Cryptanalysis and Security Enhancement on the Generation of Mu-Varadharajan Electronic Voting Protocol

Mu and Varadharajan proposed an electronic voting scheme and claimed that their scheme authenticates the voters, protects the anonymity of them, and detects the identity of double voters. Due to some weaknesses in Mu-Varadharajan scheme, several modified schemes have been proposed by Lin et al., Hwang et al., Rodriguez-Henriquez et al. and Asaar et al.; however this paper shows that these schemes suffer from some weaknesses in fulfilling the pointed properties. For this purpose, we get Hwang et al. scheme as a case study and apply our new attacks on it. Also we consider the applicability of the attacks on other pointed schemes. In addition, we present a new scheme and show that the scheme resists against the proposed attacks without loosing efficiency

Beneficial Effects of Simulated Gastro-Intestinal Digests of Fried Egg and Its Fractions on Blood Pressure, Plasma Lipids and Oxidative Stress in Spontaneously Hypertensive Rats

Background: We have previously characterized several antihypertensive peptides in simulated digests of cooked eggs and showed blood pressure lowering property of fried whole egg digest. However, the long-term effects of this hydrolysate and its fractions on blood pressure are not known. Therefore, the objectives of the study were to determine the effects of long term administration of fried whole egg hydrolysate and its fractions (i.e. egg white and egg yolk) on regulation of blood pressure and associated factors in cardiovascular disease such as plasma lipid profile and tissue oxidative stress. Methods and Results: We used spontaneously hypertensive rats (SHR), an animal model of essential hypertension. Hydrolysates of fried egg and its fractions were prepared by simulated gastro-intestinal digestion with pepsin and pancreatin. 16–17 week old male SHRs were orally administered fried whole egg hydrolysate, non-hydrolyzed fried whole egg, egg white hydrolysate or egg yolk hydrolysates (either defatted, or not) daily for 18 days. Blood pressure (BP) and heart rate were monitored by telemetry. Animals were sacrificed at the end of the treatment for vascular function studies and evaluating plasma lipid profile and tissue oxidative stress. BP was reduced by feeding fried whole egg hydrolysate but not by the nonhydrolyzed product suggesting a critical role for in vitro digestion in releasing anti-hypertensive peptides. Egg white hydrolysate and defatted egg yolk hydrolysate (but not egg yolk hydrolysate) also had similar effects. Reduction in BP was accompanied by the restoration of nitric oxide (NO) dependent vasorelaxation and reduction of plasma angiotensin II. Fried whole egg hydrolysate also reduced plasma levels of triglyceride although it was increased by the non-hydrolyzed sample. Additionally the hydrolyzed preparations attenuated tissue oxidative stress. Conclusion: Our results demonstrate that fried egg hydrolysates exert antihypertensive effects, improve plasma lipid profile and attenuate tissue oxidative stress in vivo

Numerous proteins with unique characteristics are degraded by the 26S proteasome following monoubiquitination

The "canonical" proteasomal degradation signal is a substrate-anchored polyubiquitin chain. However, a handful of proteins were shown to be targeted following monoubiquitination. In this study, we established-in both human and yeast cells-a systematic approach for the identification of monoubiquitination-dependent proteasomal substrates. The cellular wild-type polymerizable ubiquitin was replaced with ubiquitin that cannot form chains. Using proteomic analysis, we screened for substrates that are nevertheless degraded under these conditions compared with those that are stabilized, and therefore require polyubiquitination for their degradation. For randomly sampled representative substrates, we confirmed that their cellular stability is in agreement with our screening prediction. Importantly, the two groups display unique features: monoubiquitinated substrates are smaller than the polyubiquitinated ones, are enriched in specific pathways, and, in humans, are structurally less disordered. We suggest that monoubiquitination-dependent degradation is more widespread than assumed previously, and plays key roles in various cellular processes

Tracing scientist's research trends realtimely

In this research, we propose a method to trace scientists' research trends realtimely. By monitoring the downloads of scientific articles in the journal of Scientometrics for 744 hours, namely one month, we investigate the download statistics. Then we aggregate the keywords in these downloaded research papers, and analyze the trends of article downloading and keyword downloading. Furthermore, taking both the download of keywords and articles into consideration, we design a method to detect the emerging research trends. We find that in scientometrics field, social media, new indices to quantify scientific productivity (g-index), webometrics, semantic, text mining, open access are emerging fields that scientometrics researchers are focusing on.Comment: 13 pages, 7 figure

