Model and Performance Analysis of Piezoelectric Energy Harvester System for Different Harvester Beam Configurations

Electricity is one of the main energy resources will be used to operate many devices and appliance for making human life as comfortable. In many of the applications the small electronics equipments or devices are used which requires power in milli Watts, micro Watts, nano Watts. This small power requirement devices are gets power form battery which is nowadays replaced by the PEH energy technology. There are many configurations are used and modeled to improve the power performance of the PEH. This paper is focus on the improvements of the PEH through the continuous beam, segmented beam with tip mass and clamped – clamped continuous beam harvester. The performances of the harvesters are analyzed with the factor like voltage generation, power generation, strain stress imposed on the harvester like that. The major difficulty in the use of PEH harvester to obtain electrical energy from the vibrations or motion energy is that the output power is very less; efficiency is very poor during the low frequency periods. The vibration frequency is not at all same for all duration of vibration. So, the vibrations in the frequency reduce the output of PEH particularly at low frequency situations. So, finding and designing a suitable PEH to produce high output power in any field of vibration energy source available

Interactions among genes in the ErbB-Neuregulin signalling network are associated with increased susceptibility to schizophrenia

<p>Abstract</p> <p>Background</p> <p>Evidence of genetic association between the NRG1 (Neuregulin-1) gene and schizophrenia is now well-documented. Furthermore, several recent reports suggest association between schizophrenia and single-nucleotide polymorphisms (SNPs) in ERBB4, one of the receptors for Neuregulin-1. In this study, we have extended the previously published associations by investigating the involvement of all eight genes from the ERBB and NRG families for association with schizophrenia.</p> <p>Methods</p> <p>Eight genes from the ERBB and NRG families were tested for association to schizophrenia using a collection of 396 cases and 1,342 blood bank controls ascertained from Aberdeen, UK. A total of 365 SNPs were tested. Association testing of both alleles and genotypes was carried out using the fast Fisher's Exact Test (FET). To understand better the nature of the associations, all pairs of SNPs separated by ≥ 0.5 cM with at least nominal evidence of association (<it>P </it>< 0.10) were tested for evidence of pairwise interaction by logistic regression analysis.</p> <p>Results</p> <p>42 out of 365 tested SNPs in the eight genes from the ERBB and NRG gene families were significantly associated with schizophrenia (<it>P </it>< 0.05). Associated SNPs were located in ERBB4 and NRG1, confirming earlier reports. However, novel associations were also seen in NRG2, NRG3 and EGFR. In pairwise interaction tests, clear evidence of gene-gene interaction was detected for NRG1-NRG2, NRG1-NRG3 and EGFR-NRG2, and suggestive evidence was also seen for ERBB4-NRG1, ERBB4-NRG2, ERBB4-NRG3 and ERBB4-ERBB2. Evidence of intragenic interaction was seen for SNPs in ERBB4.</p> <p>Conclusion</p> <p>These new findings suggest that observed associations between NRG1 and schizophrenia may be mediated through functional interaction not just with ERBB4, but with other members of the NRG and ERBB families. There is evidence that genetic interaction among these loci may increase susceptibility to schizophrenia.</p

Cluster analyses from the real-world NOVELTY study : six clusters across the asthma COPD spectrum

Funding The NOVELTY study is funded by AstraZeneca. ACKNOWLEDGMENTS The authors would like to thank the patients who participated in this study and the NOVELTY Scientific Community and the NOVELTY study investigators who are listed in full in Tables E7 and E8 in the Online Repository. Medical writing support, under the direction of the authors, was provided by Richard Knight, PhD, CMC Connect, a division of IPG Health Medical Communications, funded by AstraZeneca in accordance with Good Publication Practice (GPP 2022) guidelines (Ann Intern Med. 2022;175[9]:1298-1304). J. Vestbo is supported by the NIHR Manchester Biomedical Research Centre and the NIHR Manchester Clinical Research FacilityPeer reviewedPublisher PD

Raman Spectroscopic Analysis of Fingernail Clippings Can Help Differentiate between Postmenopausal Women Who Have and Have Not Suffered a Fracture

Raman spectroscopy was applied to nail clippings from 633 postmenopausal British and Irish women, from six clinical sites, of whom 42% had experienced a fragility fracture. The objective was to build a prediction algorithm for fracture using data from four sites (known as the calibration set) and test its performance using data from the other two sites (known as the validation set). Results from the validation set showed that a novel algorithm, combining spectroscopy data with clinical data, provided area under the curve (AUC) of 74% compared to an AUC of 60% from a reduced QFracture score (a clinically accepted risk calculator) and 61% from the dual-energy X-ray absorptiometry T-score, which is in current use for the diagnosis of osteoporosis. Raman spectroscopy should be investigated further as a noninvasive tool for the early detection of enhanced risk of fragility fracture

Clinical validation of a genetic model to estimate the risk of developing choroidal neovascular age-related macular degeneration

Predictive tests for estimating the risk of developing late-stage neovascular age-related macular degeneration (AMD) are subject to unique challenges. AMD prevalence increases with age, clinical phenotypes are heterogeneous and control collections are prone to high false-negative rates, as many control subjects are likely to develop disease with advancing age. Risk prediction tests have been presented previously, using up to ten genetic markers and a range of self-reported non-genetic variables such as body mass index (BMI) and smoking history. In order to maximise the accuracy of prediction for mainstream genetic testing, we sought to derive a test comparable in performance to earlier testing models but based purely on genetic markers, which are static through life and not subject to misreporting. We report a multicentre assessment of a larger panel of single nucleotide polymorphisms (SNPs) than previously analysed, to improve further the classification performance of a predictive test to estimate the risk of developing choroidal neovascular (CNV) disease. We developed a predictive model based solely on genetic markers and avoided inclusion of self-reported variables (eg smoking history) or non-static factors (BMI, education status) that might otherwise introduce inaccuracies in calculating individual risk estimates. We describe the performance of a test panel comprising 13 SNPs genotyped across a consolidated collection of four patient cohorts obtained from academic centres deemed appropriate for pooling. We report on predictive effect sizes and their classification performance. By incorporating multiple cohorts of homogeneous ethnic origin, we obtained >80 per cent power to detect differences in genetic variants observed between cases and controls. We focused our study on CNV, a subtype of advanced AMD associated with a severe and potentially treatable form of the disease. Lastly, we followed a two-stage strategy involving both test model development and test model validation to present estimates of classification performance anticipated in the larger clinical setting. The model contained nine SNPs tagging variants in the regulators of complement activation (RCA) locus spanning the complement factor H (CFH), complement factor H-related 4 (CFHR4), complement factor H-related 5 (CFHR5) and coagulation factor XIII B subunit (F13B) genes; the four remaining SNPs targeted polymorphisms in the complement component 2 (C2), complement factor B (CFB), complement component 3 (C3) and age-related maculopathy susceptibility protein 2 (ARMS2) genes. The pooled sample size (1,132 CNV cases, 822 controls) allowed for both model development and model validation to confirm the accuracy of risk prediction. At the validation stage, our test model yielded 82 per cent sensitivity and 63 per cent specificity, comparable with metrics reported with earlier testing models that included environmental risk factors. Our test had an area under the curve of 0.80, reflecting a modest improvement compared with tests reported with fewer SNPs

Prospective observational study in patients with obstructive lung disease : NOVELTY design

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Heterogeneity within and between physician-diagnosed asthma and/or COPD : NOVELTY cohort

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Breathomics can discriminate between anti IgE-treated and non-treated severe asthma adults

Rationale: Omalizumab, an anti-IgE monoclonal antibody, is indicated in adults with severe persistent allergic asthma. Exhaled molecular markers can provide phenotypic information in asthma. Objectives: Determine whether adults with severe asthma on omalizumab (anti-IgE+) have a different breathprint compared with those who were not on anti-IgE therapy (anti-IgE-) as assessed by eNoses and gas chromatography/mass spectrometry (GC/MS) (breathomics). Methods: This was a cross-sectional analysis of the U- BIOPRED adult cohort. Severe asthma was defined by IMI-criteria [Bel, Thorax 2011]. Anti-IgE+ patients were on a regular treatment with s.c. omalizumab (150-375 mg) every 2-4 weeks. Exhaled volatile compounds trapped on adsorption tubes were analysed by a centralized eNose platform (Owlstone Lonestar, two Cyranose 320, Comon Invent, Tor Vergata TEN), including a total of 190 sensors, and GC/MS. Recursive feature elimination (http://topepo.github.io/caret/rfe.html) was used for feature selection and random forests, more robust to overfitting, for classification. Results: 9 anti- IgE+ (females/males 2/7, age 52.6±16.3 years, mean±SD, 1/2/6 current/ex/nonsmokers, pre-bronchodilator FEV1 70.6±21.1% predicted value) and 30 anti-IgE- patients (18/12 females/males, age 53.2±14.2 years, 0/16/14 current/ex/nonsmokers, pre-bronchodilator FEV1 59.6±30.7% predicted value) were studied. Conclusions: Preliminary results suggest that breathomics can distinguish between anti-IgE+ and anti-IgE- severe asthma patients

Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort

Background: Exacerbation-prone asthma is a feature of severe disease. Yet, the basis for its persistency remains unclear. Objectives: To determine the clinical and transcriptomic features of the frequent-exacerbator (FE) and of persistent FEs (PFE) in U-BIOPRED cohort. Methods: We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures. Results: Of 317 patients, 62.4 % were FE of whom 63.6% were PFE, while 37.6% were IE of whom 61.3% were PIE. Using multivariate analysis, FE was associated with short-acting beta-agonist use, sinusitis and daily oral corticosteroid use, while PFE with eczema, short-acting beta-agonist use and asthma control index. CEA Cell Adhesion Molecule 5 (CEACAM5) was the only differentially-expressed transcript in bronchial biopsies between PE and IE. There were no differentially-expressed genes in the other 4 compartments. There were higher expression scores for Type 2 , T-helper type-17 and Type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while higher expression scores of Type 2, Type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE. Conclusion: FE group and its PFE subgroup are associated with poor asthma control while expressing higher Type 1 and Type 2 activation pathways compared to IE and PIE, respectively

Novel genetic variants associated with lumbar disc degeneration in northern Europeans: A meta-analysis of 4600 subjects

Objective: Lumbar disc degeneration (LDD) is an important cause of low back pain, which is a common and costly problem. LDD is characterised by disc space narrowing and osteophyte growth at the circumference of the disc. To date, the agnostic search of the genome by genome-wide association (GWA) to identify common variants associated with LDD has not been fruitful. This study is the first GWA meta-analysis of LDD. Methods: We have developed a continuous trait based on disc space narrowing and osteophytes growth which is measurable on all forms of imaging (plain radiograph, CT scan and MRI) and performed a meta-analysis of five cohorts of Northern European extraction each having GWA data imputed to HapMap V.2. Results: This study of 4600 individuals identified four single nucleotide polymorphisms with p<5×10-8, the threshold set for genome-wide significance. We identified a variant in the PARK2 gene (p=2.8×10-8) associated with LDD. Differential methylation at one CpG island of the PARK2 promoter was observed in a small subset of subjects (β=8.74×10-4, p=0.006). Conclusions: LDD accounts for a considerable proportion of low back pain and the pathogenesis of LDD is poorly understood. This work provides evidence of association of the PARK2 gene and suggests that methylation of the PARK2 promoter may influence degeneration of the intervertebral disc. This gene has not previously been considered a candidate in LDD and further functional work is needed on this hitherto unsuspected pathway. Copyright Article author (or their employer) 2012