Generative Boltzmann Adversarial Network in Manet Attack Detection and QOS Enhancement with Latency

Mobile Ad-Hoc Network (MANET) are considered as self-configured network those does not have any centralized base station for the network monitoring and control. MANET environment does not control architecture for routing for the frequent maintenance of topology. The drastic development of Internet leads to adverse effect of development in MANET for different multimedia application those are sensitive to latency. Upon the effective maintenance of the QoS routing route discovery is performed to calculate queue and contention delay. However, the MANET requirement comprises of the complex procedure to withstand the Quality of Service (QoS) with Artificial Intelligence (AI). In MANET it is necessary to compute the MANET attacks with improved QoS with the reduced latency as existing model leads to higher routing and increased latency.  In this paper proposed a Generative Boltzmann Networking Weighted Graph (GBNWG) model for the QoS improvement in MANET to reduce latency. With GBNWG model the MANET model network performance are computed with the weighted graph model. The developed weighted graph computes the routes in the MANET network for the estimation of the available path in the routing metrices. The proposed GBNWG model is comparatively estimated with the conventional QOD technique. Simulation analysis stated that GBNWG scheme exhibits the improved performance in the QoS parameters. The GBNWG scheme improves the PDR value by 12%, 41% reduced control packets and 45% improved throughput value

Effects of occurrence data density on conservation prioritization strategies

Place-prioritization analyses are a means by which researchers can translate information on the geographic distributions of species into quantitative prioritizations of areas for biodiversity conservation action. Although several robust algorithms are now available to support this sort of analysis, their vulnerability to biases deriving from incomplete and imbalanced distributional information is not well understood. In this contribution, we took a well-sampled group (i.e., Icteridae or New World blackbirds) in an intensively sampled region (the contiguous continental United States), and developed a set of pseudo-experimental manipulations of occurrence data density—in effect, we created situations in which data density was reduced 10- or 100-fold, and situations in which data density varied 100-fold from region to region. The effects were marked: priority areas for conservation shifted, appeared, and disappeared as a function of our manipulations. That is, differences in density of data can affect the position and complexity of areas of high conservation priority that are identified using distributional areas of species derived from ecological niche modeling. The effects of data density on prioritizations become more diffuse when considerations of existing protected areas and costs related to human intervention are taken into account, but changes are still manifested. Appropriate considerations of sampling density when constructing ecological niche models to identify distributional areas of species are key to preventing artifactual biases from entering into and affecting results of analyses of conservation priority

Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined‐samples mega‐analysis

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc

A Multicenter Evaluation of Different Chemotherapy Regimens in Older Adults With Head and Neck Squamous Cell Carcinoma Undergoing Definitive Chemoradiation

PURPOSE: The number of older adults with head-and-neck squamous cell carcinoma (HNSCC) is increasing, and treatment of these patients is challenging. Although cisplatin-based chemotherapy concomitantly with radiotherapy is considered standard regimen for patients with locoregionally advanced HNSCC, there is substantial real-world heterogeneity regarding concomitant chemotherapy in older HNSCC patients. METHODS: The XXX study is an international multicenter cohort study including older (≥65 years) HNSCC patients treated with definitive radiotherapy at 13 academic centers in the United States and Europe. Here, patients with concomitant chemoradiation were analyzed regarding overall survival (OS) and progression-free survival (PFS) using Kaplan-Meier analyses, while Fine-Gray competing risks regressions were performed regarding the incidence of locoregional failures (LRFs) and distant metastases (DMs). RESULTS: Six hundred ninety-seven patients with a median age of 71 years were included in this analysis. Single-agent cisplatin was the most common chemotherapy regimen (n=310; 44%), followed by cisplatin plus 5-fluorouracil (n=137; 20%), carboplatin (n=73; 10%), and mitomycin c plus 5-fluorouracil (n=64; 9%). Carboplatin-based regimens were associated with diminished PFS (HR=1.39 [1.03-1.89], p.05). Median cumulative dose of cisplatin was 180 mg/m2 (IQR, 120-200 mg/m2). Cumulative cisplatin doses ≥200 mg/m2 were associated with increased OS (HR=0.71 [0.53-0.95], p=.02), PFS (HR=0.66 [0.51-0.87], p=.003), and lower incidence of LRFs (SHR=0.50 [0.31-0.80], p=.004). Higher cumulative cisplatin doses remained an independent prognostic variable in the multivariate regression analysis for OS (HR=0.996 [0.993-0.999], p=.009). CONCLUSIONS: Single-agent cisplatin can be considered as the standard chemotherapy regimen for older HNSCC patients who can tolerate cisplatin. Cumulative cisplatin doses are prognostically relevant also in older HNSCC patients

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Does copper enhance the antihypertensive effect of Elaeocarpus ganitrus in experimentally induced hypertensive rats?

