Design, Implementation and Performance Analysis of Highly Efficient Algorithms for AES Key Retrieval in Access-driven Cache-based Side Channel Attacks

Leakage of information between two processes sharing the same processor cache has been exploited in many novel approaches targeting various cryptographic algorithms. The software implementation of AES is an especially attractive target since it makes extensive use of cache-resident table lookups. We consider two attack scenarios where either the plaintext or ciphertext is known. We employ a multi-threaded spy process and ensure that each time slice provided to the victim (running AES) is small enough so that it makes a very limited number of table accesses. We design and implement a suite of algorithms to deduce the 128-bit AES key using as input the set of (unordered) cache line numbers captured by the spy threads in an access-driven cache-based side channel attack. Our algorithms are expressed using simple relational algebraic operations and run in under a minute. Above all, our attack is highly efficient - we demonstrate recovery of the full AES key given only about 6-7 blocks of plaintext or ciphertext (theoretically even a single block would suffice). This is a substantial improvement over previous cache-based side channel attacks that require between 100 and a million encryptions. Moreover, our attack supports varying cache hit/miss observation granularities, does not need frequent interruptions of the victim and will work even if the victim makes up to 60 cache accesses before being interrupted. Finally, we develop analytic models to estimate the number of encryptions/decryptions required as a function of access granularity and compare model results with those obtained from our experiment

Enhanced pneumothorax visualization in ICU patients using portable chest radiography

Objective Pneumothorax development can cause precipitous deterioration in ICU patients, therefore quick and accurate detection is vital. Portable chest radiography is commonly performed to exclude pneumothoraces but is hampered by supine patient position and overlying internal and external material. Also, the initial evaluation of the chest radiograph may be performed by a relatively inexperienced physician. Therefore, a tool that could significantly improve pneumothorax detection on portable radiography would be helpful in patient care. The aim of this study was to evaluate the clinical utility of novel enhancement software for pneumothorax detection in readers with varied clinical experience of detecting/excluding pneumothoraces on portable chest radiographs in ICU patients. Subjects and methods 206 portable ICU chest radiographs, 103 with pneumothoraces, were processed with and without enhancement software and reviewed by 5 readers who varied in reading experience. Images were grouped for different complexity levels. Results The mean AUC for pneumothorax detection increased for 4/5 readers from 0.846-0.957 to 0.88-0.971 with a largest improvement for the reader with least experience. No significant change was noted for the reader with the longest reading experience. The image complexity had no impact on the interpretation result. Conclusion Pneumothorax detection improves with novel enhancement software;the largest improvement is seen in less experienced readers

3D Echo systematically underestimates right ventricular volumes compared to cardiovascular magnetic resonance in adult congenital heart disease patients with moderate or severe RV dilatation

<p>Abstract</p> <p>Background</p> <p>Three dimensional echo is a relatively new technique which may offer a rapid alternative for the examination of the right heart. However its role in patients with non-standard ventricular size or anatomy is unclear. This study compared volumetric measurements of the right ventricle in 25 patients with adult congenital heart disease using both cardiovascular magnetic resonance (CMR) and three dimensional echocardiography.</p> <p>Methods</p> <p>Patients were grouped by diagnosis into those expected to have normal or near-normal RV size (patients with repaired coarctation of the aorta) and patients expected to have moderate or worse RV enlargement (patients with repaired tetralogy of Fallot or transposition of the great arteries). Right ventricular end diastolic volume, end systolic volume and ejection fraction were compared using both methods with CMR regarded as the reference standard</p> <p>Results</p> <p>Bland-Altman analysis of the 25 patients demonstrated that for both RV EDV and RV ESV, there was a significant and systematic under-estimation of volume by 3D echo compared to CMR. This bias led to a mean underestimation of RV EDV by -34% (95%CI: -91% to + 23%). The degree of underestimation was more marked for RV ESV with a bias of -42% (95%CI: -117% to + 32%). There was also a tendency to overestimate RV EF by 3D echo with a bias of approximately 13% (95% CI -52% to +27%).</p> <p>Conclusions</p> <p>Statistically significant and clinically meaningful differences in volumetric measurements were observed between the two techniques. Three dimensional echocardiography does not appear ready for routine clinical use in RV assessment in congenital heart disease patients with more than mild RV dilatation at the current time.</p

A cancer drug atlas enables synergistic targeting of independent drug vulnerabilities.

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value

Regular use of aspirin and pancreatic cancer risk

BACKGROUND: Regular use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been consistently associated with reduced risk of colorectal cancer and adenoma, and there is some evidence for a protective effect for other types of cancer. As experimental studies reveal a possible role for NSAIDs is reducing the risk of pancreatic cancer, epidemiological studies examining similar associations in human populations become more important. METHODS: In this hospital-based case-control study, 194 patients with pancreatic cancer were compared to 582 age and sex-matched patients with non-neoplastic conditions to examine the association between aspirin use and risk of pancreatic cancer. All participants received medical services at the Roswell Park Cancer Institute in Buffalo, NY and completed a comprehensive epidemiologic questionnaire that included information on demographics, lifestyle factors and medical history as well as frequency and duration of aspirin use. Patients using at least one tablet per week for at least six months were classified as regular aspirin users. Unconditional logistic regression was used to compute crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: Pancreatic cancer risk in aspirin users was not changed relative to non-users (adjusted OR = 1.00; 95% CI 0.72–1.39). No significant change in risk was found in relation to greater frequency or prolonged duration of use, in the total sample or in either gender. CONCLUSIONS: These data suggest that regular aspirin use may not be associated with lower risk of pancreatic cancer

Multiethnic Meta-Analysis Identifies Ancestry-Specific and Cross-Ancestry Loci for Pulmonary Function

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci

Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of l

Use of multidimensional item response theory methods for dementia prevalence prediction : an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. Conclusions Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Previous attempts to characterise the burden of chronic respiratory diseases have focused only on specific disease conditions, such as chronic obstructive pulmonary disease (COPD) or asthma. In this study, we aimed to characterise the burden of chronic respiratory diseases globally, providing a comprehensive and up-to-date analysis on geographical and time trends from 1990 to 2017. Methods Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, we estimated the prevalence, morbidity, and mortality attributable to chronic respiratory diseases through an analysis of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLL) by GBD super-region, from 1990 to 2017, stratified by age and sex. Specific diseases analysed included asthma, COPD, interstitial lung disease and pulmonary sarcoidosis, pneumoconiosis, and other chronic respiratory diseases. We also assessed the contribution of risk factors (smoking, second-hand smoke, ambient particulate matter and ozone pollution, household air pollution from solid fuels, and occupational risks) to chronic respiratory disease-attributable DALYs. Findings In 2017, 544.9 million people (95% uncertainty interval [UI] 506.9- 584.8) worldwide had a chronic respiratory disease, representing an increase of 39.8% compared with 1990. Chronic respiratory disease prevalence showed wide variability across GBD super-regions, with the highest prevalence among both males and females in high-income regions, and the lowest prevalence in sub-Saharan Africa and south Asia. The age-sex- specific prevalence of each chronic respiratory disease in 2017 was also highly variable geographically. Chronic respiratory diseases were the third leading cause of death in 2017 (7.0% [95% UI 6.8-7 .2] of all deaths), behind cardiovascular diseases and neoplasms. Deaths due to chronic respiratory diseases numbered 3 914 196 (95% UI 3 790 578-4 044 819) in 2017, an increase of 18.0% since 1990, while total DALYs increased by 13.3%. However, when accounting for ageing and population growth, declines were observed in age-standardised prevalence (14.3% decrease), agestandardised death rates (42.6%), and age-standardised DALY rates (38.2%). In males and females, most chronic respiratory disease-attributable deaths and DALYs were due to COPD. In regional analyses, mortality rates from chronic respiratory diseases were greatest in south Asia and lowest in sub-Saharan Africa, also across both sexes. Notably, although absolute prevalence was lower in south Asia than in most other super-regions, YLLs due to chronic respiratory diseases across the subcontinent were the highest in the world. Death rates due to interstitial lung disease and pulmonary sarcoidosis were greater than those due to pneumoconiosis in all super-regions. Smoking was the leading risk factor for chronic respiratory disease-related disability across all regions for men. Among women, household air pollution from solid fuels was the predominant risk factor for chronic respiratory diseases in south Asia and sub-Saharan Africa, while ambient particulate matter represented the leading risk factor in southeast Asia, east Asia, and Oceania, and in the Middle East and north Africa super-region. Interpretation Our study shows that chronic respiratory diseases remain a leading cause of death and disability worldwide, with growth in absolute numbers but sharp declines in several age-standardised estimators since 1990. Premature mortality from chronic respiratory diseases seems to be highest in regions with less-resourced health systems on a per-capita basis