Relation of follicular dendritic reticulum cells to Reed-Sternberg cells of Hodgkin's disease with emphasis on the expression of CD21 antigen

Based on observations of 66 cases, in which tissues were specially processed to optimize the simultaneous preservation of cell membrane antigens and morphology, we provide evidence in favor of a relationship between follicular dendritic reticulum cells (FDRC) and Reed-Sternberg (RS) cells of Hodgkin's disease (HD) other than the lymphocyte predominance subtype. RS cells were intimately related to the FDRC network (75% of cases), and the expression of CD21 antigen was frequent (41% of cases). Exclusive expression of CD21 antigen was found in 11 cases of HD, while the expression of other B-cell-associated markers (CD19, CD20, CD22) was both variable and inconsistent. The expression of T-cell antigens (CD3, CD4, CD8) was rare. Null phenotype of RS cells was observed in 27 of 66 cases (41%). Epstein-Barr virus (EBV) nucleic acids were found in 34 of 66 (51.5%) cases. Double labeling techniques showed the presence of EBV-positive RS cells within the FDRC network. A non-B-cell origin of RS cells was supported by the differential expression of EBV latent antigens in HD (latent membrane protein+, EB nuclear antigen 2-), which is unusual in EBV-driven lymphoblastoid cell lines and EBV-positive B-cell lymphomas. FDRC and RS cells are known to share morphological traits (binucleated cells), and both cell types possess Fc receptor for IgG. The hypothesis is further backed by the findings of CD15 antigen expression by occasional RS-like dysplastic FDRC in Castleman's disease (five cases), which is characterized by hyperplasia of FDRC. Whether FDRC might be the only cells involved in the conversion to RS cells by the loss or gain of antigens remains to be determined.     

Microblogs recommendations based on implicit similarity in content social networks

With the development of online social networking applications, microblogs have become a necessary online communication network in daily life. Users are interested in obtaining personalized recommendations related to their tastes and needs. In some microblog systems, tags are not available, or the use of tags is rare. In addition, user-specified social relations are extremely rare. Hence, sparsity is a problem in microblog systems. To address this problem, we propose a new framework called Pblog to alleviate sparsity. Pblog identifies users’ interests via their microblogs and social relations and computes implicit similarity among users using a new algorithm. The experimental results indicated that the use of this algorithm can improve the results. In online social networks, such as Twitter, the number of microblogs in the system is high, and it is constantly increasing. Therefore, providing personalized recommendations to target users requires considerable time. To address this problem, the Pblog framework groups similar users using the analytic hierarchy process (AHP) method. Then, Pblog prunes microblogs of the target user group and recommends microblogs with higher ratings to the target user. In the experimental results section, the Pblog framework was compared with several other frameworks. All of these frameworks were run on two datasets: Twitter and Tumblr. Based on the results of these comparisons, the Pblog framework provides more appropriate recommendations to the target user than previous frameworks.

     

A robust optimization approach for imprecise data envelopment analysis

Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA). However, the input and output data in real-world problems are often imprecise or ambiguous. Some researchers have proposed interval DEA (IDEA) and fuzzy DEA (FDEA) to deal with imprecise and ambiguous data in DEA. Nevertheless, many real-life problems use linguistic data that cannot be used as interval data and a large number of input variables in fuzzy logic could result in a significant number of rules that are needed to specify a dynamic model. In this paper, we propose an adaptation of the standard DEA under conditions of uncertainty. The proposed approach is based on a robust optimization model in which the input and output parameters are constrained to be within an uncertainty set with additional constraints based on the worst case solution with respect to the uncertainty set. Our robust DEA (RDEA) model seeks to maximize efficiency (similar to standard DEA) but under the assumption of a worst case efficiency defied by the uncertainty set and it’s supporting constraint. A Monte-Carlo simulation is used to compute the conformity of the rankings in the RDEA model. The contribution of this paper is fourfold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA; (2) we address the gap in the imprecise DEA literature for problems not suitable or difficult to model with interval or fuzzy representations; (3) we propose a robust optimization model in which the input and output parameters are constrained to be within an uncertainty set with additional constraints based on the worst case solution with respect to the uncertainty set; and (4) we use Monte-Carlo simulation to specify a range of Gamma in which the rankings of the DMUs occur with high probability.     

