Application of morphometry, static DNA ploidy analysis, and steroid receptor expression in diagnosis and prognosis of Libyan breast cancer

The aim of this study was to describe the demographic, clinicopathological, biological and morphometric features of Libyan breast cancer patients. The supporting value of nuclear morphometry and static image cytometry in the sensitivity for detecting breast cancer in conventional fine-needle aspiration biopsies were estimated. The findings were compared with findings in breast cancer in Finland and Nigeria. In addation, the value of ER and PR were evaluated. There were 131 histological samples, 41 cytological samples, and demographic and clinicopathological data from 234 Libyan patients. The Libyan breast cancer is dominantly premenopausal and in this feature it is similar to breast cancer in sub-Saharan Africans, but clearly different from breast cancer in Europeans, whose cancers are dominantly postmenopausal in character. At presention most Libyan patients have locally advanced disease, which is associated with poor survival rates. Nuclear morphometry and image DNA cytometry agree with earlier published data in the Finnish population and indicate that nuclear size and DNA analysis of nuclear content can be used to increase the cytological sensitivity and specificity in doubtful breast lesions, particularly when free cell sampling method is used. Combination of the morphometric data with earlier free cell data gave the following diagnostic guidelines: Range of overlap in free cell samples: 55 μm2 -71 μm2. Cut-off values for diagnostic purposes: Mean nuclear area (MNA) >54 μm2 for 100% detection of malignant cases (specificity 84 %), MNA < 72 μm2 for 100% detection of benign cases (sensitivity 91%). Histomorphometry showed a significant correlation between the MNA and most clinicopathological features, with the strongest association observed for histological grade (p <0.0001). MNA seems to be a prognosticator in Libyan breast cancer (Pearson’s test r = - 0.29, p = 0.019), but at lower level of significance than in the European material. A corresponding relationship was not found in shape-related morphometric features. ER and PR staining scores were in correlation with the clinical stage (p= 0.017, and 0.015, respectively), and also associated with lymph node negative patients (p=0.03, p=0.05, respectively). Receptor-positive (HR+) patients had a better survival. The fraction of HR+ cases among Libyan breast cancers is about the same as the fraction of positive cases in European breast cancer. The study suggests that also weak staining (corresponding to as few as 1% positive cells) has prognostic value. The prognostic significance may be associated with the practice to use antihormonal therapy in HR+ cases. The low survival and advanced presentation is associated with active cell proliferation, atypical nuclear morphology and aneuploid nuclear DNA content in Libyan breast cancer patients. The findings support the idea that breast cancer is not one type of disease, but should probably be classified into premenopausal and post menopausal types.

Nuclear morphometry, apoptotic and mitotic indices, and tubular differentiation in Libyan breast cancer

Aims of this study were to evaluate the relations of nuclear morphometry, mitotic and apoptotic indices, and tubular differentiation with clinicopathological features and survival rate in Libyan women. The data were compared with corresponding results on Finnish, and Nigerian female breast cancer patients. Histological samples of breast cancer (BC) from 131 patients were retrospectively studied. Mitotic activity indices (MAI and SMI), apoptotic index (AI), and fraction of fields with tubular differentiation (FTD) were estimated. Samples were also studied by computerized nuclear morphometry, such as mean nuclear area (MNA). Demographic and clinicopathological features were analyzed from 234 patients. The Libyan BC was dominantly premenopausal, and aggressive in behavior. There were statistically significant correlations between the mean nuclear area, fraction of fields with tubular differentiation, apoptotic index and proliferative indices, and most clinicopathological features. The highest significances were shown between lymph node status and the proliferative and apoptotic indices (p=0.003 with SMI, and p=0.005 with AI). There were significant associations between clinical stage and SMI and AI (p=0.002 and 0.009, respectively). The most significant associations with grade were observed with MNA and FTD (p<0.0001 and 0.001, respectively). The proliferative differences between Libyan, Nigerian and Finnish populations were prominent. These indices in Libyan were lower than in Nigerian, but higher than in Finnish patients. The Libyan patients’ AI is slightly higher than in Nigeria, but much higher than in Finland. The differences between countries may be associated with the known variation in the distribution of genetic markers in these populations. The results also indicated that morphometric factors can be reliable prognostic indicators in Libyan BC patients.

Diffusion Tensor Imaging as a Diagnostic and Research Tool: A Study on Preterm Infants

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI is based on free thermal motion (diffusion) of water molecules. The properties of diffusion can be represented using parameters such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, which are calculated from DTI data. These parameters can be used to study the microstructure in fibrous structure such as brain white matter. The aim of this study was to investigate the reproducibility of region-of-interest (ROI) analysis and determine associations between white matter integrity and antenatal and early postnatal growth at term age using DTI. Antenatal growth was studied using both the ROI and tract-based spatial statistics (TBSS) method and postnatal growth using only the TBSS method. The infants included to this study were born below 32 gestational weeks or birth weight less than 1,501 g and imaged with a 1.5 T MRI system at term age. Total number of 132 infants met the inclusion criteria between June 2004 and December 2006. Due to exclusion criteria, a total of 76 preterm infants (ROI) and 36 preterm infants (TBSS) were accepted to this study. The ROI analysis was quite reproducible at term age. Reproducibility varied between white matter structures and diffusion parameters. Normal antenatal growth was positively associated with white matter maturation at term age. The ROI analysis showed associations only in the corpus callosum. Whereas, TBSS revealed associations in several brain white matter areas. Infants with normal antenatal growth showed more mature white matter compared to small for gestational age infants. The gestational age at birth had no significant association with white matter maturation at term age. It was observed that good early postnatal growth associated negatively with white matter maturation at term age. Growth-restricted infants seemed to have delayed brain maturation that was not fully compensated at term, despite catchup growth.

Assessment of the diagnostic value of diffusion tensor imaging in patients with spinal cord compression: a meta-analysis

We investigated the diagnostic value of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of magnetic resonance diffusion tensor imaging (DTI) in patients with spinal cord compression (SCC) using a meta-analysis framework. Multiple scientific literature databases were exhaustively searched to identify articles relevant to this study. Mean values and standardized mean differences (SMDs) were calculated for the ADC and FA in normal and diseased tissues. The STATA version 12.0 software was used for statistical analysis. Of the 41 articles initially retrieved through database searches, 11 case-control studies were eligible for the meta-analysis and contained a combined total of 645 human subjects (394 patients with SCC and 251 healthy controls). All 11 studies reported data on FA, and 9 contained data related to the ADC. The combined SMDs of the ADC and FA showed that the ADC was significantly higher and the FA was lower in patients with SCC than in healthy controls. Subgroup analysis based on the b value showed higher ADCs in patients with SCC than in healthy controls at b values of both ≤500 and >500 s/mm2. In summary, the main findings of this meta-analysis revealed an increased ADC and decreased FA in patients with SCC, indicating that DTI is an important diagnostic imaging tool to assess patients suspected to have SCC.

Developing a numerical inverse-theory-based extraction of orientation-dependent relaxation rates from partially- relaxed spectra

Second-rank tensor interactions, such as quadrupolar interactions between the spin- 1 deuterium nuclei and the electric field gradients created by chemical bonds, are affected by rapid random molecular motions that modulate the orientation of the molecule with respect to the external magnetic field. In biological and model membrane systems, where a distribution of dynamically averaged anisotropies (quadrupolar splittings, chemical shift anisotropies, etc.) is present and where, in addition, various parts of the sample may undergo a partial magnetic alignment, the numerical analysis of the resulting Nuclear Magnetic Resonance (NMR) spectra is a mathematically ill-posed problem. However, numerical methods (de-Pakeing, Tikhonov regularization) exist that allow for a simultaneous determination of both the anisotropy and orientational distributions. An additional complication arises when relaxation is taken into account. This work presents a method of obtaining the orientation dependence of the relaxation rates that can be used for the analysis of the molecular motions on a broad range of time scales. An arbitrary set of exponential decay rates is described by a three-term truncated Legendre polynomial expansion in the orientation dependence, as appropriate for a second-rank tensor interaction, and a linear approximation to the individual decay rates is made. Thus a severe numerical instability caused by the presence of noise in the experimental data is avoided. At the same time, enough flexibility in the inversion algorithm is retained to achieve a meaningful mapping from raw experimental data to a set of intermediate, model-free

Geodynamics of the Andaman - Sumatra - Java Trench - Arc System Based on Gravity and Seismotectonic Study

This work aims to study the variation in subduction zone geometry along and across the arc and the fault pattern within the subducting plate. Depth of penetration as well as the dip of the Benioff zone varies considerably along the arc which corresponds to the curvature of the fold- thrust belt which varies from concave to convex in different sectors of the arc. The entire arc is divided into 27 segments and depth sections thus prepared are utilized to investigate the average dip of the Benioff zone in the different parts of the entire arc, penetration depth of the subducting lithosphere, the subduction zone geometry underlying the trench, the arctrench gap, etc.The study also describes how different seismogenic sources are identified in the region, estimation of moment release rate and deformation pattern. The region is divided into broad seismogenic belts. Based on these previous studies and seismicity Pattern, we identified several broad distinct seismogenic belts/sources. These are l) the Outer arc region consisting of Andaman-Nicobar islands 2) the back-arc Andaman Sea 3)The Sumatran fault zone(SFZ)4)Java onshore region termed as Jave Fault Zone(JFZ)5)Sumatran fore arc silver plate consisting of Mentawai fault(MFZ)6) The offshore java fore arc region 7)The Sunda Strait region.As the Seismicity is variable,it is difficult to demarcate individual seismogenic sources.Hence, we employed a moving window method having a window length of 3—4° and with 50% overlapping starting from one end to the other. We succeeded in defining 4 sources each in the Andaman fore arc and Back arc region, 9 such sources (moving windows) in the Sumatran Fault zone (SFZ), 9 sources in the offshore SFZ region and 7 sources in the offshore Java region. Because of the low seismicity along JFZ, it is separated into three seismogenic sources namely West Java, Central Java and East Java. The Sunda strait is considered as a single seismogenic source.The deformation rates for each of the seismogenic zones have been computed. A detailed error analysis of velocity tensors using Monte—Carlo simulation method has been carried out in order to obtain uncertainties. The eigen values and the respective eigen vectors of the velocity tensor are computed to analyze the actual deformation pattem for different zones. The results obtained have been discussed in the light of regional tectonics, and their implications in terms of geodynamics have been enumerated.ln the light of recent major earthquakes (26th December 2004 and 28th March 2005 events) and the ongoing seismic activity, we have recalculated the variation in the crustal deformation rates prior and after these earthquakes in Andaman—Sumatra region including the data up to 2005 and the significant results has been presented.ln this chapter, the down going lithosphere along the subduction zone is modeled using the free air gravity data by taking into consideration the thickness of the crustal layer, the thickness of the subducting slab, sediment thickness, presence of volcanism, the proximity of the continental crust etc. Here a systematic and detailed gravity interpretation constrained by seismicity and seismic data in the Andaman arc and the Andaman Sea region in order to delineate the crustal structure and density heterogeneities a Io nagnd across the arc and its correlation with the seismogenic behaviour is presented.

An algorithmic approach for collaborative-based prediction of user contexts in ubiquitous environments under consideration of legal implications

Mit Hilfe der Vorhersage von Kontexten können z. B. Dienste innerhalb einer ubiquitären Umgebung proaktiv an die Bedürfnisse der Nutzer angepasst werden. Aus diesem Grund hat die Kontextvorhersage einen signifikanten Stellenwert innerhalb des ’ubiquitous computing’. Nach unserem besten Wissen, verwenden gängige Ansätze in der Kontextvorhersage ausschließlich die Kontexthistorie des Nutzers als Datenbasis, dessen Kontexte vorhersagt werden sollen. Im Falle, dass ein Nutzer unerwartet seine gewohnte Verhaltensweise ändert, enthält die Kontexthistorie des Nutzers keine geeigneten Informationen, um eine zuverlässige Kontextvorhersage zu gewährleisten. Daraus folgt, dass Vorhersageansätze, die ausschließlich die Kontexthistorie des Nutzers verwenden, dessen Kontexte vorhergesagt werden sollen, fehlschlagen könnten. Um die Lücke der fehlenden Kontextinformationen in der Kontexthistorie des Nutzers zu schließen, führen wir den Ansatz zur kollaborativen Kontextvorhersage (CCP) ein. Dabei nutzt CCP bestehende direkte und indirekte Relationen, die zwischen den Kontexthistorien der verschiedenen Nutzer existieren können, aus. CCP basiert auf der Singulärwertzerlegung höherer Ordnung, die bereits erfolgreich in bestehenden Empfehlungssystemen eingesetzt wurde. Um Aussagen über die Vorhersagegenauigkeit des CCP Ansatzes treffen zu können, wird dieser in drei verschiedenen Experimenten evaluiert. Die erzielten Vorhersagegenauigkeiten werden mit denen von drei bekannten Kontextvorhersageansätzen, dem ’Alignment’ Ansatz, dem ’StatePredictor’ und dem ’ActiveLeZi’ Vorhersageansatz, verglichen. In allen drei Experimenten werden als Evaluationsbasis kollaborative Datensätze verwendet. Anschließend wird der CCP Ansatz auf einen realen kollaborativen Anwendungsfall, den proaktiven Schutz von Fußgängern, angewendet. Dabei werden durch die Verwendung der kollaborativen Kontextvorhersage Fußgänger frühzeitig erkannt, die potentiell Gefahr laufen, mit einem sich nähernden Auto zu kollidieren. Als kollaborative Datenbasis werden reale Bewegungskontexte der Fußgänger verwendet. Die Bewegungskontexte werden mittels Smartphones, welche die Fußgänger in ihrer Hosentasche tragen, gesammelt. Aus dem Grund, dass Kontextvorhersageansätze in erster Linie personenbezogene Kontexte wie z.B. Standortdaten oder Verhaltensmuster der Nutzer als Datenbasis zur Vorhersage verwenden, werden rechtliche Evaluationskriterien aus dem Recht des Nutzers auf informationelle Selbstbestimmung abgeleitet. Basierend auf den abgeleiteten Evaluationskriterien, werden der CCP Ansatz und weitere bekannte kontextvorhersagende Ansätze bezüglich ihrer Rechtsverträglichkeit untersucht. Die Evaluationsergebnisse zeigen die rechtliche Kompatibilität der untersuchten Vorhersageansätze bezüglich des Rechtes des Nutzers auf informationelle Selbstbestimmung auf. Zum Schluss wird in der Dissertation ein Ansatz für die verteilte und kollaborative Vorhersage von Kontexten vorgestellt. Mit Hilfe des Ansatzes wird eine Möglichkeit aufgezeigt, um den identifizierten rechtlichen Probleme, die bei der Vorhersage von Kontexten und besonders bei der kollaborativen Vorhersage von Kontexten, entgegenzuwirken.

Image-Based View Synthesis

We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position is significantly far away from the viewing cone of the example images ("view extrapolation"), yet without ever modeling the 3D structure of the scene. The method relies on synthesizing a chain of "trilinear tensors" that governs the warping function from the example images to the novel image, together with a multi-dimensional interpolation function that synthesizes the non-rigid motions of the viewed object from the virtual camera position. We show that two closely spaced example images alone are sufficient in practice to synthesize a significant viewing cone, thus demonstrating the ability of representing an object by a relatively small number of model images --- for the purpose of cheap and fast viewers that can run on standard hardware.

Image Based Rendering Using Algebraic Techniques

This paper presents an image-based rendering system using algebraic relations between different views of an object. The system uses pictures of an object taken from known positions. Given three such images it can generate "virtual'' ones as the object would look from any position near the ones that the two input images were taken from. The extrapolation from the example images can be up to about 60 degrees of rotation. The system is based on the trilinear constraints that bind any three view so fan object. As a side result, we propose two new methods for camera calibration. We developed and used one of them. We implemented the system and tested it on real images of objects and faces. We also show experimentally that even when only two images taken from unknown positions are given, the system can be used to render the object from other view points as long as we have a good estimate of the internal parameters of the camera used and we are able to find good correspondence between the example images. In addition, we present the relation between these algebraic constraints and a factorization method for shape and motion estimation. As a result we propose a method for motion estimation in the special case of orthographic projection.

