Mortality in a cohort of men expressing the glucose-6-phosphate dehydrogenase deficiency

The objective of this study was to test the hypothesis of a lower mortality from cancer and cardiovascular diseases among men expressing glucose-6-phosphate dehydrogenase (G6PD) deficiency. We designed a mortality study based on death certificates from January 1, 1982 through December 31, 1992 in a cohort of G6PD-deficient men. Cohort members were 1,756 men, identified as expressing the G6PD-deficient phenotype during a 1981 population screening of the G6PD polymorphism. The setting was the island of Sardinia, Italy. Outcome measures were cause-specific standardized mortality ratios (SMRs), which were computed as 100 times the observed/expected ratio, with the general Sardinian male population as the reference. Deaths from all causes were significantly less than expected due to decreased SMRs for ischemic heart disease (SMR, 28; 95% confidence interval [CI], 10 to 62), cerebrovascular disease (SMR, 22; 95% CI, 6 to 55), and liver cirrhosis (SMR, 12; 95% CI, 0 to 66), which explained 95.6% of the deficit in total mortality. All cancer mortality was close to the expectation, with a significant increase in the SMR for non-Hodgkin's lymphoma (SMR, 545; 95% CI, 147 to 1,395). A decrease in mortality from cardiovascular diseases was one of the study hypotheses, based on an earlier human report and experimental evidence. However, selection bias is also a likely explanation. Further analytic studies are warranted to confirm whether subjects expressing the G6PD-deficient phenotype are protected against ischemic heart disease and cerebrovascular disease. This cohort study is consistent with more recent case-control studies in rejecting the hypothesis of a decreased cancer risk among G6PD-deficient subjects. The observed increase in mortality from non-Hodgkin's lymphoma and decrease in mortality from liver cirrhosis were not previously reported.     

Molecular mechanisms of transforming growth factor-beta signaling

The present experiments examined the effects of posttraining intrahippocampal injections of the degradative enzyme-resistant methylcarbamyl analog of the bioactive phospholipid platelet-activating factor (mc-PAF) and the platelet-activating factor (PAF) receptor antagonists BN52021 and BN 50730 on memory in male Long-Evans rats trained in a hidden platform version of the Morris water maze. Following an eight-trial training session, rats received a unilateral intrahippocampal injection of mc-PAF (0.5, 1.0, or 2.0 microgram/0.5 microliter), lyso-PAF (1.0 microgram/0.5 microliter), the cell surface PAF receptor antagonist BN 52021 (0.25, 0.5, or 1.0 micrigram/0.5 microliter/, the intracellular PAF receptor antagonist BN 50730 (2.0, 5.0, or 10.0 microgram/0.5 microliter), or vehicle (50% DMSO in 0.9% saline; 0.5 microliter). On a retention test conducted 24 h after training, the escape latencies of rats administered mc-PAF (1.0 or 2.0 microgram) were significantly lower than those of the vehicle-injected controls, demonstrating a memory-enhancing effect of mc-PAF. Injections of lyso-PAF, a structurally similar metabolite of PAF, had no influence on memory, indicating that the memory-enhancing effect of mc-PAF is not caused by membrane perturbation by the phospholipid. The retention test escape latencies of rats administered BN 52021 (0.5 microgram) and BN 50730 (5.0 or 10 microgram) were significantly higher than those of the controls, indicating a memory impairing effect of both PAF antagonists. When mc-PAF, BN 52021, or BN 50730 was administered 2 h posttraining, no effect on retention was observed, indicating a time-dependent effect of the neuroactive substances on memory storage. The findings suggest a role for endogenous PAF in hippocampal-dependent memory processes.     

Fibronectin fragments modulate human retinal capillary cell proliferation and migration

Capillary morphogenesis involves cell-cell and cell-matrix interactions. Proteases elaborated by capillary cells modify the extracellular matrix (ECM) to facilitate capillary tube formation. Previously, we detected the presence of fibronectin fragments (Fn-f) associated with the proform of matrix metalloprotease-2 (MMP-2) in conditioned medium of human retinal endothelial cells (HRECs). Association of this fragment to latent MMP-2 prevented autocatalytic activation of MMP-2, suggesting a modulatory role of Fn-f in MMP-2 activation. In this report, we examined the potential role of Fn-f on two processes involved in angiogenesis, proliferation and migration of vascular cells. The effects of Fn-f on proliferation were determined by DNA synthesis and cell counts. Their effects on migration were assessed using modified Boyden chambers. Seven Fn-f were tested on vascular cell migration and/or proliferation. Three Fn-f induced migration. Fn-f of 30-kDa and 120-kDa size positively affected proliferation of microvascular cells but not macrovascular cells. A 45-kDa gelatin binding fragment of Fn inhibited HREC proliferation but stimulated pericyte and smooth muscle cell proliferation. The potency of these fragments exceeded that of the known angiogenic growth factor, basic fibroblast growth factor (bFGF), on HREC migration. ECM components such as fibronectin may influence capillary morphogenesis by the generation of fragments that can modulate proliferation, migration, and protease activation. In the setting of diabetes, excess Fn is generated and is available for degradation. Thus, the production of Fn-f may be specifically relevant to the angiogenesis observed in proliferative diabetic retinopathy.     

