Assessment of nonlinear dose-response relationships via nonparametric regression.

We propose a simple approach to assess whether a nonlinear parametric model is appropriate to depict the dose-response relationships and whether two parametric models can be applied to fit a dataset via nonparametric regression. The proposed approach can compensate for the ANOVA, which is sometimes conservative, and is very easy to implement. We illustrate the performance by analyzing experimental examples and a small simulation study.

An Android Inline Hooking Framework for the Securing Transmitted Data.

Information leaks can occur through many Android applications, including unauthorized access to sensors data. Hooking is an important technique for protecting Android applications and add security features to them even without its source code. Various hooking frameworks are developed to intercept events and process their own specific events. The hooking tools for Java methods are varied, however, the native hook has few methods. Besides, the commonly used Android hook frameworks cannot meet the requirement of hooking the native methods in shared libraries on non-root devices. Even though some approaches are able to hook these methods, they have limitations or are complicated to implement. In the paper, a feasible hooking approach for Android native methods is proposed and implemented, which does not need any modifications to both the Android framework and app's code. In this approach, the method's reference address is modified and control flow is redirected. Beyond that, this study combines this approach with VirtualXposed which aims to run it without root privileges. This hooking framework can be used to enforce security policies and monitor sensitive methods in shared objects. The evaluation of the scheme demonstrates its capability to perform hook operation without a significant runtime performance overhead on real devices and it is compatible and functional for the native hook.

Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders.

Feature selection is an important initial step of exploratory analysis in biomedical studies. Its main objective is to eliminate the covariates that are uncorrelated with the outcome. For highly correlated covariates, traditional feature selection methods, such as the Lasso, tend to select one of them and eliminate the others, although some of the eliminated ones are still scientifically valuable. To alleviate this drawback, we propose a feature selection method based on covariate space decomposition, referred herein as the "Decomposition Feature Selection" (DFS), and show that this method can lead to scientifically meaningful results in studies with correlated high dimensional data. The DFS consists of two steps: (i) decomposing the covariate space into disjoint subsets such that each of the subsets contains only uncorrelated covariates and (ii) identifying significant predictors by traditional feature selection within each covariate subset. We demonstrate through simulation studies that the DFS has superior practical performance over the Lasso type methods when multiple highly correlated covariates need to be retained. Application of the DFS is demonstrated through a study of bipolar disorders with correlated biomarkers.

An Identity-Based Anti-Quantum Privacy-Preserving Blind Authentication in Wireless Sensor Networks.

With the development of wireless sensor networks, IoT devices are crucial for the Smart City; these devices change people's lives such as e-payment and e-voting systems. However, in these two systems, the state-of-art authentication protocols based on traditional number theory cannot defeat a quantum computer attack. In order to protect user privacy and guarantee trustworthy of big data, we propose a new identity-based blind signature scheme based on number theorem research unit lattice, this scheme mainly uses a rejection sampling theorem instead of constructing a trapdoor. Meanwhile, this scheme does not depend on complex public key infrastructure and can resist quantum computer attack. Then we design an e-payment protocol using the proposed scheme. Furthermore, we prove our scheme is secure in the random oracle, and satisfies confidentiality, integrity, and non-repudiation. Finally, we demonstrate that the proposed scheme outperforms the other traditional existing identity-based blind signature schemes in signing speed and verification speed, outperforms the other lattice-based blind signature in signing speed, verification speed, and signing secret key size.

Genetic association with multiple traits in the presence of population stratification.

Testing association between a genetic marker and multiple-dependent traits is a challenging task when both binary and quantitative traits are involved. The inverted regression model is a convenient method, in which the traits are treated as predictors although the genetic marker is an ordinal response. It is known that population stratification (PS) often affects population-based association studies. However, how it would affect the inverted regression for pleiotropic association, especially with the mixed types of traits (binary and quantitative), is not examined and the performance of existing methods to correct for PS using the inverted regression analysis is unknown. In this paper, we focus on the methods based on genomic control and principal component analysis, and investigate type I error of pleiotropic association using the inverted regression model in the presence of PS with allele frequencies and the distributions (or disease prevalences) of multiple traits varying across the subpopulations. We focus on common alleles but simulation results for a rare variant are also reported. An application to the HapMap data is used for illustration.

On the Optimal Combination of Elliptically Distributed Biomarkers to Improve Diagnostic Accuracy.

Diagnostic biomarkers play a critical role in biomedical research, particularly for the diagnosis and prediction of diseases, etc. To enhance diagnostic accuracy, extensive research about combining multiple biomarkers has been developed based on the multivariate normality, which is often not true in practice, as most biomarkers follow distributions that deviate from normality. While the likelihood ratio combination is recognized to be the optimal approach, it is complicated to calculate. To achieve a more accurate and effective combination of biomarkers, especially when these biomarkers deviate from normality, we propose using a receiver operating characteristic (ROC) curve methodology based on the optimal combination of elliptically distributed biomarkers. In this paper, we derive the ROC curve function for the elliptical likelihood ratio combination. Further, proceeding from the derived best combinations of biomarkers, we propose an efficient technique via nonparametric maximum likelihood estimate (NPMLE) to build empirical estimation. Simulation results show that the proposed elliptical combination method consistently provided better performance, demonstrating its robustness in handling various distribution types of biomarkers. We apply the proposed method to two real datasets: Autism/autism spectrum disorder (ASD) and neural tube defects (NTD). In both applications, the elliptical likelihood ratio combination improves the AUC value compared to the multivariate normal likelihood ratio combination and the best linear combination.

Quantification of epicardial fat volume using low-dose cardiac scan in patients with low calcium score.

Background: We investigated the accuracy of quantifying epicardial adipose tissue volume (EATV) using low-dose cardiac scan (EATVcardiac scan) and evaluated its clinical utility in predicting coronary heart disease in patients with low or mild calcification. Methods: In total, 204 patients with clinical symptoms of coronary heart disease and coronary artery calcium score (CACS) of <100 AU were enrolled in this retrospective study. After obtaining EATVcardiac scan and EATV measured using computed tomography angiography (EATVCTA), the agreement between the two measurements was evaluated using Pearson correlation coefficient and Bland-Altman analysis. Multivariate logistic regression was used to analyze the utility of EATV in predicting plaque and vulnerable plaque. Receiver operating characteristic curves were constructed. Results: The mean EATVcardiac scan (101.51±41.57 cm3) and EATVCTA (104.57±41.34 cm3) of all patients were similar, and the two measurements were strongly correlated (r=0.9596, P<0.001). The difference between EATVcardiac scan and EATVCTA was -3.0549, with only 4.9% (10/204) of patients having values outside the 95% confidence interval (CI) range (-26.15 to 20.04; P for agreement =0.0003). Further, a significant agreement was observed between EATVcardiac scan and EATVCTA in 126 patients with plaques, with an estimated difference of -3.354, and 6.35% (8/126) of patients had values outside the 95% CI range (-31.37 to 24.66; P for agreement =0.0095). After adjustment for age and sex, EATVcardiac scan and EATVCTA were significantly associated with plaque (all P values <0.001), and the areas under the curve (AUCs) were 0.662 and 0.670 (P=0.4331), respectively. In contrast, EATVcardiac scan and EATVCTA were not associated with vulnerable plaque (P>0.05), with AUCs of 0.550 and 0.530, respectively (P=0.2157). Conclusions: The study results indicate that EATVcardiac scan and EATVCTA are equivalent. In addition, both methods provide comparable values for predicting coronary arteriosclerosis in patients with low-to-mild calcification (CACS of <100 AU).

Characterization of isolated starch from Isatis indigotica Fort. root and anhydro-sugars preparation using its decoction residues.

Isatis indigotica Fort. root (Ban-lan-gen, IIR), a traditional Chinese medicine (TCM), has an ancient and well-documented history for its medicinal properties. Aside from epigoitrin, indole alkaloids, and their corresponding derivatives as medicinal ingredients, it also contains lots of biomass such as starch. Herein, a new starch was isolated from IIR and the physicochemical properties such as amylose content, moisture content, ash content, morphology, thermal properties, and crystallography were characterized systematically. The amylose content of IIR starch was 19.84 ± 0.85%, and the size and shape of starch granules is ellipsoidal shape with sizes from 2 to 10 µm. IIR starch exhibited a C-type pattern and had 25.92% crystallinity (higher than that of corn starch). The gelatinization temperature of IIR starch was 58.68-75.41 °C, and its gelatinization enthalpy was ΔH gel = 4.33 J/g. After decocting, the IIR's residues can be used to prepare anhydro-sugars in a polar aprotic solvent. The total carbon yield of levoglucosan (LG), levoglucosenone (LGO), 5-hydroxymethylfurfural (HMF), and furfural (FF) could reach 69.81% from IIR's decoction residues in 1,4-dioxane with 15 mM H2SO4 as the catalyst. Further, the residues after dehydration were prepared into biochar by thermochemical conversion and the BET surface area of biochar was 1749.46 m2/g which has good application prospect in soil improvement and alleviates obstacles of IIR continuous cropping.

Protective antibody threshold of RTS,S/AS01 malaria vaccine correlates antigen and adjuvant dose in mouse model.

Mouse models are useful for the early down-selection of malaria vaccine candidates. The Walter Reed Army Institute of Research has optimized a transgenic Plasmodium berghei sporozoite challenge model to compare the efficacy of Plasmodium falciparum circumsporozoite protein (CSP) vaccines. GSK's RTS,S vaccine formulated in the adjuvant AS01 can protect malaria-naïve individuals against malaria. We report that the RTS,S/AS01 vaccine induces high level sterile protection in our mouse model. Down titration of the antigen at a constant AS01 dose revealed a potent antigen dose-sparing effect and the superiority of RTS,S/AS01 over a soluble CSP antigen. RTS,S-mediated protective immunity was associated with a threshold of major repeat antibody titer. Combined titration of the antigen and adjuvant showed that reducing the adjuvant could improve antibody boosting post-3rd vaccination and reduce the threshold antibody concentration required for protection. Mouse models can provide a pathway for preclinical assessment of strategies to improve CSP vaccines against malaria.

Comprehensive bioinformatic analysis of the expression and prognostic significance of TSC22D domain family genes in adult acute myeloid leukemia.

BACKGROUND: TSC22D domain family genes, including TSC22D1-4, play a principal role in cancer progression. However, their expression profiles and prognostic significance in adult acute myeloid leukemia (AML) remain unknown. METHODS: The online databases, including HPA, CCLE, EMBL-EBI, GEPIA2, BloodSpot, GENT2, UCSCXenaShiny, GSCALite, cBioportal, and GenomicScape, utilized the data of TCGA and GEO to investigate gene expression, mutation, copy number variation (CNV), and prognostic significance of the TSC22D domain family in adult AML. Computational analysis of resistance (CARE) was used to explore the effect of TSC22D3 expression on drug response. Functional enrichment analysis of TSC22D3 was performed in the TRRUST Version 2 database. The STRING, Pathway Commons, and AnimalTFDB3.0 databases were used to investigate the protein-protein interaction (PPI) network of TSC22D3. Harmonizome was used to predict target genes and kinases regulated by TSC22D3. The StarBase v2.0 and CancermiRNome databases were used to predict miRNAs regulated by TSC22D3. UCSCXenaShiny was used to investigate the correlation between TSC22D3 expression and immune infiltration. RESULTS: Compared with normal adult hematopoietic stem cells (HSCs), the expression of TSC22D3 and TSC22D4 in adult AML tissues was markedly up-regulated, whereas TSC22D1 expression was markedly down-regulated. The expression of TSC22D1 and TSC22D3 was significantly increased in adult AML tissues compared to normal adult tissues. High TSC22D3 expression was significantly associated with poor overall survival (OS) and event-free survival (EFS) in adult AML patients. Univariate and multivariate Cox analysis showed that overexpression of TSC22D3 was independently associated with adverse OS of adult AML patients. High TSC22D3 expression had a adverse impact on OS and EFS of adult AML patients in the chemotherapy group. TSC22D3 expression correlated with drug resistance to BCL2 inhibitors. Functional enrichment analysis indicated that TSC22D3 might promote AML progression. MIR143-3p sponging TSC22D3 might have anti-leukemia effect in adult AML. CONCLUSIONS: A significant increase in TSC22D3 expression was observed in adult AML tissues compared to normal adult HSCs and tissues. The prognosis of adult AML patients with high TSC22D3 expression was unfavorable, which could severe as a new prognostic biomarker and potential target for adult AML.

Differential Genome Replication of a Unique Single-Amino-Acid Mutation in the Adenovirus-4 Component of the Live Oral Adenovirus Type 4 and Type 7 Vaccine.

The FDA-approved Adenovirus Type 4 and Type 7 Vaccine, Live, Oral is highly effective and essential in preventing acute respiratory diseases (ARDs) in U.S. military recruits. Our study revealed the presence of a previously undetected mutation, not found in the wild-type human adenovirus type 4 (HAdV-4) component of the licensed vaccine, which contains an amino acid substitution (P388T) in the pre-terminal protein (pTP). This study demonstrated that replication of the T388 HAdV-4 vaccine mutant virus is favored over the wild type in WI-38 cells, the cell type utilized in vaccine manufacturing. However, results from serial human stool specimens of vaccine recipients support differential genome replication in the gastrointestinal tract (GI), demonstrated by the steady decline of the percentage of mutant T388 vaccine virus. Since vaccine efficacy depends upon GI replication and the subsequent immune response, the mutation can potentially impact vaccine efficacy.

National estimates of seroincidence and seroprevalence for herpes simplex virus type 1 and type 2 among US military adults aged 18 to 29 years.

BACKGROUND: While population-based seroprevalence studies of herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) are widespread, seroincidence studies are largely limited to select or high-risk populations. The US military offers a potential population to derive national seroincidence rate estimates for young adults (ages 18-29). METHODS: We used banked, longitudinal serum specimens collected in a cohort of 1094 military personnel aged 18 to 30 years who served between 1989 and 2005 to estimate national HSV-1 and HSV-2 seroincidence and seroprevalence for the young, adult military population, weighted according to the US Census. Serum was tested with indirect ELISA (enzyme-linked immunosorbent assay). RESULTS: Estimated national seroincidence rates for the US young, adult military population were 9.1 per 100 person-years (95% confidence interval: 4.6-13.5) for HSV-1 and 6.2 (95% confidence interval: 3.1-9.3) for HSV-2. Female sex and black race were associated with significantly higher HSV-2 seroconversion rates. Our estimated HSV1/2 seroprevalences were comparable to US national data provided by National Health and Nutrition Examination Surveys' serosurveys except for non-Hispanic blacks and Hispanics. CONCLUSION: Although these US 2000 Census-weighted estimates of HSV-1 and HSV-2 seroincidence apply only to young, military adults, they nonetheless supply, to our knowledge, the only national figures that might be used to predict US national HSV1/2 seroincidence in young adults. Thus, we believe that our findings in this military population can be used to inform the planning of HSV-1 and 2 prevention measures in the general, young-adult US population.

A Voting-Based Ensemble Deep Learning Method Focused on Multi-Step Prediction of Food Safety Risk Levels: Applications in Hazard Analysis of Heavy Metals in Grain Processing Products.

Grain processing products constitute an essential component of the human diet and are among the main sources of heavy metal intake. Therefore, a systematic assessment of risk factors and early-warning systems are vital to control heavy metal hazards in grain processing products. In this study, we established a risk assessment model to systematically analyze heavy metal hazards and combined the model with the K-means++ algorithm to perform risk level classification. We then employed deep learning models to conduct a multi-step prediction of risk levels, providing an early warning of food safety risks. By introducing a voting-ensemble technique, the accuracy of the prediction model was improved. The results indicated that the proposed model was superior to other models, exhibiting the overall accuracy of 90.47% in the 7-day prediction and thus satisfying the basic requirement of the food supervision department. This study provides a novel early-warning model for the systematic assessment of the risk level and further allows the development of targeted regulatory strategies to improve supervision efficiency.

Impact of targeted testing for latent tuberculosis infection using commercially available diagnostics.

BACKGROUND: The interferon-γ release assays (IGRAs) are increasingly being used as an alternative to the tuberculin skin test (TST). Although IGRAs may have better specificity and certain logistic advantages to the TST, their use may contribute to overtesting of low-prevalence populations if testing is not targeted. The objective of this study was to evaluate the accuracy of a risk factor questionnaire in predicting a positive test result for latent tuberculosis infection using the 3 commercially available diagnostics. METHODS: A cross-sectional comparison study was performed among recruits undergoing Army basic training at Fort Jackson, South Carolina, from April through June 2009. The tests performed included: (1) a risk factor questionnaire; (2) the QuantiFERON Gold In-Tube test (Cellestis Limited, Carnegie, Victoria, Australia); (3) the T-SPOT.TB test (Oxford Immunotec Limited, Abingdon, United Kingdom); and (4) the TST (Sanofi Pasteur Ltd., Toronto, Ontario, Canada). Prediction models used logistic regression to identify factors associated with positive test results. RFQ prediction models were developed independently for each test. RESULTS: Use of a 4-variable model resulted in 79% sensitivity, 92% specificity, and a c statistic of 0.871 in predicting a positive TST result. Targeted testing using these risk factors would reduce testing by >90%. Models predicting IGRA outcomes had similar specificities as the skin test but had lower sensitivities and c statistics. CONCLUSIONS: As with the TST, testing with IGRAs will result in false-positive results if the IGRAs are used in low-prevalence populations. Regardless of the test used, targeted testing is critical in reducing unnecessary testing and treatment. CLINICAL TRIAL REGISTRATION: NCT00804713.

Descriptive epidemiology and natural history of idiopathic venous thromboembolism in U.S. active duty enlisted personnel, 1998-2007.

The estimated incidence of idiopathic venous thromboembolism (IVTE) cases in the United States ranges from 24,000 to 282,000/year. This analysis explores the incidence and prevalence of IVTE in the military and if cases experience increased attrition. The Defense Medical Surveillance System was searched for incident IVTE cases from 1998 through 2007. Enlisted cases were each matched to 3 controls. Kaplan-Meier survival analysis and Cox proportional hazard modeling were performed. We matched 463 cases to 1,389 controls. Outpatient IVTE rates have increased markedly from 1998 through 2007. Cases of all-cause attrition risk (0.56 [95% CI = 0.44, 0.72]) and rates were significantly less than controls (p < 0.0001), and cases of medical attrition risk (1.64 [95% CI = 1.13, 2.37]) and rates were significantly higher (p < 0.01). Increasing rates with lower attrition suggests increasing case prevalence. Health care providers must maintain a high index of suspicion for venous thromboembolism to minimize adverse sequelae affecting health, unit readiness, and medical costs.

U.S. military recruits waived for pathological curvature of the spine: increased risk of discharge from service.

Selective accession waivers for medically disqualifying conditions like spinal curvature are one way the military meets its manpower needs. We evaluated retention patterns during the first 2 years of service of a cohort of military recruits with waivers for pathological curvature of the spine (spinal curvature). Recruits waived for spinal curvature (n = 417), who accessed from 1998 to 2005 were identified and matched with 3 qualified recruits. Kaplan-Meier survival analysis and Cox proportional hazards model were used to compare survival patterns and adjusted attrition hazard estimates. Waived recruits experienced significantly increased risk of "all cause" discharge (relative risk = 1.3; 95% confidence interval: 1.1, 1.5) and "existing prior to service" discharge (relative risk = 2.4; confidence interval: 1.6, 3.5). Despite the increased risk of discharge, current waiver criteria allowed a majority with spinal curvature to complete at least 2 years of service. Policy makers must consider risks and benefits before modifying the current accession standard for spinal curvature.

In vitro and in vivo inhibition of malaria parasite infection by monoclonal antibodies against Plasmodium falciparum circumsporozoite protein (CSP).

Plasmodium falciparum malaria contributes to a significant global disease burden. Circumsporozoite protein (CSP), the most abundant sporozoite stage antigen, is a prime vaccine candidate. Inhibitory monoclonal antibodies (mAbs) against CSP map to either a short junctional sequence or the central (NPNA)n repeat region. We compared in vitro and in vivo activities of six CSP-specific mAbs derived from human recipients of a recombinant CSP vaccine RTS,S/AS01 (mAbs 317 and 311); an irradiated whole sporozoite vaccine PfSPZ (mAbs CIS43 and MGG4); or individuals exposed to malaria (mAbs 580 and 663). RTS,S mAb 317 that specifically binds the (NPNA)n epitope, had the highest affinity and it elicited the best sterile protection in mice. The most potent inhibitor of sporozoite invasion in vitro was mAb CIS43 which shows dual-specific binding to the junctional sequence and (NPNA)n. In vivo mouse protection was associated with the mAb reactivity to the NANPx6 peptide, the in vitro inhibition of sporozoite invasion activity, and kinetic parameters measured using intact mAbs or their Fab fragments. Buried surface area between mAb and its target epitope was also associated with in vivo protection. Association and disconnects between in vitro and in vivo readouts has important implications for the design and down-selection of the next generation of CSP based interventions.

Exertional heat illness among overweight U.S. Army recruits in basic training.

INTRODUCTION: Heat illness has not declined in the U.S. military despite preventive measures. The increase in overweight recruits entering the U.S. military may lead to an increase in heat-related events. This study compares the risk of heat illness among U.S. Army recruits who exceeded body fat standards at accession to those who met standards. METHODS: Recruits with excess body fat and qualified applicants to the Army were required to take a preaccession fitness test during the study period (February 2005 through September 2006). The test included a 5-min step test and 1-min push-up challenge, scored as pass or fail. Incidence and outpatient usage for heat illness (any heat illness, heat stroke, heat exhaustion, and other heat illness) at 90 d of service were compared in 9667 male recruits of whom 826 had excess body fat and 8841 were qualified. There were too few heat events among women for analysis. RESULTS: The incidence odds ratio among male recruits with excess body fat compared to qualified male recruits was 3.63 (95% CI: 1.92, 6.85). Men with excess body fat had an increased incidence of heat illness with a rate ratio of 7.25 (95% CI: 4.17, 12.61). DISCUSSION: Although there were few heat illness events, the results indicate a significantly increased risk of heat illness and outpatient utilization among male recruits with excess body fat. It was estimated that approximately 70% of the relative risk for heat illnesses in men with excess body fat during basic training was associated with exceeding body fat standards. These findings may have implications for military accession and training.

Comparison of Pseudomonas aeruginosa strains reveals that Exolysin A toxin plays an additive role in virulence.

BACKGROUND: Pseudomonas aeruginosa possesses an array of virulence genes ensuring successful infection development. A two-partner secretion system Exolysin BA (ExlBA) is expressed in the PA7-like genetic outliers consisting of ExlA, a pore-forming toxin and ExlB transporter protein. Presence of exlBA in multidrug-resistant (MDR) strains has not been investigated, particularly in the strains isolated from wounded soldiers. METHODS: We screened whole genome sequences of 2439 MDR- P. aeruginosa strains for the presence of exlBA. We compiled all exlBA positive strains and compared them with a diversity set for demographics, antimicrobial profiles and phenotypic characteristics: surface motility, biofilm formation, pyocyanin production and hemolysis. We compared the virulence of strains with comparable phenotypic characteristics in Galleria mellonella. RESULTS: We identified 33 exlBA-positive strains (1.5%). These strains have increased antibiotic resistance, they are more motile, produce more robust biofilms and have comparable pyocianin production with the diversity set despite the phenotypic differences within the group. In in vivo infection models, these strains were less virulent than Type III Secretion System (T3SS) positive counterparts. CONCLUSIONS: exlBA-positive strains are wide spread among the PA7-like outliers. While not as virulent as strains possessing T3SS, these strains exhibit phenotypic features associated with virulence and are still lethal in vivo.

Preaccession fitness and body composition as predictors of attrition in U.S. Army recruits.

The Assessment of Recruit Motivation and Strength (ARMS) project evaluated whether active duty Army enlistees who exceeded weight and body-fat standards but were able to pass the ARMS physical fitness test were at elevated risk of early attrition relative to the traditional recruit population. Attrition among 1146 overweight and overbody-fat (OBF) recruits who passed ARMS was compared to 10,514 fully qualified (FQ) recruits who began service in February 2005 through September 2006. The ARMS test includes a 5-minute step test and a 1-minute pushup test. There were no significant differences in attrition between OBF and FQ at 180 days: adjusted hazard ratios were 1.17 (95% CI: 0.83, 1.65) among females and 1.23 (95% CI: 0.95, 1.58) among males. This study indicates that physically fit recruits who exceeded weight/body-fat standards were equally capable of serving at least 180 days compared to those who met standards.