrontal cortex. The severity of these changes are significantly related with the number of chemotherapy cycles and a subset of brain regions seems to present longer lasting, but more subtle, metabolic changes

Tailoring protocols for chest CT applications: when and how?

In the medical era of early detection of diseases and tailored therapies, an accurate characterization and staging of the disease is pivotal for treatment planning. The widespread use of computed tomography (CT)—often with the use of contrast material (CM)—probably represents the most important advance in diagnostic radiology. The result is a marked increase in radiation exposure of the population for medical purposes, with its intrinsic carcinogenic potential, and CM affecting kidney function. The radiologists should aim to minimize patient’s risk by reducing radiation exposure and CM amount, while maintaining the highest image quality. To achieve this goal, it is necessary to perform “patient-centric imaging”. The purpose of this review is to provide radiologists with “tips and tricks” to control radiation dose at CT, summarizing technical artifices in order to reduce image noise and increase image contrast. Also chest CT tailored protocols are supplied, with particular attention to three most common thoracic CT protocols: aortic/cardiac CT angiography (CTA), pulmonary CTA, and routine chest CT