The EXS Domain of PHO1 Participates in the Response of Shoots to Phosphate Deficiency via a Root-to-Shoot Signal.

The response of shoots to phosphate (Pi) deficiency implicates long-distance communication between roots and shoots, but the participating components are poorly understood. We have studied the topology of the Arabidopsis (Arabidopsis thaliana) PHOSPHATE1 (PHO1) Pi exporter and defined the functions of its different domains in Pi homeostasis and signaling. The results indicate that the amino and carboxyl termini of PHO1 are both oriented toward the cytosol and that the protein spans the membrane twice in the EXS domain, resulting in a total of six transmembrane α-helices. Using transient expression in Nicotiana benthamiana leaf, we demonstrated that the EXS domain of PHO1 is essential for Pi export activity and proper localization to the Golgi and trans-Golgi network, although the EXS domain by itself cannot mediate Pi export. In contrast, removal of the amino-terminal hydrophilic SPX domain does not affect the Pi export capacity of the truncated PHO1 in N. benthamiana. While the Arabidopsis pho1 mutant has low shoot Pi and shows all the hallmarks associated with Pi deficiency, including poor shoot growth and overexpression of numerous Pi deficiency-responsive genes, expression of only the EXS domain of PHO1 in the roots of the pho1 mutant results in a remarkable improvement of shoot growth despite low shoot Pi. Transcriptomic analysis of pho1 expressing the EXS domain indicates an attenuation of the Pi signaling cascade and the up-regulation of genes involved in cell wall synthesis and the synthesis or response to several phytohormones in leaves as well as an altered expression of genes responsive to abscisic acid in roots.

Performance of diagnostic centers in the classification of opportunistic screening mammograms from the Brazilian public health system (SUS)

Objective To evaluate the performance of diagnostic centers in the classification of mammography reports from an opportunistic screening undertaken by the Brazilian public health system (SUS) in the municipality of Goiânia, GO, Brazil in 2010. Materials and Methods The present ecological study analyzed data reported to the Sistema de Informação do Controle do Câncer de Mama (SISMAMA) (Breast Cancer Management Information System) by diagnostic centers involved in the mammographic screening developed by the SUS. Based on the frequency of mammograms per BI-RADS® category and on the limits established for the present study, the authors have calculated the rate of conformity for each diagnostic center. Diagnostic centers with equal rates of conformity were considered as having equal performance. Results Fifteen diagnostic centers performed mammographic studies for SUS and reported 31,198 screening mammograms. The performance of the diagnostic centers concerning BI-RADS classification has demonstrated that none of them was in conformity for all categories, one center presented conformity in five categories, two centers, in four categories, three centers, in three categories, two centers, in two categories, four centers, in one category, and three centers with no conformity. Conclusion The results of the present study demonstrate unevenness in the diagnostic centers performance in the classification of mammograms reported to SISMAMA from the opportunistic screening undertaken by SUS.

Le projet RDoC : la classification psychiatrique de demain ?

Nous présentons dans cet article l'histoire, les grands principes méthodologiques ainsi que la réception scientifique et médiatique du projet Research domain criteria (RDoC) lancé en 2009 aux États-Unis par le National institute of mental health (NIMH). Le projet RDoC, dévolu à la recherche, s'oppose au Manuel diagnostique et statistique des troubles mentaux (DSM) en mettant l'accent sur les dimensions du fonctionnement normal du cerveau, au croisement des recherches génétiques, des neurosciences cognitives et des sciences comportementales. Ce projet représente un pari sur le futur et son succès est tributaire de l'adhésion des chercheurs américains au nouveau cadre de référence qu'il propose, cadre qui reste encore largement à construire.

Classification of chronic obstructive pulmonary disease based on chest radiography

Objective Quantitative analysis of chest radiographs of patients with and without chronic obstructive pulmonary disease (COPD) determining if the data obtained from such radiographic images could classify such individuals according to the presence or absence of disease. Materials and Methods For such a purpose, three groups of chest radiographic images were utilized, namely: group 1, including 25 individuals with COPD; group 2, including 27 individuals without COPD; and group 3 (utilized for the reclassification /validation of the analysis), including 15 individuals with COPD. The COPD classification was based on spirometry. The variables normalized by retrosternal height were the following: pulmonary width (LARGP); levels of right (ALBDIR) and left (ALBESQ) diaphragmatic eventration; costophrenic angle (ANGCF); and right (DISDIR) and left (DISESQ) intercostal distances. Results As the radiographic images of patients with and without COPD were compared, statistically significant differences were observed between the two groups on the variables related to the diaphragm. In the COPD reclassification the following variables presented the highest indices of correct classification: ANGCF (80%), ALBDIR (73.3%), ALBESQ (86.7%). Conclusion The radiographic assessment of the chest demonstrated that the variables related to the diaphragm allow a better differentiation between individuals with and without COPD.

Enhanced capture of healthcare-related harms and injuries in the 11th revision of the International Classification of Diseases (ICD-11).