A new class of tobacco chitinases homologous to bacterial exo-chitinases displays antifungal activity

A novel chitinase gene of tobacco was isolated and characterized by DNA sequence analysis of a genomic clone and a cDNA clone. Comparative sequence analysis of both clones showed an identity of 94%. The proteins encoded by these sequences do not correspond to any of the previously characterized plant chitinases of classes I-IV and are designated as class V chitinases. Comparison of the chitinase class V peptide sequence with sequences in the Swiss Protein databank revealed significant sequence similarity with bacterial exo-chitinases from Bacillus circulans, Serratia marcescens and Streptomyces plicatus. It was demonstrated that class V chitinase gene expression is induced after treatment of tobacco with different forms of stress, like TMV-infection, ethylene treatment, wounding or ultraviolet irradiation. Two related chitinase class V proteins of 41 and 43 kDa were purified from Samsun NN tobacco leaves inoculated with tobacco mosaic virus. The proteins were purified by Chelating Superose chromatography and gel filtration. In vitro assays demonstrated that class V chitinases have endo-chitinase activity and exhibit antifungal activity toward Trichoderma viride and Alternaria radicina. In addition, it was shown that class V chitinase acts synergistically with tobacco class I beta-1,3-glucanase against Fusarium solani germlings.     

Testicular lymphoma: a population-based study of incidence, clinicopathological correlations and prognosis. The Danish Lymphoma Study Group, LYFO

In a Danish population-based non-Hodgkin's lymphoma registry, 2687 newly diagnosed patients were registered from 1983 to 1992. 39 had testicular involvement (TL) (incidence 0.26/10(5)/year). Median age was 71 years. 24 cases had localised and 15 had disseminated disease. Histologically, all cases were diffuse (65% diffuse centroblastic type). Of the 27 tested, 11% were of T- and 89% of B-immunophenotype. In localised cases, where surgery was supplemented by combination chemotherapy (CCT), the relapse rate was 15.4%. The relapse rate for cases with localised disease treated with other regimens (orchiectomy and/or radiotherapy) was 63.6% (P < 0.05). Median relapse-free survival was 28 and 14 months, respectively. Overall 5-year survival for all cases was 17%. Adverse prognostic factors at the univariate level were stage IV, constitutional symptoms, serum lactic dehydrogenase elevation and performance score (WHO 3-4). It is suggested that the treatment of stage IE/IIE TL should include early CCT and CNS prophylaxis.     

Smart home security: challenges,issues and solutions at different IoT layers

The Journal of Supercomputing - The Internet of Things is a rapidly evolving technology in which interconnected computing devices and sensors share data over the network to decipher different...     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

Feature Selection and Extraction Methods for Power Systems Transient Stability Assessment Employing Computational Intelligence Techniques

One of the important aspects in achieving better performance for transient stability assessment (TSA) of power systems employing computational intelligence (CI) techniques is by incorporating feature reduction techniques. For small power system the number of features may be small but when larger systems are considered the number of features increased as the size of the systems increases. Apart from employing faster CI techniques to achieve faster and accurate TSA of power system, feature reduction techniques are needed in reducing the input features while preserving the needed information so as to make faster training of the CI technique. This paper presents feature reductions techniques used, namely correlation analysis and principle component analysis, in reducing number of input features presented to two CI techniques for TSA, namely probabilistic neural network (PNN) and least squares support vector machines (LS-SVM). The proposed feature reduction techniques are implemented and tested on the IEEE 39-bus test system and 87-bus Malaysia’s power system. Numerical results are presented to demonstrate the performance of the feature reduction techniques and its effects on the accuracies and time taken for training the two CI techniques.     

Sentic Computing for social media marketing

In a world in which millions of people express their opinions about commercial products in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand or organization. Opinion mining for product positioning, in fact, is getting a more and more popular research field but the extraction of useful information from social media is not a simple task. In this work we merge AI and Semantic Web techniques to extract, encode and represent this unstructured information. In particular, we use Sentic Computing, a multi-disciplinary approach to opinion mining and sentiment analysis, to semantically and affectively analyze text and encode results in a semantic aware format according to different web ontologies. Eventually we represent this information as an interconnected knowledge base which is browsable through a multi-faceted classification website.