Validation of the Ottawa Ankle Rules in Iran: A prospective survey

BACKGROUND: Acute ankle injuries are one of the most common reasons for presenting to emergency departments, but only a small percentage of patients – approximately 15% – have clinically significant fractures. However, these patients are almost always referred for radiography. The Ottawa Ankle Rules (OARs) have been designed to reduce the number of unnecessary radiographs ordered for these patients. The objective of this study was to validate the OARs in the Iranian population. METHODS: This prospective survey was done among 200 patients with acute ankle injury from January 2004 to April 2004 in the Akhtar Orthopedics Hospital Emergency Department. Main outcome measures of this survey were: sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratios (positive and negative) of the OARs. RESULTS: Sensitivity of the OARs for detecting 37 ankle fractures (23 in the malleolar zone and 14 in the midfoot zone) was 100% for each of the two zones, and 100% for both zones. Specificity of the OARs for detecting fractures was 40.50% for both zones, 40.50% for the malleolar zone, and 56.00% for the midfoot zone. Implementation of the OARs had the potential for reducing radiographs by 33%. CONCLUSION: OARs are very accurate and highly sensitive tools for detecting ankle fractures. Implementation of these rules would lead to significant reduction in the number of radiographs, costs, radiation exposure and waiting times in emergency departments

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences

<p>Abstract</p> <p>Background</p> <p>Knowledge of structural class is used by numerous methods for identification of structural/functional characteristics of proteins and could be used for the detection of remote homologues, particularly for chains that share twilight-zone similarity. In contrast to existing sequence-based structural class predictors, which target four major classes and which are designed for high identity sequences, we predict seven classes from sequences that share twilight-zone identity with the training sequences.</p> <p>Results</p> <p>The proposed MODular Approach to Structural class prediction (MODAS) method is unique as it allows for selection of any subset of the classes. MODAS is also the first to utilize a novel, custom-built feature-based sequence representation that combines evolutionary profiles and predicted secondary structure. The features quantify information relevant to the definition of the classes including conservation of residues and arrangement and number of helix/strand segments. Our comprehensive design considers 8 feature selection methods and 4 classifiers to develop Support Vector Machine-based classifiers that are tailored for each of the seven classes. Tests on 5 twilight-zone and 1 high-similarity benchmark datasets and comparison with over two dozens of modern competing predictors show that MODAS provides the best overall accuracy that ranges between 80% and 96.7% (83.5% for the twilight-zone datasets), depending on the dataset. This translates into 19% and 8% error rate reduction when compared against the best performing competing method on two largest datasets. The proposed predictor provides accurate predictions at 58% accuracy for membrane proteins class, which is not considered by majority of existing methods, in spite that this class accounts for only 2% of the data. Our predictive model is analyzed to demonstrate how and why the input features are associated with the corresponding classes.</p> <p>Conclusions</p> <p>The improved predictions stem from the novel features that express collocation of the secondary structure segments in the protein sequence and that combine evolutionary and secondary structure information. Our work demonstrates that conservation and arrangement of the secondary structure segments predicted along the protein chain can successfully predict structural classes which are defined based on the spatial arrangement of the secondary structures. A web server is available at <url>http://biomine.ece.ualberta.ca/MODAS/</url>.</p

Folate Receptor β Targeted PET Imaging of Macrophages in Autoimmune Myocarditis

Rationale: Currently available imaging techniques have limited specificity for the detection of active myocardial inflammation. Aluminum fluoride-18-labeled 1,4,7-triazacyclononane-N,N′,N″-triacetic acid conjugated folate (18F-FOL) is a positron emission tomography (PET) tracer targeting folate receptor β (FR-β) that is expressed on activated macrophages at sites of inflammation. We evaluated 18F-FOL PET for the detection of myocardial inflammation in rats with autoimmune myocarditis and studied expression of FR-β in human cardiac sarcoidosis specimens. Methods: Myocarditis was induced by immunizing rats (n = 18) with porcine cardiac myosin in complete Freund’s adjuvant. Control rats (n = 6) were injected with Freund’s adjuvant alone. 18F-FOL was intravenously injected followed by imaging with a small animal PET/computed tomography (CT) scanner and autoradiography. Contrast-enhanced high-resolution CT or 2-deoxy-2-18F-fluoro-D-glucose (18F-FDG) PET images were used for co-registration. Rat tissue sections and myocardial autopsy samples of 6 patients with cardiac sarcoidosis were studied for macrophages and FR-β. Results: The myocardium of 10 out of 18 immunized rats showed focal macrophage-rich inflammatory lesions with FR-β expression occurring mainly in M1-polarized macrophages. PET images showed focal myocardial 18F-FOL uptake co-localizing with inflammatory lesions (SUVmean, 2.1 ± 1.1), whereas uptake in the remote myocardium of immunized rats and controls was low (SUVmean, 0.4 ± 0.2 and 0.4 ± 0.1, respectively; P </p

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses