Energy extraction from the biologic battery in the inner ear

Endocochlear potential (EP) is a battery-like electrochemical gradient found in and actively maintained by the inner ear [superscript 1, 2]. Here we demonstrate that the mammalian EP can be used as a power source for electronic devices. We achieved this by designing an anatomically sized, ultra-low quiescent-power energy harvester chip integrated with a wireless sensor capable of monitoring the EP itself. Although other forms of in vivo energy harvesting have been described in lower organisms [superscript 3, 4, 5], and thermoelectric [superscript 6], piezoelectric [superscript 7] and biofuel [superscript 8, 9] devices are promising for mammalian applications, there have been few, if any, in vivo demonstrations in the vicinity of the ear, eye and brain. In this work, the chip extracted a minimum of 1.12 nW from the EP of a guinea pig for up to 5 h, enabling a 2.4 GHz radio to transmit measurement of the EP every 40–360 s. With future optimization of electrode design, we envision using the biologic battery in the inner ear to power chemical and molecular sensors, or drug-delivery actuators for diagnosis and therapy of hearing loss and other disorders.Focus Center Research Program. Focus Center for Circuit & System Solutions. Semiconductor Research Corporation. Interconnect Focus CenterNational Institutes of Health (U.S.) (Grant K08 DC010419)National Institutes of Health (U.S.) (Grant T32 DC00038)Bertarelli Foundatio

MMP-9 gene variants increase the risk for non-atopic asthma in children

<p>Abstract</p> <p>Background</p> <p>Atopic and non-atopic wheezing may be caused by different etiologies: while eosinophils are more important in atopic asthmatic wheezers, neutrophils are predominantly found in BAL samples of young children with wheezing. Both neutrophils as well as eosinophils may secrete matrix metalloproteinase 9 (MMP-9). Considering that MMP-9 plays an important role in airway wall thickening and airway inflammation, it may influence the development of obstructive airway phenotypes in children. In the present study we investigated whether genetic variations in <it>MMP-9 </it>influence the development of different forms of childhood asthma.</p> <p>Methods</p> <p>Genotyping of four HapMap derived tagging SNPs in the <it>MMP-9 </it>gene was performed using MALDI-TOF MS in three cross sectional study populations of German children (age 9-11; N = 4,264) phenotyped for asthma and atopic diseases according to ISAAC standard procedures. Effects of single SNPs and haplotypes were studied using SAS 9.1.3 and Haploview.</p> <p>Results</p> <p>SNP rs2664538 significantly increased the risk for non-atopic wheezing (OR 2.12, 95%CI 1.40-3.21, p < 0.001) and non-atopic asthma (OR 1.66, 95%CI 1.12-2.46, p = 0.011). Furthermore, the minor allele of rs3918241 may be associated with decreased expiratory flow measurements in non-atopic children. No significant effects on the development of atopy or total serum IgE levels were observed.</p> <p>Conclusions</p> <p>Our results have shown that homozygocity for <it>MMP-9 </it>variants increase the risk to develop non-atopic forms of asthma and wheezing, which may be explained by a functional role of MMP-9 in airway remodeling. These results suggest that different wheezing disorders in childhood are affected differently by genetic alterations.</p

Data-driven approach for creating synthetic electronic medical records

<p>Abstract</p> <p>Background</p> <p>New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed.</p> <p>Methods</p> <p>This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population.</p> <p>Results</p> <p>We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified.</p> <p>Conclusions</p> <p>A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.</p

Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

<p>Abstract</p> <p>Background</p> <p>Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs), while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics.</p> <p>Methods</p> <p>In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS) SNPs ranked by Random Forests (RF) importance score for the CAMP (Childhood Asthma Management Program) population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group.</p> <p>Results</p> <p>Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC) = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors.</p> <p>Conclusions</p> <p>Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.</p

Web-based interventions for weight loss and weight maintenance among rural midlife and older women: protocol for a randomized controlled trial

Background: Weight loss is challenging and maintenance of weight loss is problematic among midlife and older rural women. Finding effective interventions using innovative delivery methods that can reach underserved and vulnerable populations of overweight and obese rural women is a public health challenge. Methods/Design: This Women Weigh-In for Wellness (The WWW study) randomized-controlled trial is designed to compare the effectiveness of theory-based behavior-change interventions using (1) website only, (2) website with peer-led support, or (3) website with professional email-counseling to facilitate initial weight loss (baseline to 6 months), guided continuing weight loss and maintenance (7-18 months) and self-directed weight maintenance (19-30 months) among rural women ages 45-69 with a BMI of 28-45. Recruitment efforts using local media will target 306 rural women who live within driving distance of a community college site where assessments will be conducted at baseline, 3, 6, 12, 18, 24 and 30 months by research nurses blinded to group assignments. Primary outcomes include changes in body weight, % weight loss, and eating and activity behavioral and biomarkers from baseline to each subsequent assessment. Secondary outcomes will be percentage of women achieving at least 5% and 10% weight loss without regain from baseline to 6, 18, and 30 months and achieving healthy eating and activity targets. Data analysis will use generalized estimating equations to analyze average change across groups and group differences in proportion of participants achieving target weight loss levels. Discussion: The Women Weigh-In for Wellness study compares innovative web-based alternatives for providing lifestyle behavior-change interventions for promoting weight loss and weight maintenance among rural women. If effective, such interventions would offer potential for reducing overweight and obesity among a vulnerable, hard-to-reach, population of rural women

An Antimicrobial Peptide Regulates Tumor-Associated Macrophage Trafficking via the Chemokine Receptor CCR2, a Model for Tumorigenesis

Tumor-associated macrophages (TAMs) constitute a significant part of infiltrating inflammatory cells that are frequently correlated with progression and poor prognosis of a variety of cancers. Tumor cell-produced human β-defensin-3 (hBD-3) has been associated with TAM trafficking in oral cancer; however, its involvement in tumor-related inflammatory processes remains largely unknown., applying a cross-desensitization strategy of CCR2 and its pharmacological inhibitor (RS102895), respectively, was also carried out. outcome and demonstrates the importance of the innate immune system in the development of tumors