Extraction,optimisation and characterisation of phenolics from Thymus vulgaris L.: phenolic content and profiles in relation to antioxidant,antidiabetic and antihypertensive properties

The objectives of this study were to examine varying extraction conditions of Thymus vulgaris L. as related to phenolic content and profiles of the extracts and their antioxidant, antihypertensive and antidiabetic properties. Phenolics were extracted under various conditions pertaining to free and bound phenolics, solvent type and combination of extraction time and temperature, and these extracts were evaluated in terms of their antioxidant activities and inhibitory activities of angiotensin‐converting enzyme (ACE), α‐glucosidase and α‐amylase. The acetone–water solvent mixture (1:1; v/v) produced the extract with the greatest phenolic content, antioxidant activity and inhibitory activities of ACE and α‐glucosidase. The optimal extraction temperature for maximum phenolic content and antioxidant activity associated with methanol extraction was 60 °C, whereas a lower temperature at 40 °C was required to maximise inhibitory activities for ACE, α‐glucosidase and α‐amylase. An inverse relationship was seen between antioxidant and glucosidase inhibitory activities vs. the ACE and α‐amylase inhibitory activities, which suggests the need for extractions to be directed to specific bioactivities of thyme extracts. Generally, the results indicate major differences in phenolic profiles among the tested extraction conditions with thymol as the predominant phenolic seen in most extractions, while gallic acid, rosmarinic acid or diosmin also predominated in other extracts. Extracts with the same predominant phenolic compound and similar phenolic content showed major disparities in their ACE, glucosidase and α‐amylase inhibitory activities, indicating that the major phenolic profiles of thyme extracts may not be necessarily related to the degree of inhibition of ACE, glucosidase and α‐amylase enzymes.     

Hodgkin''s disease and anaplastic large cell lymphoma in 1998

The purpose of this study was to investigate the effects of cohort size on maximum likelihood estimates of mortality parameters. Recent experimental investigations have stressed the importance of large cohorts for detecting leveling off of mortality rates at older ages. In the present study, emphasis was placed on evaluation of relatively small cohorts (about 150-300 individuals). Deaths were simulated under the assumption of the frailty mortality model. Two different parameter sets that resulted in differences in mean life span of more than twofold were used for simulations. Our smallest cohorts yielded parameter estimates that had generally good statistical properties, but relatively large standard errors. For tests of hypotheses concerning equality of parameters among populations or experimental treatments, empirical standard errors (obtained from several cohorts) were preferable to asymptotic standard errors (obtained for single cohorts). In particular, empirical standard errors yielded reliable type I error rates.     

CNA.42, a new monoclonal antibody directed against a fixative-resistant antigen of follicular dendritic reticulum cells

A new monoclonal antibody (MAb), CNA.42, was generated using the CEM T-cell line. It recognizes a 120-kd formalin-resistant glycosylated antigen that is mainly expressed by follicular dendritic reticulum cells (FDRCs). This antigen is also expressed by a few mononuclear cells in the paracortical area of reactive lymph nodes and by some cortical thymocytes. Two hundred and eighty-nine cases of hematopoietic tumors of various types were tested with this antibody. They showed either intact FDRC networks or FDRC networks dispersed among malignant cells. In follicular lymphomas, the follicular pattern was highlighted by CNA.42 MAb. Expanded FDRC networks were found in angioimmunoblastic T-cell lymphomas. Neoplastic cells were positive in 43.6% (24/55) of T-cell and 4.6% (6/129) of B-cell lymphomas. The highest percentage of cases with positive neoplastic cells was found in anaplastic large-cell lymphomas (62.5%; 15/24). In Hodgkin's disease, FDRC networks, sometimes encasing Hodgkin and Reed-Sternberg (HRS) cells, were found. HRS cells were also stained by this antibody in 23 (21.9%) of the 105 cases examined. A variety of normal nonlymphoid tissues and nonhematopoietic tumors, such as some neurogenic tumors, carcinoma, and occasional sarcomas, were found to be positive. Analysis of the reactivity of CNA.42 antibody with FDRCs of lymphoid tissue from different animal species showed similar reactivity to that observed in humans, suggesting widespread evolutionary conservation of the antigen recognized by this antibody. In daily diagnostic practice, CNA.42 MAb seems to be a suitable FDRC marker and possibly has an auxiliary role in recognizing T-cell lymphomas.     

Object-based road extraction from satellite images using ant colony optimization

Increasing demands for up-to-date road network and the availability of very-high-resolution (VHR) satellite images as well as the popularity of high-speed computers provide motivation and preliminary materials for researchers to propose more advanced approaches in order to increase the automation and robustness of road extraction strategies. In this article, road characteristics are modelled via object-based image analysis (OBIA). Object-based information is embedded as heuristic information in the ant colony optimization (ACO) algorithm for handling the road network extraction problem. A new neighbourhood definition in object space is introduced, which affects the transition rule in order to decrease the road gaps. Furthermore, an innovative desirability function for ACO is designed, which extracts the road objects, competently. The experimental results demonstrate the efficiency of the proposed algorithm for road extraction from VHR images. Moreover, the results of two state-of-the-art methods are compared with the proposed algorithm.     

Positive and normative use of fuzzy DEA‐BCC models: A critical view on NATO enlargement

Data envelopment analysis (DEA) is a widely used mathematical programming approach for comparing the input and output of a set of comparable decision‐making units (DMUs) by evaluating their relative efficiency. The traditional DEA methods require accurate measurement of both the inputs and outputs. However, the real evaluation of the DMUs is often characterized by imprecision and uncertainty in data definitions and measurements. The development of fuzzy DEA (FDEA) with imprecise and ambiguous data has extended the scope of application for efficiency measurement. The purpose of this paper is to develop a fuzzy DEA framework with a BCC model for measuring crisp and interval efficiencies in fuzzy environments. We use an α‐level approach to convert the fuzzy Banker, Charnes, and Cooper (BCC) (variable returns to scale) model into an interval programming model. Instead of comparing the equality (or inequality) of the two intervals, we define a variable in the interval to satisfy our constraints and maximize the efficiency value. We present a numerical example to show the similarities and differences between our solution and the solutions obtained from four fuzzy DEA methods in the literature. In addition, a case study for NATO enlargement is presented to illustrate the applicability of the proposed method.     

Conjugated linoleic acid isomers reduce blood cholesterol levels but not aortic cholesterol accumulation in hypercholesterolemic hamsters

The aim of the present study was to characterize plasma lipids and lipoprotein cholesterol and glucose concentrations in hamsters fed either cis-9, trans-11 CLA (9c, 11t CLA); trans-10, cis-12 CLA (10t, 12c CLA); or linoleic acid (LA) on the accumulation of aortic cholesterol in hypercholesterolemic hamsters. One hundred male F₁B strain Syrian Golden Hamsters (Mesocricetus auratus) (BioBreeders Inc., Watertown, MA) approximately 9 wk of age were housed in individual stainless stel hanging cages at room temperature with a 12-h light/dark cycle. Hamsters were given food and water ad libitum. Following a 1-wk period of acclimation, the hamsters were fed a chow-based (nonpurified) hypercholesterolemic diet (HCD) contaning 10% coconut oil (92% saturated fat) and 0.1% cholesterol for 2 wk. After an overnight fast, the hamsters were bled and plasma cholesterol concentrations were measured. The hamsters were then divided into 4 groups of 25 based on similar mean plasma VLDL and LDL cholesterol (non HDL-C) concentrations. Group 1 remained on the HCD (control). Group 2 was fed the HCD plus 0.5% 9c, 11t CLA isomer. Group 3 was fed the HCD plus 0.5% 10t, 12c CLA isomer. Group 4 was fed the HCD plus 0.5% LA. Compared with the control, both CLA isomers and LA had significantly lower plasma total cholesterol and HDL cholesterol concentrations (P<0.001) after 12 but not 8 wk of treatment and were not significantly different from each other. Also, both CLA isomers had significantly lower plasma non HDL-C concentrations (P<0.01) compared with the control after 12 but not 8 wk of treatment and were not significantly different from each other or the LA-fed hamsters. Plasma TG concentrations were significantly higher (P<0.004) with the 10t, 12c CLA isomer compared with the other treatments at 8 but not at 12 wk of treatment. Plasma TG concentrations were also significantly lower (P<0.03) with the 9c, 11t CLA isomer compared with the control at 12 wk of treatment. Also, the 10t, 12c CLA isomer and LA had significantly higher plasma glucose concentrations compared with the control and 9c, 11t CLA isomer (P<0.008) at 12 wk of treatment whereas at 8 wk, only the LA treatment had significantly higher plasma glucose concentrations (P<0.001) compared with the 9c, 11t CLA isomer. Although liver weights were significantly higher in 10t, 12c CLA isomer-fed hamsters, liver total cholesterol, free cholesterol, cholesterol ester, and TG concentrations were significantly lower in these hamsters compared with hamsters fed the control, 9c, 11t CLA isomer, and LA diets (P<0.05). The 9c, 11t CLA isomer and LA diets tended to reduce cholesterol accumulation in the aortic arch, whereas the 10t, 12c CLA isomer diet tended to raise cholesterol accumulation compared with the control diet; however, neither was significant. In summary, no differences were observed between the CLA isomers for changes in plasma lipids or lipoprotein cholesterol concentrations. However, the 9c, 11t CLA isomer did appear to lower plasma TG and glucose concentrations compared with the 10t, 12c CLA isomer. Such differences may increase the risk of insulin resistance and type 2 diabetes in humans when the 10t, 12c CLA isomer is fed separately.