Unrestricted Skyrme-tensor time-dependent Hartree-Fock model and its application to the nuclear response from spherical to triaxial nuclei

The nuclear time-dependent Hartree-Fock model formulated in three-dimensional space, based on the full standard Skyrme energy density functional complemented with the tensor force, is presented. Full self-consistency is achieved by the model. The application to the isovector giant dipole resonance is discussed in the linear limit, ranging from spherical nuclei (16O and 120Sn) to systems displaying axial or triaxial deformation (24Mg, 28Si, 178Os, 190W and 238U). Particular attention is paid to the spin-dependent terms from the central sector of the functional, recently included together with the tensor. They turn out to be capable of producing a qualitative change on the strength distribution in this channel. The effect on the deformation properties is also discussed. The quantitative effects on the linear response are small and, overall, the giant dipole energy remains unaffected. Calculations are compared to predictions from the (quasi)-particle random-phase approximation and experimental data where available, finding good agreement

Dimensionality reduction assisted tensor clustering

This paper is concerned with tensor clustering with the assistance of dimensionality reduction approaches. A class of formulation for tensor clustering is introduced based on tensor Tucker decomposition models. In this formulation, an extra tensor mode is formed by a collection of tensors of the same dimensions and then used to assist a Tucker decomposition in order to achieve data dimensionality reduction. We design two types of clustering models for the tensors: PCA Tensor Clustering model and Non-negative Tensor Clustering model, by utilizing different regularizations. The tensor clustering can thus be solved by the optimization method based on the alternative coordinate scheme. Interestingly, our experiments show that the proposed models yield comparable or even better performance compared to most recent clustering algorithms based on matrix factorization.

Connectivity-based parcellation of the human frontal polar cortex

The frontal pole corresponds to Brodmann area (BA) 10, the largest single architectonic area in the human frontal lobe. Generally, BA10 is thought to contain two or three subregions that subserve broad functions such as multitasking, social cognition, attention, and episodic memory. However, there is a substantial debate about the functional and structural heterogeneity of this large frontal region. Previous connectivity-based parcellation studies have identified two or three subregions in the human frontal pole. Here, we used diffusion tensor imaging to assess structural connectivity of BA10 in 35 healthy subjects and delineated subregions based on this connectivity. This allowed us to determine the correspondence of structurally based subregions with the scheme previously defined functionally. Three subregions could be defined in each subject. However, these three subregions were not spatially consistent between subjects. Therefore, we accepted a solution with two subregions that encompassed the lateral and medial frontal pole. We then examined resting-state functional connectivity of the two subregions and found significant differences between their connectivities. The medial cluster was connected to nodes of the default-mode network, which is implicated in internally focused, self-related thought, and social cognition. The lateral cluster was connected to nodes of the executive control network, associated with directed attention and working memory. These findings support the concept that there are two major anatomical subregions of the frontal pole related to differences in functional connectivity.

Heterogeneous tensor decomposition for clustering via manifold optimization

Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.

Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

Mechanosensitivity of astrocytes on optimized polyacrylamide gels analyzed by quantitative morphometry

Cells are able to detect and respond to mechanical cues from their environment. Previous studies have investigated this mechanosensitivity on various cell types, including neural cells such as astrocytes. In this study, we have carefully optimized polyacrylamide gels, commonly used as compliant growth substrates, considering their homogeneity in surface topography, mechanical properties, and coating density, and identified several potential pitfalls for the purpose of mechanosensitivity studies. The resulting astrocyte response to growth on substrates with shear storage moduli of G` = 100 Pa and G` = 10 kPa was then evaluated as a function of coating density of poly-D-lysine using quantitative morphometric analysis. Astrocytes cultured on stiff substrates showed significantly increased perimeter, area, diameter, elongation, number of extremities and overall complexity if compared to those cultured on compliant substrates. A statistically significant difference in the overall morphological score was confirmed with an artificial intelligence-based shape analysis. The dependence of the cells` morphology on PDL coating density seemed to be weak compared to the effect of the substrate stiffness and was slightly biphasic, with a maximum at 10-100 mu g ml(-1) PDL concentration. Our finding suggests that the compliance of the surrounding tissue in vivo may influence astrocyte morphology and behavior.