Ayurveda, one of the traditional systems of medicine of India, reports that the seeds of Elaeocarpus ganitrus Linn. (Tilaceae) can be used for the treatment of hypertension. The main aim is to evaluate the antihypertensive effect of Elaeocarpus ganitrus (Rudraksha) seeds. Powdered seeds were extracted by maceration, overnight, using water, in copper (E1) and glass vessel (E2) and analyzed for antihypertensive activity in cadmium chloride (1 mg/kg intraperitoneally, for a period of 15 days) induced hypertensive male Wistar rats at three dose levels. E1 was administered at the dose of 5, 10, and 15 mg/kg and E2 at dose of 10, 20, and 30 mg/kg. All the data were analyzed using one way analysis of variance (ANOVA) followed by Dunnett′s multiple comparison test. E1 and E2 did not show any toxicity at the dose of 5 g/kg in rats. It was found that 15 mg/kg of E1 and 30 mg/kg of E2 decreases the blood pressure by 30.20 mmHg and 28.96 mmHg, respectively, in hypertensive rats. Thus, it can be said that 15 mg/kg of E1 produced similar decrease in blood pressure as was observed with 30 mg/kg of E2. Copper ions in E1 might be additively affecting the reduction in blood pressure with the usage of Elaeocarpus ganitrus extracts

bddashboard: An infrastructure for biodiversity dashboards in R

The bdverse is a collection of packages that form a general framework for facilitating biodiversity science in R (programming language). Exploratory and diagnostic visualization can unveil hidden patterns and anomalies in data and allow quick and efficient exploration of massive datasets. The development of an interactive yet flexible dashboard that can be easily deployed locally or remotely is a highly valuable biodiversity informatics tool. To this end, we have developed 'bddashboard', which serves as an agile framework for biodiversity dashboard development. This project is built in R, using the Shiny package (RStudio, Inc 2021) that helps build interactive web apps in R. The following key components were developed:Core Interactive Components The basic building blocks of every dashboard are interactive plots, maps, and tables. We have explored all major visualization libraries in R and have concluded that 'plotly' (Sievert 2020) is the most mature and showcases the best value for effort. Additionally, we have concluded that 'leaflet' (Graul 2016) shows the most diverse and high-quality mapping features, and DT (DataTables library) (Xie et al. 2021) is best for rendering tabular data. Each component was modularized to better adjust it for biodiversity data and to enhance its flexibility.Field Selector The field selector is a unique module that makes each interactive component much more versatile. Users have different data and needs; thus, every combination or selection of fields can tell a different story. The field selector allows users to change the X and Y axis on plots, to choose the columns that are visible on a table, and to easily control map settings. All that in real-time, without reloading the page or disturbing the reactivity. The field selector automatically detects how many columns a plot needs and what type of columns can be passed to the X-axis or Y-axis. The field selector also displays the completeness of each field. Plot Navigation We developed the plot navigation module to prevent unwanted extreme cases. Technically, drawing 1,000 bars on a single bar plot is possible, but this visualization is not human-friendly. Navigation allows users to decide how many values they want to see on a single plot. This technique allows for fast drawing of extensive datasets without affecting page reactivity, dramatically improving performance and functioning as a fail-safe mechanism. Reactivity Reactivity creates the connection between different components. The changes in input values automatically flow to the plots, text, maps, and tables that use the input, and cause them to update. Reactivity facilitates drilling down functionality, which enhances the user’s ability to explore and investigate the data. We developed a novel and robust reactivity technique that allows us to add a new component and effectively connect it with all existing components within a dashboard tab, using only one line of code.Generic Biodiversity Tabs We developed five useful dashboard tabs (Fig. 1): (i) the Data Summary tab to give a quick overview of a dataset; (ii) the Data Completeness tab helps users get valuable information about missing records and missing Darwin Core fields; (iii) the Spatial tab is dedicated to spatial visualizations; (iv) the Taxonomic tab is designed to visualize taxonomy; and (v) the Temporal tab is designed to visualize time-related aspects. Performance and Agility To make a dashboard work smoothly and react quickly, hundreds of small and large modules, functions, and techniques must work together. Our goal was to minimize dashboard latency and maximize its data capacity. We used asynchronous modules to write non-blocking code, clusters in map components, and preprocessing and filtering data before passing it to plots to reduce the load. The 'bddashboard' package modularized architecture allows us to develop completely different interactive and reactive dashboards within mere minutes

Chemoselective synthesis of novel thiatriazolophanes

Bis-[4-alkyl/aryl-5-thia-1,2,4-triazoles] were prepared by fusion of diacids and thiosemicarbazides by condensation of aromatic acid hydrazides with isothiocyanate. Chemoselective alkylation of these bis-[4-alkyl/aryl-5-thia-1,2,4-triazoles] with 1,omega-dihaloalkanes in presence of potassium hydroxide in aqueous methanol afforded novel N-alkyl/aryl thiatriazolophanes

Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis.

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc

Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia