Microwave Spectroscopy

Contains research objectives and reports on five research projects.Signal Corps Contract DA36-039-sc-73014Signal Corps Contract DA36-039-sc-7489

Surfing a genetic association interaction network to identify modulators of antibody response to smallpox vaccine

The variation in antibody response to vaccination likely involves small contributions of numerous genetic variants, such as single-nucleotide polymorphisms (SNPs), which interact in gene networks and pathways. To accumulate the bits of genetic information relevant to the phenotype that are distributed throughout the interaction network, we develop a network eigenvector centrality algorithm (SNPrank) that is sensitive to the weak main effects, gene–gene interactions and small higher-order interactions through hub effects. Analogous to Google PageRank, we interpret the algorithm as the simulation of a random SNP surfer (RSS) that accumulates bits of information in the network through a dynamic probabilistic Markov chain. The transition matrix for the RSS is based on a data-driven genetic association interaction network (GAIN), the nodes of which are SNPs weighted by the main-effect strength and edges weighted by the gene–gene interaction strength. We apply SNPrank to a GAIN analysis of a candidate-gene association study on human immune response to smallpox vaccine. SNPrank implicates a SNP in the retinoid X receptor α (RXRA) gene through a network interaction effect on antibody response. This vitamin A- and D-signaling mediator has been previously implicated in human immune responses, although it would be neglected in a standard analysis because its significance is unremarkable outside the context of its network centrality. This work suggests SNPrank to be a powerful method for identifying network effects in genetic association data and reveals a potential vitamin regulation network association with antibody response

Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

Background: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score) provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods: Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident (< = 12 m) or older infection by 26 different algorithms. Incident infection rates (IIR) were calculated based on diagnostic sensitivity and specificity of each algorithm and the rule that the total of incident results is the sum of true-incident and false-incident results, which can be calculated by means of the pre-determined sensitivity and specificity. Results: The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline) and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models Conclusions: The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and sampling bias

Anti-tumour necrosis factor discontinuation in inflammatory bowel disease patients in remission: study protocol of a prospective, multicentre, randomized clinical trial

Background: Patients with inflammatory bowel disease who achieve remission with anti-tumour necrosis factor (anti-TNF) drugs may have treatment withdrawn due to safety concerns and cost considerations, but there is a lack of prospective, controlled data investigating this strategy. The primary study aim is to compare the rates of clinical remission at 1?year in patients who discontinue anti-TNF treatment versus those who continue treatment. Methods: This is an ongoing, prospective, double-blind, multicentre, randomized, placebo-controlled study in patients with Crohn?s disease or ulcerative colitis who have achieved clinical remission for ?6?months with an anti-TNF treatment and an immunosuppressant. Patients are being randomized 1:1 to discontinue anti-TNF therapy or continue therapy. Randomization stratifies patients by the type of inflammatory bowel disease and drug (infliximab versus adalimumab) at study inclusion. The primary endpoint of the study is sustained clinical remission at 1?year. Other endpoints include endoscopic and radiological activity, patient-reported outcomes (quality of life, work productivity), safety and predictive factors for relapse. The required sample size is 194 patients. In addition to the main analysis (discontinuation versus continuation), subanalyses will include stratification by type of inflammatory bowel disease, phenotype and previous treatment. Biological samples will be obtained to identify factors predictive of relapse after treatment withdrawal. Results: Enrolment began in 2016, and the study is expected to end in 2020. Conclusions: This study will contribute prospective, controlled data on outcomes and predictors of relapse in patients with inflammatory bowel disease after withdrawal of anti-TNF agents following achievement of clinical remission. Clinical trial reference number: EudraCT 2015-001410-1

NIOX VERO: Individualized Asthma Management in Clinical Practice

As we move toward an era of precision medicine, novel biomarkers of disease will enable the identification and personalized treatment of new endotypes. In asthma, fractional exhaled nitric oxide (FeNO) serves as a surrogate marker of airway inflammation that often correlates with the presence of sputum eosinophils. The increase in FeNO is driven by an upregulation of inducible nitric oxide synthase (iNOS) by cytokines, which are released as a result of type-2 airway inflammation. Scientific evidence supports using FeNO in routine clinical practice. In steroid-naive patients and in patients with mild asthma, FeNO levels decrease within days after corticosteroid treatment in a dose-dependent fashion and increase after steroid withdrawal. In difficult asthma, FeNO testing correlates with anti-inflammatory therapy compliance. Assessing adherence by FeNO testing can remove the confrontational aspect of questioning a patient about compliance and change the conversation to one of goal setting and ways to improve disease management. However, the most important aspect of incorporating FeNO in asthma management is the reduction in the risk of exacerbations. In a recent primary care study, reduction of exacerbation rates and improved symptom control without increasing overall inhaled corticosteroid (ICS) use were demonstrated when a FeNO-guided anti-inflammatory treatment algorithm was assessed and compared to the standard care. A truly personalized asthma management approach—showing reduction of exacerbation rates, overall use of ICS and neonatal hospitalizations—was demonstrated when FeNO testing was applied as part of the treatment algorithm that managed asthma during pregnancy. The aim of this article is to describe how FeNO and the NIOX VERO® analyzer can help to optimize diagnosis and treatment choices and to aid in the monitoring and improvement of clinical asthma outcomes in children and adults

Chemical Defence in a Millipede: Evaluation and Characterization of Antimicrobial Activity of the Defensive Secretion from Pachyiulus hungaricus (Karsch, 1881) (Diplopoda, Julida, Julidae)

The chemical defence of the millipede Pachyiulus hungaricus is reported in the present paper, in which a chemical characterization is given and antimicrobial activity is determined. In total, independently of sex, 44 compounds were identified. All compounds belong to two groups: quinones and pentyl and hexyl esters of long-chain fatty acids. The relative abundances of quinones and non-quinones were 94.7% vs. 5.3% (males) and 87.3% vs. 12.7% (females), respectively. The two dominant quinones in both sexes were 2-methyl-1,4,-benzoquinone and 2-methoxy-3-methyl-1,4-benzoquinone. Antibacterial and antifungal activity of the defensive secretion was evaluated in vitro against seven bacterial strains and eight fungal species. With the aid of a dilution technique, the antimicrobial potential of the secretion and high sensitivity of all tested strains were confirmed. The lowest minimum concentrations of these compounds (0.20-0.25 mg/mL) were sufficient for inhibition of Aeromonas hydrophila, Listeria monocytogenes and Methicillin resistant Staphylococcus aureus (MRSA). The growth of eight tested fungal species was inhibited by slightly lower concentrations of the secretion, with Fusarium equisetias the most sensitive fungus and Aspergillus flavus as the most resistant. Values of MIC and MFC in the employed microdilution assay ranged from 0.10 to above 0.35 mg/m L. The given extract contains antimicrobial components potentially useful as therapeutic agents in the pharmaceutical and agricultural industries