A study of the effect of sartorius transposition on lymph flow after ilioinguinal node dissection.

Ilioinguinal dissection is associated with a high rate of lymphatic complications. Prolonged lymph flow causes greatest concern and preventive strategies are needed. A retrospective study of 28 consecutive patients undergoing groin dissection for melanoma metastases was performed to evaluate the influence of sartorius muscle transposition on lymph flow. Modification of the surgical technique with transposition of the sartorius muscle was not associated with reduced drainage time (P = 0.66). A 2-staged approach, with initial sentinel lymph node resection and lymph node dissection in a second operation, however, lead to shortened duration of the lymph flow (P = 0.01). Prolonged lymphorrhea was more frequent in older (P = 0.03), obese (P = 0.02) patients affected by diabetes mellitus (P = 0.03) and hypertension (P = 0.04).

Characterization and multivariate classification of grapes and wines of two Cabernet Sauvignon clones

The objective of this work was to assess and characterize two clones, 169 and 685, of Cabernet Sauvignon grapes and to evaluate the wine produced from these grapes. The experiment was carried out in São Joaquim, SC, Brazil, during the 2009 harvest season. During grape ripening, the evolution of physical-chemical properties, phenolic compounds, organic acids, and anthocyanins was evaluated. During grape harvest, yield components were determined for each clone. Individual and total phenolics, individual and total anthocyanins, and antioxidant activity were evaluated for wine. The clones were also assessed regarding the duration of their phenological cycle. During ripening, the evolution of phenolic compounds and of physical-chemical parameters was similar for both clones; however, during harvest, significant differences were observed regarding yield, number of bunches per plant and berries per bunch, leaf area, and organic acid, polyphenol, and anthocyanin content. The wines produced from these clones showed significant differences regarding chemical composition. The clones showed similar phenological cycle and responses to bioclimatic parameters. Principal component analysis shows that clone 685 is strongly correlated with color characteristics, mainly monomeric anthocyanins, while clone 169 is correlated with individual phenolic compounds.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Approximate polytope ensemble for one-class classification

In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets.

The role of interval nodes in sentinel lymph node mapping and dissection for melanoma patients.

In sentinel node (SN) biopsy, an interval SN is defined as a lymph node or group of lymph nodes located between the primary melanoma and an anatomically well-defined lymph node group directly draining the skin. As shown in previous reports, these interval SNs seem to be at the same metastatic risk as are SNs in the usual, classic areas. This study aimed to review the incidence, lymphatic anatomy, and metastatic risk of interval SNs. METHODS: SN biopsy was performed at a tertiary center by a single surgical team on a cohort of 402 consecutive patients with primary melanoma. The triple technique of localization was used-that is, lymphoscintigraphy, blue dye, and gamma-probe. Otolaryngologic melanoma and mucosal melanoma were excluded from this analysis. SNs were examined by serial sectioning and immunohistochemistry. All patients with metastatic SNs were recommended to undergo a radical selective lymph node dissection. RESULTS: The primary locations of the melanomas included the trunk (188), an upper limb (67), or a lower limb (147). Overall, 97 (24.1%) of the 402 SNs were metastatic. Interval SNs were observed in 18 patients, in all but 2 of whom classic SNs were also found. The location of the primary was truncal in 11 (61%) of the 18, upper limb in 5, and lower limb in 2. One patient with a dorsal melanoma had drainage exclusively in a cervicoscapular area that was shown on removal to contain not lymph node tissue but only a blue lymph channel without tumor cells. Apart from the interval SN, 13 patients had 1 classic SN area and 3 patients 2 classic SN areas. Of the 18 patients, 2 had at least 1 metastatic interval SN and 2 had a classic SN that was metastatic; overall, 4 (22.2%) of 18 patients were node-positive. CONCLUSION: We found that 2 of 18 interval SNs were metastatic: This study showed that preoperative lymphoscintigraphy must review all known lymphatic areas in order to exclude an interval SN.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Methylation signature of lymph node metastases in breast cancer patients.

BACKGROUND: Invasion and metastasis are two important hallmarks of malignant tumors caused by complex genetic and epigenetic alterations. The present study investigated the contribution of aberrant methylation profiles of cancer related genes, APC, BIN1, BMP6, BRCA1, CST6, ESR-b, GSTP1, P14 (ARF), P16 (CDKN2A), P21 (CDKN1A), PTEN, and TIMP3, in the matched axillary lymph node metastasis in comparison to the primary tumor tissue and the adjacent normal tissue from the same breast cancer patients to identify the potential of candidate genes methylation as metastatic markers. METHODS: The quantitative methylation analysis was performed using the SEQUENOM's EpiTYPER? assay which relies on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). RESULTS: The quantitative DNA methylation analysis of the candidate genes showed higher methylation proportion in the primary tumor tissue than that of the matched normal tissue and the differences were significant for the APC, BIN1, BMP6, BRCA1, CST6, ESR-b, P16, PTEN and TIMP3 promoter regions (P<0.05). Among those candidate methylated genes, APC, BMP6, BRCA1 and P16 displayed higher methylation proportion in the matched lymph node metastasis than that found in the normal tissue (P<0.05). The pathway analysis revealed that BMP6, BRCA1 and P16 have a role in prevention of neoplasm metastasis. CONCLUSIONS: The results of the present study showed methylation heterogeneity between primary tumors and metastatic lesion. The contribution of aberrant methylation alterations of BMP6, BRCA1 and P16 genes in lymph node metastasis might provide a further clue to establish useful biomarkers for screening metastasis.

Classification and fingerprinting of different berries based on biochemical profiling and antioxidant capacity

The objective of this work was to evaluate the biochemical composition of six berry types belonging to Fragaria, Rubus, Vaccinium and Ribes genus. Fruit samples were collected in triplicate (50 fruit each) from 18 different species or cultivars of the mentioned genera, during three years (2008 to 2010). Content of individual sugars, organic acids, flavonols, and phenolic acids were determined by high performance liquid chromatography (HPLC) analysis, while total phenolics (TPC) and total antioxidant capacity (TAC), by using spectrophotometry. Principal component analysis (PCA) and hierarchical cluster analysis (CA) were performed to evaluate the differences in fruit biochemical profile. The highest contents of bioactive components were found in Ribes nigrum and in Fragaria vesca, Rubus plicatus, and Vaccinium myrtillus. PCA and CA were able to partially discriminate between berries on the basis of their biochemical composition. Individual and total sugars, myricetin, ellagic acid, TPC and TAC showed the highest impact on biochemical composition of the berry fruits. CA separated blackberry, raspberry, and blueberry as isolate groups, while classification of strawberry, black and red currant in a specific group has not occurred. There is a large variability both between and within the different types of berries. Metabolite fingerprinting of the evaluated berries showed unique biochemical profiles and specific combination of bioactive compound contents.

A proposal for an international retinoblastoma staging system.

BACKGROUND: Although intra-retinal tumor has long been staged presurgically according to the Reese-Ellsworth (R-E) system, retinoblastoma differs from other pediatric neoplasms in never having had a widely accepted classification system that encompasses the entire spectrum of the disease. Comparisons among studies that consider disease extension, risk factors for extra-ocular relapse, and response to therapy require a universally accepted staging system for extra-ocular disease. PROCEDURE: A committee of retinoblastoma experts from large centers worldwide has developed a consensus classification that can encompass all retinoblastoma cases and is presented herein. Patients are classified according to extent of disease and the presence of overt extra-ocular extension. In addition, a proposal for substaging considering histopathological features of enucleated specimens is presented to further discriminate between Stage I and II patients. RESULTS: The following is a summary of the classification system developed-Stage 0: Patients treated conservatively (subject to presurgical ophthalmologic classifications); Stage I: Eye enucleated, completely resected histologically; Stage II: Eye enucleated, microscopic residual tumor; Stage III: Regional extension [(a) overt orbital disease, (b) preauricular or cervical lymph node extension]; Stage IV: Metastatic disease [(a) hematogenous metastasis: (1) single lesion, (2) multiple lesions; (b) CNS extension: (1) prechiasmatic lesion, (2) CNS mass, (3) leptomeningeal disease]. A proposal is also presented for substaging of enucleated Stages I and II eyes. CONCLUSIONS: The proposed staging system is the product of an international effort to adopt a uniform staging system for patients with retinoblastoma to cover the whole spectrum of the disease.

Synchronous Digital Hierarchy implementation to a Radio Transmission Node

Kiristyville markkinoille on aina tuotava jotain uutta tarjottavaa ja SDH-kortti on yksi sellainen tuote jonka Nokia Networks julkistaa osaksi uutta Nokia Flexihub Nodea. Tavoitteena on suunnitella VC-12kanavoitu STM-1 kortti yhdistämään ylemmän tason tietoliikenneverkko suuren kapasiteetin radioon. Ennen kuin markkinoilla on valmis tuote, on sen takana valtaisa määrä työtä. Erilaisia dokumentteja on pitänyt tuottaa ja sopimuksia tehdä. Esimerkiksi vaatimusmäärittelyt on oltava selvät, jotta tiedetään mitä tuotteelta halutaan. Tätä ennen on kuitenkin pitänyt ymmärtää miten SDHtoimii ja miten otsikkotavuja käsitellään. Myös erilaiset piirivalinnat aiheuttavat miettimistä, sillä markkinoilla on runsaasti valmiita piirejä SDH signaalinkäsittelyyn. Varma tiedonsiirto on tärkeää puhelinoperaattorille ja siksi joudutaan miettimään varmennuksia ja niiden toteuttamista. Myös synkronointi on tärkeä osa SDH järjestelmää ja sen toteuttaminen hyvin on tärkeää. Hälytykset on otettava huomioon ja mietittävä, miten niiden käsittely saadaan hoidettua järkevästi, ilman että mikään järjestelmän osa ruuhkautuu kohtuuttomasti. Tässä Diplomityössä on tutustuttu SDH-järjestelmään, otsikkotavujen käsittelyyn ja vaatimusmäärittelyihin.

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Current Issues in the Diagnosis and Classification of Peripheral T-Cell Lymphomas

Mature T-cell and T/NK-cell neoplasms are both uncommon and heterogeneous, among the broad category of non-Hodgkin's lymphomas. Due to the lack of specific genetic alterations in the vast majority of cases, most currently defined entities show overlapping morphologic and immunophenotypic features and therefore pose a challenge to the diagnostic pathologist. The goal of the symposium is to address current criteria for the recognition of specific subtypes of T-cell lymphoma, and to highlight new data regarding emerging immunophenotypic or molecular markers. This activity has been designed to meet the needs of practicing pathologists, and residents and fellows enrolled in training programs in anatomic and clinical pathology. It should be a particular benefit to those with an interest in hematopathology. Upon completion of this activity, participants should be better able to: -To be able to state the basis for the classification of mature T-cell malignancies involving nodal and extranodal sites. -To recognize and accurately diagnose the various subtypes of nodal and extranodal peripheral T-cell lymphomas. -To utilize immunohistochemical and molecular tests to characterize atypical T-cell proliferations. -To recognize and accurately diagnose T-cell lymphoproliferative lesions involving the skin and gastrointestinal tract, and be able to provide guidance regarding their clinical aggressiveness and management -To be able to utilize flow cytometric data to identify diverse functional T-cell subsets.