The World Health Organization (WHO) plans to submit the 11th revision of the International Classification of Diseases (ICD) to the World Health Assembly in 2018. The WHO is working toward a revised classification system that has an enhanced ability to capture health concepts in a manner that reflects current scientific evidence and that is compatible with contemporary information systems. In this paper, we present recommendations made to the WHO by the ICD revision's Quality and Safety Topic Advisory Group (Q&S TAG) for a new conceptual approach to capturing healthcare-related harms and injuries in ICD-coded data. The Q&S TAG has grouped causes of healthcare-related harm and injuries into four categories that relate to the source of the event: (a) medications and substances, (b) procedures, (c) devices and (d) other aspects of care. Under the proposed multiple coding approach, one of these sources of harm must be coded as part of a cluster of three codes to depict, respectively, a healthcare activity as a 'source' of harm, a 'mode or mechanism' of harm and a consequence of the event summarized by these codes (i.e. injury or harm). Use of this framework depends on the implementation of a new and potentially powerful code-clustering mechanism in ICD-11. This new framework for coding healthcare-related harm has great potential to improve the clinical detail of adverse event descriptions, and the overall quality of coded health data.

Bosniak classification of renal cystic lesions according to multidetector computed tomography findings

Renal cystic lesions are usually diagnosed in the radiologists' practice and therefore their characterization is crucial to determine the clinical approach to be adopted and prognosis. The Bosniak classification based on computed tomography findings has allowed for standardization and categorization of lesions in increasing order of malignancy (I, II, IIF, III and IV) in a simple and accurate way. The present iconographic essay developed with multidetector computed tomography images of selected cases from the archives of the authors' institution, is aimed at describing imaging findings that can help in the diagnosis of renal cysts.

Effects of iodinated contrast agent, xylocaine and gadolinium concentration on the signal emitted in magnetic resonance arthrography: a samples study

Objective:To investigate the effects of dilution of paramagnetic contrast agent with iodinated contrast and xylocaine on the signal intensity during magnetic resonance arthrography, and to improve the paramagnetic contrast agent concentration utilized in this imaging modality.Materials and Methods:Samples specially prepared for the study with three different concentrations of paramagnetic contrast agent diluted in saline, iodinated contrast agent and xylocaine were imaged with fast spin echo T1-weighted sequences with fat saturation. The samples were placed into flasks and graphical analysis of the signal intensity was performed as a function of the paramagnetic contrast concentration.Results:As compared with samples of equal concentrations diluted only with saline, the authors have observed an average signal intensity decrease of 20.67% for iodinated contrast agent, and of 28.34% for xylocaine. However, the increased gadolinium concentration in the samples caused decrease in signal intensity with all the dilutions.Conclusion:Minimizing the use of iodinated contrast media and xylocaine and/or the use of a gadolinium concentration of 2.5 mmol/L diluted in saline will improve the sensitivity of magnetic resonance arthrography.

Renal cell carcinoma: histological classification and correlation with imaging findings

AbstractRenal cell carcinoma (RCC) is the seventh most common histological type of cancer in the Western world and has shown a sustained increase in its prevalence. The histological classification of RCCs is of utmost importance, considering the significant prognostic and therapeutic implications of its histological subtypes. Imaging methods play an outstanding role in the diagnosis, staging and follow-up of RCC. Clear cell, papillary and chromophobe are the most common histological subtypes of RCC, and their preoperative radiological characterization, either followed or not by confirmatory percutaneous biopsy, may be particularly useful in cases of poor surgical condition, metastatic disease, central mass in a solitary kidney, and in patients eligible for molecular targeted therapy. New strategies recently developed for treating renal cancer, such as cryo and radiofrequency ablation, molecularly targeted therapy and active surveillance also require appropriate preoperative characterization of renal masses. Less common histological types, although sharing nonspecific imaging features, may be suspected on the basis of clinical and epidemiological data. The present study is aimed at reviewing the main clinical and imaging findings of histological RCC subtypes.

Receiver operating characteristic (ROC) curve for classification of18F-NaF uptake on PET/CT

Abstract Objective: To assess the cutoff values established by ROC curves to classify18F-NaF uptake as normal or malignant. Materials and Methods: PET/CT images were acquired 1 hour after administration of 185 MBq of18F-NaF. Volumes of interest (VOIs) were drawn on three regions of the skeleton as follows: proximal right humerus diaphysis (HD), proximal right femoral diaphysis (FD) and first vertebral body (VB1), in a total of 254 patients, totalling 762 VOIs. The uptake in the VOIs was classified as normal or malignant on the basis of the radiopharmaceutical distribution pattern and of the CT images. A total of 675 volumes were classified as normal and 52 were classified as malignant. Thirty-five VOIs classified as indeterminate or nonmalignant lesions were excluded from analysis. The standardized uptake value (SUV) measured on the VOIs were plotted on an ROC curve for each one of the three regions. The area under the ROC (AUC) as well as the best cutoff SUVs to classify the VOIs were calculated. The best cutoff values were established as the ones with higher result of the sum of sensitivity and specificity. Results: The AUCs were 0.933, 0.889 and 0.975 for UD, FD and VB1, respectively. The best SUV cutoffs were 9.0 (sensitivity: 73%; specificity: 99%), 8.4 (sensitivity: 79%; specificity: 94%) and 21.0 (sensitivity: 93%; specificity: 95%) for UD, FD and VB1, respectively. Conclusion: The best cutoff value varies according to bone region of analysis and it is not possible to establish one value for the whole body.

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal